From df16b2c4a5ee24173ef531b8a96bf8973fbb7eb3 Mon Sep 17 00:00:00 2001 From: Daniel Lee Date: Fri, 17 Jun 2016 10:19:52 -0400 Subject: [PATCH 1/2] release/v2.10.0: updating version numbers --- doxygen/doxygen.cfg | 2 +- stan/math/version.hpp | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/doxygen/doxygen.cfg b/doxygen/doxygen.cfg index a080717d94e..d31e1b6ea91 100644 --- a/doxygen/doxygen.cfg +++ b/doxygen/doxygen.cfg @@ -38,7 +38,7 @@ PROJECT_NAME = "Stan Math Library" # could be handy for archiving the generated documentation or if some version # control system is used. -PROJECT_NUMBER = 2.9.0 +PROJECT_NUMBER = 2.10.0 # Using the PROJECT_BRIEF tag one can provide an optional one line description # for a project that appears at the top of each page and should give viewer a diff --git a/stan/math/version.hpp b/stan/math/version.hpp index 38e7b417863..2a6faa09c52 100644 --- a/stan/math/version.hpp +++ b/stan/math/version.hpp @@ -12,7 +12,7 @@ #endif #define STAN_MATH_MAJOR 2 -#define STAN_MATH_MINOR 9 +#define STAN_MATH_MINOR 10 #define STAN_MATH_PATCH 0 namespace stan { From 771a24172486976f0a0b5299b7591cb8dd930dcd Mon Sep 17 00:00:00 2001 From: Daniel Lee Date: Fri, 17 Jun 2016 10:30:20 -0400 Subject: [PATCH 2/2] release/v2.10.0: adding built documentation. 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 (Expert) Numerical traits for algorithmic differentiation variables.
 
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 (Expert) Product traits for algorithmic differentiation variables.
 
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diff --git a/doc/api/html/_eigen_8hpp.html b/doc/api/html/_eigen_8hpp.html new file mode 100644 index 00000000000..029eeada2fc --- /dev/null +++ b/doc/api/html/_eigen_8hpp.html @@ -0,0 +1,114 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/Eigen.hpp File Reference + + + + + + + + + + +
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#include <Eigen/Dense>
+#include <Eigen/QR>
+#include <Eigen/src/Core/NumTraits.h>
+
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diff --git a/doc/api/html/_eigen_8hpp_source.html b/doc/api/html/_eigen_8hpp_source.html new file mode 100644 index 00000000000..0167131297c --- /dev/null +++ b/doc/api/html/_eigen_8hpp_source.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/Eigen.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_EIGEN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_EIGEN_HPP
+
3 
+
4 #include <Eigen/Dense>
+
5 #include <Eigen/QR>
+
6 #include <Eigen/src/Core/NumTraits.h>
+
7 
+
8 #endif
+
+
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diff --git a/doc/api/html/_f32_8hpp.html b/doc/api/html/_f32_8hpp.html new file mode 100644 index 00000000000..fff650826e8 --- /dev/null +++ b/doc/api/html/_f32_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/F32.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::F32 (T a, T b, T c, T d, T e, T z, T precision=1e-6)
 
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diff --git a/doc/api/html/_f32_8hpp_source.html b/doc/api/html/_f32_8hpp_source.html new file mode 100644 index 00000000000..214e0a063cc --- /dev/null +++ b/doc/api/html/_f32_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/F32.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_F32_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_F32_HPP
+
3 
+
4 #include <cmath>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
10  template<typename T>
+
11  T F32(T a, T b, T c, T d, T e, T z, T precision = 1e-6) {
+
12  using std::exp;
+
13  using std::log;
+
14  using std::fabs;
+
15 
+
16  T F = 1.0;
+
17 
+
18  T tNew = 0.0;
+
19 
+
20  T logT = 0.0;
+
21 
+
22  T logZ = log(z);
+
23 
+
24  int k = 0.0;
+
25 
+
26  while (fabs(tNew) > precision || k == 0) {
+
27  T p = (a + k) * (b + k) * (c + k) / ( (d + k) * (e + k) * (k + 1) );
+
28 
+
29  // If a, b, or c is a negative integer then the series terminates
+
30  // after a finite number of interations
+
31  if (p == 0) break;
+
32 
+
33  logT += (p > 0 ? 1.0 : -1.0) * log(fabs(p)) + logZ;
+
34 
+
35  tNew = exp(logT);
+
36 
+
37  F += tNew;
+
38 
+
39  ++k;
+
40  }
+
41  return F;
+
42  }
+
43 
+
44  }
+
45 }
+
46 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
T F32(T a, T b, T c, T d, T e, T z, T precision=1e-6)
Definition: F32.hpp:11
+
+
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diff --git a/doc/api/html/_l_d_l_t__alloc_8hpp.html b/doc/api/html/_l_d_l_t__alloc_8hpp.html new file mode 100644 index 00000000000..1b991e85798 --- /dev/null +++ b/doc/api/html/_l_d_l_t__alloc_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/LDLT_alloc.hpp File Reference + + + + + + + + + + +
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class  stan::math::LDLT_alloc< R, C >
 This object stores the actual (double typed) LDLT factorization of an Eigen::Matrix<var> along with pointers to its vari's which allow the *_ldlt functions to save memory. More...
 
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diff --git a/doc/api/html/_l_d_l_t__alloc_8hpp_source.html b/doc/api/html/_l_d_l_t__alloc_8hpp_source.html new file mode 100644 index 00000000000..d31c5298b1c --- /dev/null +++ b/doc/api/html/_l_d_l_t__alloc_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/LDLT_alloc.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_MAT_FUN_LDLT_ALLOC_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_LDLT_ALLOC_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
19  template<int R, int C>
+
20  class LDLT_alloc : public chainable_alloc {
+
21  public:
+
22  LDLT_alloc() : N_(0) {}
+
23  explicit LDLT_alloc(const Eigen::Matrix<var, R, C> &A) : N_(0) {
+
24  compute(A);
+
25  }
+
26 
+
32  inline void compute(const Eigen::Matrix<var, R, C> &A) {
+
33  Eigen::Matrix<double, R, C> Ad(A.rows(), A.cols());
+
34 
+
35  N_ = A.rows();
+
36  _variA.resize(A.rows(), A.cols());
+
37 
+
38  for (size_t j = 0; j < N_; j++) {
+
39  for (size_t i = 0; i < N_; i++) {
+
40  Ad(i, j) = A(i, j).val();
+
41  _variA(i, j) = A(i, j).vi_;
+
42  }
+
43  }
+
44 
+
45  _ldlt.compute(Ad);
+
46  }
+
47 
+
49  inline double log_abs_det() const {
+
50  return _ldlt.vectorD().array().log().sum();
+
51  }
+
52 
+
53  size_t N_;
+
54  Eigen::LDLT<Eigen::Matrix<double, R, C> > _ldlt;
+
55  Eigen::Matrix<vari*, R, C> _variA;
+
56  };
+
57  }
+
58 }
+
59 #endif
+ + + +
Eigen::LDLT< Eigen::Matrix< double, R, C > > _ldlt
Definition: LDLT_alloc.hpp:54
+ +
This object stores the actual (double typed) LDLT factorization of an Eigen::Matrix along with p...
Definition: LDLT_alloc.hpp:20
+
LDLT_alloc(const Eigen::Matrix< var, R, C > &A)
Definition: LDLT_alloc.hpp:23
+ +
Eigen::Matrix< vari *, R, C > _variA
Definition: LDLT_alloc.hpp:55
+
A chainable_alloc is an object which is constructed and destructed normally but the memory lifespan i...
+
double log_abs_det() const
Compute the log(abs(det(A))). This is just a convenience function.
Definition: LDLT_alloc.hpp:49
+
void compute(const Eigen::Matrix< var, R, C > &A)
Compute the LDLT factorization and store pointers to the vari's of the matrix entries to be used when...
Definition: LDLT_alloc.hpp:32
+
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diff --git a/doc/api/html/_vector_builder_8hpp.html b/doc/api/html/_vector_builder_8hpp.html new file mode 100644 index 00000000000..7bdd3b09e72 --- /dev/null +++ b/doc/api/html/_vector_builder_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/VectorBuilder.hpp File Reference + + + + + + + + + + +
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class  stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 >
 VectorBuilder allocates type T1 values to be used as intermediate values. More...
 
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diff --git a/doc/api/html/_vector_builder_8hpp_source.html b/doc/api/html/_vector_builder_8hpp_source.html new file mode 100644 index 00000000000..7183c779632 --- /dev/null +++ b/doc/api/html/_vector_builder_8hpp_source.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/VectorBuilder.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_VECTORBUILDER_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_VECTORBUILDER_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
25  template<bool used, typename T1, typename T2, typename T3 = double,
+
26  typename T4 = double, typename T5 = double, typename T6 = double,
+
27  typename T7 = double>
+
28  class VectorBuilder {
+
29  public:
+
30  VectorBuilderHelper<T1, used,
+ +
32 
+
33  explicit VectorBuilder(size_t n) : a(n) { }
+
34 
+
35  T1& operator[](size_t i) {
+
36  return a[i];
+
37  }
+
38 
+
39  inline typename
+
40  VectorBuilderHelper<T1, used,
+ +
42  data() {
+
43  return a.data();
+
44  }
+
45  };
+
46 
+
47 }
+
48 #endif
+
VectorBuilderHelper< T1, used, contains_vector< T2, T3, T4, T5, T6, T7 >::value > a
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
T1 & operator[](size_t i)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ + +
VectorBuilderHelper< T1, used, contains_vector< T2, T3, T4, T5, T6, T7 >::value >::type data()
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/_vector_view_mvt_8hpp.html b/doc/api/html/_vector_view_mvt_8hpp.html new file mode 100644 index 00000000000..376b02ae39d --- /dev/null +++ b/doc/api/html/_vector_view_mvt_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/VectorViewMvt.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
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+
VectorViewMvt.hpp File Reference
+
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diff --git a/doc/api/html/_vector_view_mvt_8hpp_source.html b/doc/api/html/_vector_view_mvt_8hpp_source.html new file mode 100644 index 00000000000..275d76bb417 --- /dev/null +++ b/doc/api/html/_vector_view_mvt_8hpp_source.html @@ -0,0 +1,186 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/VectorViewMvt.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
VectorViewMvt.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_META_VECTORVIEWMVT_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_VECTORVIEWMVT_HPP
+
3 
+ + + +
7 #include <stdexcept>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  template <typename T, bool is_array
+ +
14  <typename stan::math::value_type<T>::type>::value,
+
15  bool throw_if_accessed = false>
+
16  class VectorViewMvt {
+
17  public:
+ +
19 
+
20  explicit VectorViewMvt(matrix_t& m) : x_(&m) { }
+
21 
+
22  explicit VectorViewMvt(std::vector<matrix_t>& vm) : x_(&vm[0]) { }
+
23 
+
24  matrix_t& operator[](int i) {
+
25  if (throw_if_accessed)
+
26  throw std::out_of_range("VectorViewMvt: this cannot be accessed");
+
27  if (is_array)
+
28  return x_[i];
+
29  else
+
30  return x_[0];
+
31  }
+
32  private:
+
33  matrix_t* x_;
+
34  };
+
35 
+
40  template <typename T, bool is_array, bool throw_if_accessed>
+
41  class VectorViewMvt<const T, is_array, throw_if_accessed> {
+
42  public:
+ +
44 
+
45  explicit VectorViewMvt(const matrix_t& m) : x_(&m) { }
+
46 
+
47  explicit VectorViewMvt(const std::vector<matrix_t>& vm) : x_(&vm[0]) { }
+
48 
+
49  const matrix_t& operator[](int i) const {
+
50  if (throw_if_accessed)
+
51  throw std::out_of_range("VectorViewMvt: this cannot be accessed");
+
52  if (is_array)
+
53  return x_[i];
+
54  else
+
55  return x_[0];
+
56  }
+
57  private:
+
58  const matrix_t* x_;
+
59  };
+
60 
+
61 
+
62 }
+
63 #endif
+
64 
+
scalar_type_helper_pre< is_vector< typename stan::math::value_type< T >::type >::value, typename stan::math::value_type< T >::type, T >::type type
+
Template metaprogram indicates whether a type is vector_like.
+ + +
VectorViewMvt(std::vector< matrix_t > &vm)
+ +
matrix_t & operator[](int i)
+ + +
void out_of_range(const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
Throw an out_of_range exception with a consistently formatted message.
+ +
VectorViewMvt(matrix_t &m)
+ +
scalar_type_pre< T >::type matrix_t
+ + +
Primary template class for metaprogram to compute the type of values stored in a container.
Definition: value_type.hpp:18
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/accumulator_8hpp.html b/doc/api/html/accumulator_8hpp.html new file mode 100644 index 00000000000..b97126aa619 --- /dev/null +++ b/doc/api/html/accumulator_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/accumulator.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
+
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+
+ +
+
accumulator.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/sum.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits/is_arithmetic.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

class  stan::math::accumulator< T >
 Class to accumulate values and eventually return their sum. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/accumulator_8hpp_source.html b/doc/api/html/accumulator_8hpp_source.html new file mode 100644 index 00000000000..0b8bed85f86 --- /dev/null +++ b/doc/api/html/accumulator_8hpp_source.html @@ -0,0 +1,185 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/accumulator.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+
accumulator.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_ACCUMULATOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ACCUMULATOR_HPP
+
3 
+ + +
6 #include <boost/utility/enable_if.hpp>
+
7 #include <boost/type_traits/is_arithmetic.hpp>
+
8 #include <boost/type_traits/is_same.hpp>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
24  template <typename T>
+
25  class accumulator {
+
26  private:
+
27  std::vector<T> buf_;
+
28 
+
29  public:
+ +
34  : buf_() {
+
35  }
+
36 
+ +
41 
+
52  template <typename S>
+
53  typename boost::enable_if<boost::is_arithmetic<S>, void>::type
+
54  add(S x) {
+
55  buf_.push_back(static_cast<T>(x));
+
56  }
+
57 
+
70  template <typename S>
+
71  typename boost::disable_if<boost::is_arithmetic<S>,
+
72  typename boost::enable_if<boost::is_same<S, T>,
+
73  void>::type >::type
+
74  add(const S& x) {
+
75  buf_.push_back(x);
+
76  }
+
77 
+
87  template <typename S, int R, int C>
+
88  void add(const Eigen::Matrix<S, R, C>& m) {
+
89  for (int i = 0; i < m.size(); ++i)
+
90  add(m(i));
+
91  }
+
92 
+
102  template <typename S>
+
103  void add(const std::vector<S>& xs) {
+
104  for (size_t i = 0; i < xs.size(); ++i)
+
105  add(xs[i]);
+
106  }
+
107 
+
113  T sum() const {
+
114  using math::sum;
+
115  return sum(buf_);
+
116  }
+
117  };
+
118 
+
119 
+
120 
+
121 
+
122  }
+
123 }
+
124 
+
125 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+
T sum() const
Return the sum of the accumulated values.
+ +
accumulator()
Construct an accumulator.
Definition: accumulator.hpp:33
+
boost::disable_if< boost::is_arithmetic< S >, typename boost::enable_if< boost::is_same< S, T >, void >::type >::type add(const S &x)
Add the specified non-arithmetic value to the buffer.
Definition: accumulator.hpp:74
+ +
Class to accumulate values and eventually return their sum.
Definition: accumulator.hpp:25
+ +
void add(const std::vector< S > &xs)
Recursively add each entry in the specified standard vector to the buffer.
+
void add(const Eigen::Matrix< S, R, C > &m)
Add each entry in the specified matrix, vector, or row vector of values to the buffer.
Definition: accumulator.hpp:88
+
~accumulator()
Destroy an accumulator.
Definition: accumulator.hpp:40
+
boost::enable_if< boost::is_arithmetic< S >, void >::type add(S x)
Add the specified arithmetic type value to the buffer after static casting it to the class type T...
Definition: accumulator.hpp:54
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/add_8hpp.html b/doc/api/html/add_8hpp.html new file mode 100644 index 00000000000..ddf3accbed0 --- /dev/null +++ b/doc/api/html/add_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/add.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
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+
+ +
+
add.hpp File Reference
+
+
+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/err/check_matching_dims.hpp>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + +

+Functions

template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::add (const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
 Return the sum of the specified matrices. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::add (const Eigen::Matrix< T1, R, C > &m, const T2 &c)
 Return the sum of the specified matrix and specified scalar. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::add (const T1 &c, const Eigen::Matrix< T2, R, C > &m)
 Return the sum of the specified scalar and specified matrix. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/add_8hpp_source.html b/doc/api/html/add_8hpp_source.html new file mode 100644 index 00000000000..8280681f7c1 --- /dev/null +++ b/doc/api/html/add_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/add.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+
add.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_ADD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ADD_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
24  template <typename T1, typename T2, int R, int C>
+
25  inline
+
26  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
27  add(const Eigen::Matrix<T1, R, C>& m1,
+
28  const Eigen::Matrix<T2, R, C>& m2) {
+ +
30  "m1", m1,
+
31  "m2", m2);
+
32  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
33  R, C>
+
34  result(m1.rows(), m1.cols());
+
35  for (int i = 0; i < result.size(); ++i)
+
36  result(i) = m1(i) + m2(i);
+
37  return result;
+
38  }
+
39 
+
49  template <typename T1, typename T2, int R, int C>
+
50  inline
+
51  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
52  add(const Eigen::Matrix<T1, R, C>& m,
+
53  const T2& c) {
+
54  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
55  R, C>
+
56  result(m.rows(), m.cols());
+
57  for (int i = 0; i < result.size(); ++i)
+
58  result(i) = m(i) + c;
+
59  return result;
+
60  }
+
61 
+
71  template <typename T1, typename T2, int R, int C>
+
72  inline
+
73  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
74  add(const T1& c,
+
75  const Eigen::Matrix<T2, R, C>& m) {
+
76  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
77  R, C>
+
78  result(m.rows(), m.cols());
+
79  for (int i = 0; i < result.size(); ++i)
+
80  result(i) = c + m(i);
+
81  return result;
+
82  }
+
83 
+
84  }
+
85 }
+
86 #endif
+ + +
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
+ +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > add(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the sum of the specified matrices.
Definition: add.hpp:27
+
+
+
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diff --git a/doc/api/html/annotated.html b/doc/api/html/annotated.html new file mode 100644 index 00000000000..a71309dc50f --- /dev/null +++ b/doc/api/html/annotated.html @@ -0,0 +1,285 @@ + + + + + + +Stan Math Library: Class List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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Class List
+
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Here are the classes, structs, unions and interfaces with brief descriptions:
+
[detail level 1234]
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
 NboostReimplementing boost functionality
 NEigen(Expert) Numerical traits for algorithmic differentiation variables
 Ninternal(Expert) Product traits for algorithmic differentiation variables
 CNumTraits< stan::math::fvar< T > >Numerical traits template override for Eigen for automatic gradient variables
 CNumTraits< stan::math::var >Numerical traits template override for Eigen for automatic gradient variables
 Nstan
 NmathMatrices and templated mathematical functions
 Ccontains_fvarMetaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters
 Ccontains_nonconstant_struct
 Ccontains_vector
 Cerror_index
 Cis_constantMetaprogramming struct to detect whether a given type is constant in the mathematical sense (not the C++ const sense)
 Cis_constant_structMetaprogram to determine if a type has a base scalar type that can be assigned to type double
 Cis_constant_struct< Eigen::Block< T > >
 Cis_constant_struct< Eigen::Matrix< T, R, C > >
 Cis_constant_struct< std::vector< T > >
 Cis_fvar
 Cis_fvar< stan::math::fvar< T > >
 Cis_var
 Cis_var< stan::math::var >
 Cis_var_or_arithmetic
 Cis_vector
 Cis_vector< const T >
 Cis_vector< Eigen::Block< T > >
 Cis_vector< Eigen::Matrix< T, 1, Eigen::Dynamic > >
 Cis_vector< Eigen::Matrix< T, Eigen::Dynamic, 1 > >
 Cis_vector< std::vector< T > >
 Cis_vector_likeTemplate metaprogram indicates whether a type is vector_like
 Cis_vector_like< const T >Template metaprogram indicates whether a type is vector_like
 Cis_vector_like< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >Template metaprogram indicates whether a type is vector_like
 Cis_vector_like< T * >Template metaprogram indicates whether a type is vector_like
 Cpartials_return_type
 Cpartials_type
 Cpartials_type< stan::math::fvar< T > >
 Cpartials_type< stan::math::var >
 Creturn_typeMetaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters
 Cscalar_typeMetaprogram structure to determine the base scalar type of a template argument
 Cscalar_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >
 Cscalar_type< T * >
 Cscalar_type_preMetaprogram structure to determine the type of first container of the base scalar type of a template argument
 Csize_of_helper
 Csize_of_helper< T, true >
 CVectorBuilderVectorBuilder allocates type T1 values to be used as intermediate values
 CVectorBuilderHelperVectorBuilder allocates type T1 values to be used as intermediate values
 CVectorBuilderHelper< T1, true, false >
 CVectorBuilderHelper< T1, true, true >Template specialization for using a vector
 CVectorViewVectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[]
 CVectorView< const Eigen::Matrix< T, R, C >, true, false >
 CVectorView< const std::vector< T >, true, false >
 CVectorView< Eigen::Matrix< T, R, C >, true, false >
 CVectorView< std::vector< T >, true, false >
 CVectorView< T, false, false >
 CVectorView< T, is_array, true >
 CVectorView< T, true, false >
 CVectorViewMvt
 CVectorViewMvt< const T, is_array, throw_if_accessed >VectorViewMvt that has const correctness
 Nstd
 Cnumeric_limits< stan::math::fvar< T > >
 Cnumeric_limits< stan::math::var >Specialization of numeric limits for var objects
+
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diff --git a/doc/api/html/append__col_8hpp.html b/doc/api/html/append__col_8hpp.html new file mode 100644 index 00000000000..3ba35b41dbb --- /dev/null +++ b/doc/api/html/append__col_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/append_col.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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append_col.hpp File Reference
+
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+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > stan::math::append_col (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &B)
 Return the result of appending the second argument matrix after the first argument matrix, that is, putting them side by side, with the first matrix followed by the second matrix. More...
 
template<typename T1 , typename T2 , int C1, int C2>
Eigen::Matrix< typename return_type< T1, T2 >::type, 1, Eigen::Dynamic > stan::math::append_col (const Eigen::Matrix< T1, 1, C1 > &A, const Eigen::Matrix< T2, 1, C2 > &B)
 Return the result of concatenaing the first row vector followed by the second row vector side by side, with the result being a row vector. More...
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::append_col (const Eigen::Matrix< T, R1, C1 > &A, const Eigen::Matrix< T, R2, C2 > &B)
 Return the result of appending the second argument matrix after the first argument matrix, that is, putting them side by side, with the first matrix followed by the second matrix. More...
 
template<typename T , int C1, int C2>
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::append_col (const Eigen::Matrix< T, 1, C1 > &A, const Eigen::Matrix< T, 1, C2 > &B)
 Return the result of concatenaing the first row vector followed by the second row vector side by side, with the result being a row vector. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename return_type< T1, T2 >::type, 1, Eigen::Dynamic > stan::math::append_col (const T1 &A, const Eigen::Matrix< T2, R, C > &B)
 Return the result of stacking an scalar on top of the a row vector, with the result being a row vector. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename return_type< T1, T2 >::type, 1, Eigen::Dynamic > stan::math::append_col (const Eigen::Matrix< T1, R, C > &A, const T2 &B)
 Return the result of stacking a row vector on top of the an scalar, with the result being a row vector. More...
 
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diff --git a/doc/api/html/append__col_8hpp_source.html b/doc/api/html/append__col_8hpp_source.html new file mode 100644 index 00000000000..6f7bd0ddd5c --- /dev/null +++ b/doc/api/html/append__col_8hpp_source.html @@ -0,0 +1,242 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/append_col.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
append_col.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_APPEND_COL_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_APPEND_COL_HPP
+
3 
+ + + +
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
36  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
37  inline Eigen::Matrix<typename return_type<T1, T2>::type,
+
38  Eigen::Dynamic, Eigen::Dynamic>
+
39  append_col(const Eigen::Matrix<T1, R1, C1>& A,
+
40  const Eigen::Matrix<T2, R2, C2>& B) {
+
41  using Eigen::Dynamic;
+
42  using Eigen::Matrix;
+ +
44 
+
45  int Arows = A.rows();
+
46  int Brows = B.rows();
+
47  int Acols = A.cols();
+
48  int Bcols = B.cols();
+
49  check_size_match("append_col",
+
50  "rows of A", Arows,
+
51  "rows of B", Brows);
+
52 
+
53  Matrix<typename return_type<T1, T2>::type, Dynamic, Dynamic>
+
54  result(Arows, Acols+Bcols);
+
55  for (int j = 0; j < Acols; j++)
+
56  for (int i = 0; i < Arows; i++)
+
57  result(i, j) = A(i, j);
+
58 
+
59  for (int j = Acols, k = 0; k < Bcols; j++, k++)
+
60  for (int i = 0; i < Arows; i++)
+
61  result(i, j) = B(i, k);
+
62  return result;
+
63  }
+
64 
+
82  template <typename T1, typename T2, int C1, int C2>
+
83  inline Eigen::Matrix<typename return_type<T1, T2>::type,
+
84  1, Eigen::Dynamic>
+
85  append_col(const Eigen::Matrix<T1, 1, C1>& A,
+
86  const Eigen::Matrix<T2, 1, C2>& B) {
+
87  using Eigen::Dynamic;
+
88  using Eigen::Matrix;
+
89 
+
90  int Asize = A.size();
+
91  int Bsize = B.size();
+
92  Matrix<typename return_type<T1, T2>::type, 1, Dynamic>
+
93  result(Asize + Bsize);
+
94  for (int i = 0; i < Asize; i++)
+
95  result(i) = A(i);
+
96  for (int i = 0, j = Asize; i < Bsize; i++, j++)
+
97  result(j) = B(i);
+
98  return result;
+
99  }
+
100 
+
101 
+
126  template <typename T, int R1, int C1, int R2, int C2>
+
127  inline Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
128  append_col(const Eigen::Matrix<T, R1, C1>& A,
+
129  const Eigen::Matrix<T, R2, C2>& B) {
+
130  using Eigen::Matrix;
+
131  using Eigen::Dynamic;
+
132 
+
133  check_size_match("append_col",
+
134  "rows of A", A.rows(),
+
135  "rows of B", B.rows());
+
136 
+
137  Matrix<T, Dynamic, Dynamic> result(A.rows(), A.cols()+B.cols());
+
138  result << A, B;
+
139  return result;
+
140  }
+
141 
+
158  template <typename T, int C1, int C2>
+
159  inline Eigen::Matrix<T, 1, Eigen::Dynamic>
+
160  append_col(const Eigen::Matrix<T, 1, C1>& A,
+
161  const Eigen::Matrix<T, 1, C2>& B) {
+
162  using Eigen::Matrix;
+
163  using Eigen::Dynamic;
+
164 
+
165  Matrix<T, 1, Dynamic> result(A.size()+B.size());
+
166  result << A, B;
+
167  return result;
+
168  }
+
169 
+
170 
+
185  template <typename T1, typename T2, int R, int C>
+
186  inline Eigen::Matrix<typename return_type<T1, T2>::type,
+
187  1, Eigen::Dynamic>
+
188  append_col(const T1& A,
+
189  const Eigen::Matrix<T2, R, C>& B) {
+
190  using Eigen::Dynamic;
+
191  using Eigen::Matrix;
+
192  typedef typename return_type<T1, T2>::type return_type;
+
193 
+
194  Matrix<return_type, 1, Dynamic>
+
195  result(B.size() + 1);
+
196  result << A, B.template cast<return_type>();
+
197  return result;
+
198  }
+
199 
+
200 
+
215  template <typename T1, typename T2, int R, int C>
+
216  inline Eigen::Matrix<typename return_type<T1, T2>::type,
+
217  1, Eigen::Dynamic>
+
218  append_col(const Eigen::Matrix<T1, R, C>& A,
+
219  const T2& B) {
+
220  using Eigen::Dynamic;
+
221  using Eigen::Matrix;
+
222  typedef typename return_type<T1, T2>::type return_type;
+
223 
+
224  Matrix<return_type, 1, Dynamic>
+
225  result(A.size() + 1);
+
226  result << A.template cast<return_type>(), B;
+
227  return result;
+
228  }
+
229  }
+
230 
+
231 }
+
232 
+
233 #endif
+ + +
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > append_col(const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &B)
Return the result of appending the second argument matrix after the first argument matrix...
Definition: append_col.hpp:39
+
Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of...
Definition: return_type.hpp:19
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ +
+
+
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diff --git a/doc/api/html/append__row_8hpp.html b/doc/api/html/append__row_8hpp.html new file mode 100644 index 00000000000..cb1d2f3581d --- /dev/null +++ b/doc/api/html/append__row_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/append_row.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+ + +
+
+ +
+
append_row.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > stan::math::append_row (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &B)
 Return the result of stacking the rows of the first argument matrix on top of the second argument matrix. More...
 
template<typename T1 , typename T2 , int R1, int R2>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, 1 > stan::math::append_row (const Eigen::Matrix< T1, R1, 1 > &A, const Eigen::Matrix< T2, R2, 1 > &B)
 Return the result of stacking the first vector on top of the second vector, with the result being a vector. More...
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::append_row (const Eigen::Matrix< T, R1, C1 > &A, const Eigen::Matrix< T, R2, C2 > &B)
 Return the result of stacking the rows of the first argument matrix on top of the second argument matrix. More...
 
template<typename T , int R1, int R2>
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::append_row (const Eigen::Matrix< T, R1, 1 > &A, const Eigen::Matrix< T, R2, 1 > &B)
 Return the result of stacking the first vector on top of the second vector, with the result being a vector. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, 1 > stan::math::append_row (const T1 &A, const Eigen::Matrix< T2, R, C > &B)
 Return the result of stacking an scalar on top of the a vector, with the result being a vector. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, 1 > stan::math::append_row (const Eigen::Matrix< T1, R, C > &A, const T2 &B)
 Return the result of stacking a vector on top of the an scalar, with the result being a vector. More...
 
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diff --git a/doc/api/html/append__row_8hpp_source.html b/doc/api/html/append__row_8hpp_source.html new file mode 100644 index 00000000000..35d0feac4e5 --- /dev/null +++ b/doc/api/html/append__row_8hpp_source.html @@ -0,0 +1,244 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/append_row.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
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+ + +
+
+
+
append_row.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_APPEND_ROW_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_APPEND_ROW_HPP
+
3 
+ + + +
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
34  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
35  inline Eigen::Matrix<typename return_type<T1, T2>::type,
+
36  Eigen::Dynamic, Eigen::Dynamic>
+
37  append_row(const Eigen::Matrix<T1, R1, C1>& A,
+
38  const Eigen::Matrix<T2, R2, C2>& B) {
+
39  using Eigen::Dynamic;
+
40  using Eigen::Matrix;
+
41 
+
42  int Arows = A.rows();
+
43  int Brows = B.rows();
+
44  int Acols = A.cols();
+
45  int Bcols = B.cols();
+
46  check_size_match("append_row",
+
47  "columns of A", Acols,
+
48  "columns of B", Bcols);
+
49 
+
50  Matrix<typename return_type<T1, T2>::type, Dynamic, Dynamic>
+
51  result(Arows + Brows, Acols);
+
52  for (int j = 0; j < Acols; j++) {
+
53  for (int i = 0; i < Arows; i++)
+
54  result(i, j) = A(i, j);
+
55  for (int i = Arows, k = 0; k < Brows; i++, k++)
+
56  result(i, j) = B(k, j);
+
57  }
+
58  return result;
+
59  }
+
60 
+
61 
+
77  template <typename T1, typename T2, int R1, int R2>
+
78  inline Eigen::Matrix<typename return_type<T1, T2>::type,
+
79  Eigen::Dynamic, 1>
+
80  append_row(const Eigen::Matrix<T1, R1, 1>& A,
+
81  const Eigen::Matrix<T2, R2, 1>& B) {
+
82  using Eigen::Dynamic;
+
83  using Eigen::Matrix;
+
84 
+
85  int Asize = A.size();
+
86  int Bsize = B.size();
+
87  Matrix<typename return_type<T1, T2>::type, 1, Dynamic>
+
88  result(Asize + Bsize);
+
89  for (int i = 0; i < Asize; i++)
+
90  result(i) = A(i);
+
91  for (int i = 0, j = Asize; i < Bsize; i++, j++)
+
92  result(j) = B(i);
+
93  return result;
+
94  }
+
95 
+
96 
+
119  template <typename T, int R1, int C1, int R2, int C2>
+
120  inline Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
121  append_row(const Eigen::Matrix<T, R1, C1>& A,
+
122  const Eigen::Matrix<T, R2, C2>& B) {
+
123  using Eigen::Dynamic;
+
124  using Eigen::Matrix;
+
125 
+
126  check_size_match("append_row",
+
127  "columns of A", A.cols(),
+
128  "columns of B", B.cols());
+
129 
+
130  Matrix<T, Dynamic, Dynamic>
+
131  result(A.rows() + B.rows(), A.cols());
+
132  result << A, B;
+
133  return result;
+
134  }
+
135 
+
136 
+
153  template <typename T, int R1, int R2>
+
154  inline Eigen::Matrix<T, Eigen::Dynamic, 1>
+
155  append_row(const Eigen::Matrix<T, R1, 1>& A,
+
156  const Eigen::Matrix<T, R2, 1>& B) {
+
157  using Eigen::Dynamic;
+
158  using Eigen::Matrix;
+
159 
+
160  Matrix<T, Dynamic, 1> result(A.size()+B.size());
+
161  result << A, B;
+
162  return result;
+
163  }
+
164 
+
165 
+
179  template <typename T1, typename T2, int R, int C>
+
180  inline Eigen::Matrix<typename return_type<T1, T2>::type,
+
181  Eigen::Dynamic, 1>
+
182  append_row(const T1& A,
+
183  const Eigen::Matrix<T2, R, C>& B) {
+
184  using Eigen::Dynamic;
+
185  using Eigen::Matrix;
+
186  typedef typename return_type<T1, T2>::type return_type;
+
187 
+
188  Matrix<return_type, Dynamic, 1>
+
189  result(B.size() + 1);
+
190  result << A, B.template cast<return_type>();
+
191  return result;
+
192  }
+
193 
+
194 
+
208  template <typename T1, typename T2, int R, int C>
+
209  inline Eigen::Matrix<typename return_type<T1, T2>::type,
+
210  Eigen::Dynamic, 1>
+
211  append_row(const Eigen::Matrix<T1, R, C>& A,
+
212  const T2& B) {
+
213  using Eigen::Dynamic;
+
214  using Eigen::Matrix;
+
215  typedef typename return_type<T1, T2>::type return_type;
+
216 
+
217  Matrix<return_type, Dynamic, 1>
+
218  result(A.size() + 1);
+
219  result << A.template cast<return_type>(), B;
+
220  return result;
+
221  }
+
222 
+
223  }
+
224 
+
225 }
+
226 
+
227 #endif
+ + +
Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of...
Definition: return_type.hpp:19
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > append_row(const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &B)
Return the result of stacking the rows of the first argument matrix on top of the second argument mat...
Definition: append_row.hpp:37
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ +
+
+
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diff --git a/doc/api/html/arr_2err_2check__ordered_8hpp.html b/doc/api/html/arr_2err_2check__ordered_8hpp.html new file mode 100644 index 00000000000..b7d355fb1d4 --- /dev/null +++ b/doc/api/html/arr_2err_2check__ordered_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/err/check_ordered.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+
+ +
+
check_ordered.hpp File Reference
+
+
+
#include <stan/math/prim/arr/meta/index_type.hpp>
+#include <stan/math/prim/scal/err/domain_error.hpp>
+#include <stan/math/prim/scal/meta/error_index.hpp>
+#include <sstream>
+#include <string>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y >
bool stan::math::check_ordered (const char *function, const char *name, const std::vector< T_y > &y)
 Return true if the specified vector is sorted into strictly increasing order. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2err_2check__ordered_8hpp_source.html b/doc/api/html/arr_2err_2check__ordered_8hpp_source.html new file mode 100644 index 00000000000..27a7073e3f4 --- /dev/null +++ b/doc/api/html/arr_2err_2check__ordered_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/err/check_ordered.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+ +
+ + +
+
+
+
check_ordered.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_ERR_CHECK_ORDERED_HPP
+
2 #define STAN_MATH_PRIM_ARR_ERR_CHECK_ORDERED_HPP
+
3 
+ + + +
7 #include <sstream>
+
8 #include <string>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
29  template <typename T_y>
+
30  bool check_ordered(const char* function,
+
31  const char* name,
+
32  const std::vector<T_y>& y) {
+
33  if (y.size() == 0)
+
34  return true;
+
35 
+
36  for (size_t n = 1; n < y.size(); n++) {
+
37  if (!(y[n] > y[n-1])) {
+
38  std::ostringstream msg1;
+
39  msg1 << "is not a valid ordered vector."
+
40  << " The element at " << stan::error_index::value + n
+
41  << " is ";
+
42  std::string msg1_str(msg1.str());
+
43  std::ostringstream msg2;
+
44  msg2 << ", but should be greater than the previous element, "
+
45  << y[n-1];
+
46  std::string msg2_str(msg2.str());
+
47  domain_error(function, name, y[n],
+
48  msg1_str.c_str(), msg2_str.c_str());
+
49  return false;
+
50  }
+
51  }
+
52  return true;
+
53  }
+
54  }
+
55 }
+
56 #endif
+ + +
bool check_ordered(const char *function, const char *name, const std::vector< T_y > &y)
Return true if the specified vector is sorted into strictly increasing order.
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
+
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diff --git a/doc/api/html/arr_2fun_2fill_8hpp.html b/doc/api/html/arr_2fun_2fill_8hpp.html new file mode 100644 index 00000000000..e7c1c1d832c --- /dev/null +++ b/doc/api/html/arr_2fun_2fill_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/fill.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+
fill.hpp File Reference
+
+
+
#include <stan/math/prim/scal/fun/fill.hpp>
+#include <vector>
+
+

Go to the source code of this file.

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 Matrices and templated mathematical functions.
 
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template<typename T , typename S >
void stan::math::fill (std::vector< T > &x, const S &y)
 Fill the specified container with the specified value. More...
 
+
+
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diff --git a/doc/api/html/arr_2fun_2fill_8hpp_source.html b/doc/api/html/arr_2fun_2fill_8hpp_source.html new file mode 100644 index 00000000000..185c26dc9a8 --- /dev/null +++ b/doc/api/html/arr_2fun_2fill_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/fill.hpp Source File + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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fill.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_FUN_FILL_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_FILL_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
21  template <typename T, typename S>
+
22  void fill(std::vector<T>& x, const S& y) {
+
23  for (size_t i = 0; i < x.size(); ++i)
+
24  fill(x[i], y);
+
25  }
+
26 
+
27  }
+
28 }
+
29 #endif
+ + +
void fill(std::vector< T > &x, const S &y)
Fill the specified container with the specified value.
Definition: fill.hpp:22
+
+
+
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diff --git a/doc/api/html/arr_2fun_2promote__scalar_8hpp.html b/doc/api/html/arr_2fun_2promote__scalar_8hpp.html new file mode 100644 index 00000000000..8e2e50680ce --- /dev/null +++ b/doc/api/html/arr_2fun_2promote__scalar_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/promote_scalar.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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+
promote_scalar.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::math::promote_scalar_struct< T, std::vector< S > >
 Struct to hold static function for promoting underlying scalar types. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2fun_2promote__scalar_8hpp_source.html b/doc/api/html/arr_2fun_2promote__scalar_8hpp_source.html new file mode 100644 index 00000000000..f13ecc98198 --- /dev/null +++ b/doc/api/html/arr_2fun_2promote__scalar_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/promote_scalar.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
promote_scalar.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_FUN_PROMOTE_SCALAR_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_PROMOTE_SCALAR_HPP
+
3 
+ + + +
7 #include <vector>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
21  template <typename T, typename S>
+
22  struct promote_scalar_struct<T, std::vector<S> > {
+
31  static std::vector<typename promote_scalar_type<T, S>::type>
+
32  apply(const std::vector<S>& x) {
+
33  typedef std::vector<typename promote_scalar_type<T, S>::type> return_t;
+
34  typedef typename index_type<return_t>::type idx_t;
+
35  return_t y(x.size());
+
36  for (idx_t i = 0; i < x.size(); ++i)
+ +
38  return y;
+
39  }
+
40  };
+
41 
+
42  }
+
43 }
+
44 #endif
+ + + +
static std::vector< typename promote_scalar_type< T, S >::type > apply(const std::vector< S > &x)
Return the standard vector consisting of the recursive promotion of the elements of the input standar...
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
General struct to hold static function for promoting underlying scalar types.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2fun_2promote__scalar__type_8hpp.html b/doc/api/html/arr_2fun_2promote__scalar__type_8hpp.html new file mode 100644 index 00000000000..9c949b7fa0b --- /dev/null +++ b/doc/api/html/arr_2fun_2promote__scalar__type_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/promote_scalar_type.hpp File Reference + + + + + + + + + + +
+
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+ +
+
promote_scalar_type.hpp File Reference
+
+
+
#include <stan/math/prim/scal/fun/promote_scalar_type.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::math::promote_scalar_type< T, std::vector< S > >
 Template metaprogram to calculate a type for a container whose underlying scalar is converted from the second template parameter type to the first. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2fun_2promote__scalar__type_8hpp_source.html b/doc/api/html/arr_2fun_2promote__scalar__type_8hpp_source.html new file mode 100644 index 00000000000..1fac7f74b8e --- /dev/null +++ b/doc/api/html/arr_2fun_2promote__scalar__type_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/promote_scalar_type.hpp Source File + + + + + + + + + + +
+
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promote_scalar_type.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_FUN_PROMOTE_SCALAR_TYPE_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_PROMOTE_SCALAR_TYPE_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
18  template <typename T, typename S>
+
19  struct promote_scalar_type<T, std::vector<S> > {
+
23  typedef std::vector<typename promote_scalar_type<T, S>::type> type;
+
24  };
+
25 
+
26  }
+
27 }
+
28 #endif
+ + +
Template metaprogram to calculate a type for converting a convertible type.
+ +
std::vector< typename promote_scalar_type< T, S >::type > type
The promoted type.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2fun_2to__fvar_8hpp.html b/doc/api/html/arr_2fun_2to__fvar_8hpp.html new file mode 100644 index 00000000000..aa7376609a0 --- /dev/null +++ b/doc/api/html/arr_2fun_2to__fvar_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/arr/fun/to_fvar.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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+
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+ +
+
to_fvar.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/fwd/scal/fun/to_fvar.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

template<typename T >
std::vector< fvar< T > > stan::math::to_fvar (const std::vector< T > &v)
 
template<typename T >
std::vector< fvar< T > > stan::math::to_fvar (const std::vector< T > &v, const std::vector< T > &d)
 
template<typename T >
std::vector< fvar< T > > stan::math::to_fvar (const std::vector< fvar< T > > &v)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2fun_2to__fvar_8hpp_source.html b/doc/api/html/arr_2fun_2to__fvar_8hpp_source.html new file mode 100644 index 00000000000..04288c88dc5 --- /dev/null +++ b/doc/api/html/arr_2fun_2to__fvar_8hpp_source.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/fwd/arr/fun/to_fvar.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+
+
+
to_fvar.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_ARR_FUN_TO_FVAR_HPP
+
2 #define STAN_MATH_FWD_ARR_FUN_TO_FVAR_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template<typename T>
+
12  inline
+
13  std::vector<fvar<T> >
+
14  to_fvar(const std::vector<T>& v) {
+
15  std::vector<fvar<T> > x(v.size());
+
16  for (size_t i = 0; i < v.size(); ++i)
+
17  x[i] = T(v[i]);
+
18  return x;
+
19  }
+
20 
+
21  template<typename T>
+
22  inline
+
23  std::vector<fvar<T> >
+
24  to_fvar(const std::vector<T>& v, const std::vector<T>& d) {
+
25  std::vector<fvar<T> > x(v.size());
+
26  for (size_t i = 0; i < v.size(); ++i)
+
27  x[i] = fvar<T>(v[i], d[i]);
+
28  return x;
+
29  }
+
30 
+
31  template<typename T>
+
32  inline
+
33  std::vector<fvar<T> >
+
34  to_fvar(const std::vector<fvar<T> >& v) {
+
35  return v;
+
36  }
+
37 
+
38  }
+
39 }
+
40 #endif
+ + +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2fun_2to__var_8hpp.html b/doc/api/html/arr_2fun_2to__var_8hpp.html new file mode 100644 index 00000000000..24cc3e60a5d --- /dev/null +++ b/doc/api/html/arr_2fun_2to__var_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/fun/to_var.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
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+
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+ + +
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+ +
+
to_var.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/scal/fun/to_var.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

std::vector< var > stan::math::to_var (const std::vector< double > &v)
 Converts argument to an automatic differentiation variable. More...
 
std::vector< var > stan::math::to_var (const std::vector< var > &v)
 Converts argument to an automatic differentiation variable. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2fun_2to__var_8hpp_source.html b/doc/api/html/arr_2fun_2to__var_8hpp_source.html new file mode 100644 index 00000000000..f57d1e3c807 --- /dev/null +++ b/doc/api/html/arr_2fun_2to__var_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/fun/to_var.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+ + + + + + +
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+
+
+
to_var.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_ARR_FUN_TO_VAR_HPP
+
2 #define STAN_MATH_REV_ARR_FUN_TO_VAR_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
19  inline std::vector<var>
+
20  to_var(const std::vector<double>& v) {
+
21  std::vector<var> var_vector(v.size());
+
22  for (size_t n = 0; n < v.size(); n++)
+
23  var_vector[n] = v[n];
+
24  return var_vector;
+
25  }
+
34  inline std::vector<var>
+
35  to_var(const std::vector<var>& v) {
+
36  return v;
+
37  }
+
38 
+
39  }
+
40 }
+
41 #endif
+ + + +
std::vector< var > to_var(const std::vector< double > &v)
Converts argument to an automatic differentiation variable.
Definition: to_var.hpp:20
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2_vector_builder_helper_8hpp.html b/doc/api/html/arr_2meta_2_vector_builder_helper_8hpp.html new file mode 100644 index 00000000000..efebd01468f --- /dev/null +++ b/doc/api/html/arr_2meta_2_vector_builder_helper_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/VectorBuilderHelper.hpp File Reference + + + + + + + + + + +
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+ +
+
VectorBuilderHelper.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/VectorBuilderHelper.hpp>
+#include <stdexcept>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

class  stan::VectorBuilderHelper< T1, true, true >
 Template specialization for using a vector. More...
 
+ + + +

+Namespaces

 stan
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2_vector_builder_helper_8hpp_source.html b/doc/api/html/arr_2meta_2_vector_builder_helper_8hpp_source.html new file mode 100644 index 00000000000..b1e1d9a2c68 --- /dev/null +++ b/doc/api/html/arr_2meta_2_vector_builder_helper_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/VectorBuilderHelper.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+
VectorBuilderHelper.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_META_VECTORBUILDER_HELPER_HPP
+
2 #define STAN_MATH_PRIM_ARR_META_VECTORBUILDER_HELPER_HPP
+
3 
+ +
5 #include <stdexcept>
+
6 #include <vector>
+
7 
+
8 namespace stan {
+
9 
+
13  template<typename T1>
+
14  class VectorBuilderHelper<T1, true, true> {
+
15  private:
+
16  std::vector<T1> x_;
+
17  public:
+
18  explicit VectorBuilderHelper(size_t n) : x_(n) { }
+
19 
+
20  typedef std::vector<T1> type;
+
21 
+
22  T1& operator[](size_t i) {
+
23  return x_[i];
+
24  }
+
25 
+
26  inline type& data() {
+
27  return x_;
+
28  }
+
29  };
+
30 }
+
31 #endif
+ + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2_vector_view_8hpp.html b/doc/api/html/arr_2meta_2_vector_view_8hpp.html new file mode 100644 index 00000000000..5cff9801560 --- /dev/null +++ b/doc/api/html/arr_2meta_2_vector_view_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/VectorView.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+ + + + + + +
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+
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+
VectorView.hpp File Reference
+
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+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2_vector_view_8hpp_source.html b/doc/api/html/arr_2meta_2_vector_view_8hpp_source.html new file mode 100644 index 00000000000..e342925d56b --- /dev/null +++ b/doc/api/html/arr_2meta_2_vector_view_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/VectorView.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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+
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+
+
+
VectorView.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_ARR_SCAL_META_VECTORVIEW_HPP
+
2 #define STAN_MATH_ARR_SCAL_META_VECTORVIEW_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  template <typename T>
+
10  class VectorView<std::vector<T>, true, false> {
+
11  public:
+
12  typedef typename scalar_type<T>::type scalar_t;
+
13 
+
14  template <typename X>
+
15  explicit VectorView(X& x) : x_(&x[0]) { }
+
16 
+
17  scalar_t& operator[](int i) {
+
18  return x_[i];
+
19  }
+
20 
+
21  private:
+
22  scalar_t* x_;
+
23  };
+
24 
+
25  template <typename T>
+
26  class VectorView<const std::vector<T>, true, false> {
+
27  public:
+
28  typedef typename boost::add_const<typename scalar_type<T>::type>::type
+ +
30 
+
31  template <typename X>
+
32  explicit VectorView(X& x) : x_(&x[0]) { }
+
33 
+
34  scalar_t& operator[](int i) const {
+
35  return x_[i];
+
36  }
+
37  private:
+
38  scalar_t* x_;
+
39  };
+
40 
+
41 }
+
42 #endif
+ + + +
boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
Definition: VectorView.hpp:54
+
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+ + + + +
boost::add_const< typename scalar_type< T >::type >::type scalar_t
Definition: VectorView.hpp:29
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2container__view_8hpp.html b/doc/api/html/arr_2meta_2container__view_8hpp.html new file mode 100644 index 00000000000..9fb70b40fcb --- /dev/null +++ b/doc/api/html/arr_2meta_2container__view_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/container_view.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+ + + + + + +
+
+ + +
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+
+ +
+
container_view.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/container_view.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

class  stan::math::container_view< std::vector< T1 >, T2 >
 Template specialization for scalar view of array y with scalar type T2 with proper indexing inferred from input vector x of scalar type T1. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2container__view_8hpp_source.html b/doc/api/html/arr_2meta_2container__view_8hpp_source.html new file mode 100644 index 00000000000..d640a63a09e --- /dev/null +++ b/doc/api/html/arr_2meta_2container__view_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/container_view.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
container_view.hpp
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+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_META_CONTAINER_VIEW_HPP
+
2 #define STAN_MATH_PRIM_ARR_META_CONTAINER_VIEW_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
19  template <typename T1, typename T2>
+
20  class container_view<std::vector<T1>, T2> {
+
21  public:
+
28  container_view(const std::vector<T1>& x, T2* y)
+
29  : y_(y) { }
+
30 
+
37  T2& operator[](int i) {
+
38  return y_[i];
+
39  }
+
40  private:
+
41  T2* y_;
+
42  };
+
43  }
+
44 }
+
45 
+
46 #endif
+
container_view(const std::vector< T1 > &x, T2 *y)
Constructor.
+ + +
T2 & operator[](int i)
operator[](int i) returns reference to scalar view indexed at i
+
Primary template class for container view of array y with same structure as T1 and size as x...
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2get_8hpp.html b/doc/api/html/arr_2meta_2get_8hpp.html new file mode 100644 index 00000000000..1dd71dfd467 --- /dev/null +++ b/doc/api/html/arr_2meta_2get_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/get.hpp File Reference + + + + + + + + + + +
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#include <cstdlib>
+#include <vector>
+
+

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template<typename T >
stan::get (const std::vector< T > &x, size_t n)
 
+
+
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diff --git a/doc/api/html/arr_2meta_2get_8hpp_source.html b/doc/api/html/arr_2meta_2get_8hpp_source.html new file mode 100644 index 00000000000..2c609a97c19 --- /dev/null +++ b/doc/api/html/arr_2meta_2get_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/get.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
+
+
get.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_META_GET_HPP
+
2 #define STAN_MATH_PRIM_ARR_META_GET_HPP
+
3 
+
4 #include <cstdlib>
+
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  template <typename T>
+
10  inline T get(const std::vector<T>& x, size_t n) {
+
11  return x[n];
+
12  }
+
13 
+
14 }
+
15 #endif
+
16 
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2index__type_8hpp.html b/doc/api/html/arr_2meta_2index__type_8hpp.html new file mode 100644 index 00000000000..5d28c934fa2 --- /dev/null +++ b/doc/api/html/arr_2meta_2index__type_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/index_type.hpp File Reference + + + + + + + + + + +
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index_type.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/index_type.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::math::index_type< std::vector< T > >
 Template metaprogram class to compute the type of index for a standard vector. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2index__type_8hpp_source.html b/doc/api/html/arr_2meta_2index__type_8hpp_source.html new file mode 100644 index 00000000000..7637b6d458e --- /dev/null +++ b/doc/api/html/arr_2meta_2index__type_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/index_type.hpp Source File + + + + + + + + + + +
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index_type.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_META_INDEX_TYPE_HPP
+
2 #define STAN_MATH_PRIM_ARR_META_INDEX_TYPE_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
17  template <typename T>
+
18  struct index_type<std::vector<T> > {
+
22  typedef typename std::vector<T>::size_type type;
+
23  };
+
24 
+
25 
+
26  }
+
27 }
+
28 
+
29 
+
30 #endif
+ + +
std::vector< T >::size_type type
Typedef for index of standard vectors.
Definition: index_type.hpp:22
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
+
+
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diff --git a/doc/api/html/arr_2meta_2is__constant__struct_8hpp.html b/doc/api/html/arr_2meta_2is__constant__struct_8hpp.html new file mode 100644 index 00000000000..c07e82156f5 --- /dev/null +++ b/doc/api/html/arr_2meta_2is__constant__struct_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/is_constant_struct.hpp File Reference + + + + + + + + + + +
+
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is_constant_struct.hpp File Reference
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diff --git a/doc/api/html/arr_2meta_2is__constant__struct_8hpp_source.html b/doc/api/html/arr_2meta_2is__constant__struct_8hpp_source.html new file mode 100644 index 00000000000..c924552e2a9 --- /dev/null +++ b/doc/api/html/arr_2meta_2is__constant__struct_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/is_constant_struct.hpp Source File + + + + + + + + + + +
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+
is_constant_struct.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_META_IS_CONSTANT_STRUCT_HPP
+
2 #define STAN_MATH_PRIM_ARR_META_IS_CONSTANT_STRUCT_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9 
+
10  template <typename T>
+
11  struct is_constant_struct<std::vector<T> > {
+ +
13  };
+
14 
+
15 }
+
16 #endif
+
17 
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2is__vector_8hpp.html b/doc/api/html/arr_2meta_2is__vector_8hpp.html new file mode 100644 index 00000000000..d068927cb34 --- /dev/null +++ b/doc/api/html/arr_2meta_2is__vector_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/is_vector.hpp File Reference + + + + + + + + + + +
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+
is_vector.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/is_vector.hpp>
+#include <vector>
+
+

Go to the source code of this file.

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struct  stan::is_vector< const T >
 
struct  stan::is_vector< std::vector< T > >
 
+ + + +

+Namespaces

 stan
 
+
+
+
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diff --git a/doc/api/html/arr_2meta_2is__vector_8hpp_source.html b/doc/api/html/arr_2meta_2is__vector_8hpp_source.html new file mode 100644 index 00000000000..eed89abba5a --- /dev/null +++ b/doc/api/html/arr_2meta_2is__vector_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/is_vector.hpp Source File + + + + + + + + + + +
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+
is_vector.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_META_IS_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_ARR_META_IS_VECTOR_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  // FIXME: use boost::type_traits::remove_all_extents to
+
10  // extend to array/ptr types
+
11 
+
12  template <typename T>
+
13  struct is_vector<const T> {
+ +
15  typedef T type;
+
16  };
+
17  template <typename T>
+
18  struct is_vector<std::vector<T> > {
+
19  enum { value = 1 };
+
20  typedef T type;
+
21  };
+
22 }
+
23 #endif
+
24 
+ + + + + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2length_8hpp.html b/doc/api/html/arr_2meta_2length_8hpp.html new file mode 100644 index 00000000000..53bd1488216 --- /dev/null +++ b/doc/api/html/arr_2meta_2length_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/length.hpp File Reference + + + + + + + + + + +
+
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length.hpp File Reference
+
+
+
#include <cstdlib>
+#include <vector>
+
+

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+ + + + +

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 stan
 
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+Functions

template<typename T >
size_t stan::length (const std::vector< T > &x)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2length_8hpp_source.html b/doc/api/html/arr_2meta_2length_8hpp_source.html new file mode 100644 index 00000000000..2383c748d3e --- /dev/null +++ b/doc/api/html/arr_2meta_2length_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/length.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
+
length.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_META_LENGTH_HPP
+
2 #define STAN_MATH_PRIM_ARR_META_LENGTH_HPP
+
3 
+
4 #include <cstdlib>
+
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  template <typename T>
+
10  size_t length(const std::vector<T>& x) {
+
11  return x.size();
+
12  }
+
13 }
+
14 #endif
+
15 
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2value__type_8hpp.html b/doc/api/html/arr_2meta_2value__type_8hpp.html new file mode 100644 index 00000000000..2e540faff46 --- /dev/null +++ b/doc/api/html/arr_2meta_2value__type_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/value_type.hpp File Reference + + + + + + + + + + +
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+ +
+
value_type.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/value_type.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::math::value_type< std::vector< T > >
 Template metaprogram class to compute the type of values stored in a standard vector. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/arr_2meta_2value__type_8hpp_source.html b/doc/api/html/arr_2meta_2value__type_8hpp_source.html new file mode 100644 index 00000000000..b080aa6e425 --- /dev/null +++ b/doc/api/html/arr_2meta_2value__type_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/meta/value_type.hpp Source File + + + + + + + + + + +
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value_type.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_META_VALUE_TYPE_HPP
+
2 #define STAN_MATH_PRIM_ARR_META_VALUE_TYPE_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
16  template <typename T>
+
17  struct value_type<std::vector<T> > {
+
22  typedef typename std::vector<T>::value_type type;
+
23  };
+
24 
+
25  }
+
26 }
+
27 #endif
+ + +
std::vector< T >::value_type type
Type of value stored in a standard vector with type T entries.
Definition: value_type.hpp:22
+ +
Primary template class for metaprogram to compute the type of values stored in a container.
Definition: value_type.hpp:18
+
+
+
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diff --git a/doc/api/html/array__builder_8hpp.html b/doc/api/html/array__builder_8hpp.html new file mode 100644 index 00000000000..296dd0df7b0 --- /dev/null +++ b/doc/api/html/array__builder_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/array_builder.hpp File Reference + + + + + + + + + + +
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array_builder.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/promoter.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::math::array_builder< T >
 Structure for building up arrays in an expression (rather than in statements) using an argumentchaining add() method and a getter method array() to return the result. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/array__builder_8hpp_source.html b/doc/api/html/array__builder_8hpp_source.html new file mode 100644 index 00000000000..944132ebe1d --- /dev/null +++ b/doc/api/html/array__builder_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/array_builder.hpp Source File + + + + + + + + + + +
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+ + + + + + + +
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array_builder.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_ARRAY_BUILDER_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ARRAY_BUILDER_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
15  template <typename T>
+
16  struct array_builder {
+
17  std::vector<T> x_;
+
18  array_builder() : x_() { }
+
19  template <typename F>
+
20  array_builder& add(const F& u) {
+
21  T t;
+ +
23  x_.push_back(t);
+
24  return *this;
+
25  }
+
26  std::vector<T> array() {
+
27  return x_;
+
28  }
+
29  };
+
30 
+
31  }
+
32 }
+
33 #endif
+ + +
std::vector< T > array()
+
array_builder & add(const F &u)
+ + +
Structure for building up arrays in an expression (rather than in statements) using an argumentchaini...
+
static void promote(const F &u, T &t)
Definition: promoter.hpp:15
+
+
+
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+
assign.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/scal/err/invalid_argument.hpp>
+#include <stan/math/prim/scal/err/check_size_match.hpp>
+#include <stan/math/prim/mat/err/check_matching_sizes.hpp>
+#include <stan/math/prim/mat/err/check_matching_dims.hpp>
+#include <iostream>
+#include <sstream>
+#include <stdexcept>
+#include <string>
+#include <vector>
+
+

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+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

void stan::math::print_mat_size (int n, std::ostream &o)
 Helper function to return the matrix size as either "dynamic" or "1". More...
 
template<typename LHS , typename RHS >
void stan::math::assign (LHS &lhs, const RHS &rhs)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename LHS , typename RHS , int R1, int C1, int R2, int C2>
void stan::math::assign (Eigen::Matrix< LHS, R1, C1 > &x, const Eigen::Matrix< RHS, R2, C2 > &y)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename LHS , typename RHS , int R, int C>
void stan::math::assign (Eigen::Matrix< LHS, R, C > &x, const Eigen::Matrix< RHS, R, C > &y)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename LHS , typename RHS , int R, int C>
void stan::math::assign (Eigen::Block< LHS > x, const Eigen::Matrix< RHS, R, C > &y)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename LHS , typename RHS >
void stan::math::assign (std::vector< LHS > &x, const std::vector< RHS > &y)
 Copy the right-hand side's value to the left-hand side variable. More...
 
+
+
+
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diff --git a/doc/api/html/assign_8hpp_source.html b/doc/api/html/assign_8hpp_source.html new file mode 100644 index 00000000000..f42c919b58f --- /dev/null +++ b/doc/api/html/assign_8hpp_source.html @@ -0,0 +1,213 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/assign.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
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+ + +
+
+
+
assign.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_ASSIGN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ASSIGN_HPP
+
3 
+ + + + + +
9 #include <iostream>
+
10 #include <sstream>
+
11 #include <stdexcept>
+
12 #include <string>
+
13 #include <vector>
+
14 
+
15 namespace stan {
+
16 
+
17  namespace math {
+
18 
+
26  void print_mat_size(int n, std::ostream& o) {
+
27  if (n == Eigen::Dynamic)
+
28  o << "dynamically sized";
+
29  else
+
30  o << n;
+
31  }
+
32 
+
33  // Recursive assignment with size match checking and promotion
+
34 
+
49  template <typename LHS, typename RHS>
+
50  inline void
+
51  assign(LHS& lhs, const RHS& rhs) {
+
52  lhs = rhs;
+
53  }
+
54 
+
75  template <typename LHS, typename RHS, int R1, int C1, int R2, int C2>
+
76  inline void
+
77  assign(Eigen::Matrix<LHS, R1, C1>& x,
+
78  const Eigen::Matrix<RHS, R2, C2>& y) {
+
79  std::stringstream ss;
+
80  ss << "shapes must match, but found"
+
81  << " left-hand side rows=";
+
82  print_mat_size(R1, ss);
+
83  ss << "; left-hand side cols=";
+
84  print_mat_size(C1, ss);
+
85  ss << "; right-hand side rows=";
+
86  print_mat_size(R2, ss);
+
87  ss << "; right-hand side cols=";
+
88  print_mat_size(C2, ss);
+
89  std::string ss_str(ss.str());
+
90  invalid_argument("assign(Eigen::Matrix, Eigen::Matrix)",
+
91  "", "", ss_str.c_str());
+
92  }
+
93 
+
111  template <typename LHS, typename RHS, int R, int C>
+
112  inline void
+
113  assign(Eigen::Matrix<LHS, R, C>& x,
+
114  const Eigen::Matrix<RHS, R, C>& y) {
+ +
116  "left-hand-side", x,
+
117  "right-hand-side", y);
+
118  for (int i = 0; i < x.size(); ++i)
+
119  assign(x(i), y(i));
+
120  }
+
121 
+
140  template <typename LHS, typename RHS, int R, int C>
+
141  inline void
+
142  assign(Eigen::Block<LHS> x,
+
143  const Eigen::Matrix<RHS, R, C>& y) {
+ +
145  "left-hand side rows", x.rows(),
+
146  "right-hand side rows", y.rows());
+ +
148  "left-hand side cols", x.cols(),
+
149  "right-hand side cols", y.cols());
+
150  for (int n = 0; n < y.cols(); ++n)
+
151  for (int m = 0; m < y.rows(); ++m)
+
152  assign(x(m, n), y(m, n));
+
153  }
+
154 
+
155 
+
175  template <typename LHS, typename RHS>
+
176  inline void
+
177  assign(std::vector<LHS>& x, const std::vector<RHS>& y) {
+ +
179  "left-hand side", x,
+
180  "right-hand side", y);
+
181  for (size_t i = 0; i < x.size(); ++i)
+
182  assign(x[i], y[i]);
+
183  }
+
184 
+
185  }
+
186 }
+
187 #endif
+ + + + + +
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ +
void assign(LHS &lhs, const RHS &rhs)
Copy the right-hand side's value to the left-hand side variable.
Definition: assign.hpp:51
+
void print_mat_size(int n, std::ostream &o)
Helper function to return the matrix size as either "dynamic" or "1".
Definition: assign.hpp:26
+
+
+
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diff --git a/doc/api/html/autocorrelation_8hpp.html b/doc/api/html/autocorrelation_8hpp.html new file mode 100644 index 00000000000..495fc84b13d --- /dev/null +++ b/doc/api/html/autocorrelation_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/autocorrelation.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+
+ + +
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+ + +
+
+ +
+
autocorrelation.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/mean.hpp>
+#include <unsupported/Eigen/FFT>
+#include <complex>
+#include <vector>
+
+

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+ + + + + + + + + +

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template<typename T >
void stan::math::autocorrelation (const std::vector< T > &y, std::vector< T > &ac, Eigen::FFT< T > &fft)
 Write autocorrelation estimates for every lag for the specified input sequence into the specified result using the specified FFT engine. More...
 
template<typename T >
void stan::math::autocorrelation (const std::vector< T > &y, std::vector< T > &ac)
 Write autocorrelation estimates for every lag for the specified input sequence into the specified result. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/autocorrelation_8hpp_source.html b/doc/api/html/autocorrelation_8hpp_source.html new file mode 100644 index 00000000000..00421396e3e --- /dev/null +++ b/doc/api/html/autocorrelation_8hpp_source.html @@ -0,0 +1,207 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/autocorrelation.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + + + + + +
+
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+ + +
+
+
+
autocorrelation.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_AUTOCORRELATION_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_AUTOCORRELATION_HPP
+
3 
+ +
5 #include <unsupported/Eigen/FFT>
+
6 #include <complex>
+
7 #include <vector>
+
8 
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  namespace {
+
19  size_t fft_next_good_size(size_t N) {
+
20  if (N <= 2) return 2;
+
21  while (true) {
+
22  size_t m = N;
+
23  while ((m % 2) == 0) m /= 2;
+
24  while ((m % 3) == 0) m /= 3;
+
25  while ((m % 5) == 0) m /= 5;
+
26  if (m <= 1)
+
27  return N;
+
28  N++;
+
29  }
+
30  }
+
31  }
+
32 
+
53  template <typename T>
+
54  void autocorrelation(const std::vector<T>& y,
+
55  std::vector<T>& ac,
+
56  Eigen::FFT<T>& fft) {
+
57  using std::vector;
+
58  using std::complex;
+
59 
+
60  size_t N = y.size();
+
61  size_t M = fft_next_good_size(N);
+
62  size_t Mt2 = 2 * M;
+
63 
+
64 
+
65  vector<complex<T> > freqvec;
+
66 
+
67  // centered_signal = y-mean(y) followed by N zeroes
+
68  vector<T> centered_signal(y);
+
69  centered_signal.insert(centered_signal.end(), Mt2-N, 0.0);
+
70  T mean = stan::math::mean(y);
+
71  for (size_t i = 0; i < N; i++)
+
72  centered_signal[i] -= mean;
+
73 
+
74  fft.fwd(freqvec, centered_signal);
+
75  for (size_t i = 0; i < Mt2; ++i)
+
76  freqvec[i] = complex<T>(norm(freqvec[i]), 0.0);
+
77 
+
78  fft.inv(ac, freqvec);
+
79  ac.resize(N);
+
80 
+
81  /*
+
82  vector<T> mask_correction_factors;
+
83  vector<T> mask;
+
84  mask.insert(mask.end(), N, 1.0);
+
85  mask.insert(mask.end(), N, 0.0);
+
86 
+
87  freqvec.resize(0);
+
88  fft.fwd(freqvec, mask);
+
89  for (size_t i = 0; i < Nt2; ++i)
+
90  freqvec[i] = complex<T>(norm(freqvec[i]), 0.0);
+
91 
+
92  fft.inv(mask_correction_factors, freqvec);
+
93 
+
94  for (size_t i = 0; i < N; ++i) {
+
95  ac[i] /= mask_correction_factors[i];
+
96  }
+
97  */
+
98  for (size_t i = 0; i < N; ++i) {
+
99  ac[i] /= (N - i);
+
100  }
+
101  T var = ac[0];
+
102  for (size_t i = 0; i < N; ++i)
+
103  ac[i] /= var;
+
104  }
+
105 
+
122  template <typename T>
+
123  void autocorrelation(const std::vector<T>& y,
+
124  std::vector<T>& ac) {
+
125  Eigen::FFT<T> fft;
+
126  return autocorrelation(y, ac, fft);
+
127  }
+
128 
+
129 
+
130  }
+
131 }
+
132 
+
133 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
boost::math::tools::promote_args< T >::type mean(const std::vector< T > &v)
Returns the sample mean (i.e., average) of the coefficients in the specified standard vector...
Definition: mean.hpp:23
+
void autocorrelation(const std::vector< T > &y, std::vector< T > &ac, Eigen::FFT< T > &fft)
Write autocorrelation estimates for every lag for the specified input sequence into the specified res...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/autocovariance_8hpp.html b/doc/api/html/autocovariance_8hpp.html new file mode 100644 index 00000000000..2ece9261446 --- /dev/null +++ b/doc/api/html/autocovariance_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/autocovariance.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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autocovariance.hpp File Reference
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+
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+ + + + + + + +

+Namespaces

 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + + + + + + +

+Functions

template<typename T >
void stan::math::autocovariance (const std::vector< T > &y, std::vector< T > &acov, Eigen::FFT< T > &fft)
 Write autocovariance estimates for every lag for the specified input sequence into the specified result using the specified FFT engine. More...
 
template<typename T >
void stan::math::autocovariance (const std::vector< T > &y, std::vector< T > &acov)
 Write autocovariance estimates for every lag for the specified input sequence into the specified result. More...
 
+
+
+
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diff --git a/doc/api/html/autocovariance_8hpp_source.html b/doc/api/html/autocovariance_8hpp_source.html new file mode 100644 index 00000000000..138334e0964 --- /dev/null +++ b/doc/api/html/autocovariance_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/autocovariance.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
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+ + + + + + +
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+
+
+
autocovariance.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_AUTOCOVARIANCE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_AUTOCOVARIANCE_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12 
+
33  template <typename T>
+
34  void autocovariance(const std::vector<T>& y,
+
35  std::vector<T>& acov,
+
36  Eigen::FFT<T>& fft) {
+
37  stan::math::autocorrelation(y, acov, fft);
+
38 
+
39  T var = stan::math::variance(y) * (y.size()-1) / y.size();
+
40  for (size_t i = 0; i < y.size(); i++) {
+
41  acov[i] *= var;
+
42  }
+
43  }
+
44 
+
61  template <typename T>
+
62  void autocovariance(const std::vector<T>& y,
+
63  std::vector<T>& acov) {
+
64  Eigen::FFT<T> fft;
+
65  autocovariance(y, acov, fft);
+
66  }
+
67 
+
68 
+
69  }
+
70 }
+
71 
+
72 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
boost::math::tools::promote_args< T >::type variance(const std::vector< T > &v)
Returns the sample variance (divide by length - 1) of the coefficients in the specified standard vect...
Definition: variance.hpp:24
+
void autocovariance(const std::vector< T > &y, std::vector< T > &acov, Eigen::FFT< T > &fft)
Write autocovariance estimates for every lag for the specified input sequence into the specified resu...
+
void autocorrelation(const std::vector< T > &y, std::vector< T > &ac, Eigen::FFT< T > &fft)
Write autocorrelation estimates for every lag for the specified input sequence into the specified res...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/autodiffstackstorage_8hpp.html b/doc/api/html/autodiffstackstorage_8hpp.html new file mode 100644 index 00000000000..e192df146a1 --- /dev/null +++ b/doc/api/html/autodiffstackstorage_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/autodiffstackstorage.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
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+
autodiffstackstorage.hpp File Reference
+
+
+
#include <stan/math/memory/stack_alloc.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + +

+Classes

struct  stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
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diff --git a/doc/api/html/autodiffstackstorage_8hpp_source.html b/doc/api/html/autodiffstackstorage_8hpp_source.html new file mode 100644 index 00000000000..3d856ff91cb --- /dev/null +++ b/doc/api/html/autodiffstackstorage_8hpp_source.html @@ -0,0 +1,176 @@ + + + + + + +Stan Math Library: stan/math/rev/core/autodiffstackstorage.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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autodiffstackstorage.hpp
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1 #ifndef STAN_MATH_REV_CORE_AUTODIFFSTACKSTORAGE_HPP
+
2 #define STAN_MATH_REV_CORE_AUTODIFFSTACKSTORAGE_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template<typename ChainableT,
+
11  typename ChainableAllocT>
+ +
13  static std::vector<ChainableT*> var_stack_;
+
14  static std::vector<ChainableT*> var_nochain_stack_;
+
15  static std::vector<ChainableAllocT*> var_alloc_stack_;
+ +
17 
+
18  // nested positions
+
19  static std::vector<size_t> nested_var_stack_sizes_;
+
20  static std::vector<size_t> nested_var_nochain_stack_sizes_;
+
21  static std::vector<size_t> nested_var_alloc_stack_starts_;
+
22  };
+
23 
+
24  template<typename ChainableT, typename ChainableAllocT>
+
25  std::vector<ChainableT*>
+ +
27 
+
28  template<typename ChainableT, typename ChainableAllocT>
+
29  std::vector<ChainableT*>
+ +
31 
+
32  template<typename ChainableT, typename ChainableAllocT>
+
33  std::vector<ChainableAllocT*>
+ +
35 
+
36  template<typename ChainableT, typename ChainableAllocT>
+ + +
39 
+
40  template<typename ChainableT, typename ChainableAllocT>
+
41  std::vector<size_t>
+ +
43 
+
44  template<typename ChainableT, typename ChainableAllocT>
+
45  std::vector<size_t>
+ +
47  ::nested_var_nochain_stack_sizes_;
+
48 
+
49  template<typename ChainableT, typename ChainableAllocT>
+
50  std::vector<size_t>
+ +
52  ::nested_var_alloc_stack_starts_;
+
53 
+
54  }
+
55 }
+
56 #endif
+ + +
static std::vector< ChainableAllocT * > var_alloc_stack_
+
static std::vector< ChainableT * > var_nochain_stack_
+
static std::vector< size_t > nested_var_nochain_stack_sizes_
+
static std::vector< size_t > nested_var_stack_sizes_
+ + +
static std::vector< ChainableT * > var_stack_
+
An instance of this class provides a memory pool through which blocks of raw memory may be allocated ...
Definition: stack_alloc.hpp:74
+
static std::vector< size_t > nested_var_alloc_stack_starts_
+
+
+
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+
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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template<typename T_n , typename T_prob >
return_type< T_prob >::type stan::math::bernoulli_ccdf_log (const T_n &n, const T_prob &theta)
 
+
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diff --git a/doc/api/html/bernoulli__ccdf__log_8hpp_source.html b/doc/api/html/bernoulli__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..ced10e39775 --- /dev/null +++ b/doc/api/html/bernoulli__ccdf__log_8hpp_source.html @@ -0,0 +1,224 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_ccdf_log.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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bernoulli_ccdf_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/bernoulli_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <typename T_n, typename T_prob>
+
25  typename return_type<T_prob>::type
+
26  bernoulli_ccdf_log(const T_n& n, const T_prob& theta) {
+
27  static const char* function("stan::math::bernoulli_ccdf_log");
+ +
29  T_partials_return;
+
30 
+ + + + +
35 
+
36  // Ensure non-zero argument lenghts
+
37  if (!(stan::length(n) && stan::length(theta)))
+
38  return 0.0;
+
39 
+
40  T_partials_return P(0.0);
+
41 
+
42  // Validate arguments
+
43  check_finite(function, "Probability parameter", theta);
+
44  check_bounded(function, "Probability parameter", theta, 0.0, 1.0);
+
45  check_consistent_sizes(function,
+
46  "Random variable", n,
+
47  "Probability parameter", theta);
+
48 
+
49  // set up template expressions wrapping scalars into vector views
+
50  VectorView<const T_n> n_vec(n);
+
51  VectorView<const T_prob> theta_vec(theta);
+
52  size_t size = max_size(n, theta);
+
53 
+
54  // Compute vectorized cdf_log and gradient
+ +
56  using std::log;
+
57  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
58 
+
59  // Explicit return for extreme values
+
60  // The gradients are technically ill-defined, but treated as zero
+
61  for (size_t i = 0; i < stan::length(n); i++) {
+
62  if (value_of(n_vec[i]) < 0)
+
63  return operands_and_partials.value(0.0);
+
64  }
+
65 
+
66  for (size_t i = 0; i < size; i++) {
+
67  // Explicit results for extreme values
+
68  // The gradients are technically ill-defined, but treated as zero
+
69  if (value_of(n_vec[i]) >= 1) {
+
70  return operands_and_partials.value(stan::math::negative_infinity());
+
71  } else {
+
72  const T_partials_return Pi = value_of(theta_vec[i]);
+
73 
+
74  P += log(Pi);
+
75 
+ +
77  operands_and_partials.d_x1[i] += 1 / Pi;
+
78  }
+
79  }
+
80 
+
81  return operands_and_partials.value(P);
+
82  }
+
83  }
+
84 }
+
85 #endif
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
return_type< T_prob >::type bernoulli_ccdf_log(const T_n &n, const T_prob &theta)
+
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
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diff --git a/doc/api/html/bernoulli__cdf_8hpp.html b/doc/api/html/bernoulli__cdf_8hpp.html new file mode 100644 index 00000000000..c54ecd503db --- /dev/null +++ b/doc/api/html/bernoulli__cdf_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_cdf.hpp File Reference + + + + + + + + + + +
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+ + + + +

+Functions

template<typename T_n , typename T_prob >
return_type< T_prob >::type stan::math::bernoulli_cdf (const T_n &n, const T_prob &theta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/bernoulli__cdf_8hpp_source.html b/doc/api/html/bernoulli__cdf_8hpp_source.html new file mode 100644 index 00000000000..1e0dc8a131c --- /dev/null +++ b/doc/api/html/bernoulli__cdf_8hpp_source.html @@ -0,0 +1,225 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_cdf.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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bernoulli_cdf.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_CDF_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/bernoulli_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  // Bernoulli CDF
+
24  template <typename T_n, typename T_prob>
+
25  typename return_type<T_prob>::type
+
26  bernoulli_cdf(const T_n& n, const T_prob& theta) {
+
27  static const char* function("stan::math::bernoulli_cdf");
+ +
29  T_partials_return;
+
30 
+ + + + +
35 
+
36  // Ensure non-zero argument lenghts
+
37  if (!(stan::length(n) && stan::length(theta)))
+
38  return 1.0;
+
39 
+
40  T_partials_return P(1.0);
+
41 
+
42  // Validate arguments
+
43  check_finite(function, "Probability parameter", theta);
+
44  check_bounded(function, "Probability parameter", theta, 0.0, 1.0);
+
45  check_consistent_sizes(function,
+
46  "Random variable", n,
+
47  "Probability parameter", theta);
+
48 
+
49  // set up template expressions wrapping scalars into vector views
+
50  VectorView<const T_n> n_vec(n);
+
51  VectorView<const T_prob> theta_vec(theta);
+
52  size_t size = max_size(n, theta);
+
53 
+
54  // Compute vectorized CDF and gradient
+ +
56  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
57 
+
58  // Explicit return for extreme values
+
59  // The gradients are technically ill-defined, but treated as zero
+
60  for (size_t i = 0; i < stan::length(n); i++) {
+
61  if (value_of(n_vec[i]) < 0)
+
62  return operands_and_partials.value(0.0);
+
63  }
+
64 
+
65  for (size_t i = 0; i < size; i++) {
+
66  // Explicit results for extreme values
+
67  // The gradients are technically ill-defined, but treated as zero
+
68  if (value_of(n_vec[i]) >= 1)
+
69  continue;
+
70 
+
71  const T_partials_return Pi = 1 - value_of(theta_vec[i]);
+
72 
+
73  P *= Pi;
+
74 
+ +
76  operands_and_partials.d_x1[i] += - 1 / Pi;
+
77  }
+
78 
+ +
80  for (size_t i = 0; i < stan::length(theta); ++i)
+
81  operands_and_partials.d_x1[i] *= P;
+
82  }
+
83  return operands_and_partials.value(P);
+
84  }
+
85 
+
86  } // namespace math
+
87 } // namespace stan
+
88 #endif
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
return_type< T_prob >::type bernoulli_cdf(const T_n &n, const T_prob &theta)
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/bernoulli__cdf__log_8hpp.html b/doc/api/html/bernoulli__cdf__log_8hpp.html new file mode 100644 index 00000000000..fe4952bea71 --- /dev/null +++ b/doc/api/html/bernoulli__cdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_cdf_log.hpp File Reference + + + + + + + + + + +
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+ + + + +

+Functions

template<typename T_n , typename T_prob >
return_type< T_prob >::type stan::math::bernoulli_cdf_log (const T_n &n, const T_prob &theta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/bernoulli__cdf__log_8hpp_source.html b/doc/api/html/bernoulli__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..29639102d5e --- /dev/null +++ b/doc/api/html/bernoulli__cdf__log_8hpp_source.html @@ -0,0 +1,224 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_cdf_log.hpp Source File + + + + + + + + + + +
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bernoulli_cdf_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/bernoulli_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <typename T_n, typename T_prob>
+
25  typename return_type<T_prob>::type
+
26  bernoulli_cdf_log(const T_n& n, const T_prob& theta) {
+
27  static const char* function("stan::math::bernoulli_cdf_log");
+ +
29  T_partials_return;
+
30 
+ + + + +
35 
+
36  // Ensure non-zero argument lenghts
+
37  if (!(stan::length(n) && stan::length(theta)))
+
38  return 0.0;
+
39 
+
40  T_partials_return P(0.0);
+
41 
+
42  // Validate arguments
+
43  check_finite(function, "Probability parameter", theta);
+
44  check_bounded(function, "Probability parameter", theta, 0.0, 1.0);
+
45  check_consistent_sizes(function,
+
46  "Random variable", n,
+
47  "Probability parameter", theta);
+
48 
+
49  // set up template expressions wrapping scalars into vector views
+
50  VectorView<const T_n> n_vec(n);
+
51  VectorView<const T_prob> theta_vec(theta);
+
52  size_t size = max_size(n, theta);
+
53 
+
54  // Compute vectorized cdf_log and gradient
+ +
56  using std::log;
+
57  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
58 
+
59  // Explicit return for extreme values
+
60  // The gradients are technically ill-defined, but treated as zero
+
61  for (size_t i = 0; i < stan::length(n); i++) {
+
62  if (value_of(n_vec[i]) < 0)
+
63  return operands_and_partials.value(stan::math::negative_infinity());
+
64  }
+
65 
+
66  for (size_t i = 0; i < size; i++) {
+
67  // Explicit results for extreme values
+
68  // The gradients are technically ill-defined, but treated as zero
+
69  if (value_of(n_vec[i]) >= 1)
+
70  continue;
+
71 
+
72  const T_partials_return Pi = 1 - value_of(theta_vec[i]);
+
73 
+
74  P += log(Pi);
+
75 
+ +
77  operands_and_partials.d_x1[i] -= 1 / Pi;
+
78  }
+
79 
+
80  return operands_and_partials.value(P);
+
81  }
+
82 
+
83  }
+
84 }
+
85 #endif
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
return_type< T_prob >::type bernoulli_cdf_log(const T_n &n, const T_prob &theta)
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/bernoulli__log_8hpp.html b/doc/api/html/bernoulli__log_8hpp.html new file mode 100644 index 00000000000..7435e7ce579 --- /dev/null +++ b/doc/api/html/bernoulli__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_log.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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+Functions

template<bool propto, typename T_n , typename T_prob >
return_type< T_prob >::type stan::math::bernoulli_log (const T_n &n, const T_prob &theta)
 
template<typename T_y , typename T_prob >
return_type< T_prob >::type stan::math::bernoulli_log (const T_y &n, const T_prob &theta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/bernoulli__log_8hpp_source.html b/doc/api/html/bernoulli__log_8hpp_source.html new file mode 100644 index 00000000000..2c7387535f9 --- /dev/null +++ b/doc/api/html/bernoulli__log_8hpp_source.html @@ -0,0 +1,268 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_log.hpp Source File + + + + + + + + + + +
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bernoulli_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/bernoulli_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  // Bernoulli(n|theta) [0 <= n <= 1; 0 <= theta <= 1]
+
25  // FIXME: documentation
+
26  template <bool propto, typename T_n, typename T_prob>
+
27  typename return_type<T_prob>::type
+
28  bernoulli_log(const T_n& n,
+
29  const T_prob& theta) {
+
30  static const char* function("stan::math::bernoulli_log");
+ +
32  T_partials_return;
+
33 
+ + +
36  using stan::math::log1m;
+ + + +
40  using std::log;
+
41 
+
42  // check if any vectors are zero length
+
43  if (!(stan::length(n)
+
44  && stan::length(theta)))
+
45  return 0.0;
+
46 
+
47  // set up return value accumulator
+
48  T_partials_return logp(0.0);
+
49 
+
50  // validate args (here done over var, which should be OK)
+
51  check_bounded(function, "n", n, 0, 1);
+
52  check_finite(function, "Probability parameter", theta);
+
53  check_bounded(function, "Probability parameter", theta, 0.0, 1.0);
+
54  check_consistent_sizes(function,
+
55  "Random variable", n,
+
56  "Probability parameter", theta);
+
57 
+
58  // check if no variables are involved and prop-to
+ +
60  return 0.0;
+
61 
+
62  // set up template expressions wrapping scalars into vector views
+
63  VectorView<const T_n> n_vec(n);
+
64  VectorView<const T_prob> theta_vec(theta);
+
65  size_t N = max_size(n, theta);
+
66  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
67 
+
68  if (length(theta) == 1) {
+
69  size_t sum = 0;
+
70  for (size_t n = 0; n < N; n++) {
+
71  sum += value_of(n_vec[n]);
+
72  }
+
73  const T_partials_return theta_dbl = value_of(theta_vec[0]);
+
74  // avoid nans when sum == N or sum == 0
+
75  if (sum == N) {
+
76  logp += N * log(theta_dbl);
+ +
78  operands_and_partials.d_x1[0] += N / theta_dbl;
+
79  } else if (sum == 0) {
+
80  logp += N * log1m(theta_dbl);
+ +
82  operands_and_partials.d_x1[0] += N / (theta_dbl - 1);
+
83  } else {
+
84  const T_partials_return log_theta = log(theta_dbl);
+
85  const T_partials_return log1m_theta = log1m(theta_dbl);
+
86 
+
87  logp += sum * log_theta;
+
88  logp += (N - sum) * log1m_theta;
+
89 
+
90  // gradient
+ +
92  operands_and_partials.d_x1[0] += sum / theta_dbl;
+
93  operands_and_partials.d_x1[0] += (N - sum) / (theta_dbl - 1);
+
94  }
+
95  }
+
96  } else {
+
97  for (size_t n = 0; n < N; n++) {
+
98  // pull out values of arguments
+
99  const int n_int = value_of(n_vec[n]);
+
100  const T_partials_return theta_dbl = value_of(theta_vec[n]);
+
101 
+
102  if (n_int == 1)
+
103  logp += log(theta_dbl);
+
104  else
+
105  logp += log1m(theta_dbl);
+
106 
+
107  // gradient
+ +
109  if (n_int == 1)
+
110  operands_and_partials.d_x1[n] += 1.0 / theta_dbl;
+
111  else
+
112  operands_and_partials.d_x1[n] += 1.0 / (theta_dbl - 1);
+
113  }
+
114  }
+
115  }
+
116  return operands_and_partials.value(logp);
+
117  }
+
118 
+
119  template <typename T_y, typename T_prob>
+
120  inline
+ +
122  bernoulli_log(const T_y& n,
+
123  const T_prob& theta) {
+
124  return bernoulli_log<false>(n, theta);
+
125  }
+
126  } // namespace math
+
127 } // namespace stan
+
128 #endif
+ +
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+
return_type< T_prob >::type bernoulli_log(const T_n &n, const T_prob &theta)
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/bernoulli__logit__log_8hpp.html b/doc/api/html/bernoulli__logit__log_8hpp.html new file mode 100644 index 00000000000..14b02937a22 --- /dev/null +++ b/doc/api/html/bernoulli__logit__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_logit_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_n , typename T_prob >
return_type< T_prob >::type stan::math::bernoulli_logit_log (const T_n &n, const T_prob &theta)
 
template<typename T_n , typename T_prob >
return_type< T_prob >::type stan::math::bernoulli_logit_log (const T_n &n, const T_prob &theta)
 
+
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diff --git a/doc/api/html/bernoulli__logit__log_8hpp_source.html b/doc/api/html/bernoulli__logit__log_8hpp_source.html new file mode 100644 index 00000000000..5c3c5c83556 --- /dev/null +++ b/doc/api/html/bernoulli__logit__log_8hpp_source.html @@ -0,0 +1,254 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_logit_log.hpp Source File + + + + + + + + + + +
+
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bernoulli_logit_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_LOGIT_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_LOGIT_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/bernoulli_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  // Bernoulli(n|inv_logit(theta)) [0 <= n <= 1; -inf <= theta <= inf]
+
25  // FIXME: documentation
+
26  template <bool propto, typename T_n, typename T_prob>
+
27  typename return_type<T_prob>::type
+
28  bernoulli_logit_log(const T_n& n, const T_prob& theta) {
+
29  static const char* function("stan::math::bernoulli_logit_log");
+ +
31  T_partials_return;
+
32 
+ + + + + + +
39  using stan::math::log1p;
+ +
41  using std::exp;
+
42 
+
43  // check if any vectors are zero length
+
44  if (!(stan::length(n)
+
45  && stan::length(theta)))
+
46  return 0.0;
+
47 
+
48  // set up return value accumulator
+
49  T_partials_return logp(0.0);
+
50 
+
51  // validate args (here done over var, which should be OK)
+
52  check_bounded(function, "n", n, 0, 1);
+
53  check_not_nan(function, "Logit transformed probability parameter", theta);
+
54  check_consistent_sizes(function,
+
55  "Random variable", n,
+
56  "Probability parameter", theta);
+
57 
+
58  // check if no variables are involved and prop-to
+ +
60  return 0.0;
+
61 
+
62  // set up template expressions wrapping scalars into vector views
+
63  VectorView<const T_n> n_vec(n);
+
64  VectorView<const T_prob> theta_vec(theta);
+
65  size_t N = max_size(n, theta);
+
66  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
67 
+
68  for (size_t n = 0; n < N; n++) {
+
69  // pull out values of arguments
+
70  const int n_int = value_of(n_vec[n]);
+
71  const T_partials_return theta_dbl = value_of(theta_vec[n]);
+
72 
+
73  // reusable subexpression values
+
74  const int sign = 2*n_int-1;
+
75  const T_partials_return ntheta = sign * theta_dbl;
+
76  const T_partials_return exp_m_ntheta = exp(-ntheta);
+
77 
+
78  // Handle extreme values gracefully using Taylor approximations.
+
79  static const double cutoff = 20.0;
+
80  if (ntheta > cutoff)
+
81  logp -= exp_m_ntheta;
+
82  else if (ntheta < -cutoff)
+
83  logp += ntheta;
+
84  else
+
85  logp -= log1p(exp_m_ntheta);
+
86 
+
87  // gradients
+ +
89  static const double cutoff = 20.0;
+
90  if (ntheta > cutoff)
+
91  operands_and_partials.d_x1[n] -= exp_m_ntheta;
+
92  else if (ntheta < -cutoff)
+
93  operands_and_partials.d_x1[n] += sign;
+
94  else
+
95  operands_and_partials.d_x1[n] += sign * exp_m_ntheta
+
96  / (exp_m_ntheta + 1);
+
97  }
+
98  }
+
99  return operands_and_partials.value(logp);
+
100  }
+
101 
+
102  template <typename T_n,
+
103  typename T_prob>
+
104  inline
+ +
106  bernoulli_logit_log(const T_n& n,
+
107  const T_prob& theta) {
+
108  return bernoulli_logit_log<false>(n, theta);
+
109  }
+
110 
+
111  } // namespace math
+
112 } // namespace stan
+
113 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
int sign(const T &z)
Definition: sign.hpp:9
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
return_type< T_prob >::type bernoulli_logit_log(const T_n &n, const T_prob &theta)
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/bernoulli__rng_8hpp.html b/doc/api/html/bernoulli__rng_8hpp.html new file mode 100644 index 00000000000..2986c61add1 --- /dev/null +++ b/doc/api/html/bernoulli__rng_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_rng.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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template<class RNG >
int stan::math::bernoulli_rng (const double theta, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/bernoulli__rng_8hpp_source.html b/doc/api/html/bernoulli__rng_8hpp_source.html new file mode 100644 index 00000000000..9681d085363 --- /dev/null +++ b/doc/api/html/bernoulli__rng_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/bernoulli_rng.hpp Source File + + + + + + + + + + +
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bernoulli_rng.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BERNOULLI_RNG_HPP
+
3 
+
4 #include <boost/random/bernoulli_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + +
15 
+
16 namespace stan {
+
17 
+
18  namespace math {
+
19 
+
20  template <class RNG>
+
21  inline int
+
22  bernoulli_rng(const double theta,
+
23  RNG& rng) {
+
24  using boost::variate_generator;
+
25  using boost::bernoulli_distribution;
+
26 
+
27  static const char* function("stan::math::bernoulli_rng");
+
28 
+ + +
31 
+
32  check_finite(function, "Probability parameter", theta);
+
33  check_bounded(function, "Probability parameter", theta, 0, 1);
+
34 
+
35  variate_generator<RNG&, bernoulli_distribution<> >
+
36  bernoulli_rng(rng, bernoulli_distribution<>(theta));
+
37  return bernoulli_rng();
+
38  }
+
39  }
+
40 }
+
41 #endif
+ + +
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
int bernoulli_rng(const double theta, RNG &rng)
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + + +
+
+
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diff --git a/doc/api/html/beta__binomial__ccdf__log_8hpp.html b/doc/api/html/beta__binomial__ccdf__log_8hpp.html new file mode 100644 index 00000000000..74e3605b072 --- /dev/null +++ b/doc/api/html/beta__binomial__ccdf__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type stan::math::beta_binomial_ccdf_log (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
+
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diff --git a/doc/api/html/beta__binomial__ccdf__log_8hpp_source.html b/doc/api/html/beta__binomial__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..6d091e772c6 --- /dev/null +++ b/doc/api/html/beta__binomial__ccdf__log_8hpp_source.html @@ -0,0 +1,300 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_ccdf_log.hpp Source File + + + + + + + + + + +
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beta_binomial_ccdf_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + +
21 #include <cmath>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <typename T_n, typename T_N,
+
28  typename T_size1, typename T_size2>
+
29  typename return_type<T_size1, T_size2>::type
+
30  beta_binomial_ccdf_log(const T_n& n, const T_N& N, const T_size1& alpha,
+
31  const T_size2& beta) {
+
32  static const char* function("stan::math::beta_binomial_ccdf_log");
+
33  typedef typename stan::partials_return_type<T_n, T_N, T_size1,
+
34  T_size2>::type
+
35  T_partials_return;
+
36 
+ + + + + +
42 
+
43  // Ensure non-zero argument lengths
+
44  if (!(stan::length(n) && stan::length(N) && stan::length(alpha)
+
45  && stan::length(beta)))
+
46  return 0.0;
+
47 
+
48  T_partials_return P(0.0);
+
49 
+
50  // Validate arguments
+
51  check_nonnegative(function, "Population size parameter", N);
+
52  check_positive_finite(function,
+
53  "First prior sample size parameter", alpha);
+
54  check_positive_finite(function,
+
55  "Second prior sample size parameter", beta);
+
56  check_consistent_sizes(function,
+
57  "Successes variable", n,
+
58  "Population size parameter", N,
+
59  "First prior sample size parameter", alpha,
+
60  "Second prior sample size parameter", beta);
+
61 
+
62  // Wrap arguments in vector views
+
63  VectorView<const T_n> n_vec(n);
+
64  VectorView<const T_N> N_vec(N);
+
65  VectorView<const T_size1> alpha_vec(alpha);
+
66  VectorView<const T_size2> beta_vec(beta);
+
67  size_t size = max_size(n, N, alpha, beta);
+
68 
+
69  // Compute vectorized cdf_log and gradient
+
70  using stan::math::lgamma;
+
71  using stan::math::lbeta;
+
72  using stan::math::digamma;
+
73  using std::exp;
+
74  using std::log;
+
75  using std::exp;
+
76 
+ +
78  operands_and_partials(alpha, beta);
+
79 
+
80  // Explicit return for extreme values
+
81  // The gradients are technically ill-defined, but treated as neg infinity
+
82  for (size_t i = 0; i < stan::length(n); i++) {
+
83  if (value_of(n_vec[i]) <= 0)
+
84  return operands_and_partials.value(0.0);
+
85  }
+
86 
+
87  for (size_t i = 0; i < size; i++) {
+
88  // Explicit results for extreme values
+
89  // The gradients are technically ill-defined, but treated as zero
+
90  if (value_of(n_vec[i]) >= value_of(N_vec[i])) {
+
91  return operands_and_partials.value(stan::math::negative_infinity());
+
92  }
+
93 
+
94  const T_partials_return n_dbl = value_of(n_vec[i]);
+
95  const T_partials_return N_dbl = value_of(N_vec[i]);
+
96  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
97  const T_partials_return beta_dbl = value_of(beta_vec[i]);
+
98 
+
99  const T_partials_return mu = alpha_dbl + n_dbl + 1;
+
100  const T_partials_return nu = beta_dbl + N_dbl - n_dbl - 1;
+
101 
+
102  const T_partials_return F = stan::math::F32((T_partials_return)1, mu,
+
103  -N_dbl + n_dbl + 1,
+
104  n_dbl + 2, 1 - nu,
+
105  (T_partials_return)1);
+
106 
+
107  T_partials_return C = lgamma(nu) - lgamma(N_dbl - n_dbl);
+
108  C += lgamma(mu) - lgamma(n_dbl + 2);
+
109  C += lgamma(N_dbl + 2) - lgamma(N_dbl + alpha_dbl + beta_dbl);
+
110  C = exp(C);
+
111 
+
112  C *= F / exp(lbeta(alpha_dbl, beta_dbl));
+
113  C /= N_dbl + 1;
+
114 
+
115  const T_partials_return Pi = C;
+
116 
+
117  P += log(Pi);
+
118 
+
119  T_partials_return dF[6];
+
120  T_partials_return digammaOne = 0;
+
121  T_partials_return digammaTwo = 0;
+
122 
+ +
124  digammaOne = digamma(mu + nu);
+
125  digammaTwo = digamma(alpha_dbl + beta_dbl);
+
126  stan::math::grad_F32(dF, (T_partials_return)1, mu, -N_dbl + n_dbl + 1,
+
127  n_dbl + 2, 1 - nu, (T_partials_return)1);
+
128  }
+ +
130  const T_partials_return g
+
131  = - C * (digamma(mu) - digammaOne + dF[1] / F
+
132  - digamma(alpha_dbl) + digammaTwo);
+
133  operands_and_partials.d_x1[i] -= g / Pi;
+
134  }
+ +
136  const T_partials_return g
+
137  = - C * (digamma(nu) - digammaOne - dF[4] / F - digamma(beta_dbl)
+
138  + digammaTwo);
+
139  operands_and_partials.d_x2[i] -= g / Pi;
+
140  }
+
141  }
+
142 
+
143  return operands_and_partials.value(P);
+
144  }
+
145 
+
146  }
+
147 }
+
148 #endif
+
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
void grad_F32(T *g, T a, T b, T c, T d, T e, T z, T precision=1e-6)
Definition: grad_F32.hpp:11
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
return_type< T_size1, T_size2 >::type beta_binomial_ccdf_log(const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
+
T F32(T a, T b, T c, T d, T e, T z, T precision=1e-6)
Definition: F32.hpp:11
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__binomial__cdf_8hpp.html b/doc/api/html/beta__binomial__cdf_8hpp.html new file mode 100644 index 00000000000..a892a086cc4 --- /dev/null +++ b/doc/api/html/beta__binomial__cdf_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_cdf.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
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+
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beta_binomial_cdf.hpp File Reference
+
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+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type stan::math::beta_binomial_cdf (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__binomial__cdf_8hpp_source.html b/doc/api/html/beta__binomial__cdf_8hpp_source.html new file mode 100644 index 00000000000..18a51e5e77a --- /dev/null +++ b/doc/api/html/beta__binomial__cdf_8hpp_source.html @@ -0,0 +1,310 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
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+ + +
+
+
+
beta_binomial_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + + + +
21 #include <cmath>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  // Beta-Binomial CDF
+
28  template <typename T_n, typename T_N,
+
29  typename T_size1, typename T_size2>
+
30  typename return_type<T_size1, T_size2>::type
+
31  beta_binomial_cdf(const T_n& n, const T_N& N, const T_size1& alpha,
+
32  const T_size2& beta) {
+
33  static const char* function("stan::math::beta_binomial_cdf");
+
34  typedef typename stan::partials_return_type<T_n, T_N, T_size1,
+
35  T_size2>::type
+
36  T_partials_return;
+
37 
+ + + + + +
43 
+
44  // Ensure non-zero argument lengths
+
45  if (!(stan::length(n) && stan::length(N) && stan::length(alpha)
+
46  && stan::length(beta)))
+
47  return 1.0;
+
48 
+
49  T_partials_return P(1.0);
+
50 
+
51  // Validate arguments
+
52  check_nonnegative(function, "Population size parameter", N);
+
53  check_positive_finite(function,
+
54  "First prior sample size parameter", alpha);
+
55  check_positive_finite(function,
+
56  "Second prior sample size parameter", beta);
+
57  check_consistent_sizes(function,
+
58  "Successes variable", n,
+
59  "Population size parameter", N,
+
60  "First prior sample size parameter", alpha,
+
61  "Second prior sample size parameter", beta);
+
62 
+
63  // Wrap arguments in vector views
+
64  VectorView<const T_n> n_vec(n);
+
65  VectorView<const T_N> N_vec(N);
+
66  VectorView<const T_size1> alpha_vec(alpha);
+
67  VectorView<const T_size2> beta_vec(beta);
+
68  size_t size = max_size(n, N, alpha, beta);
+
69 
+
70  // Compute vectorized CDF and gradient
+
71  using stan::math::lgamma;
+
72  using stan::math::lbeta;
+
73  using stan::math::digamma;
+
74  using std::exp;
+
75  using std::exp;
+
76 
+ +
78  operands_and_partials(alpha, beta);
+
79 
+
80  // Explicit return for extreme values
+
81  // The gradients are technically ill-defined, but treated as zero
+
82  for (size_t i = 0; i < stan::length(n); i++) {
+
83  if (value_of(n_vec[i]) <= 0)
+
84  return operands_and_partials.value(0.0);
+
85  }
+
86 
+
87  for (size_t i = 0; i < size; i++) {
+
88  // Explicit results for extreme values
+
89  // The gradients are technically ill-defined, but treated as zero
+
90  if (value_of(n_vec[i]) >= value_of(N_vec[i])) {
+
91  continue;
+
92  }
+
93 
+
94  const T_partials_return n_dbl = value_of(n_vec[i]);
+
95  const T_partials_return N_dbl = value_of(N_vec[i]);
+
96  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
97  const T_partials_return beta_dbl = value_of(beta_vec[i]);
+
98 
+
99  const T_partials_return mu = alpha_dbl + n_dbl + 1;
+
100  const T_partials_return nu = beta_dbl + N_dbl - n_dbl - 1;
+
101 
+
102  const T_partials_return F = stan::math::F32((T_partials_return)1, mu,
+
103  -N_dbl + n_dbl + 1,
+
104  n_dbl + 2, 1 - nu,
+
105  (T_partials_return)1);
+
106 
+
107  T_partials_return C = lgamma(nu) - lgamma(N_dbl - n_dbl);
+
108  C += lgamma(mu) - lgamma(n_dbl + 2);
+
109  C += lgamma(N_dbl + 2) - lgamma(N_dbl + alpha_dbl + beta_dbl);
+
110  C = exp(C);
+
111 
+
112  C *= F / exp(lbeta(alpha_dbl, beta_dbl));
+
113  C /= N_dbl + 1;
+
114 
+
115  const T_partials_return Pi = 1 - C;
+
116 
+
117  P *= Pi;
+
118 
+
119  T_partials_return dF[6];
+
120  T_partials_return digammaOne = 0;
+
121  T_partials_return digammaTwo = 0;
+
122 
+ +
124  digammaOne = digamma(mu + nu);
+
125  digammaTwo = digamma(alpha_dbl + beta_dbl);
+
126  stan::math::grad_F32(dF, (T_partials_return)1, mu, -N_dbl + n_dbl + 1,
+
127  n_dbl + 2,
+
128  1 - nu, (T_partials_return)1);
+
129  }
+ +
131  const T_partials_return g
+
132  = - C * (digamma(mu) - digammaOne + dF[1] / F
+
133  - digamma(alpha_dbl) + digammaTwo);
+
134  operands_and_partials.d_x1[i]
+
135  += g / Pi;
+
136  }
+ +
138  const T_partials_return g
+
139  = - C * (digamma(nu) - digammaOne - dF[4] / F - digamma(beta_dbl)
+
140  + digammaTwo);
+
141  operands_and_partials.d_x2[i]
+
142  += g / Pi;
+
143  }
+
144  }
+
145 
+ +
147  for (size_t i = 0; i < stan::length(alpha); ++i)
+
148  operands_and_partials.d_x1[i] *= P;
+
149  }
+ +
151  for (size_t i = 0; i < stan::length(beta); ++i)
+
152  operands_and_partials.d_x2[i] *= P;
+
153  }
+
154 
+
155  return operands_and_partials.value(P);
+
156  }
+
157 
+
158  }
+
159 }
+
160 #endif
+
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_size1, T_size2 >::type beta_binomial_cdf(const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
void grad_F32(T *g, T a, T b, T c, T d, T e, T z, T precision=1e-6)
Definition: grad_F32.hpp:11
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
T F32(T a, T b, T c, T d, T e, T z, T precision=1e-6)
Definition: F32.hpp:11
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__binomial__cdf__log_8hpp.html b/doc/api/html/beta__binomial__cdf__log_8hpp.html new file mode 100644 index 00000000000..0700710b4e2 --- /dev/null +++ b/doc/api/html/beta__binomial__cdf__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+ +
+
beta_binomial_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type stan::math::beta_binomial_cdf_log (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__binomial__cdf__log_8hpp_source.html b/doc/api/html/beta__binomial__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..c41d2cf70ec --- /dev/null +++ b/doc/api/html/beta__binomial__cdf__log_8hpp_source.html @@ -0,0 +1,300 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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beta_binomial_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + +
21 #include <cmath>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <typename T_n, typename T_N,
+
28  typename T_size1, typename T_size2>
+
29  typename return_type<T_size1, T_size2>::type
+
30  beta_binomial_cdf_log(const T_n& n, const T_N& N, const T_size1& alpha,
+
31  const T_size2& beta) {
+
32  static const char* function("stan::math::beta_binomial_cdf_log");
+
33  typedef typename stan::partials_return_type<T_n, T_N, T_size1,
+
34  T_size2>::type
+
35  T_partials_return;
+
36 
+ + + + + +
42 
+
43  // Ensure non-zero argument lengths
+
44  if (!(stan::length(n) && stan::length(N) && stan::length(alpha)
+
45  && stan::length(beta)))
+
46  return 0.0;
+
47 
+
48  T_partials_return P(0.0);
+
49 
+
50  // Validate arguments
+
51  check_nonnegative(function, "Population size parameter", N);
+
52  check_positive_finite(function,
+
53  "First prior sample size parameter", alpha);
+
54  check_positive_finite(function,
+
55  "Second prior sample size parameter", beta);
+
56  check_consistent_sizes(function,
+
57  "Successes variable", n,
+
58  "Population size parameter", N,
+
59  "First prior sample size parameter", alpha,
+
60  "Second prior sample size parameter", beta);
+
61 
+
62  // Wrap arguments in vector views
+
63  VectorView<const T_n> n_vec(n);
+
64  VectorView<const T_N> N_vec(N);
+
65  VectorView<const T_size1> alpha_vec(alpha);
+
66  VectorView<const T_size2> beta_vec(beta);
+
67  size_t size = max_size(n, N, alpha, beta);
+
68 
+
69  // Compute vectorized cdf_log and gradient
+
70  using stan::math::lgamma;
+
71  using stan::math::digamma;
+
72  using stan::math::lbeta;
+
73  using std::exp;
+
74  using std::log;
+
75  using std::exp;
+
76 
+ +
78  operands_and_partials(alpha, beta);
+
79 
+
80  // Explicit return for extreme values
+
81  // The gradients are technically ill-defined, but treated as neg infinity
+
82  for (size_t i = 0; i < stan::length(n); i++) {
+
83  if (value_of(n_vec[i]) <= 0)
+
84  return operands_and_partials.value(stan::math::negative_infinity());
+
85  }
+
86 
+
87  for (size_t i = 0; i < size; i++) {
+
88  // Explicit results for extreme values
+
89  // The gradients are technically ill-defined, but treated as zero
+
90  if (value_of(n_vec[i]) >= value_of(N_vec[i])) {
+
91  continue;
+
92  }
+
93 
+
94  const T_partials_return n_dbl = value_of(n_vec[i]);
+
95  const T_partials_return N_dbl = value_of(N_vec[i]);
+
96  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
97  const T_partials_return beta_dbl = value_of(beta_vec[i]);
+
98 
+
99  const T_partials_return mu = alpha_dbl + n_dbl + 1;
+
100  const T_partials_return nu = beta_dbl + N_dbl - n_dbl - 1;
+
101 
+
102  const T_partials_return F = stan::math::F32((T_partials_return)1, mu,
+
103  -N_dbl + n_dbl + 1,
+
104  n_dbl + 2, 1 - nu,
+
105  (T_partials_return)1);
+
106 
+
107  T_partials_return C = lgamma(nu) - lgamma(N_dbl - n_dbl);
+
108  C += lgamma(mu) - lgamma(n_dbl + 2);
+
109  C += lgamma(N_dbl + 2) - lgamma(N_dbl + alpha_dbl + beta_dbl);
+
110  C = exp(C);
+
111 
+
112  C *= F / exp(lbeta(alpha_dbl, beta_dbl));
+
113  C /= N_dbl + 1;
+
114 
+
115  const T_partials_return Pi = 1 - C;
+
116 
+
117  P += log(Pi);
+
118 
+
119  T_partials_return dF[6];
+
120  T_partials_return digammaOne = 0;
+
121  T_partials_return digammaTwo = 0;
+
122 
+ +
124  digammaOne = digamma(mu + nu);
+
125  digammaTwo = digamma(alpha_dbl + beta_dbl);
+
126  stan::math::grad_F32(dF, (T_partials_return)1, mu, -N_dbl + n_dbl + 1,
+
127  n_dbl + 2, 1 - nu, (T_partials_return)1);
+
128  }
+ +
130  const T_partials_return g
+
131  = - C * (digamma(mu) - digammaOne + dF[1] / F
+
132  - digamma(alpha_dbl) + digammaTwo);
+
133  operands_and_partials.d_x1[i] += g / Pi;
+
134  }
+ +
136  const T_partials_return g
+
137  = - C * (digamma(nu) - digammaOne - dF[4] / F - digamma(beta_dbl)
+
138  + digammaTwo);
+
139  operands_and_partials.d_x2[i] += g / Pi;
+
140  }
+
141  }
+
142 
+
143  return operands_and_partials.value(P);
+
144  }
+
145 
+
146  }
+
147 }
+
148 #endif
+
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
return_type< T_size1, T_size2 >::type beta_binomial_cdf_log(const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
void grad_F32(T *g, T a, T b, T c, T d, T e, T z, T precision=1e-6)
Definition: grad_F32.hpp:11
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
T F32(T a, T b, T c, T d, T e, T z, T precision=1e-6)
Definition: F32.hpp:11
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__binomial__log_8hpp.html b/doc/api/html/beta__binomial__log_8hpp.html new file mode 100644 index 00000000000..d1c197893ce --- /dev/null +++ b/doc/api/html/beta__binomial__log_8hpp.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_log.hpp File Reference + + + + + + + + + + +
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+
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+
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+ + + + + + + +

+Functions

template<bool propto, typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type stan::math::beta_binomial_log (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type stan::math::beta_binomial_log (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__binomial__log_8hpp_source.html b/doc/api/html/beta__binomial__log_8hpp_source.html new file mode 100644 index 00000000000..923c3ba227a --- /dev/null +++ b/doc/api/html/beta__binomial__log_8hpp_source.html @@ -0,0 +1,335 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
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+
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+
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+
beta_binomial_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  // BetaBinomial(n|alpha, beta) [alpha > 0; beta > 0; n >= 0]
+
28  template <bool propto,
+
29  typename T_n, typename T_N,
+
30  typename T_size1, typename T_size2>
+
31  typename return_type<T_size1, T_size2>::type
+
32  beta_binomial_log(const T_n& n,
+
33  const T_N& N,
+
34  const T_size1& alpha,
+
35  const T_size2& beta) {
+
36  static const char* function("stan::math::beta_binomial_log");
+ +
38  T_partials_return;
+
39 
+ + + + + +
45 
+
46  // check if any vectors are zero length
+
47  if (!(stan::length(n)
+
48  && stan::length(N)
+
49  && stan::length(alpha)
+
50  && stan::length(beta)))
+
51  return 0.0;
+
52 
+
53  T_partials_return logp(0.0);
+
54  check_nonnegative(function, "Population size parameter", N);
+
55  check_positive_finite(function,
+
56  "First prior sample size parameter", alpha);
+
57  check_positive_finite(function,
+
58  "Second prior sample size parameter", beta);
+
59  check_consistent_sizes(function,
+
60  "Successes variable", n,
+
61  "Population size parameter", N,
+
62  "First prior sample size parameter", alpha,
+
63  "Second prior sample size parameter", beta);
+
64 
+
65  // check if no variables are involved and prop-to
+ +
67  return 0.0;
+
68 
+ +
70  operands_and_partials(alpha, beta);
+
71 
+
72  VectorView<const T_n> n_vec(n);
+
73  VectorView<const T_N> N_vec(N);
+
74  VectorView<const T_size1> alpha_vec(alpha);
+
75  VectorView<const T_size2> beta_vec(beta);
+
76  size_t size = max_size(n, N, alpha, beta);
+
77 
+
78  for (size_t i = 0; i < size; i++) {
+
79  if (n_vec[i] < 0 || n_vec[i] > N_vec[i])
+
80  return operands_and_partials.value(LOG_ZERO);
+
81  }
+
82 
+
83  using stan::math::lbeta;
+ +
85  using stan::math::digamma;
+
86 
+ +
88  T_partials_return, T_n, T_N>
+
89  normalizing_constant(max_size(N, n));
+
90  for (size_t i = 0; i < max_size(N, n); i++)
+ +
92  normalizing_constant[i]
+
93  = binomial_coefficient_log(N_vec[i], n_vec[i]);
+
94 
+ +
96  T_partials_return, T_n, T_N, T_size1, T_size2>
+
97  lbeta_numerator(size);
+
98  for (size_t i = 0; i < size; i++)
+ +
100  lbeta_numerator[i] = lbeta(n_vec[i] + value_of(alpha_vec[i]),
+
101  N_vec[i] - n_vec[i]
+
102  + value_of(beta_vec[i]));
+
103 
+ +
105  T_partials_return, T_size1, T_size2>
+
106  lbeta_denominator(max_size(alpha, beta));
+
107  for (size_t i = 0; i < max_size(alpha, beta); i++)
+ +
109  lbeta_denominator[i] = lbeta(value_of(alpha_vec[i]),
+
110  value_of(beta_vec[i]));
+
111 
+ +
113  T_partials_return, T_n, T_size1>
+
114  digamma_n_plus_alpha(max_size(n, alpha));
+
115  for (size_t i = 0; i < max_size(n, alpha); i++)
+ +
117  digamma_n_plus_alpha[i]
+
118  = digamma(n_vec[i] + value_of(alpha_vec[i]));
+
119 
+ +
121  T_partials_return, T_N, T_size1, T_size2>
+
122  digamma_N_plus_alpha_plus_beta(max_size(N, alpha, beta));
+
123  for (size_t i = 0; i < max_size(N, alpha, beta); i++)
+ +
125  digamma_N_plus_alpha_plus_beta[i]
+
126  = digamma(N_vec[i] + value_of(alpha_vec[i])
+
127  + value_of(beta_vec[i]));
+
128 
+ +
130  T_partials_return, T_size1, T_size2>
+
131  digamma_alpha_plus_beta(max_size(alpha, beta));
+
132  for (size_t i = 0; i < max_size(alpha, beta); i++)
+ +
134  digamma_alpha_plus_beta[i]
+
135  = digamma(value_of(alpha_vec[i]) + value_of(beta_vec[i]));
+
136 
+ +
138  T_partials_return, T_size1> digamma_alpha(length(alpha));
+
139  for (size_t i = 0; i < length(alpha); i++)
+ +
141  digamma_alpha[i] = digamma(value_of(alpha_vec[i]));
+
142 
+ +
144  T_partials_return, T_size2>
+
145  digamma_beta(length(beta));
+
146  for (size_t i = 0; i < length(beta); i++)
+ +
148  digamma_beta[i] = digamma(value_of(beta_vec[i]));
+
149 
+
150  for (size_t i = 0; i < size; i++) {
+ +
152  logp += normalizing_constant[i];
+ +
154  logp += lbeta_numerator[i] - lbeta_denominator[i];
+
155 
+ +
157  operands_and_partials.d_x1[i]
+
158  += digamma_n_plus_alpha[i]
+
159  - digamma_N_plus_alpha_plus_beta[i]
+
160  + digamma_alpha_plus_beta[i]
+
161  - digamma_alpha[i];
+ +
163  operands_and_partials.d_x2[i]
+
164  += digamma(value_of(N_vec[i]-n_vec[i]+beta_vec[i]))
+
165  - digamma_N_plus_alpha_plus_beta[i]
+
166  + digamma_alpha_plus_beta[i]
+
167  - digamma_beta[i];
+
168  }
+
169  return operands_and_partials.value(logp);
+
170  }
+
171 
+
172  template <typename T_n,
+
173  typename T_N,
+
174  typename T_size1,
+
175  typename T_size2>
+ +
177  beta_binomial_log(const T_n& n, const T_N& N,
+
178  const T_size1& alpha, const T_size2& beta) {
+
179  return beta_binomial_log<false>(n, N, alpha, beta);
+
180  }
+
181 
+
182  }
+
183 }
+
184 #endif
+
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > binomial_coefficient_log(const fvar< T > &x1, const fvar< T > &x2)
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
This class builds partial derivatives with respect to a set of operands.
+
return_type< T_size1, T_size2 >::type beta_binomial_log(const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__binomial__rng_8hpp.html b/doc/api/html/beta__binomial__rng_8hpp.html new file mode 100644 index 00000000000..5efe4c1e460 --- /dev/null +++ b/doc/api/html/beta__binomial__rng_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_rng.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/beta__binomial__rng_8hpp_source.html b/doc/api/html/beta__binomial__rng_8hpp_source.html new file mode 100644 index 00000000000..1df61c24e92 --- /dev/null +++ b/doc/api/html/beta__binomial__rng_8hpp_source.html @@ -0,0 +1,176 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_binomial_rng.hpp Source File + + + + + + + + + + +
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beta_binomial_rng.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_BINOMIAL_RNG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  template <class RNG>
+
24  inline int
+
25  beta_binomial_rng(const int N,
+
26  const double alpha,
+
27  const double beta,
+
28  RNG& rng) {
+
29  static const char* function("stan::math::beta_binomial_rng");
+
30 
+ + +
33 
+
34  check_nonnegative(function, "Population size parameter", N);
+
35  check_positive_finite(function,
+
36  "First prior sample size parameter", alpha);
+
37  check_positive_finite(function,
+
38  "Second prior sample size parameter", beta);
+
39 
+
40  double a = stan::math::beta_rng(alpha, beta, rng);
+
41  while (a > 1 || a < 0)
+
42  a = stan::math::beta_rng(alpha, beta, rng);
+
43  return stan::math::binomial_rng(N, a, rng);
+
44  }
+
45  }
+
46 }
+
47 #endif
+ +
double beta_rng(const double alpha, const double beta, RNG &rng)
Definition: beta_rng.hpp:29
+ + + +
int beta_binomial_rng(const int N, const double alpha, const double beta, RNG &rng)
+ + + + + + + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
int binomial_rng(const int N, const double theta, RNG &rng)
+
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__ccdf__log_8hpp.html b/doc/api/html/beta__ccdf__log_8hpp.html new file mode 100644 index 00000000000..a1b4ce49495 --- /dev/null +++ b/doc/api/html/beta__ccdf__log_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_ccdf_log.hpp File Reference + + + + + + + + + + +
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+Functions

template<typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type stan::math::beta_ccdf_log (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__ccdf__log_8hpp_source.html b/doc/api/html/beta__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..682edde8c4f --- /dev/null +++ b/doc/api/html/beta__ccdf__log_8hpp_source.html @@ -0,0 +1,307 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_ccdf_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + +
25 #include <boost/math/special_functions/gamma.hpp>
+
26 #include <boost/random/gamma_distribution.hpp>
+
27 #include <boost/random/variate_generator.hpp>
+
28 #include <cmath>
+
29 
+
30 namespace stan {
+
31 
+
32  namespace math {
+
33 
+
34  template <typename T_y, typename T_scale_succ, typename T_scale_fail>
+
35  typename return_type<T_y, T_scale_succ, T_scale_fail>::type
+
36  beta_ccdf_log(const T_y& y, const T_scale_succ& alpha,
+
37  const T_scale_fail& beta) {
+
38  typedef typename stan::partials_return_type<T_y, T_scale_succ,
+
39  T_scale_fail>::type
+
40  T_partials_return;
+
41 
+
42  // Size checks
+
43  if ( !( stan::length(y) && stan::length(alpha)
+
44  && stan::length(beta) ) )
+
45  return 0.0;
+
46 
+
47  // Error checks
+
48  static const char* function("stan::math::beta_cdf");
+
49 
+ + + + +
54  using boost::math::tools::promote_args;
+ + +
57 
+
58  T_partials_return ccdf_log(0.0);
+
59 
+
60  check_positive_finite(function, "First shape parameter", alpha);
+
61  check_positive_finite(function, "Second shape parameter", beta);
+
62  check_not_nan(function, "Random variable", y);
+
63  check_nonnegative(function, "Random variable", y);
+
64  check_less_or_equal(function, "Random variable", y, 1);
+
65  check_consistent_sizes(function,
+
66  "Random variable", y,
+
67  "First shape parameter", alpha,
+
68  "Second shape parameter", beta);
+
69 
+
70  // Wrap arguments in vectors
+
71  VectorView<const T_y> y_vec(y);
+
72  VectorView<const T_scale_succ> alpha_vec(alpha);
+
73  VectorView<const T_scale_fail> beta_vec(beta);
+
74  size_t N = max_size(y, alpha, beta);
+
75 
+ +
77  operands_and_partials(y, alpha, beta);
+
78 
+
79  // Compute CDF and its gradients
+ +
81  using stan::math::digamma;
+
82  using stan::math::lbeta;
+
83  using std::pow;
+
84  using std::exp;
+
85  using std::log;
+
86  using std::exp;
+
87 
+
88  // Cache a few expensive function calls if alpha or beta is a parameter
+ +
90  T_scale_fail>::value,
+
91  T_partials_return, T_scale_succ, T_scale_fail>
+
92  digamma_alpha_vec(max_size(alpha, beta));
+ +
94  T_scale_fail>::value,
+
95  T_partials_return, T_scale_succ, T_scale_fail>
+
96  digamma_beta_vec(max_size(alpha, beta));
+ +
98  T_scale_fail>::value,
+
99  T_partials_return, T_scale_succ, T_scale_fail>
+
100  digamma_sum_vec(max_size(alpha, beta));
+
101 
+ +
103  for (size_t i = 0; i < N; i++) {
+
104  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
105  const T_partials_return beta_dbl = value_of(beta_vec[i]);
+
106 
+
107  digamma_alpha_vec[i] = digamma(alpha_dbl);
+
108  digamma_beta_vec[i] = digamma(beta_dbl);
+
109  digamma_sum_vec[i] = digamma(alpha_dbl + beta_dbl);
+
110  }
+
111  }
+
112 
+
113  // Compute vectorized CDFLog and gradient
+
114  for (size_t n = 0; n < N; n++) {
+
115  // Pull out values
+
116  const T_partials_return y_dbl = value_of(y_vec[n]);
+
117  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
118  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
119  const T_partials_return betafunc_dbl = exp(lbeta(alpha_dbl, beta_dbl));
+
120 
+
121  // Compute
+
122  const T_partials_return Pn = 1.0 - inc_beta(alpha_dbl, beta_dbl, y_dbl);
+
123 
+
124  ccdf_log += log(Pn);
+
125 
+ +
127  operands_and_partials.d_x1[n] -= pow(1-y_dbl, beta_dbl-1)
+
128  * pow(y_dbl, alpha_dbl-1) / betafunc_dbl / Pn;
+
129 
+
130  T_partials_return g1 = 0;
+
131  T_partials_return g2 = 0;
+
132 
+ +
134  stan::math::grad_reg_inc_beta(g1, g2, alpha_dbl, beta_dbl, y_dbl,
+
135  digamma_alpha_vec[n],
+
136  digamma_beta_vec[n],
+
137  digamma_sum_vec[n],
+
138  betafunc_dbl);
+
139  }
+ +
141  operands_and_partials.d_x2[n] -= g1 / Pn;
+ +
143  operands_and_partials.d_x3[n] -= g2 / Pn;
+
144  }
+
145 
+
146  return operands_and_partials.value(ccdf_log);
+
147  }
+
148  }
+
149 }
+
150 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_ccdf_log(const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__cdf_8hpp.html b/doc/api/html/beta__cdf_8hpp.html new file mode 100644 index 00000000000..075e2fc0d0b --- /dev/null +++ b/doc/api/html/beta__cdf_8hpp.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
beta_cdf.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type stan::math::beta_cdf (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 Calculates the beta cumulative distribution function for the given variate and scale variables. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__cdf_8hpp_source.html b/doc/api/html/beta__cdf_8hpp_source.html new file mode 100644 index 00000000000..b82d526523d --- /dev/null +++ b/doc/api/html/beta__cdf_8hpp_source.html @@ -0,0 +1,313 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
beta_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + + +
26 #include <boost/math/special_functions/gamma.hpp>
+
27 #include <boost/random/gamma_distribution.hpp>
+
28 #include <boost/random/variate_generator.hpp>
+
29 #include <cmath>
+
30 
+
31 namespace stan {
+
32 
+
33  namespace math {
+
34 
+
47  template <typename T_y, typename T_scale_succ, typename T_scale_fail>
+
48  typename return_type<T_y, T_scale_succ, T_scale_fail>::type
+
49  beta_cdf(const T_y& y, const T_scale_succ& alpha,
+
50  const T_scale_fail& beta) {
+
51  typedef typename stan::partials_return_type<T_y, T_scale_succ,
+
52  T_scale_fail>::type
+
53  T_partials_return;
+
54 
+
55  // Size checks
+
56  if (!(stan::length(y) && stan::length(alpha)
+
57  && stan::length(beta)))
+
58  return 1.0;
+
59 
+
60  // Error checks
+
61  static const char* function("stan::math::beta_cdf");
+
62  using boost::math::tools::promote_args;
+
63 
+
64  T_partials_return P(1.0);
+
65 
+
66  check_positive_finite(function, "First shape parameter", alpha);
+
67  check_positive_finite(function, "Second shape parameter", beta);
+
68  check_not_nan(function, "Random variable", y);
+
69  check_consistent_sizes(function,
+
70  "Random variable", y,
+
71  "First shape parameter", alpha,
+
72  "Second shape parameter", beta);
+
73  check_nonnegative(function, "Random variable", y);
+
74  check_less_or_equal(function, "Random variable", y, 1);
+
75 
+
76  // Wrap arguments in vectors
+
77  VectorView<const T_y> y_vec(y);
+
78  VectorView<const T_scale_succ> alpha_vec(alpha);
+
79  VectorView<const T_scale_fail> beta_vec(beta);
+
80  size_t N = max_size(y, alpha, beta);
+
81 
+ +
83  operands_and_partials(y, alpha, beta);
+
84 
+
85  // Explicit return for extreme values
+
86  // The gradients are technically ill-defined, but treated as zero
+
87  for (size_t i = 0; i < stan::length(y); i++) {
+
88  if (value_of(y_vec[i]) <= 0)
+
89  return operands_and_partials.value(0.0);
+
90  }
+
91 
+
92  // Compute CDF and its gradients
+
93 
+
94  // Cache a few expensive function calls if alpha or beta is a parameter
+ +
96  T_scale_fail>::value,
+
97  T_partials_return, T_scale_succ, T_scale_fail>
+
98  digamma_alpha_vec(max_size(alpha, beta));
+
99 
+ +
101  T_scale_fail>::value,
+
102  T_partials_return, T_scale_succ, T_scale_fail>
+
103  digamma_beta_vec(max_size(alpha, beta));
+
104 
+ +
106  T_scale_fail>::value,
+
107  T_partials_return, T_scale_succ, T_scale_fail>
+
108  digamma_sum_vec(max_size(alpha, beta));
+
109 
+ +
111  for (size_t n = 0; n < N; n++) {
+
112  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
113  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
114 
+
115  digamma_alpha_vec[n] = digamma(alpha_dbl);
+
116  digamma_beta_vec[n] = digamma(beta_dbl);
+
117  digamma_sum_vec[n] = digamma(alpha_dbl + beta_dbl);
+
118  }
+
119  }
+
120 
+
121  // Compute vectorized CDF and gradient
+
122  for (size_t n = 0; n < N; n++) {
+
123  // Explicit results for extreme values
+
124  // The gradients are technically ill-defined, but treated as zero
+
125  if (value_of(y_vec[n]) >= 1.0) continue;
+
126 
+
127  // Pull out values
+
128  const T_partials_return y_dbl = value_of(y_vec[n]);
+
129  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
130  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
131 
+
132  // Compute
+
133  const T_partials_return Pn = inc_beta(alpha_dbl, beta_dbl, y_dbl);
+
134 
+
135  P *= Pn;
+
136 
+ +
138  operands_and_partials.d_x1[n]
+
139  += inc_beta_ddz(alpha_dbl, beta_dbl, y_dbl) / Pn;
+
140 
+ +
142  operands_and_partials.d_x2[n]
+
143  += inc_beta_dda(alpha_dbl, beta_dbl, y_dbl,
+
144  digamma_alpha_vec[n], digamma_sum_vec[n]) / Pn;
+ +
146  operands_and_partials.d_x3[n]
+
147  += inc_beta_ddb(alpha_dbl, beta_dbl, y_dbl,
+
148  digamma_beta_vec[n], digamma_sum_vec[n]) / Pn;
+
149  }
+
150 
+ +
152  for (size_t n = 0; n < stan::length(y); ++n)
+
153  operands_and_partials.d_x1[n] *= P;
+
154  }
+ +
156  for (size_t n = 0; n < stan::length(alpha); ++n)
+
157  operands_and_partials.d_x2[n] *= P;
+
158  }
+ +
160  for (size_t n = 0; n < stan::length(beta); ++n)
+
161  operands_and_partials.d_x3[n] *= P;
+
162  }
+
163 
+
164  return operands_and_partials.value(P);
+
165  }
+
166 
+
167  }
+
168 }
+
169 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T inc_beta_dda(T a, T b, T z, T digamma_a, T digamma_ab)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a.
+ + +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T inc_beta_ddb(T a, T b, T z, T digamma_b, T digamma_ab)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to b.
+
T inc_beta_ddz(T a, T b, T z)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to z.
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ + +
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_cdf(const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
Calculates the beta cumulative distribution function for the given variate and scale variables...
Definition: beta_cdf.hpp:49
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__cdf__log_8hpp.html b/doc/api/html/beta__cdf__log_8hpp.html new file mode 100644 index 00000000000..27869a4c301 --- /dev/null +++ b/doc/api/html/beta__cdf__log_8hpp.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
beta_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type stan::math::beta_cdf_log (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/beta__cdf__log_8hpp_source.html b/doc/api/html/beta__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..638209220ca --- /dev/null +++ b/doc/api/html/beta__cdf__log_8hpp_source.html @@ -0,0 +1,306 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+
+
beta_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + +
24 #include <boost/math/special_functions/gamma.hpp>
+
25 #include <boost/random/gamma_distribution.hpp>
+
26 #include <boost/random/variate_generator.hpp>
+
27 #include <cmath>
+
28 
+
29 namespace stan {
+
30 
+
31  namespace math {
+
32 
+
33  template <typename T_y, typename T_scale_succ, typename T_scale_fail>
+
34  typename return_type<T_y, T_scale_succ, T_scale_fail>::type
+
35  beta_cdf_log(const T_y& y, const T_scale_succ& alpha,
+
36  const T_scale_fail& beta) {
+
37  typedef typename stan::partials_return_type<T_y, T_scale_succ,
+
38  T_scale_fail>::type
+
39  T_partials_return;
+
40 
+
41  // Size checks
+
42  if ( !( stan::length(y) && stan::length(alpha)
+
43  && stan::length(beta) ) )
+
44  return 0.0;
+
45 
+
46  // Error checks
+
47  static const char* function("stan::math::beta_cdf");
+
48 
+ + + + +
53  using boost::math::tools::promote_args;
+ + +
56 
+
57  T_partials_return cdf_log(0.0);
+
58 
+
59  check_positive_finite(function, "First shape parameter", alpha);
+
60  check_positive_finite(function, "Second shape parameter", beta);
+
61  check_not_nan(function, "Random variable", y);
+
62  check_nonnegative(function, "Random variable", y);
+
63  check_less_or_equal(function, "Random variable", y, 1);
+
64  check_consistent_sizes(function,
+
65  "Random variable", y,
+
66  "First shape parameter", alpha,
+
67  "Second shape parameter", beta);
+
68 
+
69  // Wrap arguments in vectors
+
70  VectorView<const T_y> y_vec(y);
+
71  VectorView<const T_scale_succ> alpha_vec(alpha);
+
72  VectorView<const T_scale_fail> beta_vec(beta);
+
73  size_t N = max_size(y, alpha, beta);
+
74 
+ +
76  operands_and_partials(y, alpha, beta);
+
77 
+
78  // Compute CDF and its gradients
+ +
80  using stan::math::digamma;
+
81  using stan::math::lbeta;
+
82  using std::pow;
+
83  using std::exp;
+
84  using std::log;
+
85  using std::exp;
+
86 
+
87  // Cache a few expensive function calls if alpha or beta is a parameter
+ +
89  T_scale_fail>::value,
+
90  T_partials_return, T_scale_succ, T_scale_fail>
+
91  digamma_alpha_vec(max_size(alpha, beta));
+
92 
+ +
94  T_scale_fail>::value,
+
95  T_partials_return, T_scale_succ, T_scale_fail>
+
96  digamma_beta_vec(max_size(alpha, beta));
+
97 
+ +
99  T_scale_fail>::value,
+
100  T_partials_return, T_scale_succ, T_scale_fail>
+
101  digamma_sum_vec(max_size(alpha, beta));
+
102 
+ +
104  for (size_t i = 0; i < N; i++) {
+
105  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
106  const T_partials_return beta_dbl = value_of(beta_vec[i]);
+
107 
+
108  digamma_alpha_vec[i] = digamma(alpha_dbl);
+
109  digamma_beta_vec[i] = digamma(beta_dbl);
+
110  digamma_sum_vec[i] = digamma(alpha_dbl + beta_dbl);
+
111  }
+
112  }
+
113 
+
114  // Compute vectorized CDFLog and gradient
+
115  for (size_t n = 0; n < N; n++) {
+
116  // Pull out values
+
117  const T_partials_return y_dbl = value_of(y_vec[n]);
+
118  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
119  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
120  const T_partials_return betafunc_dbl = exp(lbeta(alpha_dbl, beta_dbl));
+
121  // Compute
+
122  const T_partials_return Pn = inc_beta(alpha_dbl, beta_dbl, y_dbl);
+
123 
+
124  cdf_log += log(Pn);
+
125 
+ +
127  operands_and_partials.d_x1[n] += pow(1-y_dbl, beta_dbl-1)
+
128  * pow(y_dbl, alpha_dbl-1) / betafunc_dbl / Pn;
+
129 
+
130  T_partials_return g1 = 0;
+
131  T_partials_return g2 = 0;
+
132 
+ +
134  stan::math::grad_reg_inc_beta(g1, g2, alpha_dbl, beta_dbl, y_dbl,
+
135  digamma_alpha_vec[n],
+
136  digamma_beta_vec[n], digamma_sum_vec[n],
+
137  betafunc_dbl);
+
138  }
+ +
140  operands_and_partials.d_x2[n] += g1 / Pn;
+ +
142  operands_and_partials.d_x3[n] += g2 / Pn;
+
143  }
+
144 
+
145  return operands_and_partials.value(cdf_log);
+
146  }
+
147 
+
148  }
+
149 }
+
150 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_cdf_log(const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
+ + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/beta__log_8hpp.html b/doc/api/html/beta__log_8hpp.html new file mode 100644 index 00000000000..ce18ce87d7d --- /dev/null +++ b/doc/api/html/beta__log_8hpp.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type stan::math::beta_log (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 The log of the beta density for the specified scalar(s) given the specified sample size(s). More...
 
template<typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type stan::math::beta_log (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 
+
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diff --git a/doc/api/html/beta__log_8hpp_source.html b/doc/api/html/beta__log_8hpp_source.html new file mode 100644 index 00000000000..bcc89120aee --- /dev/null +++ b/doc/api/html/beta__log_8hpp_source.html @@ -0,0 +1,358 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_log.hpp Source File + + + + + + + + + + +
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beta_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + +
24 #include <boost/math/special_functions/gamma.hpp>
+
25 #include <boost/random/gamma_distribution.hpp>
+
26 #include <boost/random/variate_generator.hpp>
+
27 #include <cmath>
+
28 
+
29 namespace stan {
+
30 
+
31  namespace math {
+
32 
+
51  template <bool propto,
+
52  typename T_y, typename T_scale_succ, typename T_scale_fail>
+
53  typename return_type<T_y, T_scale_succ, T_scale_fail>::type
+
54  beta_log(const T_y& y,
+
55  const T_scale_succ& alpha, const T_scale_fail& beta) {
+
56  static const char* function("stan::math::beta_log");
+
57 
+
58  typedef typename stan::partials_return_type<T_y,
+
59  T_scale_succ,
+
60  T_scale_fail>::type
+
61  T_partials_return;
+
62 
+
63  using stan::math::digamma;
+
64  using stan::math::lgamma;
+
65 
+ +
67  using stan::is_vector;
+ + + + +
72  using stan::math::log1m;
+ + + + +
77  using std::log;
+
78 
+
79  // check if any vectors are zero length
+
80  if (!(stan::length(y)
+
81  && stan::length(alpha)
+
82  && stan::length(beta)))
+
83  return 0.0;
+
84 
+
85  // set up return value accumulator
+
86  T_partials_return logp(0.0);
+
87 
+
88  // validate args (here done over var, which should be OK)
+
89  check_positive_finite(function, "First shape parameter", alpha);
+
90  check_positive_finite(function, "Second shape parameter", beta);
+
91  check_not_nan(function, "Random variable", y);
+
92  check_consistent_sizes(function,
+
93  "Random variable", y,
+
94  "First shape parameter", alpha,
+
95  "Second shape parameter", beta);
+
96  check_nonnegative(function, "Random variable", y);
+
97  check_less_or_equal(function, "Random variable", y, 1);
+
98 
+
99  // check if no variables are involved and prop-to
+ +
101  return 0.0;
+
102 
+
103  VectorView<const T_y> y_vec(y);
+
104  VectorView<const T_scale_succ> alpha_vec(alpha);
+
105  VectorView<const T_scale_fail> beta_vec(beta);
+
106  size_t N = max_size(y, alpha, beta);
+
107 
+
108  for (size_t n = 0; n < N; n++) {
+
109  const T_partials_return y_dbl = value_of(y_vec[n]);
+
110  if (y_dbl < 0 || y_dbl > 1)
+
111  return LOG_ZERO;
+
112  }
+
113 
+
114  // set up template expressions wrapping scalars into vector views
+ +
116  operands_and_partials(y, alpha, beta);
+
117 
+ +
119  T_partials_return, T_y>
+
120  log_y(length(y));
+ +
122  T_partials_return, T_y>
+
123  log1m_y(length(y));
+
124 
+
125  for (size_t n = 0; n < length(y); n++) {
+ +
127  log_y[n] = log(value_of(y_vec[n]));
+ +
129  log1m_y[n] = log1m(value_of(y_vec[n]));
+
130  }
+
131 
+ +
133  T_partials_return, T_scale_succ>
+
134  lgamma_alpha(length(alpha));
+ +
136  T_partials_return, T_scale_succ>
+
137  digamma_alpha(length(alpha));
+
138  for (size_t n = 0; n < length(alpha); n++) {
+ +
140  lgamma_alpha[n] = lgamma(value_of(alpha_vec[n]));
+ +
142  digamma_alpha[n] = digamma(value_of(alpha_vec[n]));
+
143  }
+
144 
+ +
146  T_partials_return, T_scale_fail>
+
147  lgamma_beta(length(beta));
+ +
149  T_partials_return, T_scale_fail>
+
150  digamma_beta(length(beta));
+
151 
+
152  for (size_t n = 0; n < length(beta); n++) {
+ +
154  lgamma_beta[n] = lgamma(value_of(beta_vec[n]));
+ +
156  digamma_beta[n] = digamma(value_of(beta_vec[n]));
+
157  }
+
158 
+ +
160  T_partials_return, T_scale_succ, T_scale_fail>
+
161  lgamma_alpha_beta(max_size(alpha, beta));
+
162 
+ +
164  T_scale_fail>::value,
+
165  T_partials_return, T_scale_succ, T_scale_fail>
+
166  digamma_alpha_beta(max_size(alpha, beta));
+
167 
+
168  for (size_t n = 0; n < max_size(alpha, beta); n++) {
+
169  const T_partials_return alpha_beta = value_of(alpha_vec[n])
+
170  + value_of(beta_vec[n]);
+ +
172  lgamma_alpha_beta[n] = lgamma(alpha_beta);
+ +
174  digamma_alpha_beta[n] = digamma(alpha_beta);
+
175  }
+
176 
+
177  for (size_t n = 0; n < N; n++) {
+
178  // pull out values of arguments
+
179  const T_partials_return y_dbl = value_of(y_vec[n]);
+
180  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
181  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
182 
+
183  // log probability
+ +
185  logp += lgamma_alpha_beta[n];
+ +
187  logp -= lgamma_alpha[n];
+ +
189  logp -= lgamma_beta[n];
+ +
191  logp += (alpha_dbl-1.0) * log_y[n];
+ +
193  logp += (beta_dbl-1.0) * log1m_y[n];
+
194 
+
195  // gradients
+ +
197  operands_and_partials.d_x1[n] += (alpha_dbl-1)/y_dbl
+
198  + (beta_dbl-1)/(y_dbl-1);
+ +
200  operands_and_partials.d_x2[n]
+
201  += log_y[n] + digamma_alpha_beta[n] - digamma_alpha[n];
+ +
203  operands_and_partials.d_x3[n]
+
204  += log1m_y[n] + digamma_alpha_beta[n] - digamma_beta[n];
+
205  }
+
206  return operands_and_partials.value(logp);
+
207  }
+
208 
+
209  template <typename T_y, typename T_scale_succ, typename T_scale_fail>
+ +
211  beta_log(const T_y& y, const T_scale_succ& alpha,
+
212  const T_scale_fail& beta) {
+
213  return beta_log<false>(y, alpha, beta);
+
214  }
+
215 
+
216  }
+
217 }
+
218 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_log(const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
The log of the beta density for the specified scalar(s) given the specified sample size(s)...
Definition: beta_log.hpp:54
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/beta__rng_8hpp.html b/doc/api/html/beta__rng_8hpp.html new file mode 100644 index 00000000000..7ed99632c14 --- /dev/null +++ b/doc/api/html/beta__rng_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::beta_rng (const double alpha, const double beta, RNG &rng)
 
+
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diff --git a/doc/api/html/beta__rng_8hpp_source.html b/doc/api/html/beta__rng_8hpp_source.html new file mode 100644 index 00000000000..3af9981d101 --- /dev/null +++ b/doc/api/html/beta__rng_8hpp_source.html @@ -0,0 +1,180 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/beta_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BETA_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BETA_RNG_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 #include <boost/random/gamma_distribution.hpp>
+
6 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + +
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <class RNG>
+
28  inline double
+
29  beta_rng(const double alpha,
+
30  const double beta,
+
31  RNG& rng) {
+
32  using boost::variate_generator;
+
33  using boost::random::gamma_distribution;
+
34  // Error checks
+
35  static const char* function("stan::math::beta_rng");
+
36 
+ +
38 
+
39  check_positive_finite(function, "First shape parameter", alpha);
+
40  check_positive_finite(function, "Second shape parameter", beta);
+
41 
+
42  variate_generator<RNG&, gamma_distribution<> >
+
43  rng_gamma_alpha(rng, gamma_distribution<>(alpha, 1.0));
+
44  variate_generator<RNG&, gamma_distribution<> >
+
45  rng_gamma_beta(rng, gamma_distribution<>(beta, 1.0));
+
46  double a = rng_gamma_alpha();
+
47  double b = rng_gamma_beta();
+
48  return a / (a + b);
+
49  }
+
50 
+
51  }
+
52 }
+
53 #endif
+ + +
double beta_rng(const double alpha, const double beta, RNG &rng)
Definition: beta_rng.hpp:29
+ + + + + + + + + + + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
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diff --git a/doc/api/html/binomial__ccdf__log_8hpp.html b/doc/api/html/binomial__ccdf__log_8hpp.html new file mode 100644 index 00000000000..5966bb734b4 --- /dev/null +++ b/doc/api/html/binomial__ccdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type stan::math::binomial_ccdf_log (const T_n &n, const T_N &N, const T_prob &theta)
 
+
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diff --git a/doc/api/html/binomial__ccdf__log_8hpp_source.html b/doc/api/html/binomial__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..0bcf7df0d7b --- /dev/null +++ b/doc/api/html/binomial__ccdf__log_8hpp_source.html @@ -0,0 +1,260 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_ccdf_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + +
23 #include <boost/random/binomial_distribution.hpp>
+
24 #include <boost/random/variate_generator.hpp>
+
25 #include <cmath>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_n, typename T_N, typename T_prob>
+
32  typename return_type<T_prob>::type
+
33  binomial_ccdf_log(const T_n& n, const T_N& N, const T_prob& theta) {
+
34  static const char* function("stan::math::binomial_ccdf_log");
+ +
36  T_partials_return;
+
37 
+ + + + + + +
44 
+
45  // Ensure non-zero arguments lenghts
+
46  if (!(stan::length(n) && stan::length(N) && stan::length(theta)))
+
47  return 0.0;
+
48 
+
49  T_partials_return P(0.0);
+
50 
+
51  // Validate arguments
+
52  check_nonnegative(function, "Population size parameter", N);
+
53  check_finite(function, "Probability parameter", theta);
+
54  check_bounded(function, "Probability parameter", theta, 0.0, 1.0);
+
55  check_consistent_sizes(function,
+
56  "Successes variable", n,
+
57  "Population size parameter", N,
+
58  "Probability parameter", theta);
+
59 
+
60  // Wrap arguments in vector views
+
61  VectorView<const T_n> n_vec(n);
+
62  VectorView<const T_N> N_vec(N);
+
63  VectorView<const T_prob> theta_vec(theta);
+
64  size_t size = max_size(n, N, theta);
+
65 
+
66  // Compute vectorized cdf_log and gradient
+ + +
69  using stan::math::lbeta;
+
70  using std::exp;
+
71  using std::pow;
+
72  using std::log;
+
73  using std::exp;
+
74 
+
75  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
76 
+
77  // Explicit return for extreme values
+
78  // The gradients are technically ill-defined,
+
79  // but treated as negative infinity
+
80  for (size_t i = 0; i < stan::length(n); i++) {
+
81  if (value_of(n_vec[i]) < 0)
+
82  return operands_and_partials.value(0.0);
+
83  }
+
84 
+
85  for (size_t i = 0; i < size; i++) {
+
86  // Explicit results for extreme values
+
87  // The gradients are technically ill-defined, but treated as zero
+
88  if (value_of(n_vec[i]) >= value_of(N_vec[i])) {
+
89  return operands_and_partials.value(stan::math::negative_infinity());
+
90  }
+
91  const T_partials_return n_dbl = value_of(n_vec[i]);
+
92  const T_partials_return N_dbl = value_of(N_vec[i]);
+
93  const T_partials_return theta_dbl = value_of(theta_vec[i]);
+
94  const T_partials_return betafunc = exp(lbeta(N_dbl-n_dbl, n_dbl+1));
+
95  const T_partials_return Pi = 1.0 - inc_beta(N_dbl - n_dbl, n_dbl + 1,
+
96  1 - theta_dbl);
+
97 
+
98  P += log(Pi);
+
99 
+ +
101  operands_and_partials.d_x1[i] += pow(theta_dbl, n_dbl)
+
102  * pow(1-theta_dbl, N_dbl-n_dbl-1) / betafunc / Pi;
+
103  }
+
104 
+
105  return operands_and_partials.value(P);
+
106  }
+
107  }
+
108 }
+
109 #endif
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
return_type< T_prob >::type binomial_ccdf_log(const T_n &n, const T_N &N, const T_prob &theta)
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
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diff --git a/doc/api/html/binomial__cdf_8hpp.html b/doc/api/html/binomial__cdf_8hpp.html new file mode 100644 index 00000000000..d11cc0a1b80 --- /dev/null +++ b/doc/api/html/binomial__cdf_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_cdf.hpp File Reference + + + + + + + + + + +
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template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type stan::math::binomial_cdf (const T_n &n, const T_N &N, const T_prob &theta)
 
+
+
+
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diff --git a/doc/api/html/binomial__cdf_8hpp_source.html b/doc/api/html/binomial__cdf_8hpp_source.html new file mode 100644 index 00000000000..bb251bcb0de --- /dev/null +++ b/doc/api/html/binomial__cdf_8hpp_source.html @@ -0,0 +1,265 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_cdf.hpp Source File + + + + + + + + + + +
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binomial_cdf.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + +
23 #include <boost/random/binomial_distribution.hpp>
+
24 #include <boost/random/variate_generator.hpp>
+
25 #include <cmath>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  // Binomial CDF
+
32  template <typename T_n, typename T_N, typename T_prob>
+
33  typename return_type<T_prob>::type
+
34  binomial_cdf(const T_n& n, const T_N& N, const T_prob& theta) {
+
35  static const char* function("stan::math::binomial_cdf");
+ +
37  T_partials_return;
+
38 
+ + + + + + +
45 
+
46  // Ensure non-zero arguments lenghts
+
47  if (!(stan::length(n) && stan::length(N) && stan::length(theta)))
+
48  return 1.0;
+
49 
+
50  T_partials_return P(1.0);
+
51 
+
52  // Validate arguments
+
53  check_nonnegative(function, "Population size parameter", N);
+
54  check_finite(function, "Probability parameter", theta);
+
55  check_bounded(function, "Probability parameter", theta, 0.0, 1.0);
+
56  check_consistent_sizes(function,
+
57  "Successes variable", n,
+
58  "Population size parameter", N,
+
59  "Probability parameter", theta);
+
60 
+
61 
+
62  // Wrap arguments in vector views
+
63  VectorView<const T_n> n_vec(n);
+
64  VectorView<const T_N> N_vec(N);
+
65  VectorView<const T_prob> theta_vec(theta);
+
66  size_t size = max_size(n, N, theta);
+
67 
+
68  // Compute vectorized CDF and gradient
+ + +
71  using stan::math::lbeta;
+
72  using std::exp;
+
73  using std::pow;
+
74  using std::exp;
+
75 
+
76  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
77 
+
78  // Explicit return for extreme values
+
79  // The gradients are technically ill-defined, but treated as zero
+
80  for (size_t i = 0; i < stan::length(n); i++) {
+
81  if (value_of(n_vec[i]) < 0)
+
82  return operands_and_partials.value(0.0);
+
83  }
+
84 
+
85  for (size_t i = 0; i < size; i++) {
+
86  // Explicit results for extreme values
+
87  // The gradients are technically ill-defined, but treated as zero
+
88  if (value_of(n_vec[i]) >= value_of(N_vec[i])) {
+
89  continue;
+
90  }
+
91 
+
92  const T_partials_return n_dbl = value_of(n_vec[i]);
+
93  const T_partials_return N_dbl = value_of(N_vec[i]);
+
94  const T_partials_return theta_dbl = value_of(theta_vec[i]);
+
95  const T_partials_return betafunc = exp(lbeta(N_dbl-n_dbl, n_dbl+1));
+
96  const T_partials_return Pi = inc_beta(N_dbl - n_dbl, n_dbl + 1,
+
97  1 - theta_dbl);
+
98 
+
99  P *= Pi;
+
100 
+ +
102  operands_and_partials.d_x1[i] -= pow(theta_dbl, n_dbl)
+
103  * pow(1-theta_dbl, N_dbl-n_dbl-1) / betafunc / Pi;
+
104  }
+
105 
+ +
107  for (size_t i = 0; i < stan::length(theta); ++i)
+
108  operands_and_partials.d_x1[i] *= P;
+
109  }
+
110 
+
111  return operands_and_partials.value(P);
+
112  }
+
113 
+
114  }
+
115 }
+
116 #endif
+
return_type< T_prob >::type binomial_cdf(const T_n &n, const T_N &N, const T_prob &theta)
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/binomial__cdf__log_8hpp.html b/doc/api/html/binomial__cdf__log_8hpp.html new file mode 100644 index 00000000000..39f6fc15da9 --- /dev/null +++ b/doc/api/html/binomial__cdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_cdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type stan::math::binomial_cdf_log (const T_n &n, const T_N &N, const T_prob &theta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/binomial__cdf__log_8hpp_source.html b/doc/api/html/binomial__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..7d7f941eb38 --- /dev/null +++ b/doc/api/html/binomial__cdf__log_8hpp_source.html @@ -0,0 +1,261 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_cdf_log.hpp Source File + + + + + + + + + + +
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binomial_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + +
23 #include <boost/random/binomial_distribution.hpp>
+
24 #include <boost/random/variate_generator.hpp>
+
25 #include <cmath>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_n, typename T_N, typename T_prob>
+
32  typename return_type<T_prob>::type
+
33  binomial_cdf_log(const T_n& n, const T_N& N, const T_prob& theta) {
+
34  static const char* function("stan::math::binomial_cdf_log");
+ +
36  T_partials_return;
+
37 
+ + + + + + +
44 
+
45  // Ensure non-zero arguments lenghts
+
46  if (!(stan::length(n) && stan::length(N) && stan::length(theta)))
+
47  return 0.0;
+
48 
+
49  T_partials_return P(0.0);
+
50 
+
51  // Validate arguments
+
52  check_nonnegative(function, "Population size parameter", N);
+
53  check_finite(function, "Probability parameter", theta);
+
54  check_bounded(function, "Probability parameter", theta, 0.0, 1.0);
+
55  check_consistent_sizes(function,
+
56  "Successes variable", n,
+
57  "Population size parameter", N,
+
58  "Probability parameter", theta);
+
59 
+
60  // Wrap arguments in vector views
+
61  VectorView<const T_n> n_vec(n);
+
62  VectorView<const T_N> N_vec(N);
+
63  VectorView<const T_prob> theta_vec(theta);
+
64  size_t size = max_size(n, N, theta);
+
65 
+
66  // Compute vectorized cdf_log and gradient
+ + +
69  using stan::math::lbeta;
+
70  using std::exp;
+
71  using std::pow;
+
72  using std::log;
+
73  using std::exp;
+
74 
+
75  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
76 
+
77  // Explicit return for extreme values
+
78  // The gradients are technically ill-defined,
+
79  // but treated as negative infinity
+
80  for (size_t i = 0; i < stan::length(n); i++) {
+
81  if (value_of(n_vec[i]) < 0)
+
82  return operands_and_partials.value(stan::math::negative_infinity());
+
83  }
+
84 
+
85  for (size_t i = 0; i < size; i++) {
+
86  // Explicit results for extreme values
+
87  // The gradients are technically ill-defined, but treated as zero
+
88  if (value_of(n_vec[i]) >= value_of(N_vec[i])) {
+
89  continue;
+
90  }
+
91  const T_partials_return n_dbl = value_of(n_vec[i]);
+
92  const T_partials_return N_dbl = value_of(N_vec[i]);
+
93  const T_partials_return theta_dbl = value_of(theta_vec[i]);
+
94  const T_partials_return betafunc = exp(lbeta(N_dbl-n_dbl, n_dbl+1));
+
95  const T_partials_return Pi = inc_beta(N_dbl - n_dbl, n_dbl + 1,
+
96  1 - theta_dbl);
+
97 
+
98  P += log(Pi);
+
99 
+ +
101  operands_and_partials.d_x1[i] -= pow(theta_dbl, n_dbl)
+
102  * pow(1-theta_dbl, N_dbl-n_dbl-1) / betafunc / Pi;
+
103  }
+
104 
+
105  return operands_and_partials.value(P);
+
106  }
+
107 
+
108  }
+
109 }
+
110 #endif
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
return_type< T_prob >::type binomial_cdf_log(const T_n &n, const T_N &N, const T_prob &theta)
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
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diff --git a/doc/api/html/binomial__log_8hpp.html b/doc/api/html/binomial__log_8hpp.html new file mode 100644 index 00000000000..e189699d517 --- /dev/null +++ b/doc/api/html/binomial__log_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type stan::math::binomial_log (const T_n &n, const T_N &N, const T_prob &theta)
 
template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type stan::math::binomial_log (const T_n &n, const T_N &N, const T_prob &theta)
 
+
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diff --git a/doc/api/html/binomial__log_8hpp_source.html b/doc/api/html/binomial__log_8hpp_source.html new file mode 100644 index 00000000000..027679aee4d --- /dev/null +++ b/doc/api/html/binomial__log_8hpp_source.html @@ -0,0 +1,288 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_log.hpp Source File + + + + + + + + + + +
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+
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+
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binomial_log.hpp
+
+
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + +
24 #include <boost/random/binomial_distribution.hpp>
+
25 #include <boost/random/variate_generator.hpp>
+
26 
+
27 
+
28 namespace stan {
+
29 
+
30  namespace math {
+
31 
+
32  // Binomial(n|N, theta) [N >= 0; 0 <= n <= N; 0 <= theta <= 1]
+
33  template <bool propto,
+
34  typename T_n,
+
35  typename T_N,
+
36  typename T_prob>
+
37  typename return_type<T_prob>::type
+
38  binomial_log(const T_n& n,
+
39  const T_N& N,
+
40  const T_prob& theta) {
+ +
42  T_partials_return;
+
43 
+
44  static const char* function("stan::math::binomial_log");
+
45 
+ + + + + + +
52 
+
53  // check if any vectors are zero length
+
54  if (!(stan::length(n)
+
55  && stan::length(N)
+
56  && stan::length(theta)))
+
57  return 0.0;
+
58 
+
59  T_partials_return logp = 0;
+
60  check_bounded(function, "Successes variable", n, 0, N);
+
61  check_nonnegative(function, "Population size parameter", N);
+
62  check_finite(function, "Probability parameter", theta);
+
63  check_bounded(function, "Probability parameter", theta, 0.0, 1.0);
+
64  check_consistent_sizes(function,
+
65  "Successes variable", n,
+
66  "Population size parameter", N,
+
67  "Probability parameter", theta);
+
68 
+
69 
+
70  // check if no variables are involved and prop-to
+ +
72  return 0.0;
+
73 
+
74  // set up template expressions wrapping scalars into vector views
+
75  VectorView<const T_n> n_vec(n);
+
76  VectorView<const T_N> N_vec(N);
+
77  VectorView<const T_prob> theta_vec(theta);
+
78  size_t size = max_size(n, N, theta);
+
79 
+
80  OperandsAndPartials<T_prob> operands_and_partials(theta);
+
81 
+ + +
84  using stan::math::log1m;
+
85 
+ +
87  for (size_t i = 0; i < size; ++i)
+
88  logp += binomial_coefficient_log(N_vec[i], n_vec[i]);
+
89  }
+
90 
+ +
92  for (size_t i = 0; i < length(theta); ++i)
+
93  log1m_theta[i] = log1m(value_of(theta_vec[i]));
+
94 
+
95  // no test for include_summand because return if not live
+
96  for (size_t i = 0; i < size; ++i)
+
97  logp += multiply_log(n_vec[i], value_of(theta_vec[i]))
+
98  + (N_vec[i] - n_vec[i]) * log1m_theta[i];
+
99 
+
100  if (length(theta) == 1) {
+
101  T_partials_return temp1 = 0;
+
102  T_partials_return temp2 = 0;
+
103  for (size_t i = 0; i < size; ++i) {
+
104  temp1 += n_vec[i];
+
105  temp2 += N_vec[i] - n_vec[i];
+
106  }
+ +
108  operands_and_partials.d_x1[0]
+
109  += temp1 / value_of(theta_vec[0])
+
110  - temp2 / (1.0 - value_of(theta_vec[0]));
+
111  }
+
112  } else {
+ +
114  for (size_t i = 0; i < size; ++i)
+
115  operands_and_partials.d_x1[i]
+
116  += n_vec[i] / value_of(theta_vec[i])
+
117  - (N_vec[i] - n_vec[i]) / (1.0 - value_of(theta_vec[i]));
+
118  }
+
119  }
+
120 
+
121  return operands_and_partials.value(logp);
+
122  }
+
123 
+
124  template <typename T_n,
+
125  typename T_N,
+
126  typename T_prob>
+
127  inline
+ +
129  binomial_log(const T_n& n,
+
130  const T_N& N,
+
131  const T_prob& theta) {
+
132  return binomial_log<false>(n, N, theta);
+
133  }
+
134 
+
135  }
+
136 }
+
137 #endif
+
fvar< T > binomial_coefficient_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
return_type< T_prob >::type binomial_log(const T_n &n, const T_N &N, const T_prob &theta)
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/binomial__logit__log_8hpp.html b/doc/api/html/binomial__logit__log_8hpp.html new file mode 100644 index 00000000000..2897538d596 --- /dev/null +++ b/doc/api/html/binomial__logit__log_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_logit_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
binomial_logit_log.hpp File Reference
+
+
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Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type stan::math::binomial_logit_log (const T_n &n, const T_N &N, const T_prob &alpha)
 
template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type stan::math::binomial_logit_log (const T_n &n, const T_N &N, const T_prob &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/binomial__logit__log_8hpp_source.html b/doc/api/html/binomial__logit__log_8hpp_source.html new file mode 100644 index 00000000000..f70e884f977 --- /dev/null +++ b/doc/api/html/binomial__logit__log_8hpp_source.html @@ -0,0 +1,291 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_logit_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
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+
+
binomial_logit_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_LOGIT_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_LOGIT_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + +
24 #include <boost/random/binomial_distribution.hpp>
+
25 #include <boost/random/variate_generator.hpp>
+
26 
+
27 
+
28 namespace stan {
+
29 
+
30  namespace math {
+
31 
+
32  // BinomialLogit(n|N, alpha) [N >= 0; 0 <= n <= N]
+
33  // BinomialLogit(n|N, alpha) = Binomial(n|N, inv_logit(alpha))
+
34  template <bool propto,
+
35  typename T_n,
+
36  typename T_N,
+
37  typename T_prob>
+
38  typename return_type<T_prob>::type
+
39  binomial_logit_log(const T_n& n,
+
40  const T_N& N,
+
41  const T_prob& alpha) {
+ +
43  T_partials_return;
+
44 
+
45  static const char* function("stan::math::binomial_logit_log");
+
46 
+ + + + + + +
53 
+
54  // check if any vectors are zero length
+
55  if (!(stan::length(n)
+
56  && stan::length(N)
+
57  && stan::length(alpha)))
+
58  return 0.0;
+
59 
+
60  T_partials_return logp = 0;
+
61  check_bounded(function, "Successes variable", n, 0, N);
+
62  check_nonnegative(function, "Population size parameter", N);
+
63  check_finite(function, "Probability parameter", alpha);
+
64  check_consistent_sizes(function,
+
65  "Successes variable", n,
+
66  "Population size parameter", N,
+
67  "Probability parameter", alpha);
+
68 
+
69  // check if no variables are involved and prop-to
+ +
71  return 0.0;
+
72 
+
73  // set up template expressions wrapping scalars into vector views
+
74  VectorView<const T_n> n_vec(n);
+
75  VectorView<const T_N> N_vec(N);
+
76  VectorView<const T_prob> alpha_vec(alpha);
+
77  size_t size = max_size(n, N, alpha);
+
78 
+
79  OperandsAndPartials<T_prob> operands_and_partials(alpha);
+
80 
+ + + +
84 
+ +
86  for (size_t i = 0; i < size; ++i)
+
87  logp += binomial_coefficient_log(N_vec[i], n_vec[i]);
+
88  }
+
89 
+ +
91  log_inv_logit_alpha(length(alpha));
+
92  for (size_t i = 0; i < length(alpha); ++i)
+
93  log_inv_logit_alpha[i] = log_inv_logit(value_of(alpha_vec[i]));
+
94 
+ +
96  log_inv_logit_neg_alpha(length(alpha));
+
97  for (size_t i = 0; i < length(alpha); ++i)
+
98  log_inv_logit_neg_alpha[i] = log_inv_logit(-value_of(alpha_vec[i]));
+
99 
+
100  for (size_t i = 0; i < size; ++i)
+
101  logp += n_vec[i] * log_inv_logit_alpha[i]
+
102  + (N_vec[i] - n_vec[i]) * log_inv_logit_neg_alpha[i];
+
103 
+
104  if (length(alpha) == 1) {
+
105  T_partials_return temp1 = 0;
+
106  T_partials_return temp2 = 0;
+
107  for (size_t i = 0; i < size; ++i) {
+
108  temp1 += n_vec[i];
+
109  temp2 += N_vec[i] - n_vec[i];
+
110  }
+ +
112  operands_and_partials.d_x1[0]
+
113  += temp1 * inv_logit(-value_of(alpha_vec[0]))
+
114  - temp2 * inv_logit(value_of(alpha_vec[0]));
+
115  }
+
116  } else {
+ +
118  for (size_t i = 0; i < size; ++i)
+
119  operands_and_partials.d_x1[i]
+
120  += n_vec[i] * inv_logit(-value_of(alpha_vec[i]))
+
121  - (N_vec[i] - n_vec[i]) * inv_logit(value_of(alpha_vec[i]));
+
122  }
+
123  }
+
124 
+
125  return operands_and_partials.value(logp);
+
126  }
+
127 
+
128  template <typename T_n,
+
129  typename T_N,
+
130  typename T_prob>
+
131  inline
+ +
133  binomial_logit_log(const T_n& n,
+
134  const T_N& N,
+
135  const T_prob& alpha) {
+
136  return binomial_logit_log<false>(n, N, alpha);
+
137  }
+
138  }
+
139 }
+
140 #endif
+
fvar< T > binomial_coefficient_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
fvar< T > log_inv_logit(const fvar< T > &x)
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
return_type< T_prob >::type binomial_logit_log(const T_n &n, const T_N &N, const T_prob &alpha)
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/binomial__rng_8hpp.html b/doc/api/html/binomial__rng_8hpp.html new file mode 100644 index 00000000000..793ab9e45dd --- /dev/null +++ b/doc/api/html/binomial__rng_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_rng.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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+
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+
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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<class RNG >
int stan::math::binomial_rng (const int N, const double theta, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/binomial__rng_8hpp_source.html b/doc/api/html/binomial__rng_8hpp_source.html new file mode 100644 index 00000000000..f97d6c531e3 --- /dev/null +++ b/doc/api/html/binomial__rng_8hpp_source.html @@ -0,0 +1,186 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/binomial_rng.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+
binomial_rng.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_BINOMIAL_RNG_HPP
+
3 
+
4 #include <boost/random/binomial_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + +
22 
+
23 
+
24 namespace stan {
+
25 
+
26  namespace math {
+
27 
+
28  template <class RNG>
+
29  inline int
+
30  binomial_rng(const int N,
+
31  const double theta,
+
32  RNG& rng) {
+
33  using boost::variate_generator;
+
34  using boost::binomial_distribution;
+
35 
+
36  static const char* function("stan::math::binomial_rng");
+
37 
+ + + + +
42 
+
43  check_nonnegative(function, "Population size parameter", N);
+
44  check_finite(function, "Probability parameter", theta);
+
45  check_less_or_equal(function, "Probability parameter", theta, 1.0);
+
46  check_greater_or_equal(function, "Probability parameter", theta, 0.0);
+
47 
+
48  variate_generator<RNG&, binomial_distribution<> >
+
49  binomial_rng(rng, binomial_distribution<>(N, theta));
+
50  return binomial_rng();
+
51  }
+
52 
+
53  }
+
54 }
+
55 #endif
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+ + + + + + + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + + +
int binomial_rng(const int N, const double theta, RNG &rng)
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/block_8hpp.html b/doc/api/html/block_8hpp.html new file mode 100644 index 00000000000..8f9fc5db87b --- /dev/null +++ b/doc/api/html/block_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/block.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::block (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t nrows, size_t ncols)
 Return a nrows x ncols submatrix starting at (i-1, j-1). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/block_8hpp_source.html b/doc/api/html/block_8hpp_source.html new file mode 100644 index 00000000000..69686435a9d --- /dev/null +++ b/doc/api/html/block_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/block.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_BLOCK_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_BLOCK_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
20  template <typename T>
+
21  inline
+
22  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
23  block(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m,
+
24  size_t i, size_t j, size_t nrows, size_t ncols) {
+ + +
27 
+
28  check_row_index("block", "i", m, i);
+
29  check_row_index("block", "i+nrows-1", m, i+nrows-1);
+
30  check_column_index("block", "j", m, j);
+
31  check_column_index("block", "j+ncols-1", m, j+ncols-1);
+
32  return m.block(i - 1, j - 1, nrows, ncols);
+
33  }
+
34 
+
35  }
+
36 }
+
37 #endif
+ + +
bool check_row_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
Return true if the specified index is a valid row of the matrix.
+ + +
bool check_column_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
Return true if the specified index is a valid column of the matrix.
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > block(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t nrows, size_t ncols)
Return a nrows x ncols submatrix starting at (i-1, j-1).
Definition: block.hpp:23
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diff --git a/doc/api/html/boost__fpclassify_8hpp.html b/doc/api/html/boost__fpclassify_8hpp.html new file mode 100644 index 00000000000..331137ea7b5 --- /dev/null +++ b/doc/api/html/boost__fpclassify_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_fpclassify.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/fpclassify.hpp>
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template<>
int boost::math::fpclassify (const stan::math::var &v)
 Categorizes the given stan::math::var value. More...
 
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diff --git a/doc/api/html/boost__fpclassify_8hpp_source.html b/doc/api/html/boost__fpclassify_8hpp_source.html new file mode 100644 index 00000000000..e834c8c8a8f --- /dev/null +++ b/doc/api/html/boost__fpclassify_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_fpclassify.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_BOOST_FPCLASSIFY_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_BOOST_FPCLASSIFY_HPP
+
3 
+
4 #include <boost/math/special_functions/fpclassify.hpp>
+
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace boost {
+
8 
+
9  namespace math {
+
10 
+
22  template <>
+
23  inline
+
24  int fpclassify(const stan::math::var& v) {
+
25  return (boost::math::fpclassify)(v.val());
+
26  }
+
27 
+
28  }
+
29 }
+
30 #endif
+
31 
+ +
int fpclassify(const stan::math::var &v)
Categorizes the given stan::math::var value.
+
Reimplementing boost functionality.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
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diff --git a/doc/api/html/boost__isfinite_8hpp.html b/doc/api/html/boost__isfinite_8hpp.html new file mode 100644 index 00000000000..4524c4203e0 --- /dev/null +++ b/doc/api/html/boost__isfinite_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_isfinite.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/rev/core.hpp>
+
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bool boost::math::isfinite (const stan::math::var &v)
 Checks if the given number has finite value. More...
 
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diff --git a/doc/api/html/boost__isfinite_8hpp_source.html b/doc/api/html/boost__isfinite_8hpp_source.html new file mode 100644 index 00000000000..15cbf3654da --- /dev/null +++ b/doc/api/html/boost__isfinite_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_isfinite.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_BOOST_ISFINITE_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_BOOST_ISFINITE_HPP
+
3 
+
4 #include <boost/math/special_functions/fpclassify.hpp>
+
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace boost {
+
8 
+
9  namespace math {
+
10 
+
20  template <>
+
21  inline
+
22  bool isfinite(const stan::math::var& v) {
+
23  return (boost::math::isfinite)(v.val());
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+
29 
+ +
bool isfinite(const stan::math::var &v)
Checks if the given number has finite value.
+
Reimplementing boost functionality.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
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diff --git a/doc/api/html/boost__isinf_8hpp.html b/doc/api/html/boost__isinf_8hpp.html new file mode 100644 index 00000000000..480077ae2f1 --- /dev/null +++ b/doc/api/html/boost__isinf_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_isinf.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/rev/core.hpp>
+
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template<>
bool boost::math::isinf (const stan::math::var &v)
 Checks if the given number is infinite. More...
 
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diff --git a/doc/api/html/boost__isinf_8hpp_source.html b/doc/api/html/boost__isinf_8hpp_source.html new file mode 100644 index 00000000000..c255001399c --- /dev/null +++ b/doc/api/html/boost__isinf_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_isinf.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_BOOST_ISINF_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_BOOST_ISINF_HPP
+
3 
+
4 #include <boost/math/special_functions/fpclassify.hpp>
+
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace boost {
+
8 
+
9  namespace math {
+
10 
+
20  template <>
+
21  inline
+
22  bool isinf(const stan::math::var& v) {
+
23  return (boost::math::isinf)(v.val());
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+
29 
+ +
Reimplementing boost functionality.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
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diff --git a/doc/api/html/boost__isnan_8hpp.html b/doc/api/html/boost__isnan_8hpp.html new file mode 100644 index 00000000000..77d879c1c37 --- /dev/null +++ b/doc/api/html/boost__isnan_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_isnan.hpp File Reference + + + + + + + + + + +
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boost_isnan.hpp File Reference
+
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#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/rev/core.hpp>
+
+

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 boost
 Reimplementing boost functionality.
 
 boost::math
 Reimplmeneting boost functionality for stan::math::var and and bugs in classification of integer types.
 
+ + + + + +

+Functions

template<>
bool boost::math::isnan (const stan::math::var &v)
 Checks if the given number is NaN. More...
 
+
+
+
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diff --git a/doc/api/html/boost__isnan_8hpp_source.html b/doc/api/html/boost__isnan_8hpp_source.html new file mode 100644 index 00000000000..e8546b92a6a --- /dev/null +++ b/doc/api/html/boost__isnan_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_isnan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_BOOST_ISNAN_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_BOOST_ISNAN_HPP
+
3 
+
4 #include <boost/math/special_functions/fpclassify.hpp>
+
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace boost {
+
8 
+
9  namespace math {
+
10 
+
20  template <>
+
21  inline
+
22  bool isnan(const stan::math::var& v) {
+
23  return (boost::math::isnan)(v.val());
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+
29 
+ +
Reimplementing boost functionality.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
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diff --git a/doc/api/html/boost__isnormal_8hpp.html b/doc/api/html/boost__isnormal_8hpp.html new file mode 100644 index 00000000000..9a2b89385dd --- /dev/null +++ b/doc/api/html/boost__isnormal_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_isnormal.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/rev/core.hpp>
+
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template<>
bool boost::math::isnormal (const stan::math::var &v)
 Checks if the given number is normal. More...
 
+
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diff --git a/doc/api/html/boost__isnormal_8hpp_source.html b/doc/api/html/boost__isnormal_8hpp_source.html new file mode 100644 index 00000000000..14433f64aa2 --- /dev/null +++ b/doc/api/html/boost__isnormal_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/boost_isnormal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_BOOST_ISNORMAL_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_BOOST_ISNORMAL_HPP
+
3 
+
4 #include <boost/math/special_functions/fpclassify.hpp>
+
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace boost {
+
8 
+
9  namespace math {
+
10 
+
20  template <>
+
21  inline
+
22  bool isnormal(const stan::math::var& v) {
+
23  return (boost::math::isnormal)(v.val());
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+
29 
+ +
Reimplementing boost functionality.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnormal(const stan::math::var &v)
Checks if the given number is normal.
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
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diff --git a/doc/api/html/calculate__chain_8hpp.html b/doc/api/html/calculate__chain_8hpp.html new file mode 100644 index 00000000000..b3f6b5da19a --- /dev/null +++ b/doc/api/html/calculate__chain_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/calculate_chain.hpp File Reference + + + + + + + + + + +
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double stan::math::calculate_chain (const double &x, const double &val)
 
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diff --git a/doc/api/html/calculate__chain_8hpp_source.html b/doc/api/html/calculate__chain_8hpp_source.html new file mode 100644 index 00000000000..69a0bae9e2e --- /dev/null +++ b/doc/api/html/calculate__chain_8hpp_source.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/calculate_chain.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_CALCULATE_CHAIN_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_CALCULATE_CHAIN_HPP
+
3 
+
4 #include <valarray>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8  inline double calculate_chain(const double& x, const double& val) {
+
9  return std::exp(x - val); // works out to inv_logit(x)
+
10  }
+
11  }
+
12 }
+
13 #endif
+ +
double calculate_chain(const double &x, const double &val)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
+
+
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diff --git a/doc/api/html/categorical__log_8hpp.html b/doc/api/html/categorical__log_8hpp.html new file mode 100644 index 00000000000..f9bc4a2c7f3 --- /dev/null +++ b/doc/api/html/categorical__log_8hpp.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/categorical_log.hpp File Reference + + + + + + + + + + +
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categorical_log.hpp File Reference
+
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+
#include <boost/random/uniform_01.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <stan/math/prim/mat/err/check_simplex.hpp>
+#include <stan/math/prim/scal/err/check_bounded.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <stan/math/prim/mat/fun/sum.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <cmath>
+#include <vector>
+
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template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::categorical_log (int n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::categorical_log (const typename math::index_type< Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > >::type n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::categorical_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::categorical_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
+
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diff --git a/doc/api/html/categorical__log_8hpp_source.html b/doc/api/html/categorical__log_8hpp_source.html new file mode 100644 index 00000000000..f8311fda027 --- /dev/null +++ b/doc/api/html/categorical__log_8hpp_source.html @@ -0,0 +1,250 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/categorical_log.hpp Source File + + + + + + + + + + +
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+ + +
+ +
+ + +
+
+
+
categorical_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_CATEGORICAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_CATEGORICAL_LOG_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + +
14 #include <cmath>
+
15 #include <vector>
+
16 
+
17 namespace stan {
+
18 
+
19  namespace math {
+
20 
+
21  // Categorical(n|theta) [0 < n <= N; 0 <= theta[n] <= 1; SUM theta = 1]
+
22  template <bool propto,
+
23  typename T_prob>
+
24  typename boost::math::tools::promote_args<T_prob>::type
+ +
26  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta) {
+
27  static const char* function("stan::math::categorical_log");
+
28 
+ + +
31  using boost::math::tools::promote_args;
+ +
33  using std::log;
+
34 
+
35  int lb = 1;
+
36 
+
37  T_prob lp = 0.0;
+
38  check_bounded(function, "Number of categories", n, lb, theta.size());
+
39 
+ +
41  if (!check_simplex(function, "Probabilities parameter", theta))
+
42  return lp;
+
43  } else {
+
44  if (!check_simplex(function, "Probabilities parameter", theta))
+
45  return lp;
+
46  }
+
47 
+ +
49  return log(theta(n-1));
+
50  return 0.0;
+
51  }
+
52 
+
53  template <typename T_prob>
+
54  inline
+
55  typename boost::math::tools::promote_args<T_prob>::type
+
56  categorical_log(const typename
+
57  math::index_type<Eigen::Matrix<T_prob,
+
58  Eigen::Dynamic, 1> >::type n,
+
59  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta) {
+
60  return categorical_log<false>(n, theta);
+
61  }
+
62 
+
63 
+
64  // Categorical(n|theta) [0 < n <= N; 0 <= theta[n] <= 1; SUM theta = 1]
+
65  template <bool propto,
+
66  typename T_prob>
+
67  typename boost::math::tools::promote_args<T_prob>::type
+
68  categorical_log(const std::vector<int>& ns,
+
69  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta) {
+
70  static const char* function("stan::math::categorical_log");
+
71 
+
72  using boost::math::tools::promote_args;
+ + +
75  using stan::math::sum;
+ +
77  using std::log;
+
78 
+
79  int lb = 1;
+
80 
+
81  T_prob lp = 0.0;
+
82  for (size_t i = 0; i < ns.size(); ++i)
+
83  check_bounded(function, "element of outcome array", ns[i],
+
84  lb, theta.size());
+
85 
+ +
87  if (!check_simplex(function, "Probabilities parameter", theta))
+
88  return lp;
+
89  } else {
+
90  if (!check_simplex(function, "Probabilities parameter", theta))
+
91  return lp;
+
92  }
+
93 
+ +
95  return 0.0;
+
96 
+
97  if (ns.size() == 0)
+
98  return 0.0;
+
99 
+
100  Eigen::Matrix<T_prob, Eigen::Dynamic, 1> log_theta(theta.size());
+
101  for (int i = 0; i < theta.size(); ++i)
+
102  log_theta(i) = log(theta(i));
+
103 
+
104  Eigen::Matrix<typename boost::math::tools::promote_args<T_prob>::type,
+
105  Eigen::Dynamic, 1> log_theta_ns(ns.size());
+
106  for (size_t i = 0; i < ns.size(); ++i)
+
107  log_theta_ns(i) = log_theta(ns[i] - 1);
+
108 
+
109  return sum(log_theta_ns);
+
110  }
+
111 
+
112 
+
113  template <typename T_prob>
+
114  inline
+
115  typename boost::math::tools::promote_args<T_prob>::type
+
116  categorical_log(const std::vector<int>& ns,
+
117  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta) {
+
118  return categorical_log<false>(ns, theta);
+
119  }
+
120 
+
121  }
+
122 }
+
123 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ +
boost::math::tools::promote_args< T_prob >::type categorical_log(int n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
+ + + +
bool check_simplex(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is simplex.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/categorical__logit__log_8hpp.html b/doc/api/html/categorical__logit__log_8hpp.html new file mode 100644 index 00000000000..a00e1dfcf30 --- /dev/null +++ b/doc/api/html/categorical__logit__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/categorical_logit_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
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+
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+
categorical_logit_log.hpp File Reference
+
+
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Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + +

+Functions

template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::categorical_logit_log (int n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::categorical_logit_log (int n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
 
template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::categorical_logit_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::categorical_logit_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/categorical__logit__log_8hpp_source.html b/doc/api/html/categorical__logit__log_8hpp_source.html new file mode 100644 index 00000000000..8d410a44f79 --- /dev/null +++ b/doc/api/html/categorical__logit__log_8hpp_source.html @@ -0,0 +1,222 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/categorical_logit_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
categorical_logit_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_CATEGORICAL_LOGIT_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_CATEGORICAL_LOGIT_LOG_HPP
+
3 
+ + + + + + + +
11 #include <boost/math/tools/promotion.hpp>
+
12 #include <vector>
+
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
17 
+
18  // CategoricalLog(n|theta) [0 < n <= N, theta unconstrained], no checking
+
19  template <bool propto,
+
20  typename T_prob>
+
21  typename boost::math::tools::promote_args<T_prob>::type
+ +
23  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>&
+
24  beta) {
+
25  static const char* function("stan::math::categorical_logit_log");
+
26 
+ + + +
30 
+
31  check_bounded(function, "categorical outcome out of support", n,
+
32  1, beta.size());
+
33  check_finite(function, "log odds parameter", beta);
+
34 
+ +
36  return 0.0;
+
37 
+
38  // FIXME: wasteful vs. creating term (n-1) if not vectorized
+
39  return beta(n-1) - log_sum_exp(beta); // == log_softmax(beta)(n-1);
+
40  }
+
41 
+
42  template <typename T_prob>
+
43  inline
+
44  typename boost::math::tools::promote_args<T_prob>::type
+ +
46  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>&
+
47  beta) {
+
48  return categorical_logit_log<false>(n, beta);
+
49  }
+
50 
+
51  template <bool propto,
+
52  typename T_prob>
+
53  typename boost::math::tools::promote_args<T_prob>::type
+
54  categorical_logit_log(const std::vector<int>& ns,
+
55  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>&
+
56  beta) {
+
57  static const char* function("stan::math::categorical_logit_log");
+
58 
+ + + +
62  using stan::math::sum;
+
63 
+
64  for (size_t k = 0; k < ns.size(); ++k)
+
65  check_bounded(function, "categorical outcome out of support",
+
66  ns[k], 1, beta.size());
+
67  check_finite(function, "log odds parameter", beta);
+
68 
+ +
70  return 0.0;
+
71 
+
72  if (ns.size() == 0)
+
73  return 0.0;
+
74 
+
75  Eigen::Matrix<T_prob, Eigen::Dynamic, 1> log_softmax_beta
+
76  = log_softmax(beta);
+
77 
+
78  // FIXME: replace with more efficient sum()
+
79  Eigen::Matrix<typename boost::math::tools::promote_args<T_prob>::type,
+
80  Eigen::Dynamic, 1> results(ns.size());
+
81  for (size_t i = 0; i < ns.size(); ++i)
+
82  results[i] = log_softmax_beta(ns[i] - 1);
+
83  return sum(results);
+
84  }
+
85 
+
86  template <typename T_prob>
+
87  inline
+
88  typename boost::math::tools::promote_args<T_prob>::type
+
89  categorical_logit_log(const std::vector<int>& ns,
+
90  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>&
+
91  beta) {
+
92  return categorical_logit_log<false>(ns, beta);
+
93  }
+
94 
+
95 
+
96  }
+
97 }
+
98 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+
boost::math::tools::promote_args< T_prob >::type categorical_logit_log(int n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
+ +
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > log_softmax(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
Definition: log_softmax.hpp:16
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/categorical__rng_8hpp.html b/doc/api/html/categorical__rng_8hpp.html new file mode 100644 index 00000000000..606e230dca9 --- /dev/null +++ b/doc/api/html/categorical__rng_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/categorical_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+ + +
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+ + +
+
+ +
+
categorical_rng.hpp File Reference
+
+
+
#include <boost/random/uniform_01.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <stan/math/prim/mat/err/check_simplex.hpp>
+#include <stan/math/prim/scal/err/check_bounded.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <stan/math/prim/mat/fun/sum.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+
+

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+ + + + +

+Functions

template<class RNG >
int stan::math::categorical_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &theta, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/categorical__rng_8hpp_source.html b/doc/api/html/categorical__rng_8hpp_source.html new file mode 100644 index 00000000000..2ceed53f4db --- /dev/null +++ b/doc/api/html/categorical__rng_8hpp_source.html @@ -0,0 +1,168 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/categorical_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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categorical_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_CATEGORICAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_CATEGORICAL_RNG_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + +
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
17 
+
18  template <class RNG>
+
19  inline int
+
20  categorical_rng(const Eigen::Matrix<double, Eigen::Dynamic, 1>& theta,
+
21  RNG& rng) {
+
22  using boost::variate_generator;
+
23  using boost::uniform_01;
+ +
25 
+
26  static const char* function("stan::math::categorical_rng");
+
27 
+
28  check_simplex(function, "Probabilities parameter", theta);
+
29 
+
30  variate_generator<RNG&, uniform_01<> >
+
31  uniform01_rng(rng, uniform_01<>());
+
32 
+
33  Eigen::VectorXd index(theta.rows());
+
34  index.setZero();
+
35 
+
36  for (int i = 0; i < theta.rows(); i++) {
+
37  for (int j = i; j < theta.rows(); j++)
+
38  index(j) += theta(i, 0);
+
39  }
+
40 
+
41  double c = uniform01_rng();
+
42  int b = 0;
+
43  while (c > index(b, 0))
+
44  b++;
+
45  return b + 1;
+
46  }
+
47  }
+
48 }
+
49 #endif
+ + + +
int categorical_rng(const Eigen::Matrix< double, Eigen::Dynamic, 1 > &theta, RNG &rng)
+ + + + +
bool check_simplex(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is simplex.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cauchy__ccdf__log_8hpp.html b/doc/api/html/cauchy__ccdf__log_8hpp.html new file mode 100644 index 00000000000..f9a79bd77de --- /dev/null +++ b/doc/api/html/cauchy__ccdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_ccdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
cauchy_ccdf_log.hpp File Reference
+
+
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::cauchy_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cauchy__ccdf__log_8hpp_source.html b/doc/api/html/cauchy__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..ae0923cc234 --- /dev/null +++ b/doc/api/html/cauchy__ccdf__log_8hpp_source.html @@ -0,0 +1,236 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_ccdf_log.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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cauchy_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CAUCHY_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CAUCHY_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/cauchy_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <typename T_y, typename T_loc, typename T_scale>
+
25  typename return_type<T_y, T_loc, T_scale>::type
+
26  cauchy_ccdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+ +
28  T_partials_return;
+
29 
+
30  // Size checks
+
31  if ( !( stan::length(y) && stan::length(mu)
+
32  && stan::length(sigma) ) )
+
33  return 0.0;
+
34 
+
35  static const char* function("stan::math::cauchy_cdf");
+
36 
+ + + + +
41  using boost::math::tools::promote_args;
+ +
43 
+
44  T_partials_return ccdf_log(0.0);
+
45 
+
46  check_not_nan(function, "Random variable", y);
+
47  check_finite(function, "Location parameter", mu);
+
48  check_positive_finite(function, "Scale parameter", sigma);
+
49  check_consistent_sizes(function,
+
50  "Random variable", y,
+
51  "Location parameter", mu,
+
52  "Scale Parameter", sigma);
+
53 
+
54  // Wrap arguments in vectors
+
55  VectorView<const T_y> y_vec(y);
+
56  VectorView<const T_loc> mu_vec(mu);
+
57  VectorView<const T_scale> sigma_vec(sigma);
+
58  size_t N = max_size(y, mu, sigma);
+
59 
+ +
61  operands_and_partials(y, mu, sigma);
+
62 
+
63  // Compute CDFLog and its gradients
+
64  using std::atan;
+
65  using stan::math::pi;
+
66  using std::log;
+
67 
+
68  // Compute vectorized CDF and gradient
+
69  for (size_t n = 0; n < N; n++) {
+
70  // Pull out values
+
71  const T_partials_return y_dbl = value_of(y_vec[n]);
+
72  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
73  const T_partials_return sigma_inv_dbl = 1.0 / value_of(sigma_vec[n]);
+
74  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
75  const T_partials_return z = (y_dbl - mu_dbl) * sigma_inv_dbl;
+
76 
+
77  // Compute
+
78  const T_partials_return Pn = 0.5 - atan(z) / pi();
+
79  ccdf_log += log(Pn);
+
80 
+
81  const T_partials_return rep_deriv = 1.0 / (Pn * pi()
+
82  * (z * z * sigma_dbl
+
83  + sigma_dbl));
+ +
85  operands_and_partials.d_x1[n] -= rep_deriv;
+ +
87  operands_and_partials.d_x2[n] += rep_deriv;
+ +
89  operands_and_partials.d_x3[n] += rep_deriv * z;
+
90  }
+
91  return operands_and_partials.value(ccdf_log);
+
92  }
+
93  }
+
94 }
+
95 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
fvar< T > atan(const fvar< T > &x)
Definition: atan.hpp:12
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
return_type< T_y, T_loc, T_scale >::type cauchy_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/cauchy__cdf_8hpp.html b/doc/api/html/cauchy__cdf_8hpp.html new file mode 100644 index 00000000000..ebe56e07214 --- /dev/null +++ b/doc/api/html/cauchy__cdf_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_cdf.hpp File Reference + + + + + + + + + + +
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+Functions

template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::cauchy_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 Calculates the cauchy cumulative distribution function for the given variate, location, and scale. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cauchy__cdf_8hpp_source.html b/doc/api/html/cauchy__cdf_8hpp_source.html new file mode 100644 index 00000000000..61cf60fc1b7 --- /dev/null +++ b/doc/api/html/cauchy__cdf_8hpp_source.html @@ -0,0 +1,262 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_cdf.hpp Source File + + + + + + + + + + +
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cauchy_cdf.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CAUCHY_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CAUCHY_CDF_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/cauchy_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <limits>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
36  template <typename T_y, typename T_loc, typename T_scale>
+
37  typename return_type<T_y, T_loc, T_scale>::type
+
38  cauchy_cdf(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+ +
40  T_partials_return;
+
41 
+
42  // Size checks
+
43  if ( !( stan::length(y) && stan::length(mu)
+
44  && stan::length(sigma) ) )
+
45  return 1.0;
+
46 
+
47  static const char* function("stan::math::cauchy_cdf");
+
48 
+ + + + +
53  using boost::math::tools::promote_args;
+ +
55 
+
56  T_partials_return P(1.0);
+
57 
+
58  check_not_nan(function, "Random variable", y);
+
59  check_finite(function, "Location parameter", mu);
+
60  check_positive_finite(function, "Scale parameter", sigma);
+
61  check_consistent_sizes(function,
+
62  "Random variable", y,
+
63  "Location parameter", mu,
+
64  "Scale Parameter", sigma);
+
65 
+
66  // Wrap arguments in vectors
+
67  VectorView<const T_y> y_vec(y);
+
68  VectorView<const T_loc> mu_vec(mu);
+
69  VectorView<const T_scale> sigma_vec(sigma);
+
70  size_t N = max_size(y, mu, sigma);
+
71 
+ +
73  operands_and_partials(y, mu, sigma);
+
74 
+
75  // Explicit return for extreme values
+
76  // The gradients are technically ill-defined, but treated as zero
+
77  for (size_t i = 0; i < stan::length(y); i++) {
+
78  if (value_of(y_vec[i]) == -std::numeric_limits<double>::infinity())
+
79  return operands_and_partials.value(0.0);
+
80  }
+
81 
+
82  // Compute CDF and its gradients
+
83  using std::atan;
+
84  using stan::math::pi;
+
85 
+
86  // Compute vectorized CDF and gradient
+
87  for (size_t n = 0; n < N; n++) {
+
88  // Explicit results for extreme values
+
89  // The gradients are technically ill-defined, but treated as zero
+
90  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
91  continue;
+
92  }
+
93 
+
94  // Pull out values
+
95  const T_partials_return y_dbl = value_of(y_vec[n]);
+
96  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
97  const T_partials_return sigma_inv_dbl = 1.0 / value_of(sigma_vec[n]);
+
98 
+
99  const T_partials_return z = (y_dbl - mu_dbl) * sigma_inv_dbl;
+
100 
+
101  // Compute
+
102  const T_partials_return Pn = atan(z) / pi() + 0.5;
+
103 
+
104  P *= Pn;
+
105 
+ +
107  operands_and_partials.d_x1[n]
+
108  += sigma_inv_dbl / (pi() * (1.0 + z * z) * Pn);
+ +
110  operands_and_partials.d_x2[n]
+
111  += - sigma_inv_dbl / (pi() * (1.0 + z * z) * Pn);
+ +
113  operands_and_partials.d_x3[n]
+
114  += - z * sigma_inv_dbl / (pi() * (1.0 + z * z) * Pn);
+
115  }
+
116 
+ +
118  for (size_t n = 0; n < stan::length(y); ++n)
+
119  operands_and_partials.d_x1[n] *= P;
+
120  }
+ +
122  for (size_t n = 0; n < stan::length(mu); ++n)
+
123  operands_and_partials.d_x2[n] *= P;
+
124  }
+ +
126  for (size_t n = 0; n < stan::length(sigma); ++n)
+
127  operands_and_partials.d_x3[n] *= P;
+
128  }
+
129 
+
130  return operands_and_partials.value(P);
+
131  }
+
132  }
+
133 }
+
134 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
fvar< T > atan(const fvar< T > &x)
Definition: atan.hpp:12
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
return_type< T_y, T_loc, T_scale >::type cauchy_cdf(const T_y &y, const T_loc &mu, const T_scale &sigma)
Calculates the cauchy cumulative distribution function for the given variate, location, and scale.
Definition: cauchy_cdf.hpp:38
+ +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cauchy__cdf__log_8hpp.html b/doc/api/html/cauchy__cdf__log_8hpp.html new file mode 100644 index 00000000000..c53c77b1fcc --- /dev/null +++ b/doc/api/html/cauchy__cdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_cdf_log.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
+
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+
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+
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+Functions

template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::cauchy_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cauchy__cdf__log_8hpp_source.html b/doc/api/html/cauchy__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..037d3177b53 --- /dev/null +++ b/doc/api/html/cauchy__cdf__log_8hpp_source.html @@ -0,0 +1,237 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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cauchy_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CAUCHY_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CAUCHY_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/cauchy_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <typename T_y, typename T_loc, typename T_scale>
+
25  typename return_type<T_y, T_loc, T_scale>::type
+
26  cauchy_cdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+ +
28  T_partials_return;
+
29 
+
30  // Size checks
+
31  if ( !( stan::length(y) && stan::length(mu)
+
32  && stan::length(sigma) ) )
+
33  return 0.0;
+
34 
+
35  static const char* function("stan::math::cauchy_cdf");
+
36 
+ + + + +
41  using boost::math::tools::promote_args;
+ +
43 
+
44  T_partials_return cdf_log(0.0);
+
45 
+
46  check_not_nan(function, "Random variable", y);
+
47  check_finite(function, "Location parameter", mu);
+
48  check_positive_finite(function, "Scale parameter", sigma);
+
49  check_consistent_sizes(function,
+
50  "Random variable", y,
+
51  "Location parameter", mu,
+
52  "Scale Parameter", sigma);
+
53 
+
54  // Wrap arguments in vectors
+
55  VectorView<const T_y> y_vec(y);
+
56  VectorView<const T_loc> mu_vec(mu);
+
57  VectorView<const T_scale> sigma_vec(sigma);
+
58  size_t N = max_size(y, mu, sigma);
+
59 
+ +
61  operands_and_partials(y, mu, sigma);
+
62 
+
63  // Compute CDFLog and its gradients
+
64  using std::atan;
+
65  using stan::math::pi;
+
66  using std::log;
+
67 
+
68  // Compute vectorized CDF and gradient
+
69  for (size_t n = 0; n < N; n++) {
+
70  // Pull out values
+
71  const T_partials_return y_dbl = value_of(y_vec[n]);
+
72  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
73  const T_partials_return sigma_inv_dbl = 1.0 / value_of(sigma_vec[n]);
+
74  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
75 
+
76  const T_partials_return z = (y_dbl - mu_dbl) * sigma_inv_dbl;
+
77 
+
78  // Compute
+
79  const T_partials_return Pn = atan(z) / pi() + 0.5;
+
80  cdf_log += log(Pn);
+
81 
+
82  const T_partials_return rep_deriv
+
83  = 1.0 / (pi() * Pn * (z * z * sigma_dbl + sigma_dbl));
+ +
85  operands_and_partials.d_x1[n] += rep_deriv;
+ +
87  operands_and_partials.d_x2[n] -= rep_deriv;
+ +
89  operands_and_partials.d_x3[n] -= rep_deriv * z;
+
90  }
+
91  return operands_and_partials.value(cdf_log);
+
92  }
+
93 
+
94  }
+
95 }
+
96 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_loc, T_scale >::type cauchy_cdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
fvar< T > atan(const fvar< T > &x)
Definition: atan.hpp:12
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cauchy__log_8hpp.html b/doc/api/html/cauchy__log_8hpp.html new file mode 100644 index 00000000000..0bf0db53311 --- /dev/null +++ b/doc/api/html/cauchy__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_log.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
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+
+
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+ + + + + + + +

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template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::cauchy_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 The log of the Cauchy density for the specified scalar(s) given the specified location parameter(s) and scale parameter(s). More...
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::cauchy_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
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diff --git a/doc/api/html/cauchy__log_8hpp_source.html b/doc/api/html/cauchy__log_8hpp_source.html new file mode 100644 index 00000000000..e64bb6e67c2 --- /dev/null +++ b/doc/api/html/cauchy__log_8hpp_source.html @@ -0,0 +1,283 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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cauchy_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CAUCHY_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CAUCHY_LOG_HPP
+
3 
+ + + + + + + + + + + + + +
17 #include <boost/random/cauchy_distribution.hpp>
+
18 #include <boost/random/variate_generator.hpp>
+
19 #include <cmath>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
42  template <bool propto,
+
43  typename T_y, typename T_loc, typename T_scale>
+
44  typename return_type<T_y, T_loc, T_scale>::type
+
45  cauchy_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
46  static const char* function("stan::math::cauchy_log");
+ +
48  T_partials_return;
+
49 
+ + + + + + +
56 
+
57  // check if any vectors are zero length
+
58  if (!(stan::length(y)
+
59  && stan::length(mu)
+
60  && stan::length(sigma)))
+
61  return 0.0;
+
62 
+
63  // set up return value accumulator
+
64  T_partials_return logp(0.0);
+
65 
+
66  // validate args (here done over var, which should be OK)
+
67  check_not_nan(function, "Random variable", y);
+
68  check_finite(function, "Location parameter", mu);
+
69  check_positive_finite(function, "Scale parameter", sigma);
+
70  check_consistent_sizes(function,
+
71  "Random variable", y,
+
72  "Location parameter", mu,
+
73  "Scale parameter", sigma);
+
74 
+
75  // check if no variables are involved and prop-to
+ +
77  return 0.0;
+
78 
+
79  using stan::math::log1p;
+
80  using stan::math::square;
+
81  using std::log;
+
82 
+
83  // set up template expressions wrapping scalars into vector views
+
84  VectorView<const T_y> y_vec(y);
+
85  VectorView<const T_loc> mu_vec(mu);
+
86  VectorView<const T_scale> sigma_vec(sigma);
+
87  size_t N = max_size(y, mu, sigma);
+
88 
+ +
90  VectorBuilder<true, T_partials_return,
+
91  T_scale> sigma_squared(length(sigma));
+ +
93  T_partials_return, T_scale> log_sigma(length(sigma));
+
94  for (size_t i = 0; i < length(sigma); i++) {
+
95  const T_partials_return sigma_dbl = value_of(sigma_vec[i]);
+
96  inv_sigma[i] = 1.0 / sigma_dbl;
+
97  sigma_squared[i] = sigma_dbl * sigma_dbl;
+ +
99  log_sigma[i] = log(sigma_dbl);
+
100  }
+
101  }
+
102 
+ +
104  operands_and_partials(y, mu, sigma);
+
105 
+
106  for (size_t n = 0; n < N; n++) {
+
107  // pull out values of arguments
+
108  const T_partials_return y_dbl = value_of(y_vec[n]);
+
109  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
110 
+
111  // reusable subexpression values
+
112  const T_partials_return y_minus_mu
+
113  = y_dbl - mu_dbl;
+
114  const T_partials_return y_minus_mu_squared
+
115  = y_minus_mu * y_minus_mu;
+
116  const T_partials_return y_minus_mu_over_sigma
+
117  = y_minus_mu * inv_sigma[n];
+
118  const T_partials_return y_minus_mu_over_sigma_squared
+
119  = y_minus_mu_over_sigma * y_minus_mu_over_sigma;
+
120 
+
121  // log probability
+ +
123  logp += NEG_LOG_PI;
+ +
125  logp -= log_sigma[n];
+ +
127  logp -= log1p(y_minus_mu_over_sigma_squared);
+
128 
+
129  // gradients
+ +
131  operands_and_partials.d_x1[n] -= 2 * y_minus_mu
+
132  / (sigma_squared[n] + y_minus_mu_squared);
+ +
134  operands_and_partials.d_x2[n] += 2 * y_minus_mu
+
135  / (sigma_squared[n] + y_minus_mu_squared);
+ +
137  operands_and_partials.d_x3[n]
+
138  += (y_minus_mu_squared - sigma_squared[n])
+
139  * inv_sigma[n] / (sigma_squared[n] + y_minus_mu_squared);
+
140  }
+
141  return operands_and_partials.value(logp);
+
142  }
+
143 
+
144  template <typename T_y, typename T_loc, typename T_scale>
+
145  inline
+ +
147  cauchy_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
148  return cauchy_log<false>(y, mu, sigma);
+
149  }
+
150 
+
151 
+
152  }
+
153 }
+
154 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
const double NEG_LOG_PI
Definition: constants.hpp:186
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
return_type< T_y, T_loc, T_scale >::type cauchy_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
The log of the Cauchy density for the specified scalar(s) given the specified location parameter(s) a...
Definition: cauchy_log.hpp:45
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cauchy__rng_8hpp.html b/doc/api/html/cauchy__rng_8hpp.html new file mode 100644 index 00000000000..04da18c5099 --- /dev/null +++ b/doc/api/html/cauchy__rng_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::cauchy_rng (const double mu, const double sigma, RNG &rng)
 
+
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diff --git a/doc/api/html/cauchy__rng_8hpp_source.html b/doc/api/html/cauchy__rng_8hpp_source.html new file mode 100644 index 00000000000..4bfa2d799a8 --- /dev/null +++ b/doc/api/html/cauchy__rng_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/cauchy_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CAUCHY_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CAUCHY_RNG_HPP
+
3 
+
4 #include <boost/random/cauchy_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + +
15 
+
16 namespace stan {
+
17 
+
18  namespace math {
+
19 
+
20  template <class RNG>
+
21  inline double
+
22  cauchy_rng(const double mu,
+
23  const double sigma,
+
24  RNG& rng) {
+
25  using boost::variate_generator;
+
26  using boost::random::cauchy_distribution;
+
27 
+
28  static const char* function("stan::math::cauchy_rng");
+
29 
+ + +
32 
+
33  check_finite(function, "Location parameter", mu);
+
34  check_positive_finite(function, "Scale parameter", sigma);
+
35 
+
36  variate_generator<RNG&, cauchy_distribution<> >
+
37  cauchy_rng(rng, cauchy_distribution<>(mu, sigma));
+
38  return cauchy_rng();
+
39  }
+
40  }
+
41 }
+
42 #endif
+ + + + + +
double cauchy_rng(const double mu, const double sigma, RNG &rng)
Definition: cauchy_rng.hpp:22
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
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diff --git a/doc/api/html/chainable__alloc_8hpp.html b/doc/api/html/chainable__alloc_8hpp.html new file mode 100644 index 00000000000..2145171afcc --- /dev/null +++ b/doc/api/html/chainable__alloc_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/chainable_alloc.hpp File Reference + + + + + + + + + + +
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class  stan::math::chainable_alloc
 A chainable_alloc is an object which is constructed and destructed normally but the memory lifespan is managed along with the arena allocator for the gradient calculation. More...
 
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+Namespaces

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diff --git a/doc/api/html/chainable__alloc_8hpp_source.html b/doc/api/html/chainable__alloc_8hpp_source.html new file mode 100644 index 00000000000..0de406b1ab2 --- /dev/null +++ b/doc/api/html/chainable__alloc_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/core/chainable_alloc.hpp Source File + + + + + + + + + + +
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chainable_alloc.hpp
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1 #ifndef STAN_MATH_REV_CORE_CHAINABLE_ALLOC_HPP
+
2 #define STAN_MATH_REV_CORE_CHAINABLE_ALLOC_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+ +
17  public:
+ +
19  ChainableStack::var_alloc_stack_.push_back(this);
+
20  }
+
21  virtual ~chainable_alloc() { }
+
22  };
+
23 
+
24  }
+
25 }
+
26 #endif
+ +
static std::vector< ChainableAllocT * > var_alloc_stack_
+ + +
A chainable_alloc is an object which is constructed and destructed normally but the memory lifespan i...
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/chainablestack_8hpp.html b/doc/api/html/chainablestack_8hpp.html new file mode 100644 index 00000000000..9a3d6202afb --- /dev/null +++ b/doc/api/html/chainablestack_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/chainablestack.hpp File Reference + + + + + + + + + + +
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+Typedefs

typedef AutodiffStackStorage< vari, chainable_alloc > stan::math::ChainableStack
 
+
+
+
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diff --git a/doc/api/html/chainablestack_8hpp_source.html b/doc/api/html/chainablestack_8hpp_source.html new file mode 100644 index 00000000000..a0330d8b070 --- /dev/null +++ b/doc/api/html/chainablestack_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/chainablestack.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_CHAINABLESTACK_HPP
+
2 #define STAN_MATH_REV_CORE_CHAINABLESTACK_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class vari;
+ +
11 
+ +
13 
+
14  }
+
15 }
+
16 #endif
+ + +
A chainable_alloc is an object which is constructed and destructed normally but the memory lifespan i...
+
AutodiffStackStorage< vari, chainable_alloc > ChainableStack
+ +
+
+
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diff --git a/doc/api/html/check__bounded_8hpp.html b/doc/api/html/check__bounded_8hpp.html new file mode 100644 index 00000000000..2ea8bd04168 --- /dev/null +++ b/doc/api/html/check__bounded_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_bounded.hpp File Reference + + + + + + + + + + +
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struct  stan::math::detail::bounded< T_y, T_low, T_high, y_is_vec >
 
struct  stan::math::detail::bounded< T_y, T_low, T_high, true >
 
+ + + + + + + + +

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 stan::math::detail
 
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+Functions

template<typename T_y , typename T_low , typename T_high >
bool stan::math::check_bounded (const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
 Return true if the value is between the low and high values, inclusively. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__bounded_8hpp_source.html b/doc/api/html/check__bounded_8hpp_source.html new file mode 100644 index 00000000000..4edf27e09aa --- /dev/null +++ b/doc/api/html/check__bounded_8hpp_source.html @@ -0,0 +1,213 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_bounded.hpp Source File + + + + + + + + + + +
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check_bounded.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_BOUNDED_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_BOUNDED_HPP
+
3 
+ + + + +
8 #include <string>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace detail {
+
14 
+
15  // implemented using structs because there is no partial specialization
+
16  // for templated functions
+
17  //
+
18  // default implementation works for scalar T_y. T_low and T_high can
+
19  // be either scalar or vector
+
20  //
+
21  // throws if y, low, or high is nan
+
22  template <typename T_y, typename T_low, typename T_high,
+
23  bool y_is_vec>
+
24  struct bounded {
+
25  static bool check(const char* function,
+
26  const char* name,
+
27  const T_y& y,
+
28  const T_low& low,
+
29  const T_high& high) {
+
30  using stan::max_size;
+
31 
+
32  VectorView<const T_low> low_vec(low);
+
33  VectorView<const T_high> high_vec(high);
+
34  for (size_t n = 0; n < max_size(low, high); n++) {
+
35  if (!(low_vec[n] <= y && y <= high_vec[n])) {
+
36  std::stringstream msg;
+
37  msg << ", but must be between ";
+
38  msg << "(" << low_vec[n] << ", " << high_vec[n] << ")";
+
39  std::string msg_str(msg.str());
+
40  domain_error(function, name, y,
+
41  "is ", msg_str.c_str());
+
42  }
+
43  }
+
44  return true;
+
45  }
+
46  };
+
47 
+
48  template <typename T_y, typename T_low, typename T_high>
+
49  struct bounded<T_y, T_low, T_high, true> {
+
50  static bool check(const char* function,
+
51  const char* name,
+
52  const T_y& y,
+
53  const T_low& low,
+
54  const T_high& high) {
+
55  using stan::length;
+
56  using stan::get;
+
57 
+
58  VectorView<const T_low> low_vec(low);
+
59  VectorView<const T_high> high_vec(high);
+
60  for (size_t n = 0; n < length(y); n++) {
+
61  if (!(low_vec[n] <= get(y, n) && get(y, n) <= high_vec[n])) {
+
62  std::stringstream msg;
+
63  msg << ", but must be between ";
+
64  msg << "(" << low_vec[n] << ", " << high_vec[n] << ")";
+
65  std::string msg_str(msg.str());
+
66  domain_error_vec(function, name, y, n,
+
67  "is ", msg_str.c_str());
+
68  }
+
69  }
+
70  return true;
+
71  }
+
72  };
+
73  }
+
74 
+
94  template <typename T_y, typename T_low, typename T_high>
+
95  inline bool check_bounded(const char* function,
+
96  const char* name,
+
97  const T_y& y,
+
98  const T_low& low,
+
99  const T_high& high) {
+
100  return detail::bounded<T_y, T_low, T_high,
+ +
102  ::check(function, name, y, low, high);
+
103  }
+
104 
+
105  }
+
106 }
+
107 #endif
+
Template metaprogram indicates whether a type is vector_like.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
static bool check(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
+ +
static bool check(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
+ +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
+
+
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diff --git a/doc/api/html/check__cholesky__factor_8hpp.html b/doc/api/html/check__cholesky__factor_8hpp.html new file mode 100644 index 00000000000..903c221a06e --- /dev/null +++ b/doc/api/html/check__cholesky__factor_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_cholesky_factor.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_cholesky_factor (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a valid Cholesky factor. More...
 
+
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diff --git a/doc/api/html/check__cholesky__factor_8hpp_source.html b/doc/api/html/check__cholesky__factor_8hpp_source.html new file mode 100644 index 00000000000..c722f1becb2 --- /dev/null +++ b/doc/api/html/check__cholesky__factor_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_cholesky_factor.hpp Source File + + + + + + + + + + +
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check_cholesky_factor.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_CHOLESKY_FACTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_CHOLESKY_FACTOR_HPP
+
3 
+ + + + +
8 
+
9 
+
10 namespace stan {
+
11  namespace math {
+
33  template <typename T_y>
+
34  inline bool
+ +
36  const char* function,
+
37  const char* name,
+
38  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
39  ) {
+
40  check_less_or_equal(function, "columns and rows of Cholesky factor",
+
41  y.cols(), y.rows());
+
42  check_positive(function, "columns of Cholesky factor", y.cols());
+
43  check_lower_triangular(function, name, y);
+
44  for (int i = 0; i < y.cols(); ++i)
+
45  // FIXME: should report row
+
46  check_positive(function, name, y(i, i));
+
47  return true;
+
48  }
+
49 
+
50  }
+
51 }
+
52 #endif
+
bool check_cholesky_factor(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a valid Cholesky factor.
+ + + +
bool check_lower_triangular(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is lower triangular.
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__cholesky__factor__corr_8hpp.html b/doc/api/html/check__cholesky__factor__corr_8hpp.html new file mode 100644 index 00000000000..600959f84ef --- /dev/null +++ b/doc/api/html/check__cholesky__factor__corr_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_cholesky_factor_corr.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+ + + + + + +
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+
check_cholesky_factor_corr.hpp File Reference
+
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+ + + + + + + +

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 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y >
bool stan::math::check_cholesky_factor_corr (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a valid Cholesky factor of a correlation matrix. More...
 
+
+
+
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diff --git a/doc/api/html/check__cholesky__factor__corr_8hpp_source.html b/doc/api/html/check__cholesky__factor__corr_8hpp_source.html new file mode 100644 index 00000000000..bf1465c7296 --- /dev/null +++ b/doc/api/html/check__cholesky__factor__corr_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_cholesky_factor_corr.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
+
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+
+
+
check_cholesky_factor_corr.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_CHOLESKY_FACTOR_CORR_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_CHOLESKY_FACTOR_CORR_HPP
+
3 
+ + + + + + +
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
37  template <typename T_y>
+
38  bool
+ +
40  const char* function,
+
41  const char* name,
+
42  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
43  ) {
+
44  using Eigen::Dynamic;
+
45  check_square(function, name, y);
+
46  check_lower_triangular(function, name, y);
+
47  for (int i = 0; i < y.rows(); ++i)
+
48  check_positive(function, name, y(i, i));
+
49  for (int i = 0; i < y.rows(); ++i) {
+
50  Eigen::Matrix<T_y, Dynamic, 1>
+
51  y_i = y.row(i).transpose();
+
52  check_unit_vector(function, name, y_i);
+
53  }
+
54  return true;
+
55  }
+
56 
+
57  }
+
58 }
+
59 #endif
+ + + + +
bool check_lower_triangular(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is lower triangular.
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
bool check_cholesky_factor_corr(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a valid Cholesky factor of a correlation matrix.
+
bool check_unit_vector(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is unit vector.
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__column__index_8hpp.html b/doc/api/html/check__column__index_8hpp.html new file mode 100644 index 00000000000..6e3aaf6b26e --- /dev/null +++ b/doc/api/html/check__column__index_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_column_index.hpp File Reference + + + + + + + + + + +
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+
check_column_index.hpp File Reference
+
+
+
#include <stan/math/prim/scal/err/out_of_range.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/scal/meta/error_index.hpp>
+#include <sstream>
+#include <string>
+
+

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 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y , int R, int C>
bool stan::math::check_column_index (const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
 Return true if the specified index is a valid column of the matrix. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__column__index_8hpp_source.html b/doc/api/html/check__column__index_8hpp_source.html new file mode 100644 index 00000000000..988e732fef9 --- /dev/null +++ b/doc/api/html/check__column__index_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_column_index.hpp Source File + + + + + + + + + + +
+
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+
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+
check_column_index.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_COLUMN_INDEX_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_COLUMN_INDEX_HPP
+
3 
+ + + +
7 #include <sstream>
+
8 #include <string>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
36  template <typename T_y, int R, int C>
+
37  inline bool check_column_index(const char* function,
+
38  const char* name,
+
39  const Eigen::Matrix<T_y, R, C>& y,
+
40  const size_t i) {
+ +
42  && i < static_cast<size_t>(y.cols()) + stan::error_index::value)
+
43  return true;
+
44 
+
45  std::stringstream msg;
+
46  msg << " for columns of " << name;
+
47  std::string msg_str(msg.str());
+
48  out_of_range(function,
+
49  y.cols(),
+
50  i,
+
51  msg_str.c_str());
+
52  return false;
+
53  }
+
54 
+
55  }
+
56 }
+
57 #endif
+ + + +
void out_of_range(const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
Throw an out_of_range exception with a consistently formatted message.
+ +
bool check_column_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
Return true if the specified index is a valid column of the matrix.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__consistent__size_8hpp.html b/doc/api/html/check__consistent__size_8hpp.html new file mode 100644 index 00000000000..33a9675b398 --- /dev/null +++ b/doc/api/html/check__consistent__size_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_consistent_size.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
+ +
+
check_consistent_size.hpp File Reference
+
+
+
#include <stan/math/prim/scal/err/invalid_argument.hpp>
+#include <stan/math/prim/scal/meta/size_of.hpp>
+#include <sstream>
+#include <string>
+
+

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 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T >
bool stan::math::check_consistent_size (const char *function, const char *name, const T &x, size_t expected_size)
 Return true if the dimension of x is consistent, which is defined to be expected_size if x is a vector or 1 if x is not a vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__consistent__size_8hpp_source.html b/doc/api/html/check__consistent__size_8hpp_source.html new file mode 100644 index 00000000000..ef7ff64ed39 --- /dev/null +++ b/doc/api/html/check__consistent__size_8hpp_source.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_consistent_size.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
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+
check_consistent_size.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_CONSISTENT_SIZE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_CONSISTENT_SIZE_HPP
+
3 
+ + +
6 #include <sstream>
+
7 #include <string>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
28  template <typename T>
+
29  inline bool check_consistent_size(const char* function,
+
30  const char* name,
+
31  const T& x,
+
32  size_t expected_size) {
+ +
34  return true;
+
35  if (is_vector<T>::value && expected_size == stan::size_of(x))
+
36  return true;
+
37 
+
38  std::stringstream msg;
+
39  msg << ", expecting dimension = "
+
40  << expected_size
+
41  << "; a function was called with arguments of different "
+
42  << "scalar, array, vector, or matrix types, and they were not "
+
43  << "consistently sized; all arguments must be scalars or "
+
44  << "multidimensional values of the same shape.";
+
45  std::string msg_str(msg.str());
+
46 
+
47  invalid_argument(function, name, stan::size_of(x),
+
48  "has dimension = ",
+
49  msg_str.c_str());
+
50  return false;
+
51  }
+
52 
+
53  }
+
54 }
+
55 #endif
+ + + + +
bool check_consistent_size(const char *function, const char *name, const T &x, size_t expected_size)
Return true if the dimension of x is consistent, which is defined to be expected_size if x is a vecto...
+
size_t size_of(const T &x)
Definition: size_of.hpp:24
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__consistent__sizes_8hpp.html b/doc/api/html/check__consistent__sizes_8hpp.html new file mode 100644 index 00000000000..857c0830858 --- /dev/null +++ b/doc/api/html/check__consistent__sizes_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_consistent_sizes.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
check_consistent_sizes.hpp File Reference
+
+
+
#include <stan/math/prim/scal/err/check_consistent_size.hpp>
+#include <algorithm>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + +

+Functions

template<typename T1 , typename T2 >
bool stan::math::check_consistent_sizes (const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
 Return true if the dimension of x1 is consistent with x2. More...
 
template<typename T1 , typename T2 , typename T3 >
bool stan::math::check_consistent_sizes (const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2, const char *name3, const T3 &x3)
 Return true if the dimension of x1, x2, and x3 are consistent. More...
 
template<typename T1 , typename T2 , typename T3 , typename T4 >
bool stan::math::check_consistent_sizes (const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2, const char *name3, const T3 &x3, const char *name4, const T4 &x4)
 Return true if the dimension of x1, x2, x3, and x4 are consistent. More...
 
template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 >
bool stan::math::check_consistent_sizes (const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2, const char *name3, const T3 &x3, const char *name4, const T4 &x4, const char *name5, const T5 &x5)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__consistent__sizes_8hpp_source.html b/doc/api/html/check__consistent__sizes_8hpp_source.html new file mode 100644 index 00000000000..917606f1e6a --- /dev/null +++ b/doc/api/html/check__consistent__sizes_8hpp_source.html @@ -0,0 +1,204 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_consistent_sizes.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+
+
check_consistent_sizes.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_CONSISTENT_SIZES_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_CONSISTENT_SIZES_HPP
+
3 
+ +
5 
+
6 #include <algorithm>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
30  template <typename T1, typename T2>
+
31  inline bool check_consistent_sizes(const char* function,
+
32  const char* name1,
+
33  const T1& x1,
+
34  const char* name2,
+
35  const T2& x2) {
+
36  using stan::is_vector;
+ + +
39  return check_consistent_size(function, name1, x1, max_size)
+
40  && check_consistent_size(function, name2, x2, max_size);
+
41  }
+
42 
+
65  template <typename T1, typename T2, typename T3>
+
66  inline bool check_consistent_sizes(const char* function,
+
67  const char* name1,
+
68  const T1& x1,
+
69  const char* name2,
+
70  const T2& x2,
+
71  const char* name3,
+
72  const T3& x3) {
+ + + +
76  return check_consistent_size(function, name1, x1, max_size)
+
77  && check_consistent_size(function, name2, x2, max_size)
+
78  && check_consistent_size(function, name3, x3, max_size);
+
79  }
+
80 
+
106  template <typename T1, typename T2, typename T3, typename T4>
+
107  inline bool check_consistent_sizes(const char* function,
+
108  const char* name1,
+
109  const T1& x1,
+
110  const char* name2,
+
111  const T2& x2,
+
112  const char* name3,
+
113  const T3& x3,
+
114  const char* name4,
+
115  const T4& x4) {
+
116  size_t max_size
+ + + +
120  is_vector<T4>::value * size_of(x4))));
+
121  return check_consistent_size(function, name1, x1, max_size)
+
122  && check_consistent_size(function, name2, x2, max_size)
+
123  && check_consistent_size(function, name3, x3, max_size)
+
124  && check_consistent_size(function, name4, x4, max_size);
+
125  }
+
126  template <typename T1, typename T2, typename T3, typename T4,
+
127  typename T5>
+
128  inline bool check_consistent_sizes(const char* function,
+
129  const char* name1,
+
130  const T1& x1,
+
131  const char* name2,
+
132  const T2& x2,
+
133  const char* name3,
+
134  const T3& x3,
+
135  const char* name4,
+
136  const T4& x4,
+
137  const char* name5,
+
138  const T5& x5) {
+
139  size_t max_size = std::max(size_of(x1),
+
140  std::max(size_of(x2),
+
141  std::max(size_of(x3),
+
142  std::max(size_of(x4),
+
143  size_of(x5)))));
+
144  return check_consistent_size(function, name1, x1, max_size)
+
145  && check_consistent_size(function, name2, x2, max_size)
+
146  && check_consistent_size(function, name3, x3, max_size)
+
147  && check_consistent_size(function, name4, x4, max_size)
+
148  && check_consistent_size(function, name5, x5, max_size);
+
149  }
+
150 
+
151  }
+
152 }
+
153 #endif
+ + + +
bool check_consistent_size(const char *function, const char *name, const T &x, size_t expected_size)
Return true if the dimension of x is consistent, which is defined to be expected_size if x is a vecto...
+
size_t size_of(const T &x)
Definition: size_of.hpp:24
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__corr__matrix_8hpp.html b/doc/api/html/check__corr__matrix_8hpp.html new file mode 100644 index 00000000000..89f1201ac69 --- /dev/null +++ b/doc/api/html/check__corr__matrix_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_corr_matrix.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+
+ +
+
check_corr_matrix.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y >
bool stan::math::check_corr_matrix (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a valid correlation matrix. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__corr__matrix_8hpp_source.html b/doc/api/html/check__corr__matrix_8hpp_source.html new file mode 100644 index 00000000000..922b2091240 --- /dev/null +++ b/doc/api/html/check__corr__matrix_8hpp_source.html @@ -0,0 +1,187 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_corr_matrix.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
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+ + +
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+
+
check_corr_matrix.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_CORR_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_CORR_MATRIX_HPP
+
3 
+ + + + + + + + + +
13 #include <sstream>
+
14 #include <string>
+
15 
+
16 namespace stan {
+
17 
+
18  namespace math {
+
43  template <typename T_y>
+
44  inline bool
+ +
46  const char* function,
+
47  const char* name,
+
48  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
49  ) {
+
50  using Eigen::Matrix;
+ +
52 
+
53  typedef typename index_type<Matrix<
+
54  T_y, Eigen::Dynamic, Eigen::Dynamic> >::type size_t;
+
55 
+
56  check_size_match(function,
+
57  "Rows of correlation matrix", y.rows(),
+
58  "columns of correlation matrix", y.cols());
+
59  check_positive_size(function, name, "rows", y.rows());
+
60  check_symmetric(function, "y", y);
+
61 
+
62  for (size_t k = 0; k < y.rows(); ++k) {
+
63  if (!(fabs(y(k, k) - 1.0) <= CONSTRAINT_TOLERANCE)) {
+
64  std::ostringstream msg;
+
65  msg << "is not a valid correlation matrix. "
+
66  << name << "(" << stan::error_index::value + k
+
67  << "," << stan::error_index::value + k
+
68  << ") is ";
+
69  std::string msg_str(msg.str());
+
70  domain_error(function, name, y(k, k),
+
71  msg_str.c_str(),
+
72  ", but should be near 1.0");
+
73  return false;
+
74  }
+
75  }
+
76  stan::math::check_pos_definite(function, "y", y);
+
77  return true;
+
78  }
+
79 
+
80  }
+
81 }
+
82 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
bool check_positive_size(const char *function, const char *name, const char *expr, const int size)
Return true if size is positive.
+ + + +
const double CONSTRAINT_TOLERANCE
The tolerance for checking arithmetic bounds In rank and in simplexes.
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
bool check_corr_matrix(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a valid correlation matrix.
+
bool check_pos_definite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified square, symmetric matrix is positive definite.
+ + +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__cov__matrix_8hpp.html b/doc/api/html/check__cov__matrix_8hpp.html new file mode 100644 index 00000000000..901245a31d6 --- /dev/null +++ b/doc/api/html/check__cov__matrix_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_cov_matrix.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_cov_matrix (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a valid covariance matrix. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__cov__matrix_8hpp_source.html b/doc/api/html/check__cov__matrix_8hpp_source.html new file mode 100644 index 00000000000..53801eee46d --- /dev/null +++ b/doc/api/html/check__cov__matrix_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_cov_matrix.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_COV_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_COV_MATRIX_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
29  template <typename T_y>
+
30  inline bool
+ +
32  const char* function,
+
33  const char* name,
+
34  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
35  ) {
+
36  check_pos_definite(function, name, y);
+
37  return true;
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+ + +
bool check_cov_matrix(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a valid covariance matrix.
+
bool check_pos_definite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified square, symmetric matrix is positive definite.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__equal_8hpp.html b/doc/api/html/check__equal_8hpp.html new file mode 100644 index 00000000000..884a53e6b4f --- /dev/null +++ b/doc/api/html/check__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_equal.hpp File Reference + + + + + + + + + + +
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+ + + + + +

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template<typename T_y , typename T_eq >
bool stan::math::check_equal (const char *function, const char *name, const T_y &y, const T_eq &eq)
 Return true if y is equal to eq. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__equal_8hpp_source.html b/doc/api/html/check__equal_8hpp_source.html new file mode 100644 index 00000000000..7861dca785a --- /dev/null +++ b/doc/api/html/check__equal_8hpp_source.html @@ -0,0 +1,196 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_equal.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_EQUAL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_EQUAL_HPP
+
3 
+ + + + + +
9 #include <string>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  namespace {
+
15  template <typename T_y,
+
16  typename T_eq,
+
17  bool is_vec>
+
18  struct equal {
+
19  static bool check(const char* function,
+
20  const char* name,
+
21  const T_y& y,
+
22  const T_eq& eq) {
+
23  using stan::length;
+
24  VectorView<const T_eq> eq_vec(eq);
+
25  for (size_t n = 0; n < length(eq); n++) {
+
26  if (!(y == eq_vec[n])) {
+
27  std::stringstream msg;
+
28  msg << ", but must be equal to ";
+
29  msg << eq_vec[n];
+
30  std::string msg_str(msg.str());
+
31 
+
32  domain_error(function, name, y,
+
33  "is ", msg_str.c_str());
+
34  }
+
35  }
+
36  return true;
+
37  }
+
38  };
+
39 
+
40  // throws if y or eq is nan
+
41  template <typename T_y,
+
42  typename T_eq>
+
43  struct equal<T_y, T_eq, true> {
+
44  static bool check(const char* function,
+
45  const char* name,
+
46  const T_y& y,
+
47  const T_eq& eq) {
+
48  using stan::length;
+
49  using stan::get;
+
50  VectorView<const T_eq> eq_vec(eq);
+
51  for (size_t n = 0; n < length(y); n++) {
+
52  if (!(get(y, n) == eq_vec[n])) {
+
53  std::stringstream msg;
+
54  msg << ", but must be equal to ";
+
55  msg << eq_vec[n];
+
56  std::string msg_str(msg.str());
+
57  domain_error_vec(function, name, y, n,
+
58  "is ", msg_str.c_str());
+
59  }
+
60  }
+
61  return true;
+
62  }
+
63  };
+
64  }
+
65 
+
89  template <typename T_y, typename T_eq>
+
90  inline bool check_equal(const char* function,
+
91  const char* name,
+
92  const T_y& y,
+
93  const T_eq& eq) {
+
94  return equal<T_y, T_eq, is_vector_like<T_y>::value>
+
95  ::check(function, name, y, eq);
+
96  }
+
97  }
+
98 }
+
99 #endif
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
bool check_equal(const char *function, const char *name, const T_y &y, const T_eq &eq)
Return true if y is equal to eq.
Definition: check_equal.hpp:90
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__finite_8hpp.html b/doc/api/html/check__finite_8hpp.html new file mode 100644 index 00000000000..839e081e262 --- /dev/null +++ b/doc/api/html/check__finite_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_finite.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y >
bool stan::math::check_finite (const char *function, const char *name, const T_y &y)
 Return true if y is finite. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__finite_8hpp_source.html b/doc/api/html/check__finite_8hpp_source.html new file mode 100644 index 00000000000..39b3bcc3d82 --- /dev/null +++ b/doc/api/html/check__finite_8hpp_source.html @@ -0,0 +1,176 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_finite.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+ + + + + + +
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+
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+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_FINITE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_FINITE_HPP
+
3 
+ + + + + +
9 #include <boost/math/special_functions/fpclassify.hpp>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  namespace {
+
15  template <typename T_y, bool is_vec>
+
16  struct finite {
+
17  static bool check(const char* function,
+
18  const char* name,
+
19  const T_y& y) {
+ + +
22  domain_error(function, name, y,
+
23  "is ", ", but must be finite!");
+
24  return true;
+
25  }
+
26  };
+
27 
+
28  template <typename T_y>
+
29  struct finite<T_y, true> {
+
30  static bool check(const char* function,
+
31  const char* name,
+
32  const T_y& y) {
+ +
34  using stan::length;
+
35  for (size_t n = 0; n < length(y); n++) {
+ +
37  domain_error_vec(function, name, y, n,
+
38  "is ", ", but must be finite!");
+
39  }
+
40  return true;
+
41  }
+
42  };
+
43  }
+
44 
+
61  template <typename T_y>
+
62  inline bool check_finite(const char* function,
+
63  const char* name,
+
64  const T_y& y) {
+
65  return finite<T_y, is_vector_like<T_y>::value>
+
66  ::check(function, name, y);
+
67  }
+
68  }
+
69 }
+
70 #endif
+
bool isfinite(const stan::math::var &v)
Checks if the given number has finite value.
+ +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__greater_8hpp.html b/doc/api/html/check__greater_8hpp.html new file mode 100644 index 00000000000..8394f8795da --- /dev/null +++ b/doc/api/html/check__greater_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_greater.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y , typename T_low >
bool stan::math::check_greater (const char *function, const char *name, const T_y &y, const T_low &low)
 Return true if y is strictly greater than low. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__greater_8hpp_source.html b/doc/api/html/check__greater_8hpp_source.html new file mode 100644 index 00000000000..ddeb24f2335 --- /dev/null +++ b/doc/api/html/check__greater_8hpp_source.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_greater.hpp Source File + + + + + + + + + + +
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+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+ + +
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+
+
check_greater.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_GREATER_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_GREATER_HPP
+
3 
+ + + + + +
9 #include <functional>
+
10 #include <string>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  namespace {
+
16  template <typename T_y,
+
17  typename T_low,
+
18  bool is_vec>
+
19  struct greater {
+
20  static bool check(const char* function,
+
21  const char* name,
+
22  const T_y& y,
+
23  const T_low& low) {
+
24  using stan::length;
+
25  VectorView<const T_low> low_vec(low);
+
26  for (size_t n = 0; n < length(low); n++) {
+
27  if (!(y > low_vec[n])) {
+
28  std::stringstream msg;
+
29  msg << ", but must be greater than ";
+
30  msg << low_vec[n];
+
31  std::string msg_str(msg.str());
+
32  domain_error(function, name, y,
+
33  "is ", msg_str.c_str());
+
34  }
+
35  }
+
36  return true;
+
37  }
+
38  };
+
39 
+
40  template <typename T_y,
+
41  typename T_low>
+
42  struct greater<T_y, T_low, true> {
+
43  static bool check(const char* function,
+
44  const char* name,
+
45  const T_y& y,
+
46  const T_low& low) {
+
47  using stan::length;
+
48  VectorView<const T_low> low_vec(low);
+
49  for (size_t n = 0; n < length(y); n++) {
+
50  if (!(stan::get(y, n) > low_vec[n])) {
+
51  std::stringstream msg;
+
52  msg << ", but must be greater than ";
+
53  msg << low_vec[n];
+
54  std::string msg_str(msg.str());
+
55  domain_error_vec(function, name, y, n,
+
56  "is ", msg_str.c_str());
+
57  }
+
58  }
+
59  return true;
+
60  }
+
61  };
+
62  }
+
63 
+
83  template <typename T_y, typename T_low>
+
84  inline bool check_greater(const char* function,
+
85  const char* name,
+
86  const T_y& y,
+
87  const T_low& low) {
+
88  return greater<T_y, T_low, is_vector_like<T_y>::value>
+
89  ::check(function, name, y, low);
+
90  }
+
91  }
+
92 }
+
93 #endif
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__greater__or__equal_8hpp.html b/doc/api/html/check__greater__or__equal_8hpp.html new file mode 100644 index 00000000000..b5c6bea245e --- /dev/null +++ b/doc/api/html/check__greater__or__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_greater_or_equal.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
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+
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+ + + + + + + +

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+ + + + + +

+Functions

template<typename T_y , typename T_low >
bool stan::math::check_greater_or_equal (const char *function, const char *name, const T_y &y, const T_low &low)
 Return true if y is greater or equal than low. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__greater__or__equal_8hpp_source.html b/doc/api/html/check__greater__or__equal_8hpp_source.html new file mode 100644 index 00000000000..dcc74606d82 --- /dev/null +++ b/doc/api/html/check__greater__or__equal_8hpp_source.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_greater_or_equal.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
check_greater_or_equal.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_GREATER_OR_EQUAL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_GREATER_OR_EQUAL_HPP
+
3 
+ + + + + +
9 #include <string>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  namespace {
+
15  template <typename T_y,
+
16  typename T_low,
+
17  bool is_vec>
+
18  struct greater_or_equal {
+
19  static bool check(const char* function,
+
20  const char* name,
+
21  const T_y& y,
+
22  const T_low& low) {
+
23  using stan::length;
+
24  VectorView<const T_low> low_vec(low);
+
25  for (size_t n = 0; n < length(low); n++) {
+
26  if (!(y >= low_vec[n])) {
+
27  std::stringstream msg;
+
28  msg << ", but must be greater than or equal to ";
+
29  msg << low_vec[n];
+
30  std::string msg_str(msg.str());
+
31  domain_error(function, name, y,
+
32  "is ", msg_str.c_str());
+
33  }
+
34  }
+
35  return true;
+
36  }
+
37  };
+
38 
+
39  template <typename T_y,
+
40  typename T_low>
+
41  struct greater_or_equal<T_y, T_low, true> {
+
42  static bool check(const char* function,
+
43  const char* name,
+
44  const T_y& y,
+
45  const T_low& low) {
+
46  using stan::length;
+
47  using stan::get;
+
48  VectorView<const T_low> low_vec(low);
+
49  for (size_t n = 0; n < length(y); n++) {
+
50  if (!(get(y, n) >= low_vec[n])) {
+
51  std::stringstream msg;
+
52  msg << ", but must be greater than or equal to ";
+
53  msg << low_vec[n];
+
54  std::string msg_str(msg.str());
+
55  domain_error_vec(function, name, y, n,
+
56  "is ", msg_str.c_str());
+
57  }
+
58  }
+
59  return true;
+
60  }
+
61  };
+
62  }
+
63 
+
83  template <typename T_y, typename T_low>
+
84  inline bool check_greater_or_equal(const char* function,
+
85  const char* name,
+
86  const T_y& y,
+
87  const T_low& low) {
+
88  return greater_or_equal<T_y, T_low, is_vector_like<T_y>::value>
+
89  ::check(function, name, y, low);
+
90  }
+
91  }
+
92 }
+
93 #endif
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__ldlt__factor_8hpp.html b/doc/api/html/check__ldlt__factor_8hpp.html new file mode 100644 index 00000000000..baba3d2362c --- /dev/null +++ b/doc/api/html/check__ldlt__factor_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_ldlt_factor.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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+
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+ +
+
check_ldlt_factor.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/scal/err/domain_error.hpp>
+#include <stan/math/prim/mat/fun/LDLT_factor.hpp>
+#include <sstream>
+#include <string>
+
+

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 Matrices and templated mathematical functions.
 
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+Functions

template<typename T , int R, int C>
bool stan::math::check_ldlt_factor (const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
 Return true if the argument is a valid stan::math::LDLT_factor. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__ldlt__factor_8hpp_source.html b/doc/api/html/check__ldlt__factor_8hpp_source.html new file mode 100644 index 00000000000..bfb8a50a1af --- /dev/null +++ b/doc/api/html/check__ldlt__factor_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_ldlt_factor.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
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+
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+
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+
+
check_ldlt_factor.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_LDLT_FACTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_LDLT_FACTOR_HPP
+
3 
+ + + +
7 #include <sstream>
+
8 #include <string>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
33  template <typename T, int R, int C>
+
34  inline bool check_ldlt_factor(const char* function,
+
35  const char* name,
+ +
37  if (!A.success()) {
+
38  std::ostringstream msg;
+
39  msg << "is not positive definite. "
+
40  << "last conditional variance is ";
+
41  std::string msg_str(msg.str());
+
42  const T too_small = A.vectorD().tail(1)(0);
+
43  domain_error(function, name, too_small,
+
44  msg_str.c_str(), ".");
+
45  return false;
+
46  }
+
47  return true;
+
48  }
+
49 
+
50  }
+
51 }
+
52 #endif
+ + + +
Eigen::Matrix< T, Eigen::Dynamic, 1 > vectorD() const
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodi...
Definition: LDLT_factor.hpp:58
+
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__less_8hpp.html b/doc/api/html/check__less_8hpp.html new file mode 100644 index 00000000000..01b9753800e --- /dev/null +++ b/doc/api/html/check__less_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_less.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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+
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+
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check_less.hpp File Reference
+
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+ + + + + + + +

+Namespaces

 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y , typename T_high >
bool stan::math::check_less (const char *function, const char *name, const T_y &y, const T_high &high)
 Return true if y is strictly less than high. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__less_8hpp_source.html b/doc/api/html/check__less_8hpp_source.html new file mode 100644 index 00000000000..f3f0843aa62 --- /dev/null +++ b/doc/api/html/check__less_8hpp_source.html @@ -0,0 +1,191 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_less.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
check_less.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_LESS_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_LESS_HPP
+
3 
+ + + + + +
9 #include <functional>
+
10 #include <string>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  namespace {
+
16  template <typename T_y, typename T_high, bool is_vec>
+
17  struct less {
+
18  static bool check(const char* function,
+
19  const char* name,
+
20  const T_y& y,
+
21  const T_high& high) {
+
22  using stan::length;
+
23  VectorView<const T_high> high_vec(high);
+
24  for (size_t n = 0; n < length(high); n++) {
+
25  if (!(y < high_vec[n])) {
+
26  std::stringstream msg;
+
27  msg << ", but must be less than ";
+
28  msg << high_vec[n];
+
29  std::string msg_str(msg.str());
+
30  domain_error(function, name, y,
+
31  "is ", msg_str.c_str());
+
32  }
+
33  }
+
34  return true;
+
35  }
+
36  };
+
37 
+
38  template <typename T_y, typename T_high>
+
39  struct less<T_y, T_high, true> {
+
40  static bool check(const char* function,
+
41  const char* name,
+
42  const T_y& y,
+
43  const T_high& high) {
+
44  using stan::length;
+
45  VectorView<const T_high> high_vec(high);
+
46  for (size_t n = 0; n < length(y); n++) {
+
47  if (!(stan::get(y, n) < high_vec[n])) {
+
48  std::stringstream msg;
+
49  msg << ", but must be less than ";
+
50  msg << high_vec[n];
+
51  std::string msg_str(msg.str());
+
52  domain_error_vec(function, name, y, n,
+
53  "is ", msg_str.c_str());
+
54  }
+
55  }
+
56  return true;
+
57  }
+
58  };
+
59  }
+
60 
+
80  template <typename T_y, typename T_high>
+
81  inline bool check_less(const char* function,
+
82  const char* name,
+
83  const T_y& y,
+
84  const T_high& high) {
+
85  return less<T_y, T_high, is_vector_like<T_y>::value>
+
86  ::check(function, name, y, high);
+
87  }
+
88  }
+
89 }
+
90 #endif
+
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__less__or__equal_8hpp.html b/doc/api/html/check__less__or__equal_8hpp.html new file mode 100644 index 00000000000..652188b3ae7 --- /dev/null +++ b/doc/api/html/check__less__or__equal_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_less_or_equal.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
check_less_or_equal.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y , typename T_high >
bool stan::math::check_less_or_equal (const char *function, const char *name, const T_y &y, const T_high &high)
 Return true if y is less or equal to high. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__less__or__equal_8hpp_source.html b/doc/api/html/check__less__or__equal_8hpp_source.html new file mode 100644 index 00000000000..79f84b89565 --- /dev/null +++ b/doc/api/html/check__less__or__equal_8hpp_source.html @@ -0,0 +1,192 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_less_or_equal.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
check_less_or_equal.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_LESS_OR_EQUAL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_LESS_OR_EQUAL_HPP
+
3 
+ + + + + + +
10 #include <string>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  namespace {
+
16  template <typename T_y, typename T_high, bool is_vec>
+
17  struct less_or_equal {
+
18  static bool check(const char* function,
+
19  const char* name,
+
20  const T_y& y,
+
21  const T_high& high) {
+
22  using stan::length;
+
23  VectorView<const T_high> high_vec(high);
+
24  for (size_t n = 0; n < length(high); n++) {
+
25  if (!(y <= high_vec[n])) {
+
26  std::stringstream msg;
+
27  msg << ", but must be less than or equal to ";
+
28  msg << high_vec[n];
+
29  std::string msg_str(msg.str());
+
30  domain_error(function, name, y,
+
31  "is ", msg_str.c_str());
+
32  }
+
33  }
+
34  return true;
+
35  }
+
36  };
+
37 
+
38  template <typename T_y, typename T_high>
+
39  struct less_or_equal<T_y, T_high, true> {
+
40  static bool check(const char* function,
+
41  const char* name,
+
42  const T_y& y,
+
43  const T_high& high) {
+
44  using stan::length;
+
45  VectorView<const T_high> high_vec(high);
+
46  for (size_t n = 0; n < length(y); n++) {
+
47  if (!(stan::get(y, n) <= high_vec[n])) {
+
48  std::stringstream msg;
+
49  msg << ", but must be less than or equal to ";
+
50  msg << high_vec[n];
+
51  std::string msg_str(msg.str());
+
52  domain_error_vec(function, name, y, n,
+
53  "is ", msg_str.c_str());
+
54  }
+
55  }
+
56  return true;
+
57  }
+
58  };
+
59  }
+
60 
+
80  template <typename T_y, typename T_high>
+
81  inline bool check_less_or_equal(const char* function,
+
82  const char* name,
+
83  const T_y& y,
+
84  const T_high& high) {
+
85  return less_or_equal<T_y, T_high, is_vector_like<T_y>::value>
+
86  ::check(function, name, y, high);
+
87  }
+
88  }
+
89 }
+
90 #endif
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__lower__triangular_8hpp.html b/doc/api/html/check__lower__triangular_8hpp.html new file mode 100644 index 00000000000..c610352f301 --- /dev/null +++ b/doc/api/html/check__lower__triangular_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_lower_triangular.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
check_lower_triangular.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/scal/meta/error_index.hpp>
+#include <stan/math/prim/scal/err/domain_error.hpp>
+#include <sstream>
+#include <string>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y >
bool stan::math::check_lower_triangular (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is lower triangular. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__lower__triangular_8hpp_source.html b/doc/api/html/check__lower__triangular_8hpp_source.html new file mode 100644 index 00000000000..890b33cfdf3 --- /dev/null +++ b/doc/api/html/check__lower__triangular_8hpp_source.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_lower_triangular.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
check_lower_triangular.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_LOWER_TRIANGULAR_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_LOWER_TRIANGULAR_HPP
+
3 
+ + + +
7 #include <sstream>
+
8 #include <string>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
32  template <typename T_y>
+
33  inline bool
+ +
35  const char* function,
+
36  const char* name,
+
37  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
38  ) {
+
39  for (int n = 1; n < y.cols(); ++n) {
+
40  for (int m = 0; m < n && m < y.rows(); ++m) {
+
41  if (y(m, n) != 0) {
+
42  std::stringstream msg;
+
43  msg << "is not lower triangular;"
+
44  << " " << name << "[" << stan::error_index::value + m << ","
+
45  << stan::error_index::value + n << "]=";
+
46  std::string msg_str(msg.str());
+
47  domain_error(function, name, y(m, n),
+
48  msg_str.c_str());
+
49  return false;
+
50  }
+
51  }
+
52  }
+
53  return true;
+
54  }
+
55 
+
56  }
+
57 }
+
58 #endif
+ +
bool check_lower_triangular(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is lower triangular.
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__matching__dims_8hpp.html b/doc/api/html/check__matching__dims_8hpp.html new file mode 100644 index 00000000000..3a0f7bc7e3f --- /dev/null +++ b/doc/api/html/check__matching__dims_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_matching_dims.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
check_matching_dims.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
bool stan::math::check_matching_dims (const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
 Return true if the two matrices are of the same size. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__matching__dims_8hpp_source.html b/doc/api/html/check__matching__dims_8hpp_source.html new file mode 100644 index 00000000000..e81463392c1 --- /dev/null +++ b/doc/api/html/check__matching__dims_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_matching_dims.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
check_matching_dims.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_MATCHING_DIMS_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_MATCHING_DIMS_HPP
+
3 
+ + + +
7 #include <sstream>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
36  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
37  inline bool check_matching_dims(const char* function,
+
38  const char* name1,
+
39  const Eigen::Matrix<T1, R1, C1>& y1,
+
40  const char* name2,
+
41  const Eigen::Matrix<T2, R2, C2>& y2) {
+
42  check_size_match(function,
+
43  "Rows of ", name1, y1.rows(),
+
44  "rows of ", name2, y2.rows());
+
45  check_size_match(function,
+
46  "Columns of ", name1, y1.cols(),
+
47  "columns of ", name2, y2.cols());
+
48  return true;
+
49  }
+
50 
+
51  }
+
52 }
+
53 #endif
+ + +
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ + +
+
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diff --git a/doc/api/html/check__matching__sizes_8hpp.html b/doc/api/html/check__matching__sizes_8hpp.html new file mode 100644 index 00000000000..6a92ff747a9 --- /dev/null +++ b/doc/api/html/check__matching__sizes_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_matching_sizes.hpp File Reference + + + + + + + + + + +
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template<typename T_y1 , typename T_y2 >
bool stan::math::check_matching_sizes (const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
 Return true if two structures at the same size. More...
 
+
+
+
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diff --git a/doc/api/html/check__matching__sizes_8hpp_source.html b/doc/api/html/check__matching__sizes_8hpp_source.html new file mode 100644 index 00000000000..f8143f73f0b --- /dev/null +++ b/doc/api/html/check__matching__sizes_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_matching_sizes.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_MATCHING_SIZES_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_MATCHING_SIZES_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
28  template <typename T_y1, typename T_y2>
+
29  inline bool check_matching_sizes(const char* function,
+
30  const char* name1,
+
31  const T_y1& y1,
+
32  const char* name2,
+
33  const T_y2& y2) {
+
34  check_size_match(function,
+
35  "size of ", name1, y1.size(),
+
36  "size of ", name2, y2.size());
+
37  return true;
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+ + +
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__multiplicable_8hpp.html b/doc/api/html/check__multiplicable_8hpp.html new file mode 100644 index 00000000000..c13ee863047 --- /dev/null +++ b/doc/api/html/check__multiplicable_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_multiplicable.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
bool stan::math::check_multiplicable (const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
 Return true if the matrices can be multiplied. More...
 
+
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diff --git a/doc/api/html/check__multiplicable_8hpp_source.html b/doc/api/html/check__multiplicable_8hpp_source.html new file mode 100644 index 00000000000..3174c1cb943 --- /dev/null +++ b/doc/api/html/check__multiplicable_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_multiplicable.hpp Source File + + + + + + + + + + +
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check_multiplicable.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_MULTIPLICABLE_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_MULTIPLICABLE_HPP
+
3 
+
4 
+ + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
32  template <typename T1, typename T2>
+
33  inline bool check_multiplicable(const char* function,
+
34  const char* name1,
+
35  const T1& y1,
+
36  const char* name2,
+
37  const T2& y2) {
+
38  check_positive_size(function, name1, "rows()", y1.rows());
+
39  check_positive_size(function, name2, "cols()", y2.cols());
+
40  check_size_match(function,
+
41  "Columns of ", name1, y1.cols(),
+
42  "Rows of ", name2, y2.rows());
+
43  check_positive_size(function, name1, "cols()", y1.cols());
+
44  return true;
+
45  }
+
46  }
+
47 }
+
48 #endif
+ +
bool check_positive_size(const char *function, const char *name, const char *expr, const int size)
Return true if size is positive.
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__nonnegative_8hpp.html b/doc/api/html/check__nonnegative_8hpp.html new file mode 100644 index 00000000000..159b89fb8a6 --- /dev/null +++ b/doc/api/html/check__nonnegative_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_nonnegative.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_nonnegative (const char *function, const char *name, const T_y &y)
 Return true if y is non-negative. More...
 
+
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diff --git a/doc/api/html/check__nonnegative_8hpp_source.html b/doc/api/html/check__nonnegative_8hpp_source.html new file mode 100644 index 00000000000..8d3fe5b893c --- /dev/null +++ b/doc/api/html/check__nonnegative_8hpp_source.html @@ -0,0 +1,179 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_nonnegative.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_NONNEGATIVE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_NONNEGATIVE_HPP
+
3 
+ + + + + +
9 #include <boost/type_traits/is_unsigned.hpp>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15  namespace {
+
16  template <typename T_y, bool is_vec>
+
17  struct nonnegative {
+
18  static bool check(const char* function,
+
19  const char* name,
+
20  const T_y& y) {
+
21  // have to use not is_unsigned. is_signed will be false
+
22  // floating point types that have no unsigned versions.
+
23  if (!boost::is_unsigned<T_y>::value && !(y >= 0))
+
24  domain_error(function, name, y,
+
25  "is ", ", but must be >= 0!");
+
26  return true;
+
27  }
+
28  };
+
29 
+
30  template <typename T_y>
+
31  struct nonnegative<T_y, true> {
+
32  static bool check(const char* function,
+
33  const char* name,
+
34  const T_y& y) {
+
35  using stan::length;
+ +
37 
+
38  for (size_t n = 0; n < length(y); n++) {
+
39  if (!boost::is_unsigned<typename value_type<T_y>::type>::value
+
40  && !(stan::get(y, n) >= 0))
+
41  domain_error_vec(function, name, y, n,
+
42  "is ", ", but must be >= 0!");
+
43  }
+
44  return true;
+
45  }
+
46  };
+
47  }
+
48 
+
65  template <typename T_y>
+
66  inline bool check_nonnegative(const char* function,
+
67  const char* name,
+
68  const T_y& y) {
+
69  return nonnegative<T_y, is_vector_like<T_y>::value>
+
70  ::check(function, name, y);
+
71  }
+
72  }
+
73 }
+
74 #endif
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
Primary template class for metaprogram to compute the type of values stored in a container.
Definition: value_type.hpp:18
+
+
+
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diff --git a/doc/api/html/check__nonzero__size_8hpp.html b/doc/api/html/check__nonzero__size_8hpp.html new file mode 100644 index 00000000000..1f800429696 --- /dev/null +++ b/doc/api/html/check__nonzero__size_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/err/check_nonzero_size.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/err/invalid_argument.hpp>
+#include <string>
+
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template<typename T_y >
bool stan::math::check_nonzero_size (const char *function, const char *name, const T_y &y)
 Return true if the specified matrix/vector is of non-zero size. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__nonzero__size_8hpp_source.html b/doc/api/html/check__nonzero__size_8hpp_source.html new file mode 100644 index 00000000000..53a0c804a97 --- /dev/null +++ b/doc/api/html/check__nonzero__size_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/err/check_nonzero_size.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_NONZERO_SIZE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_NONZERO_SIZE_HPP
+
3 
+ +
5 #include <string>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
29  template <typename T_y>
+
30  inline bool check_nonzero_size(const char* function,
+
31  const char* name,
+
32  const T_y& y) {
+
33  if (y.size() > 0)
+
34  return true;
+
35 
+
36  invalid_argument(function, name, 0,
+
37  "has size ",
+
38  ", but must have a non-zero size");
+
39  return false;
+
40  }
+
41 
+
42  }
+
43 }
+
44 #endif
+ + +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
+
+
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diff --git a/doc/api/html/check__not__nan_8hpp.html b/doc/api/html/check__not__nan_8hpp.html new file mode 100644 index 00000000000..0ec23ac6c74 --- /dev/null +++ b/doc/api/html/check__not__nan_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_not_nan.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_not_nan (const char *function, const char *name, const T_y &y)
 Return true if y is not NaN. More...
 
+
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diff --git a/doc/api/html/check__not__nan_8hpp_source.html b/doc/api/html/check__not__nan_8hpp_source.html new file mode 100644 index 00000000000..4eb79adffef --- /dev/null +++ b/doc/api/html/check__not__nan_8hpp_source.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_not_nan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_NOT_NAN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_NOT_NAN_HPP
+
3 
+ + + + + +
9 #include <boost/math/special_functions/fpclassify.hpp>
+
10 
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  namespace {
+
16  template <typename T_y, bool is_vec>
+
17  struct not_nan {
+
18  static bool check(const char* function,
+
19  const char* name,
+
20  const T_y& y) {
+ + +
23  domain_error(function, name, y,
+
24  "is ", ", but must not be nan!");
+
25  return true;
+
26  }
+
27  };
+
28 
+
29  template <typename T_y>
+
30  struct not_nan<T_y, true> {
+
31  static bool check(const char* function,
+
32  const char* name,
+
33  const T_y& y) {
+ +
35  for (size_t n = 0; n < stan::length(y); n++) {
+ +
37  domain_error_vec(function, name, y, n,
+
38  "is ", ", but must not be nan!");
+
39  }
+
40  return true;
+
41  }
+
42  };
+
43  }
+
44 
+
62  template <typename T_y>
+
63  inline bool check_not_nan(const char* function,
+
64  const char* name,
+
65  const T_y& y) {
+
66  return not_nan<T_y, is_vector_like<T_y>::value>
+
67  ::check(function, name, y);
+
68  }
+
69 
+
70  }
+
71 }
+
72 #endif
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+ +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + + +
+
+
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diff --git a/doc/api/html/check__pos__definite_8hpp.html b/doc/api/html/check__pos__definite_8hpp.html new file mode 100644 index 00000000000..6b0305481de --- /dev/null +++ b/doc/api/html/check__pos__definite_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_pos_definite.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_pos_definite (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified square, symmetric matrix is positive definite. More...
 
template<typename Derived >
bool stan::math::check_pos_definite (const char *function, const char *name, const Eigen::LDLT< Derived > &cholesky)
 Return true if the specified LDLT transform of a matrix is positive definite. More...
 
template<typename Derived >
bool stan::math::check_pos_definite (const char *function, const char *name, const Eigen::LLT< Derived > &cholesky)
 Return true if the specified LLT transform of a matrix is positive definite. More...
 
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+
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diff --git a/doc/api/html/check__pos__definite_8hpp_source.html b/doc/api/html/check__pos__definite_8hpp_source.html new file mode 100644 index 00000000000..b4e1795628a --- /dev/null +++ b/doc/api/html/check__pos__definite_8hpp_source.html @@ -0,0 +1,198 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_pos_definite.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_POS_DEFINITE_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_POS_DEFINITE_HPP
+
3 
+ + + + + + + + + + + +
15 namespace stan {
+
16 
+
17  namespace math {
+
18 
+
35  template <typename T_y>
+
36  inline bool
+ +
38  const char* function,
+
39  const char* name,
+
40  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
41  ) {
+
42  check_symmetric(function, name, y);
+
43  check_positive_size(function, name, "rows", y.rows());
+
44 
+
45  if (y.rows() == 1 && !(y(0, 0) > CONSTRAINT_TOLERANCE))
+
46  domain_error(function, name, y, "is not positive definite: ");
+
47 
+
48  using Eigen::LDLT;
+
49  using Eigen::Matrix;
+
50  using Eigen::Dynamic;
+
51  LDLT< Matrix<double, Dynamic, Dynamic> > cholesky
+
52  = value_of_rec(y).ldlt();
+
53  if (cholesky.info() != Eigen::Success
+
54  || !cholesky.isPositive()
+
55  || (cholesky.vectorD().array() <= 0.0).any())
+
56  domain_error(function, name, y, "is not positive definite:\n");
+
57  check_not_nan(function, name, y);
+
58  return true;
+
59  }
+
60 
+
75  template <typename Derived>
+
76  inline bool
+
77  check_pos_definite(const char* function,
+
78  const char* name,
+
79  const Eigen::LDLT<Derived>& cholesky) {
+
80  if (cholesky.info() != Eigen::Success
+
81  || !cholesky.isPositive()
+
82  || !(cholesky.vectorD().array() > 0.0).all())
+
83  domain_error(function, "LDLT decomposition of", " failed", name);
+
84  return true;
+
85  }
+
86 
+
101  template <typename Derived>
+
102  inline bool
+
103  check_pos_definite(const char* function,
+
104  const char* name,
+
105  const Eigen::LLT<Derived>& cholesky) {
+
106  if (cholesky.info() != Eigen::Success
+
107  || !(cholesky.matrixLLT().diagonal().array() > 0.0).all())
+
108  domain_error(function, "Cholesky decomposition of", " failed", name);
+
109  return true;
+
110  }
+
111 
+
112  }
+
113 }
+
114 #endif
+ + +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+
bool check_positive_size(const char *function, const char *name, const char *expr, const int size)
Return true if size is positive.
+ +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+ + + + + + +
const double CONSTRAINT_TOLERANCE
The tolerance for checking arithmetic bounds In rank and in simplexes.
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
bool check_pos_definite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified square, symmetric matrix is positive definite.
+ +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__pos__semidefinite_8hpp.html b/doc/api/html/check__pos__semidefinite_8hpp.html new file mode 100644 index 00000000000..241cd42d8e4 --- /dev/null +++ b/doc/api/html/check__pos__semidefinite_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_pos_semidefinite.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_pos_semidefinite (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is positive definite. More...
 
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diff --git a/doc/api/html/check__pos__semidefinite_8hpp_source.html b/doc/api/html/check__pos__semidefinite_8hpp_source.html new file mode 100644 index 00000000000..67650aba1cc --- /dev/null +++ b/doc/api/html/check__pos__semidefinite_8hpp_source.html @@ -0,0 +1,168 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_pos_semidefinite.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_POS_SEMIDEFINITE_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_POS_SEMIDEFINITE_HPP
+
3 
+ + + + + + + + +
12 #include <sstream>
+
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
33  template <typename T_y>
+
34  inline bool
+ +
36  const char* function,
+
37  const char* name,
+
38  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
39  ) {
+
40  check_symmetric(function, name, y);
+
41  check_positive_size(function, name, "rows", y.rows());
+
42 
+
43  if (y.rows() == 1 && !(y(0, 0) >= 0.0))
+
44  domain_error(function, name, y, "is not positive semi-definite: ");
+
45 
+
46  using Eigen::LDLT;
+
47  using Eigen::Matrix;
+
48  using Eigen::Dynamic;
+
49  LDLT<Matrix<double, Dynamic, Dynamic> > cholesky
+
50  = value_of_rec(y).ldlt();
+
51  if (cholesky.info() != Eigen::Success
+
52  || (cholesky.vectorD().array() < 0.0).any())
+
53  domain_error(function, name, y, "is not positive semi-definite:\n");
+
54  check_not_nan(function, name, y);
+
55  return true;
+
56  }
+
57 
+
58  }
+
59 }
+
60 #endif
+ + +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+
bool check_positive_size(const char *function, const char *name, const char *expr, const int size)
Return true if size is positive.
+ +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+ + +
bool check_pos_semidefinite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is positive definite.
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__positive_8hpp.html b/doc/api/html/check__positive_8hpp.html new file mode 100644 index 00000000000..e09fea23c28 --- /dev/null +++ b/doc/api/html/check__positive_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_positive.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_positive (const char *function, const char *name, const T_y &y)
 Return true if y is positive. More...
 
+
+
+
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diff --git a/doc/api/html/check__positive_8hpp_source.html b/doc/api/html/check__positive_8hpp_source.html new file mode 100644 index 00000000000..ef14c1d4c64 --- /dev/null +++ b/doc/api/html/check__positive_8hpp_source.html @@ -0,0 +1,183 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_positive.hpp Source File + + + + + + + + + + +
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check_positive.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_POSITIVE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_POSITIVE_HPP
+
3 
+ + + + + + +
10 #include <boost/type_traits/is_unsigned.hpp>
+
11 
+
12 namespace stan {
+
13 
+
14  namespace math {
+
15 
+
16  namespace {
+
17 
+
18  template <typename T_y, bool is_vec>
+
19  struct positive {
+
20  static bool check(const char* function,
+
21  const char* name,
+
22  const T_y& y) {
+
23  // have to use not is_unsigned. is_signed will be false
+
24  // floating point types that have no unsigned versions.
+
25  if (!boost::is_unsigned<T_y>::value && !(y > 0))
+
26  domain_error(function, name, y,
+
27  "is ", ", but must be > 0!");
+
28  return true;
+
29  }
+
30  };
+
31 
+
32  template <typename T_y>
+
33  struct positive<T_y, true> {
+
34  static bool check(const char* function,
+
35  const char* name,
+
36  const T_y& y) {
+ +
38  using stan::length;
+
39  for (size_t n = 0; n < length(y); n++) {
+
40  if (!boost::is_unsigned<typename value_type<T_y>::type>::value
+
41  && !(stan::get(y, n) > 0))
+
42  domain_error_vec(function, name, y, n,
+
43  "is ", ", but must be > 0!");
+
44  }
+
45  return true;
+
46  }
+
47  };
+
48 
+
49  }
+
50 
+
67  template <typename T_y>
+
68  inline bool check_positive(const char* function,
+
69  const char* name,
+
70  const T_y& y) {
+
71  return positive<T_y, is_vector_like<T_y>::value>
+
72  ::check(function, name, y);
+
73  }
+
74 
+
75  }
+
76 }
+
77 #endif
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + + +
Primary template class for metaprogram to compute the type of values stored in a container.
Definition: value_type.hpp:18
+
+
+
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diff --git a/doc/api/html/check__positive__finite_8hpp.html b/doc/api/html/check__positive__finite_8hpp.html new file mode 100644 index 00000000000..74d0eef5949 --- /dev/null +++ b/doc/api/html/check__positive__finite_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_positive_finite.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_positive_finite (const char *function, const char *name, const T_y &y)
 Return true if y is positive and finite. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__positive__finite_8hpp_source.html b/doc/api/html/check__positive__finite_8hpp_source.html new file mode 100644 index 00000000000..0bef16be022 --- /dev/null +++ b/doc/api/html/check__positive__finite_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_positive_finite.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_POSITIVE_FINITE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_POSITIVE_FINITE_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
27  template <typename T_y>
+
28  inline bool check_positive_finite(const char* function,
+
29  const char* name,
+
30  const T_y& y) {
+
31  stan::math::check_positive(function, name, y);
+
32  stan::math::check_finite(function, name, y);
+
33 
+
34  return true;
+
35  }
+
36 
+
37  }
+
38 }
+
39 #endif
+ + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__positive__ordered_8hpp.html b/doc/api/html/check__positive__ordered_8hpp.html new file mode 100644 index 00000000000..72d5c3316d1 --- /dev/null +++ b/doc/api/html/check__positive__ordered_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_positive_ordered.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_positive_ordered (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, 1 > &y)
 Return true if the specified vector contains non-negative values and is sorted into strictly increasing order. More...
 
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diff --git a/doc/api/html/check__positive__ordered_8hpp_source.html b/doc/api/html/check__positive__ordered_8hpp_source.html new file mode 100644 index 00000000000..945a8ba5161 --- /dev/null +++ b/doc/api/html/check__positive__ordered_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_positive_ordered.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_POSITIVE_ORDERED_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_POSITIVE_ORDERED_HPP
+
3 
+ + + + +
8 
+
9 #include <sstream>
+
10 #include <string>
+
11 
+
12 namespace stan {
+
13 
+
14  namespace math {
+
15 
+
30  template <typename T_y>
+
31  bool
+
32  check_positive_ordered(const char* function,
+
33  const char* name,
+
34  const Eigen::Matrix<T_y, Eigen::Dynamic, 1>& y) {
+
35  using Eigen::Dynamic;
+
36  using Eigen::Matrix;
+ +
38 
+
39  typedef typename index_type<Matrix<T_y, Dynamic, 1> >::type size_type;
+
40  if (y.size() == 0) {
+
41  return true;
+
42  }
+
43  if (y[0] < 0) {
+
44  std::ostringstream msg;
+
45  msg << "is not a valid positive_ordered vector."
+
46  << " The element at " << stan::error_index::value
+
47  << " is ";
+
48  std::string msg_str(msg.str());
+
49  domain_error(function, name, y[0],
+
50  msg_str.c_str(), ", but should be postive.");
+
51  return false;
+
52  }
+
53  check_ordered(function, name, y);
+
54  return true;
+
55  }
+
56  }
+
57 }
+
58 #endif
+ + +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
bool check_ordered(const char *function, const char *name, const std::vector< T_y > &y)
Return true if the specified vector is sorted into strictly increasing order.
+ + +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
bool check_positive_ordered(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, 1 > &y)
Return true if the specified vector contains non-negative values and is sorted into strictly increasi...
+ +
+
+
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diff --git a/doc/api/html/check__positive__size_8hpp.html b/doc/api/html/check__positive__size_8hpp.html new file mode 100644 index 00000000000..63e8be0d53c --- /dev/null +++ b/doc/api/html/check__positive__size_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_positive_size.hpp File Reference + + + + + + + + + + +
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+#include <sstream>
+#include <string>
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bool stan::math::check_positive_size (const char *function, const char *name, const char *expr, const int size)
 Return true if size is positive. More...
 
+
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diff --git a/doc/api/html/check__positive__size_8hpp_source.html b/doc/api/html/check__positive__size_8hpp_source.html new file mode 100644 index 00000000000..6c775cceee8 --- /dev/null +++ b/doc/api/html/check__positive__size_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_positive_size.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_POSITIVE_SIZE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_POSITIVE_SIZE_HPP
+
3 
+ +
5 #include <sstream>
+
6 #include <string>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
23  inline bool check_positive_size(const char* function,
+
24  const char* name,
+
25  const char* expr,
+
26  const int size) {
+
27  if (size <= 0) {
+
28  std::stringstream msg;
+
29  msg << "; dimension size expression = " << expr;
+
30  std::string msg_str(msg.str());
+
31  invalid_argument(function, name, size,
+
32  "must have a positive size, but is ",
+
33  msg_str.c_str());
+
34  }
+
35  return true;
+
36  }
+
37 
+
38  }
+
39 }
+
40 #endif
+
bool check_positive_size(const char *function, const char *name, const char *expr, const int size)
Return true if size is positive.
+ + +
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
+
+
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diff --git a/doc/api/html/check__range_8hpp.html b/doc/api/html/check__range_8hpp.html new file mode 100644 index 00000000000..3dca3013c22 --- /dev/null +++ b/doc/api/html/check__range_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_range.hpp File Reference + + + + + + + + + + +
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bool stan::math::check_range (const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
 Return true if specified index is within range. More...
 
bool stan::math::check_range (const char *function, const char *name, const int max, const int index, const char *error_msg)
 Return true if specified index is within range. More...
 
bool stan::math::check_range (const char *function, const char *name, const int max, const int index)
 Return true if specified index is within range. More...
 
+
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diff --git a/doc/api/html/check__range_8hpp_source.html b/doc/api/html/check__range_8hpp_source.html new file mode 100644 index 00000000000..2033ff05a55 --- /dev/null +++ b/doc/api/html/check__range_8hpp_source.html @@ -0,0 +1,176 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_range.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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check_range.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_RANGE_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_RANGE_HPP
+
3 
+ + + +
7 #include <sstream>
+
8 #include <string>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
29  inline bool check_range(const char* function,
+
30  const char* name,
+
31  const int max,
+
32  const int index,
+
33  const int nested_level,
+
34  const char* error_msg) {
+
35  if ((index >= stan::error_index::value)
+
36  && (index < max + stan::error_index::value))
+
37  return true;
+
38 
+
39  std::stringstream msg;
+
40  msg << "; index position = " << nested_level;
+
41  std::string msg_str(msg.str());
+
42 
+
43  out_of_range(function, max, index, msg_str.c_str(), error_msg);
+
44  return false;
+
45  }
+
46 
+
62  inline bool check_range(const char* function,
+
63  const char* name,
+
64  const int max,
+
65  const int index,
+
66  const char* error_msg) {
+
67  if ((index >= stan::error_index::value)
+
68  && (index < max + stan::error_index::value))
+
69  return true;
+
70 
+
71  out_of_range(function, max, index, error_msg);
+
72  return false;
+
73  }
+
74 
+
89  inline bool check_range(const char* function,
+
90  const char* name,
+
91  const int max,
+
92  const int index) {
+
93  if ((index >= stan::error_index::value)
+
94  && (index < max + stan::error_index::value))
+
95  return true;
+
96 
+
97  out_of_range(function, max, index);
+
98  return false;
+
99  }
+
100 
+
101 
+
102  }
+
103 }
+
104 #endif
+ + +
bool check_range(const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
Return true if specified index is within range.
Definition: check_range.hpp:29
+ + +
void out_of_range(const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
Throw an out_of_range exception with a consistently formatted message.
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ +
+
+
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diff --git a/doc/api/html/check__row__index_8hpp.html b/doc/api/html/check__row__index_8hpp.html new file mode 100644 index 00000000000..788b6815622 --- /dev/null +++ b/doc/api/html/check__row__index_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_row_index.hpp File Reference + + + + + + + + + + +
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+
check_row_index.hpp File Reference
+
+
+
#include <stan/math/prim/scal/err/out_of_range.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <sstream>
+#include <string>
+
+

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template<typename T_y , int R, int C>
bool stan::math::check_row_index (const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
 Return true if the specified index is a valid row of the matrix. More...
 
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diff --git a/doc/api/html/check__row__index_8hpp_source.html b/doc/api/html/check__row__index_8hpp_source.html new file mode 100644 index 00000000000..06f55d8a846 --- /dev/null +++ b/doc/api/html/check__row__index_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_row_index.hpp Source File + + + + + + + + + + +
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check_row_index.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_ROW_INDEX_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_ROW_INDEX_HPP
+
3 
+ + +
6 
+
7 #include <sstream>
+
8 #include <string>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
31  template <typename T_y, int R, int C>
+
32  inline bool check_row_index(const char* function,
+
33  const char* name,
+
34  const Eigen::Matrix<T_y, R, C>& y,
+
35  size_t i) {
+ +
37  && i < static_cast<size_t>(y.rows()) + stan::error_index::value)
+
38  return true;
+
39 
+
40  std::stringstream msg;
+
41  msg << " for rows of " << name;
+
42  std::string msg_str(msg.str());
+
43  out_of_range(function,
+
44  y.rows(),
+
45  i,
+
46  msg_str.c_str());
+
47  return false;
+
48  }
+
49 
+
50  }
+
51 }
+
52 #endif
+ + +
bool check_row_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
Return true if the specified index is a valid row of the matrix.
+ +
void out_of_range(const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
Throw an out_of_range exception with a consistently formatted message.
+ +
+
+
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diff --git a/doc/api/html/check__simplex_8hpp.html b/doc/api/html/check__simplex_8hpp.html new file mode 100644 index 00000000000..5282b607a41 --- /dev/null +++ b/doc/api/html/check__simplex_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_simplex.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+Functions

template<typename T_prob >
bool stan::math::check_simplex (const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 Return true if the specified vector is simplex. More...
 
+
+
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diff --git a/doc/api/html/check__simplex_8hpp_source.html b/doc/api/html/check__simplex_8hpp_source.html new file mode 100644 index 00000000000..0d044a42d5a --- /dev/null +++ b/doc/api/html/check__simplex_8hpp_source.html @@ -0,0 +1,181 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_simplex.hpp Source File + + + + + + + + + + +
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check_simplex.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_SIMPLEX_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_SIMPLEX_HPP
+
3 
+ + + + + + +
10 #include <sstream>
+
11 #include <string>
+
12 
+
13 namespace stan {
+
14 
+
15  namespace math {
+
16 
+
40  template <typename T_prob>
+
41  bool check_simplex(const char* function,
+
42  const char* name,
+
43  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta) {
+
44  using Eigen::Dynamic;
+
45  using Eigen::Matrix;
+ +
47 
+
48  typedef typename index_type<Matrix<T_prob, Dynamic, 1> >::type size_t;
+
49 
+
50  check_nonzero_size(function, name, theta);
+
51  if (!(fabs(1.0 - theta.sum()) <= CONSTRAINT_TOLERANCE)) {
+
52  std::stringstream msg;
+
53  T_prob sum = theta.sum();
+
54  msg << "is not a valid simplex.";
+
55  msg.precision(10);
+
56  msg << " sum(" << name << ") = " << sum
+
57  << ", but should be ";
+
58  std::string msg_str(msg.str());
+
59  domain_error(function, name, 1.0,
+
60  msg_str.c_str());
+
61  return false;
+
62  }
+
63  for (size_t n = 0; n < theta.size(); n++) {
+
64  if (!(theta[n] >= 0)) {
+
65  std::ostringstream msg;
+
66  msg << "is not a valid simplex. "
+
67  << name << "[" << n + stan::error_index::value << "]"
+
68  << " = ";
+
69  std::string msg_str(msg.str());
+
70  domain_error(function, name, theta[n],
+
71  msg_str.c_str(),
+
72  ", but should be greater than or equal to 0");
+
73  return false;
+
74  }
+
75  }
+
76  return true;
+
77  }
+
78  }
+
79 }
+
80 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ + +
const double CONSTRAINT_TOLERANCE
The tolerance for checking arithmetic bounds In rank and in simplexes.
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
bool check_simplex(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is simplex.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__size__match_8hpp.html b/doc/api/html/check__size__match_8hpp.html new file mode 100644 index 00000000000..22b2ca84203 --- /dev/null +++ b/doc/api/html/check__size__match_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_size_match.hpp File Reference + + + + + + + + + + +
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+
check_size_match.hpp File Reference
+
+
+
#include <boost/type_traits/common_type.hpp>
+#include <stan/math/prim/scal/err/invalid_argument.hpp>
+#include <stan/math/prim/scal/meta/likely.hpp>
+#include <sstream>
+#include <string>
+
+

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template<typename T_size1 , typename T_size2 >
bool stan::math::check_size_match (const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
 Return true if the provided sizes match. More...
 
template<typename T_size1 , typename T_size2 >
bool stan::math::check_size_match (const char *function, const char *expr_i, const char *name_i, T_size1 i, const char *expr_j, const char *name_j, T_size2 j)
 Return true if the provided sizes match. More...
 
+
+
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diff --git a/doc/api/html/check__size__match_8hpp_source.html b/doc/api/html/check__size__match_8hpp_source.html new file mode 100644 index 00000000000..053f8d7ac0c --- /dev/null +++ b/doc/api/html/check__size__match_8hpp_source.html @@ -0,0 +1,172 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/check_size_match.hpp Source File + + + + + + + + + + +
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check_size_match.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_CHECK_SIZE_MATCH_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_CHECK_SIZE_MATCH_HPP
+
3 
+
4 #include <boost/type_traits/common_type.hpp>
+ + +
7 #include <sstream>
+
8 #include <string>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
29  template <typename T_size1, typename T_size2>
+
30  inline bool check_size_match(const char* function,
+
31  const char* name_i,
+
32  T_size1 i,
+
33  const char* name_j,
+
34  T_size2 j) {
+
35  if (likely(i == static_cast<T_size1>(j)))
+
36  return true;
+
37 
+
38  std::ostringstream msg;
+
39  msg << ") and "
+
40  << name_j << " (" << j << ") must match in size";
+
41  std::string msg_str(msg.str());
+
42  invalid_argument(function, name_i, i,
+
43  "(", msg_str.c_str());
+
44  return false;
+
45  }
+
46 
+
47 
+
66  template <typename T_size1, typename T_size2>
+
67  inline bool check_size_match(const char* function,
+
68  const char* expr_i,
+
69  const char* name_i,
+
70  T_size1 i,
+
71  const char* expr_j,
+
72  const char* name_j,
+
73  T_size2 j) {
+
74  if (likely(i == static_cast<T_size1>(j)))
+
75  return true;
+
76  std::ostringstream updated_name;
+
77  updated_name << expr_i << name_i;
+
78  std::string updated_name_str(updated_name.str());
+
79  std::ostringstream msg;
+
80  msg << ") and "
+
81  << expr_j << name_j
+
82  << " (" << j << ") must match in size";
+
83  std::string msg_str(msg.str());
+
84  invalid_argument(function, updated_name_str.c_str(), i,
+
85  "(", msg_str.c_str());
+
86  return false;
+
87  }
+
88 
+
89  }
+
90 }
+
91 #endif
+ + +
#define likely(x)
Definition: likely.hpp:8
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ +
+
+
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diff --git a/doc/api/html/check__spsd__matrix_8hpp.html b/doc/api/html/check__spsd__matrix_8hpp.html new file mode 100644 index 00000000000..3e5ad5aaaa2 --- /dev/null +++ b/doc/api/html/check__spsd__matrix_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_spsd_matrix.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_spsd_matrix (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a square, symmetric, and positive semi-definite. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__spsd__matrix_8hpp_source.html b/doc/api/html/check__spsd__matrix_8hpp_source.html new file mode 100644 index 00000000000..e14d7d50290 --- /dev/null +++ b/doc/api/html/check__spsd__matrix_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_spsd_matrix.hpp Source File + + + + + + + + + + +
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check_spsd_matrix.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_SPSD_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_SPSD_MATRIX_HPP
+
3 
+ + + + + +
9 
+
10 namespace stan {
+
11  namespace math {
+
29  template <typename T_y>
+
30  inline bool
+ +
32  const char* function,
+
33  const char* name,
+
34  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
35  ) {
+
36  check_square(function, name, y);
+
37  check_positive_size(function, name, "rows()", y.rows());
+
38  check_symmetric(function, name, y);
+
39  check_pos_semidefinite(function, name, y);
+
40  return true;
+
41  }
+
42 
+
43  }
+
44 }
+
45 #endif
+
bool check_positive_size(const char *function, const char *name, const char *expr, const int size)
Return true if size is positive.
+ + + +
bool check_spsd_matrix(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a square, symmetric, and positive semi-definite.
+
bool check_pos_semidefinite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is positive definite.
+ +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
+
+
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diff --git a/doc/api/html/check__square_8hpp.html b/doc/api/html/check__square_8hpp.html new file mode 100644 index 00000000000..5e77ae2ced7 --- /dev/null +++ b/doc/api/html/check__square_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_square.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_square (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is square. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__square_8hpp_source.html b/doc/api/html/check__square_8hpp_source.html new file mode 100644 index 00000000000..3ca9c218b19 --- /dev/null +++ b/doc/api/html/check__square_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_square.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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check_square.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_SQUARE_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_SQUARE_HPP
+
3 
+ + +
6 #include <sstream>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
26  template <typename T_y>
+
27  inline bool
+
28  check_square(const char* function,
+
29  const char* name,
+
30  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y) {
+
31  check_size_match(function,
+
32  "Expecting a square matrix; rows of ", name, y.rows(),
+
33  "columns of ", name, y.cols());
+
34  return true;
+
35  }
+
36 
+
37  }
+
38 }
+
39 #endif
+ + +
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__std__vector__index_8hpp.html b/doc/api/html/check__std__vector__index_8hpp.html new file mode 100644 index 00000000000..f5f6637e7ef --- /dev/null +++ b/doc/api/html/check__std__vector__index_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_std_vector_index.hpp File Reference + + + + + + + + + + +
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+
+
+
#include <stan/math/prim/scal/err/out_of_range.hpp>
+#include <sstream>
+#include <string>
+#include <vector>
+
+

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template<typename T >
bool stan::math::check_std_vector_index (const char *function, const char *name, const std::vector< T > &y, int i)
 Return true if the specified index is valid in std vector. More...
 
+
+
+
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diff --git a/doc/api/html/check__std__vector__index_8hpp_source.html b/doc/api/html/check__std__vector__index_8hpp_source.html new file mode 100644 index 00000000000..8ca43037aa5 --- /dev/null +++ b/doc/api/html/check__std__vector__index_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_std_vector_index.hpp Source File + + + + + + + + + + +
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check_std_vector_index.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_STD_VECTOR_INDEX_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_STD_VECTOR_INDEX_HPP
+
3 
+ +
5 
+
6 #include <sstream>
+
7 #include <string>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
29  template <typename T>
+
30  inline bool check_std_vector_index(const char* function,
+
31  const char* name,
+
32  const std::vector<T>& y,
+
33  int i) {
+
34  if (i >= static_cast<int>(stan::error_index::value)
+
35  && i < static_cast<int>(y.size() + stan::error_index::value))
+
36  return true;
+
37 
+
38  std::stringstream msg;
+
39  msg << " for " << name;
+
40  std::string msg_str(msg.str());
+
41  out_of_range(function, y.size(), i, msg_str.c_str());
+
42  return false;
+
43  }
+
44 
+
45  }
+
46 }
+
47 #endif
+ + +
bool check_std_vector_index(const char *function, const char *name, const std::vector< T > &y, int i)
Return true if the specified index is valid in std vector.
+ +
void out_of_range(const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
Throw an out_of_range exception with a consistently formatted message.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__symmetric_8hpp.html b/doc/api/html/check__symmetric_8hpp.html new file mode 100644 index 00000000000..6a6d6d6061f --- /dev/null +++ b/doc/api/html/check__symmetric_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_symmetric.hpp File Reference + + + + + + + + + + +
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template<typename T_y >
bool stan::math::check_symmetric (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is symmetric. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__symmetric_8hpp_source.html b/doc/api/html/check__symmetric_8hpp_source.html new file mode 100644 index 00000000000..29d1f70effb --- /dev/null +++ b/doc/api/html/check__symmetric_8hpp_source.html @@ -0,0 +1,190 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_symmetric.hpp Source File + + + + + + + + + + +
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check_symmetric.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_SYMMETRIC_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_SYMMETRIC_HPP
+
3 
+ + + + + + + +
11 #include <sstream>
+
12 #include <string>
+
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
17 
+
35  template <typename T_y>
+
36  inline bool
+ +
38  const char* function,
+
39  const char* name,
+
40  const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y
+
41  ) {
+
42  check_square(function, name, y);
+
43 
+
44  using Eigen::Matrix;
+ +
46  using std::fabs;
+
47  using Eigen::Dynamic;
+
48 
+
49  typedef typename index_type<Matrix<T_y, Dynamic, Dynamic> >::type
+
50  size_type;
+
51 
+
52  size_type k = y.rows();
+
53  if (k == 1)
+
54  return true;
+
55  for (size_type m = 0; m < k; ++m) {
+
56  for (size_type n = m + 1; n < k; ++n) {
+
57  if (!(fabs(value_of(y(m, n)) - value_of(y(n, m)))
+ +
59  std::ostringstream msg1;
+
60  msg1 << "is not symmetric. "
+
61  << name << "[" << stan::error_index::value + m << ","
+
62  << stan::error_index::value +n << "] = ";
+
63  std::string msg1_str(msg1.str());
+
64  std::ostringstream msg2;
+
65  msg2 << ", but "
+
66  << name << "[" << stan::error_index::value +n << ","
+ +
68  << "] = " << y(n, m);
+
69  std::string msg2_str(msg2.str());
+
70  domain_error(function, name, y(m, n),
+
71  msg1_str.c_str(), msg2_str.c_str());
+
72  return false;
+
73  }
+
74  }
+
75  }
+
76  return true;
+
77  }
+
78 
+
79  }
+
80 }
+
81 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
const double CONSTRAINT_TOLERANCE
The tolerance for checking arithmetic bounds In rank and in simplexes.
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + + + +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__unit__vector_8hpp.html b/doc/api/html/check__unit__vector_8hpp.html new file mode 100644 index 00000000000..a2d81cdc5c0 --- /dev/null +++ b/doc/api/html/check__unit__vector_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_unit_vector.hpp File Reference + + + + + + + + + + +
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template<typename T_prob >
bool stan::math::check_unit_vector (const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 Return true if the specified vector is unit vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__unit__vector_8hpp_source.html b/doc/api/html/check__unit__vector_8hpp_source.html new file mode 100644 index 00000000000..d12c3b6150e --- /dev/null +++ b/doc/api/html/check__unit__vector_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_unit_vector.hpp Source File + + + + + + + + + + +
+
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+
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+
check_unit_vector.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_UNIT_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_UNIT_VECTOR_HPP
+
3 
+ + + + +
8 #include <sstream>
+
9 #include <string>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
35  template <typename T_prob>
+
36  bool check_unit_vector(const char* function,
+
37  const char* name,
+
38  const Eigen::Matrix<T_prob,
+
39  Eigen::Dynamic, 1>& theta) {
+
40  check_nonzero_size(function, name, theta);
+
41  T_prob ssq = theta.squaredNorm();
+
42  if (!(fabs(1.0 - ssq) <= CONSTRAINT_TOLERANCE)) {
+
43  std::stringstream msg;
+
44  msg << "is not a valid unit vector."
+
45  << " The sum of the squares of the elements should be 1, but is ";
+
46  std::string msg_str(msg.str());
+
47  domain_error(function, name, ssq, msg_str.c_str());
+
48  }
+
49  return true;
+
50  }
+
51 
+
52  }
+
53 }
+
54 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ + +
const double CONSTRAINT_TOLERANCE
The tolerance for checking arithmetic bounds In rank and in simplexes.
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
bool check_unit_vector(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is unit vector.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__vector_8hpp.html b/doc/api/html/check__vector_8hpp.html new file mode 100644 index 00000000000..26df64107f8 --- /dev/null +++ b/doc/api/html/check__vector_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_vector.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
bool stan::math::check_vector (const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
 Return true if the matrix is either a row vector or column vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/check__vector_8hpp_source.html b/doc/api/html/check__vector_8hpp_source.html new file mode 100644 index 00000000000..d9b62580c84 --- /dev/null +++ b/doc/api/html/check__vector_8hpp_source.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_vector.hpp Source File + + + + + + + + + + +
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check_vector.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_VECTOR_HPP
+
3 
+ + + + +
8 #include <sstream>
+
9 #include <string>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
33  template <typename T, int R, int C>
+
34  inline bool check_vector(const char* function,
+
35  const char* name,
+
36  const Eigen::Matrix<T, R, C>& x) {
+
37  if (R == 1)
+
38  return true;
+
39  if (C == 1)
+
40  return true;
+
41  if (x.rows() == 1 || x.cols() == 1)
+
42  return true;
+
43 
+
44  std::ostringstream msg;
+
45  msg << ") has " << x.rows() << " rows and "
+
46  << x.cols() << " columns but it should be a vector so it should "
+
47  << "either have 1 row or 1 column";
+
48  std::string msg_str(msg.str());
+
49  invalid_argument(function,
+
50  name,
+
51  typename scalar_type<T>::type(),
+
52  "(", msg_str.c_str());
+
53  return false;
+
54  }
+
55 
+
56  }
+
57 }
+
58 #endif
+
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ + +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+ +
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/chi__square__ccdf__log_8hpp.html b/doc/api/html/chi__square__ccdf__log_8hpp.html new file mode 100644 index 00000000000..1e9c9a98d89 --- /dev/null +++ b/doc/api/html/chi__square__ccdf__log_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::chi_square_ccdf_log (const T_y &y, const T_dof &nu)
 
+
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diff --git a/doc/api/html/chi__square__ccdf__log_8hpp_source.html b/doc/api/html/chi__square__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..e73e4dbb78c --- /dev/null +++ b/doc/api/html/chi__square__ccdf__log_8hpp_source.html @@ -0,0 +1,272 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_ccdf_log.hpp Source File + + + + + + + + + + +
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chi_square_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/chi_squared_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 #include <limits>
+
23 
+
24 namespace stan {
+
25 
+
26  namespace math {
+
27 
+
28  template <typename T_y, typename T_dof>
+
29  typename return_type<T_y, T_dof>::type
+
30  chi_square_ccdf_log(const T_y& y, const T_dof& nu) {
+
31  static const char* function("stan::math::chi_square_ccdf_log");
+ +
33  T_partials_return;
+
34 
+ + + + + +
40 
+
41  T_partials_return ccdf_log(0.0);
+
42 
+
43  // Size checks
+
44  if (!(stan::length(y) && stan::length(nu)))
+
45  return ccdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_nonnegative(function, "Random variable", y);
+
49  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
50  check_consistent_sizes(function,
+
51  "Random variable", y,
+
52  "Degrees of freedom parameter", nu);
+
53 
+
54  // Wrap arguments in vectors
+
55  VectorView<const T_y> y_vec(y);
+
56  VectorView<const T_dof> nu_vec(nu);
+
57  size_t N = max_size(y, nu);
+
58 
+ +
60  operands_and_partials(y, nu);
+
61 
+
62  // Explicit return for extreme values
+
63  // The gradients are technically ill-defined, but treated as zero
+
64  for (size_t i = 0; i < stan::length(y); i++) {
+
65  if (value_of(y_vec[i]) == 0)
+
66  return operands_and_partials.value(0.0);
+
67  }
+
68 
+
69  // Compute ccdf_log and its gradients
+
70  using stan::math::gamma_p;
+
71  using stan::math::digamma;
+
72  using boost::math::tgamma;
+
73  using std::exp;
+
74  using std::pow;
+
75  using std::log;
+
76  using std::exp;
+
77 
+
78  // Cache a few expensive function calls if nu is a parameter
+ +
80  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
82  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
83 
+ +
85  for (size_t i = 0; i < stan::length(nu); i++) {
+
86  const T_partials_return alpha_dbl = value_of(nu_vec[i]) * 0.5;
+
87  gamma_vec[i] = tgamma(alpha_dbl);
+
88  digamma_vec[i] = digamma(alpha_dbl);
+
89  }
+
90  }
+
91 
+
92  // Compute vectorized ccdf_log and gradient
+
93  for (size_t n = 0; n < N; n++) {
+
94  // Explicit results for extreme values
+
95  // The gradients are technically ill-defined, but treated as zero
+
96  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
97  return operands_and_partials.value(stan::math::negative_infinity());
+
98 
+
99  // Pull out values
+
100  const T_partials_return y_dbl = value_of(y_vec[n]);
+
101  const T_partials_return alpha_dbl = value_of(nu_vec[n]) * 0.5;
+
102  const T_partials_return beta_dbl = 0.5;
+
103 
+
104  // Compute
+
105  const T_partials_return Pn = 1.0 - gamma_p(alpha_dbl, beta_dbl * y_dbl);
+
106 
+
107  ccdf_log += log(Pn);
+
108 
+ +
110  operands_and_partials.d_x1[n] -= beta_dbl * exp(-beta_dbl * y_dbl)
+
111  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+ +
113  operands_and_partials.d_x2[n]
+
114  += 0.5 * stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
115  * y_dbl, gamma_vec[n],
+
116  digamma_vec[n]) / Pn;
+
117  }
+
118 
+
119  return operands_and_partials.value(ccdf_log);
+
120  }
+
121  }
+
122 }
+
123 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_dof >::type chi_square_ccdf_log(const T_y &y, const T_dof &nu)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/chi__square__cdf_8hpp.html b/doc/api/html/chi__square__cdf_8hpp.html new file mode 100644 index 00000000000..b6e9d43e60a --- /dev/null +++ b/doc/api/html/chi__square__cdf_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_cdf.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
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+
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+
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template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::chi_square_cdf (const T_y &y, const T_dof &nu)
 Calculates the chi square cumulative distribution function for the given variate and degrees of freedom. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/chi__square__cdf_8hpp_source.html b/doc/api/html/chi__square__cdf_8hpp_source.html new file mode 100644 index 00000000000..0c03c431e13 --- /dev/null +++ b/doc/api/html/chi__square__cdf_8hpp_source.html @@ -0,0 +1,278 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_cdf.hpp Source File + + + + + + + + + + +
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chi_square_cdf.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/chi_squared_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 #include <limits>
+
23 
+
24 namespace stan {
+
25 
+
26  namespace math {
+
27 
+
37  template <typename T_y, typename T_dof>
+
38  typename return_type<T_y, T_dof>::type
+
39  chi_square_cdf(const T_y& y, const T_dof& nu) {
+
40  static const char* function("stan::math::chi_square_cdf");
+ +
42  T_partials_return;
+
43 
+ + + + + +
49 
+
50  T_partials_return cdf(1.0);
+
51 
+
52  // Size checks
+
53  if (!(stan::length(y) && stan::length(nu)))
+
54  return cdf;
+
55 
+
56  check_not_nan(function, "Random variable", y);
+
57  check_nonnegative(function, "Random variable", y);
+
58  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
59  check_consistent_sizes(function,
+
60  "Random variable", y,
+
61  "Degrees of freedom parameter", nu);
+
62 
+
63  // Wrap arguments in vectors
+
64  VectorView<const T_y> y_vec(y);
+
65  VectorView<const T_dof> nu_vec(nu);
+
66  size_t N = max_size(y, nu);
+
67 
+ +
69  operands_and_partials(y, nu);
+
70 
+
71  // Explicit return for extreme values
+
72  // The gradients are technically ill-defined, but treated as zero
+
73  for (size_t i = 0; i < stan::length(y); i++) {
+
74  if (value_of(y_vec[i]) == 0)
+
75  return operands_and_partials.value(0.0);
+
76  }
+
77 
+
78  // Compute CDF and its gradients
+
79  using stan::math::gamma_p;
+
80  using stan::math::digamma;
+
81  using boost::math::tgamma;
+
82  using std::exp;
+
83  using std::pow;
+
84  using std::exp;
+
85 
+
86  // Cache a few expensive function calls if nu is a parameter
+ +
88  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
90  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
91 
+ +
93  for (size_t i = 0; i < stan::length(nu); i++) {
+
94  const T_partials_return alpha_dbl = value_of(nu_vec[i]) * 0.5;
+
95  gamma_vec[i] = tgamma(alpha_dbl);
+
96  digamma_vec[i] = digamma(alpha_dbl);
+
97  }
+
98  }
+
99 
+
100  // Compute vectorized CDF and gradient
+
101  for (size_t n = 0; n < N; n++) {
+
102  // Explicit results for extreme values
+
103  // The gradients are technically ill-defined, but treated as zero
+
104  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
105  continue;
+
106 
+
107  // Pull out values
+
108  const T_partials_return y_dbl = value_of(y_vec[n]);
+
109  const T_partials_return alpha_dbl = value_of(nu_vec[n]) * 0.5;
+
110  const T_partials_return beta_dbl = 0.5;
+
111 
+
112  // Compute
+
113  const T_partials_return Pn = gamma_p(alpha_dbl, beta_dbl * y_dbl);
+
114 
+
115  cdf *= Pn;
+
116 
+ +
118  operands_and_partials.d_x1[n] += beta_dbl * exp(-beta_dbl * y_dbl)
+
119  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+ +
121  operands_and_partials.d_x2[n]
+
122  -= 0.5 * stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
123  * y_dbl, gamma_vec[n],
+
124  digamma_vec[n]) / Pn;
+
125  }
+
126 
+ +
128  for (size_t n = 0; n < stan::length(y); ++n)
+
129  operands_and_partials.d_x1[n] *= cdf;
+
130  }
+ +
132  for (size_t n = 0; n < stan::length(nu); ++n)
+
133  operands_and_partials.d_x2[n] *= cdf;
+
134  }
+
135 
+
136  return operands_and_partials.value(cdf);
+
137  }
+
138  }
+
139 }
+
140 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
return_type< T_y, T_dof >::type chi_square_cdf(const T_y &y, const T_dof &nu)
Calculates the chi square cumulative distribution function for the given variate and degrees of freed...
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/chi__square__cdf__log_8hpp.html b/doc/api/html/chi__square__cdf__log_8hpp.html new file mode 100644 index 00000000000..facbfa95340 --- /dev/null +++ b/doc/api/html/chi__square__cdf__log_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
chi_square_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::chi_square_cdf_log (const T_y &y, const T_dof &nu)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/chi__square__cdf__log_8hpp_source.html b/doc/api/html/chi__square__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..49ad13634e0 --- /dev/null +++ b/doc/api/html/chi__square__cdf__log_8hpp_source.html @@ -0,0 +1,273 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
chi_square_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/chi_squared_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 #include <limits>
+
23 
+
24 namespace stan {
+
25 
+
26  namespace math {
+
27 
+
28  template <typename T_y, typename T_dof>
+
29  typename return_type<T_y, T_dof>::type
+
30  chi_square_cdf_log(const T_y& y, const T_dof& nu) {
+
31  static const char* function("stan::math::chi_square_cdf_log");
+ +
33  T_partials_return;
+
34 
+ + + + + +
40 
+
41  T_partials_return cdf_log(0.0);
+
42 
+
43  // Size checks
+
44  if (!(stan::length(y) && stan::length(nu)))
+
45  return cdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_nonnegative(function, "Random variable", y);
+
49  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
50  check_consistent_sizes(function,
+
51  "Random variable", y,
+
52  "Degrees of freedom parameter", nu);
+
53 
+
54  // Wrap arguments in vectors
+
55  VectorView<const T_y> y_vec(y);
+
56  VectorView<const T_dof> nu_vec(nu);
+
57  size_t N = max_size(y, nu);
+
58 
+ +
60  operands_and_partials(y, nu);
+
61 
+
62  // Explicit return for extreme values
+
63  // The gradients are technically ill-defined, but treated as zero
+
64  for (size_t i = 0; i < stan::length(y); i++) {
+
65  if (value_of(y_vec[i]) == 0)
+
66  return operands_and_partials.value(stan::math::negative_infinity());
+
67  }
+
68 
+
69  // Compute cdf_log and its gradients
+
70  using stan::math::gamma_p;
+
71  using stan::math::digamma;
+
72  using boost::math::tgamma;
+
73  using std::exp;
+
74  using std::pow;
+
75  using std::log;
+
76  using std::exp;
+
77 
+
78  // Cache a few expensive function calls if nu is a parameter
+ +
80  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
82  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
83 
+ +
85  for (size_t i = 0; i < stan::length(nu); i++) {
+
86  const T_partials_return alpha_dbl = value_of(nu_vec[i]) * 0.5;
+
87  gamma_vec[i] = tgamma(alpha_dbl);
+
88  digamma_vec[i] = digamma(alpha_dbl);
+
89  }
+
90  }
+
91 
+
92  // Compute vectorized cdf_log and gradient
+
93  for (size_t n = 0; n < N; n++) {
+
94  // Explicit results for extreme values
+
95  // The gradients are technically ill-defined, but treated as zero
+
96  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
97  return operands_and_partials.value(0.0);
+
98 
+
99  // Pull out values
+
100  const T_partials_return y_dbl = value_of(y_vec[n]);
+
101  const T_partials_return alpha_dbl = value_of(nu_vec[n]) * 0.5;
+
102  const T_partials_return beta_dbl = 0.5;
+
103 
+
104  // Compute
+
105  const T_partials_return Pn = gamma_p(alpha_dbl, beta_dbl * y_dbl);
+
106 
+
107  cdf_log += log(Pn);
+
108 
+ +
110  operands_and_partials.d_x1[n] += beta_dbl * exp(-beta_dbl * y_dbl)
+
111  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+ +
113  operands_and_partials.d_x2[n]
+
114  -= 0.5 * stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
115  * y_dbl, gamma_vec[n],
+
116  digamma_vec[n]) / Pn;
+
117  }
+
118 
+
119  return operands_and_partials.value(cdf_log);
+
120  }
+
121 
+
122  }
+
123 }
+
124 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
return_type< T_y, T_dof >::type chi_square_cdf_log(const T_y &y, const T_dof &nu)
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/chi__square__log_8hpp.html b/doc/api/html/chi__square__log_8hpp.html new file mode 100644 index 00000000000..a66c3cc22a3 --- /dev/null +++ b/doc/api/html/chi__square__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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+ + +
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+ +
+
chi_square_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::chi_square_log (const T_y &y, const T_dof &nu)
 The log of a chi-squared density for y with the specified degrees of freedom parameter. More...
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::chi_square_log (const T_y &y, const T_dof &nu)
 
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diff --git a/doc/api/html/chi__square__log_8hpp_source.html b/doc/api/html/chi__square__log_8hpp_source.html new file mode 100644 index 00000000000..6fa575ae5d8 --- /dev/null +++ b/doc/api/html/chi__square__log_8hpp_source.html @@ -0,0 +1,282 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_log.hpp Source File + + + + + + + + + + +
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chi_square_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/chi_squared_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
46  template <bool propto,
+
47  typename T_y, typename T_dof>
+
48  typename return_type<T_y, T_dof>::type
+
49  chi_square_log(const T_y& y, const T_dof& nu) {
+
50  static const char* function("stan::math::chi_square_log");
+ +
52  T_partials_return;
+
53 
+
54  // check if any vectors are zero length
+
55  if (!(stan::length(y)
+
56  && stan::length(nu)))
+
57  return 0.0;
+
58 
+ + + + + +
64 
+
65  T_partials_return logp(0.0);
+
66  check_not_nan(function, "Random variable", y);
+
67  check_nonnegative(function, "Random variable", y);
+
68  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
69  check_consistent_sizes(function,
+
70  "Random variable", y,
+
71  "Degrees of freedom parameter", nu);
+
72 
+
73 
+
74  // set up template expressions wrapping scalars into vector views
+
75  VectorView<const T_y> y_vec(y);
+
76  VectorView<const T_dof> nu_vec(nu);
+
77  size_t N = max_size(y, nu);
+
78 
+
79  for (size_t n = 0; n < length(y); n++)
+
80  if (value_of(y_vec[n]) < 0)
+
81  return LOG_ZERO;
+
82 
+
83  // check if no variables are involved and prop-to
+ +
85  return 0.0;
+
86 
+ +
88  using boost::math::lgamma;
+ +
90  using std::log;
+
91 
+ +
93  T_partials_return, T_y> log_y(length(y));
+
94  for (size_t i = 0; i < length(y); i++)
+ +
96  log_y[i] = log(value_of(y_vec[i]));
+
97 
+ +
99  T_partials_return, T_y> inv_y(length(y));
+
100  for (size_t i = 0; i < length(y); i++)
+ +
102  inv_y[i] = 1.0 / value_of(y_vec[i]);
+
103 
+ +
105  T_partials_return, T_dof> lgamma_half_nu(length(nu));
+ +
107  T_partials_return, T_dof>
+
108  digamma_half_nu_over_two(length(nu));
+
109 
+
110  for (size_t i = 0; i < length(nu); i++) {
+
111  T_partials_return half_nu = 0.5 * value_of(nu_vec[i]);
+ +
113  lgamma_half_nu[i] = lgamma(half_nu);
+ +
115  digamma_half_nu_over_two[i] = digamma(half_nu) * 0.5;
+
116  }
+
117 
+
118  OperandsAndPartials<T_y, T_dof> operands_and_partials(y, nu);
+
119 
+
120  for (size_t n = 0; n < N; n++) {
+
121  const T_partials_return y_dbl = value_of(y_vec[n]);
+
122  const T_partials_return half_y = 0.5 * y_dbl;
+
123  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+
124  const T_partials_return half_nu = 0.5 * nu_dbl;
+ +
126  logp += nu_dbl * NEG_LOG_TWO_OVER_TWO - lgamma_half_nu[n];
+ +
128  logp += (half_nu-1.0) * log_y[n];
+ +
130  logp -= half_y;
+
131 
+ +
133  operands_and_partials.d_x1[n] += (half_nu-1.0)*inv_y[n] - 0.5;
+
134  }
+ +
136  operands_and_partials.d_x2[n] += NEG_LOG_TWO_OVER_TWO
+
137  - digamma_half_nu_over_two[n] + log_y[n]*0.5;
+
138  }
+
139  }
+
140  return operands_and_partials.value(logp);
+
141  }
+
142 
+
143  template <typename T_y, typename T_dof>
+
144  inline
+ +
146  chi_square_log(const T_y& y, const T_dof& nu) {
+
147  return chi_square_log<false>(y, nu);
+
148  }
+
149 
+
150  }
+
151 }
+
152 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_y, T_dof >::type chi_square_log(const T_y &y, const T_dof &nu)
The log of a chi-squared density for y with the specified degrees of freedom parameter.
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
const double NEG_LOG_TWO_OVER_TWO
Definition: constants.hpp:191
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
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diff --git a/doc/api/html/chi__square__rng_8hpp.html b/doc/api/html/chi__square__rng_8hpp.html new file mode 100644 index 00000000000..a142263fb74 --- /dev/null +++ b/doc/api/html/chi__square__rng_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_rng.hpp File Reference + + + + + + + + + + +
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chi_square_rng.hpp File Reference
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+Functions

template<class RNG >
double stan::math::chi_square_rng (const double nu, RNG &rng)
 
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diff --git a/doc/api/html/chi__square__rng_8hpp_source.html b/doc/api/html/chi__square__rng_8hpp_source.html new file mode 100644 index 00000000000..32647fdef77 --- /dev/null +++ b/doc/api/html/chi__square__rng_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/chi_square_rng.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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chi_square_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_CHI_SQUARE_RNG_HPP
+
3 
+
4 #include <boost/random/chi_squared_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + +
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  template <class RNG>
+
23  inline double
+
24  chi_square_rng(const double nu,
+
25  RNG& rng) {
+
26  using boost::variate_generator;
+
27  using boost::random::chi_squared_distribution;
+
28 
+
29  static const char* function("stan::math::chi_square_rng");
+
30 
+ +
32 
+
33  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
34 
+
35  variate_generator<RNG&, chi_squared_distribution<> >
+
36  chi_square_rng(rng, chi_squared_distribution<>(nu));
+
37  return chi_square_rng();
+
38  }
+
39  }
+
40 }
+
41 #endif
+ +
double chi_square_rng(const double nu, RNG &rng)
+ + + + + + + + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
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diff --git a/doc/api/html/child__type_8hpp.html b/doc/api/html/child__type_8hpp.html new file mode 100644 index 00000000000..afbbf980050 --- /dev/null +++ b/doc/api/html/child__type_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/child_type.hpp File Reference + + + + + + + + + + +
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+Classes

struct  stan::math::child_type< T >
 Primary template class for metaprogram to compute child type of T. More...
 
struct  stan::math::child_type< T_struct< T_child > >
 Specialization for template classes / structs. More...
 
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 Matrices and templated mathematical functions.
 
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diff --git a/doc/api/html/child__type_8hpp_source.html b/doc/api/html/child__type_8hpp_source.html new file mode 100644 index 00000000000..55cd757e2a8 --- /dev/null +++ b/doc/api/html/child__type_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/child_type.hpp Source File + + + + + + + + + + +
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child_type.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_META_CHILD_TYPE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_CHILD_TYPE_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  namespace math {
+
7 
+
18  template <typename T>
+
19  struct child_type {
+
20  typedef double type;
+
21  };
+
22 
+
33  template <template<typename> class T_struct, typename T_child>
+
34  struct child_type<T_struct<T_child> >{
+
35  typedef T_child type;
+
36  };
+
37 
+
38  }
+
39 }
+
40 
+
41 
+
42 #endif
+ + + +
Primary template class for metaprogram to compute child type of T.
Definition: child_type.hpp:19
+
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diff --git a/doc/api/html/cholesky__corr__constrain_8hpp.html b/doc/api/html/cholesky__corr__constrain_8hpp.html new file mode 100644 index 00000000000..928bfcfd46c --- /dev/null +++ b/doc/api/html/cholesky__corr__constrain_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_corr_constrain.hpp File Reference + + + + + + + + + + +
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cholesky_corr_constrain.hpp File Reference
+
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+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/scal/fun/log1m.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <stan/math/prim/scal/fun/corr_constrain.hpp>
+#include <cmath>
+#include <iostream>
+#include <stdexcept>
+
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+Functions

template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cholesky_corr_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y, int K)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cholesky_corr_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y, int K, T &lp)
 
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diff --git a/doc/api/html/cholesky__corr__constrain_8hpp_source.html b/doc/api/html/cholesky__corr__constrain_8hpp_source.html new file mode 100644 index 00000000000..335a3c4cf88 --- /dev/null +++ b/doc/api/html/cholesky__corr__constrain_8hpp_source.html @@ -0,0 +1,220 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_corr_constrain.hpp Source File + + + + + + + + + + +
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cholesky_corr_constrain.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CHOLESKY_CORR_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CHOLESKY_CORR_CONSTRAIN_HPP
+
3 
+ + + + +
8 #include <cmath>
+
9 #include <iostream>
+
10 #include <stdexcept>
+
11 
+
12 namespace stan {
+
13 
+
14  namespace math {
+
15 
+
16  // CHOLESKY CORRELATION MATRIX
+
17 
+
18  template <typename T>
+
19  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
20  cholesky_corr_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& y,
+
21  int K) {
+
22  using std::sqrt;
+
23  using Eigen::Matrix;
+
24  using Eigen::Dynamic;
+
25  using stan::math::square;
+
26  int k_choose_2 = (K * (K - 1)) / 2;
+
27  if (k_choose_2 != y.size()) {
+
28  throw std::domain_error("y is not a valid unconstrained cholesky "
+
29  "correlation matrix."
+
30  "Require (K choose 2) elements in y.");
+
31  }
+
32  Matrix<T, Dynamic, 1> z(k_choose_2);
+
33  for (int i = 0; i < k_choose_2; ++i)
+
34  z(i) = corr_constrain(y(i));
+
35  Matrix<T, Dynamic, Dynamic> x(K, K);
+
36  if (K == 0) return x;
+
37  T zero(0);
+
38  for (int j = 1; j < K; ++j)
+
39  for (int i = 0; i < j; ++i)
+
40  x(i, j) = zero;
+
41  x(0, 0) = 1;
+
42  int k = 0;
+
43  for (int i = 1; i < K; ++i) {
+
44  x(i, 0) = z(k++);
+
45  T sum_sqs(square(x(i, 0)));
+
46  for (int j = 1; j < i; ++j) {
+
47  x(i, j) = z(k++) * sqrt(1.0 - sum_sqs);
+
48  sum_sqs += square(x(i, j));
+
49  }
+
50  x(i, i) = sqrt(1.0 - sum_sqs);
+
51  }
+
52  return x;
+
53  }
+
54 
+
55  // FIXME to match above after debugged
+
56  template <typename T>
+
57  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
58  cholesky_corr_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& y,
+
59  int K,
+
60  T& lp) {
+
61  using std::sqrt;
+
62  using Eigen::Matrix;
+
63  using Eigen::Dynamic;
+
64  using stan::math::log1m;
+
65  using stan::math::square;
+
66  int k_choose_2 = (K * (K - 1)) / 2;
+
67  if (k_choose_2 != y.size()) {
+
68  throw std::domain_error("y is not a valid unconstrained cholesky "
+
69  "correlation matrix."
+
70  " Require (K choose 2) elements in y.");
+
71  }
+
72  Matrix<T, Dynamic, 1> z(k_choose_2);
+
73  for (int i = 0; i < k_choose_2; ++i)
+
74  z(i) = corr_constrain(y(i), lp);
+
75  Matrix<T, Dynamic, Dynamic> x(K, K);
+
76  if (K == 0) return x;
+
77  T zero(0);
+
78  for (int j = 1; j < K; ++j)
+
79  for (int i = 0; i < j; ++i)
+
80  x(i, j) = zero;
+
81  x(0, 0) = 1;
+
82  int k = 0;
+
83  for (int i = 1; i < K; ++i) {
+
84  x(i, 0) = z(k++);
+
85  T sum_sqs = square(x(i, 0));
+
86  for (int j = 1; j < i; ++j) {
+
87  lp += 0.5 * log1m(sum_sqs);
+
88  x(i, j) = z(k++) * sqrt(1.0 - sum_sqs);
+
89  sum_sqs += square(x(i, j));
+
90  }
+
91  x(i, i) = sqrt(1.0 - sum_sqs);
+
92  }
+
93  return x;
+
94  }
+
95 
+
96  }
+
97 
+
98 }
+
99 
+
100 #endif
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_corr_constrain(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y, int K)
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
T corr_constrain(const T x)
Return the result of transforming the specified scalar to have a valid correlation value between -1 a...
+
+
+
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diff --git a/doc/api/html/cholesky__corr__free_8hpp.html b/doc/api/html/cholesky__corr__free_8hpp.html new file mode 100644 index 00000000000..d67ebec8046 --- /dev/null +++ b/doc/api/html/cholesky__corr__free_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_corr_free.hpp File Reference + + + + + + + + + + +
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cholesky_corr_free.hpp File Reference
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::cholesky_corr_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x)
 
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diff --git a/doc/api/html/cholesky__corr__free_8hpp_source.html b/doc/api/html/cholesky__corr__free_8hpp_source.html new file mode 100644 index 00000000000..e62c2505483 --- /dev/null +++ b/doc/api/html/cholesky__corr__free_8hpp_source.html @@ -0,0 +1,165 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_corr_free.hpp Source File + + + + + + + + + + +
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cholesky_corr_free.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_CHOLESKY_CORR_FREE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CHOLESKY_CORR_FREE_HPP
+
3 
+ + + + + +
9 #include <cmath>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15 
+
16  template <typename T>
+
17  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
18  cholesky_corr_free(const Eigen::Matrix
+
19  <T, Eigen::Dynamic, Eigen::Dynamic>& x) {
+
20  using std::sqrt;
+
21  using Eigen::Matrix;
+
22  using Eigen::Dynamic;
+
23  using stan::math::square;
+
24 
+
25  stan::math::check_square("cholesky_corr_free", "x", x);
+
26  // should validate lower-triangular, unit lengths
+
27 
+
28  int K = (x.rows() * (x.rows() - 1)) / 2;
+
29  Matrix<T, Dynamic, 1> z(K);
+
30  int k = 0;
+
31  for (int i = 1; i < x.rows(); ++i) {
+
32  z(k++) = corr_free(x(i, 0));
+
33  double sum_sqs = square(x(i, 0));
+
34  for (int j = 1; j < i; ++j) {
+
35  z(k++) = corr_free(x(i, j) / sqrt(1.0 - sum_sqs));
+
36  sum_sqs += square(x(i, j));
+
37  }
+
38  }
+
39  return z;
+
40  }
+
41  }
+
42 
+
43 }
+
44 
+
45 #endif
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > cholesky_corr_free(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x)
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
T corr_free(const T y)
Return the unconstrained scalar that when transformed to a valid correlation produces the specified v...
Definition: corr_free.hpp:29
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
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diff --git a/doc/api/html/cholesky__factor__constrain_8hpp.html b/doc/api/html/cholesky__factor__constrain_8hpp.html new file mode 100644 index 00000000000..f6b9d3bc20b --- /dev/null +++ b/doc/api/html/cholesky__factor__constrain_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_factor_constrain.hpp File Reference + + + + + + + + + + +
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cholesky_factor_constrain.hpp File Reference
+
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/sum.hpp>
+#include <cmath>
+#include <stdexcept>
+#include <vector>
+
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cholesky_factor_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, int M, int N)
 Return the Cholesky factor of the specified size read from the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cholesky_factor_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, int M, int N, T &lp)
 Return the Cholesky factor of the specified size read from the specified vector and increment the specified log probability reference with the log Jacobian adjustment of the transform. More...
 
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diff --git a/doc/api/html/cholesky__factor__constrain_8hpp_source.html b/doc/api/html/cholesky__factor__constrain_8hpp_source.html new file mode 100644 index 00000000000..38bb0244197 --- /dev/null +++ b/doc/api/html/cholesky__factor__constrain_8hpp_source.html @@ -0,0 +1,189 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_factor_constrain.hpp Source File + + + + + + + + + + +
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cholesky_factor_constrain.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CHOLESKY_FACTOR_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CHOLESKY_FACTOR_CONSTRAIN_HPP
+
3 
+ + +
6 #include <cmath>
+
7 #include <stdexcept>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  // CHOLESKY FACTOR
+
15 
+
27  template <typename T>
+
28  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
29  cholesky_factor_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
30  int M,
+
31  int N) {
+
32  using std::exp;
+
33  if (M < N)
+
34  throw std::domain_error("cholesky_factor_constrain: "
+
35  "num rows must be >= num cols");
+
36  if (x.size() != ((N * (N + 1)) / 2 + (M - N) * N))
+
37  throw std::domain_error("cholesky_factor_constrain: x.size() must"
+
38  " be (N * (N + 1)) / 2 + (M - N) * N");
+
39  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> y(M, N);
+
40  T zero(0);
+
41  int pos = 0;
+
42  // upper square
+
43  for (int m = 0; m < N; ++m) {
+
44  for (int n = 0; n < m; ++n)
+
45  y(m, n) = x(pos++);
+
46  y(m, m) = exp(x(pos++));
+
47  for (int n = m + 1; n < N; ++n)
+
48  y(m, n) = zero;
+
49  }
+
50  // lower rectangle
+
51  for (int m = N; m < M; ++m)
+
52  for (int n = 0; n < N; ++n)
+
53  y(m, n) = x(pos++);
+
54  return y;
+
55  }
+
56 
+
71  template <typename T>
+
72  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
73  cholesky_factor_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
74  int M,
+
75  int N,
+
76  T& lp) {
+
77  // cut-and-paste from above, so checks twice
+
78 
+
79  using stan::math::sum;
+
80  if (x.size() != ((N * (N + 1)) / 2 + (M - N) * N))
+
81  throw std::domain_error("cholesky_factor_constrain: x.size() "
+
82  "must be (k choose 2) + k");
+
83  int pos = 0;
+
84  std::vector<T> log_jacobians(N);
+
85  for (int n = 0; n < N; ++n) {
+
86  pos += n;
+
87  log_jacobians[n] = x(pos++);
+
88  }
+
89  lp += sum(log_jacobians); // optimized for autodiff vs. direct lp +=
+
90  return cholesky_factor_constrain(x, M, N);
+
91  }
+
92 
+
93 
+
94  }
+
95 
+
96 }
+
97 
+
98 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_factor_constrain(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, int M, int N)
Return the Cholesky factor of the specified size read from the specified vector.
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
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diff --git a/doc/api/html/cholesky__factor__free_8hpp.html b/doc/api/html/cholesky__factor__free_8hpp.html new file mode 100644 index 00000000000..bc0367f02d2 --- /dev/null +++ b/doc/api/html/cholesky__factor__free_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_factor_free.hpp File Reference + + + + + + + + + + +
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cholesky_factor_free.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/err/check_cholesky_factor.hpp>
+#include <cmath>
+#include <stdexcept>
+
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::cholesky_factor_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return the unconstrained vector of parameters correspdonding to the specified Cholesky factor. More...
 
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diff --git a/doc/api/html/cholesky__factor__free_8hpp_source.html b/doc/api/html/cholesky__factor__free_8hpp_source.html new file mode 100644 index 00000000000..f8d3f87ed71 --- /dev/null +++ b/doc/api/html/cholesky__factor__free_8hpp_source.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_factor_free.hpp Source File + + + + + + + + + + +
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cholesky_factor_free.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CHOLESKY_FACTOR_FREE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CHOLESKY_FACTOR_FREE_HPP
+
3 
+ + +
6 #include <cmath>
+
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
22  template <typename T>
+
23  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
24  cholesky_factor_free(const Eigen::Matrix
+
25  <T, Eigen::Dynamic, Eigen::Dynamic>& y) {
+
26  using std::log;
+
27  if (!stan::math::check_cholesky_factor("cholesky_factor_free", "y", y))
+
28  throw std::domain_error("cholesky_factor_free: "
+
29  "y is not a Cholesky factor");
+
30  int M = y.rows();
+
31  int N = y.cols();
+
32  Eigen::Matrix<T, Eigen::Dynamic, 1> x((N * (N + 1)) / 2 + (M - N) * N);
+
33  int pos = 0;
+
34  // lower triangle of upper square
+
35  for (int m = 0; m < N; ++m) {
+
36  for (int n = 0; n < m; ++n)
+
37  x(pos++) = y(m, n);
+
38  // diagonal of upper square
+
39  x(pos++) = log(y(m, m));
+
40  }
+
41  // lower rectangle
+
42  for (int m = N; m < M; ++m)
+
43  for (int n = 0; n < N; ++n)
+
44  x(pos++) = y(m, n);
+
45  return x;
+
46  }
+
47 
+
48 
+
49  }
+
50 
+
51 }
+
52 
+
53 #endif
+
bool check_cholesky_factor(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a valid Cholesky factor.
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
Eigen::Matrix< T, Eigen::Dynamic, 1 > cholesky_factor_free(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
Return the unconstrained vector of parameters correspdonding to the specified Cholesky factor...
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
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+
promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > > (stan::math)   
dummy (stan::math)   numeric_limits< stan::math::fvar< T > > (std)   promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > > (stan::math)   value_type (stan::math)   
accumulator (stan::math)   
  e  
+
numeric_limits< stan::math::var > (std)   promote_scalar_type< T, std::vector< S > > (stan::math)   value_type< const T > (stan::math)   
apply_scalar_unary (stan::math)   
  o  
+
promoter (stan::math)   value_type< Eigen::Matrix< T, R, C > > (stan::math)   
apply_scalar_unary< F, double > (stan::math)   error_index (stan)   promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > > (stan::math)   value_type< std::vector< T > > (stan::math)   
apply_scalar_unary< F, int > (stan::math)   
  f  
+
ode_system (stan::math)   promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > > (stan::math)   var (stan::math)   
fvar (stan::math)   
+
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diff --git a/doc/api/html/classstan_1_1_vector_builder-members.html b/doc/api/html/classstan_1_1_vector_builder-members.html new file mode 100644 index 00000000000..b3e1dc5916c --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_builder-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_builder.html b/doc/api/html/classstan_1_1_vector_builder.html new file mode 100644 index 00000000000..01ac8a91690 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_builder.html @@ -0,0 +1,252 @@ + + + + + + +Stan Math Library: stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 > Class Template Reference
+
+
+ +

VectorBuilder allocates type T1 values to be used as intermediate values. + More...

+ +

#include <VectorBuilder.hpp>

+ + + + + + + + +

+Public Member Functions

 VectorBuilder (size_t n)
 
T1 & operator[] (size_t i)
 
VectorBuilderHelper< T1, used, contains_vector< T2, T3, T4, T5, T6, T7 >::value >::type data ()
 
+ + + +

+Public Attributes

VectorBuilderHelper< T1, used, contains_vector< T2, T3, T4, T5, T6, T7 >::value > a
 
+

Detailed Description

+

template<bool used, typename T1, typename T2, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T7 = double>
+class stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 >

+ +

VectorBuilder allocates type T1 values to be used as intermediate values.

+

There are 2 template parameters:

    +
  • used: boolean variable indicating whether this instance is used. If this is false, there is no storage allocated and operator[] throws.
  • +
  • is_vec: boolean variable indicating whether this instance should allocate a vector, if it is used. If this is false, the instance will only allocate a single double value. If this is true, it will allocate the number requested. Note that this is calculated based on template parameters T2 through T7.
  • +
+

These values are mutable.

+ +

Definition at line 28 of file VectorBuilder.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<bool used, typename T1, typename T2, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T7 = double>
+ + + + + +
+ + + + + + + + +
stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 >::VectorBuilder (size_t n)
+
+inlineexplicit
+
+ +

Definition at line 33 of file VectorBuilder.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<bool used, typename T1, typename T2, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T7 = double>
+ + + + + +
+ + + + + + + +
VectorBuilderHelper<T1, used, contains_vector<T2, T3, T4, T5, T6, T7>::value>::type stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 >::data ()
+
+inline
+
+ +

Definition at line 42 of file VectorBuilder.hpp.

+ +
+
+ +
+
+
+template<bool used, typename T1, typename T2, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T7 = double>
+ + + + + +
+ + + + + + + + +
T1& stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 >::operator[] (size_t i)
+
+inline
+
+ +

Definition at line 35 of file VectorBuilder.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<bool used, typename T1, typename T2, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T7 = double>
+ + + + +
VectorBuilderHelper<T1, used, contains_vector<T2, T3, T4, T5, T6, T7>::value> stan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 >::a
+
+ +

Definition at line 31 of file VectorBuilder.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_builder_helper-members.html b/doc/api/html/classstan_1_1_vector_builder_helper-members.html new file mode 100644 index 00000000000..88976d2edda --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_builder_helper-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorBuilderHelper< T1, used, is_vec > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_builder_helper.html b/doc/api/html/classstan_1_1_vector_builder_helper.html new file mode 100644 index 00000000000..bdce7238d07 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_builder_helper.html @@ -0,0 +1,252 @@ + + + + + + +Stan Math Library: stan::VectorBuilderHelper< T1, used, is_vec > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorBuilderHelper< T1, used, is_vec > Class Template Reference
+
+
+ +

VectorBuilder allocates type T1 values to be used as intermediate values. + More...

+ +

#include <VectorBuilderHelper.hpp>

+ + + + +

+Public Types

typedef T1 type
 
+ + + + + + + +

+Public Member Functions

 VectorBuilderHelper (size_t)
 
T1 & operator[] (size_t)
 
typedata ()
 
+

Detailed Description

+

template<typename T1, bool used, bool is_vec>
+class stan::VectorBuilderHelper< T1, used, is_vec >

+ +

VectorBuilder allocates type T1 values to be used as intermediate values.

+

There are 2 template parameters:

    +
  • used: boolean variable indicating whether this instance is used. If this is false, there is no storage allocated and operator[] throws.
  • +
  • is_vec: boolean variable indicating whether this instance should allocate a vector, if it is used. If this is false, the instance will only allocate a single double value. If this is true, it will allocate the number requested. Note that this is calculated based on template parameters T2 through T7.
  • +
+

These values are mutable.

+ +

Definition at line 25 of file VectorBuilderHelper.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1, bool used, bool is_vec>
+ + + + +
typedef T1 stan::VectorBuilderHelper< T1, used, is_vec >::type
+
+ +

Definition at line 33 of file VectorBuilderHelper.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1, bool used, bool is_vec>
+ + + + + +
+ + + + + + + + +
stan::VectorBuilderHelper< T1, used, is_vec >::VectorBuilderHelper (size_t )
+
+inlineexplicit
+
+ +

Definition at line 27 of file VectorBuilderHelper.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1, bool used, bool is_vec>
+ + + + + +
+ + + + + + + +
type& stan::VectorBuilderHelper< T1, used, is_vec >::data ()
+
+inline
+
+ +

Definition at line 35 of file VectorBuilderHelper.hpp.

+ +
+
+ +
+
+
+template<typename T1, bool used, bool is_vec>
+ + + + + +
+ + + + + + + + +
T1& stan::VectorBuilderHelper< T1, used, is_vec >::operator[] (size_t )
+
+inline
+
+ +

Definition at line 29 of file VectorBuilderHelper.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01false_01_4-members.html b/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01false_01_4-members.html new file mode 100644 index 00000000000..1c6ab82fb8a --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01false_01_4-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorBuilderHelper< T1, true, false > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01false_01_4.html b/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01false_01_4.html new file mode 100644 index 00000000000..44aee2692af --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01false_01_4.html @@ -0,0 +1,243 @@ + + + + + + +Stan Math Library: stan::VectorBuilderHelper< T1, true, false > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorBuilderHelper< T1, true, false > Class Template Reference
+
+
+ +

#include <VectorBuilderHelper.hpp>

+ + + + +

+Public Types

typedef T1 type
 
+ + + + + + + +

+Public Member Functions

 VectorBuilderHelper (size_t)
 
T1 & operator[] (size_t)
 
typedata ()
 
+

Detailed Description

+

template<typename T1>
+class stan::VectorBuilderHelper< T1, true, false >

+ + +

Definition at line 41 of file VectorBuilderHelper.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1 >
+ + + + +
typedef T1 stan::VectorBuilderHelper< T1, true, false >::type
+
+ +

Definition at line 50 of file VectorBuilderHelper.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 >
+ + + + + +
+ + + + + + + + +
stan::VectorBuilderHelper< T1, true, false >::VectorBuilderHelper (size_t )
+
+inlineexplicit
+
+ +

Definition at line 45 of file VectorBuilderHelper.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 >
+ + + + + +
+ + + + + + + +
type& stan::VectorBuilderHelper< T1, true, false >::data ()
+
+inline
+
+ +

Definition at line 52 of file VectorBuilderHelper.hpp.

+ +
+
+ +
+
+
+template<typename T1 >
+ + + + + +
+ + + + + + + + +
T1& stan::VectorBuilderHelper< T1, true, false >::operator[] (size_t )
+
+inline
+
+ +

Definition at line 46 of file VectorBuilderHelper.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01true_01_4-members.html b/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01true_01_4-members.html new file mode 100644 index 00000000000..edbbd19b3f1 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01true_01_4-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorBuilderHelper< T1, true, true > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01true_01_4.html b/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01true_01_4.html new file mode 100644 index 00000000000..60da4d7ee0e --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_builder_helper_3_01_t1_00_01true_00_01true_01_4.html @@ -0,0 +1,247 @@ + + + + + + +Stan Math Library: stan::VectorBuilderHelper< T1, true, true > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorBuilderHelper< T1, true, true > Class Template Reference
+
+
+ +

Template specialization for using a vector. + More...

+ +

#include <VectorBuilderHelper.hpp>

+ + + + +

+Public Types

typedef std::vector< T1 > type
 
+ + + + + + + +

+Public Member Functions

 VectorBuilderHelper (size_t n)
 
T1 & operator[] (size_t i)
 
typedata ()
 
+

Detailed Description

+

template<typename T1>
+class stan::VectorBuilderHelper< T1, true, true >

+ +

Template specialization for using a vector.

+ +

Definition at line 14 of file VectorBuilderHelper.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1 >
+ + + + +
typedef std::vector<T1> stan::VectorBuilderHelper< T1, true, true >::type
+
+ +

Definition at line 20 of file VectorBuilderHelper.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 >
+ + + + + +
+ + + + + + + + +
stan::VectorBuilderHelper< T1, true, true >::VectorBuilderHelper (size_t n)
+
+inlineexplicit
+
+ +

Definition at line 18 of file VectorBuilderHelper.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 >
+ + + + + +
+ + + + + + + +
type& stan::VectorBuilderHelper< T1, true, true >::data ()
+
+inline
+
+ +

Definition at line 26 of file VectorBuilderHelper.hpp.

+ +
+
+ +
+
+
+template<typename T1 >
+ + + + + +
+ + + + + + + + +
T1& stan::VectorBuilderHelper< T1, true, true >::operator[] (size_t i)
+
+inline
+
+ +

Definition at line 22 of file VectorBuilderHelper.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view-members.html b/doc/api/html/classstan_1_1_vector_view-members.html new file mode 100644 index 00000000000..690d4ac7d37 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorView< T, is_array, throw_if_accessed > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view.html b/doc/api/html/classstan_1_1_vector_view.html new file mode 100644 index 00000000000..76ba9ed9ac0 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view.html @@ -0,0 +1,264 @@ + + + + + + +Stan Math Library: stan::VectorView< T, is_array, throw_if_accessed > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorView< T, is_array, throw_if_accessed > Class Template Reference
+
+
+ +

VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[]. + More...

+ +

#include <VectorView.hpp>

+ + + + +

+Public Types

typedef boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
 
+ + + + + + + + +

+Public Member Functions

template<typename X >
 VectorView (X x)
 
scalar_toperator[] (int i)
 
scalar_toperator[] (int i) const
 
+

Detailed Description

+

template<typename T, bool is_array = stan::is_vector_like<T>::value, bool throw_if_accessed = false>
+class stan::VectorView< T, is_array, throw_if_accessed >

+ +

VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].

+

For a scalar value, any index returns the reference or pointer used to construct the view.

+

For a container, the index returns a reference to the position in the underlying container used to construct the view. WARNING: There is no bounds checking for container indices and they will segfault if accessed beyond their boundaries.

+

The first use is to read arguments to prob functions as vectors, even if scalars, so they can be read by common code (and scalars automatically broadcast up to behave like vectors) : VectorView of immutable const array of double* (no allocation).

+

The second use is to build up derivatives into common storage : VectorView of mutable shared array (no allocation because allocated on auto-diff arena memory).

+

Because it deals with references to its inputs, it is up to the client of VectorView to ensure that the container being wrapped is not modified while the VectorView is in use in such a way as to disrupt the indexing. Similarly, because it deals with references, it cannot be constructed with a literal or expression.

+
Template Parameters
+ + + + +
TType of scalar or container being wrapped.
is_arrayTrue if underlying type T can be indexed with operator[].
throw_if_accessedTrue if the behaviro is to throw an exception whenever operator[] is called.
+
+
+ +

Definition at line 48 of file VectorView.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T, bool is_array = stan::is_vector_like<T>::value, bool throw_if_accessed = false>
+ + + + +
typedef boost::conditional<boost::is_const<T>::value, typename boost::add_const< typename scalar_type<T>::type>::type, typename scalar_type<T>::type>::type stan::VectorView< T, is_array, throw_if_accessed >::scalar_t
+
+ +

Definition at line 54 of file VectorView.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T, bool is_array = stan::is_vector_like<T>::value, bool throw_if_accessed = false>
+
+template<typename X >
+ + + + + +
+ + + + + + + + +
stan::VectorView< T, is_array, throw_if_accessed >::VectorView (x)
+
+inlineexplicit
+
+ +

Definition at line 57 of file VectorView.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T, bool is_array = stan::is_vector_like<T>::value, bool throw_if_accessed = false>
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< T, is_array, throw_if_accessed >::operator[] (int i)
+
+inline
+
+ +

Definition at line 62 of file VectorView.hpp.

+ +
+
+ +
+
+
+template<typename T, bool is_array = stan::is_vector_like<T>::value, bool throw_if_accessed = false>
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< T, is_array, throw_if_accessed >::operator[] (int i) const
+
+inline
+
+ +

Definition at line 67 of file VectorView.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4-members.html b/doc/api/html/classstan_1_1_vector_view_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4-members.html new file mode 100644 index 00000000000..30da81d8ffd --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorView< Eigen::Matrix< T, R, C >, true, false > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4.html b/doc/api/html/classstan_1_1_vector_view_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4.html new file mode 100644 index 00000000000..4d25104cc86 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4.html @@ -0,0 +1,217 @@ + + + + + + +Stan Math Library: stan::VectorView< Eigen::Matrix< T, R, C >, true, false > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorView< Eigen::Matrix< T, R, C >, true, false > Class Template Reference
+
+
+ +

#include <VectorView.hpp>

+ + + + +

+Public Types

typedef scalar_type< T >::type scalar_t
 
+ + + + + + +

+Public Member Functions

template<typename X >
 VectorView (X &x)
 
scalar_toperator[] (int i)
 
+

Detailed Description

+

template<typename T, int R, int C>
+class stan::VectorView< Eigen::Matrix< T, R, C >, true, false >

+ + +

Definition at line 12 of file VectorView.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + +
typedef scalar_type<T>::type stan::VectorView< Eigen::Matrix< T, R, C >, true, false >::scalar_t
+
+ +

Definition at line 14 of file VectorView.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , int R, int C>
+
+template<typename X >
+ + + + + +
+ + + + + + + + +
stan::VectorView< Eigen::Matrix< T, R, C >, true, false >::VectorView (X & x)
+
+inlineexplicit
+
+ +

Definition at line 17 of file VectorView.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< Eigen::Matrix< T, R, C >, true, false >::operator[] (int i)
+
+inline
+
+ +

Definition at line 19 of file VectorView.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01false_00_01false_01_4-members.html b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01false_00_01false_01_4-members.html new file mode 100644 index 00000000000..7f0b69bd949 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01false_00_01false_01_4-members.html @@ -0,0 +1,119 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorView< T, false, false > Member List
+
+
+ +

This is the complete list of members for stan::VectorView< T, false, false >, including all inherited members.

+ + + + + + +
operator[](int i)stan::VectorView< T, false, false >inline
operator[](int i) const stan::VectorView< T, false, false >inline
scalar_t typedefstan::VectorView< T, false, false >
VectorView(scalar_t &x)stan::VectorView< T, false, false >inlineexplicit
VectorView(scalar_t *x)stan::VectorView< T, false, false >inlineexplicit
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01false_00_01false_01_4.html b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01false_00_01false_01_4.html new file mode 100644 index 00000000000..96b749f8f33 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01false_00_01false_01_4.html @@ -0,0 +1,274 @@ + + + + + + +Stan Math Library: stan::VectorView< T, false, false > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorView< T, false, false > Class Template Reference
+
+
+ +

#include <VectorView.hpp>

+ + + + +

+Public Types

typedef boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
 
+ + + + + + + + + +

+Public Member Functions

 VectorView (scalar_t &x)
 
 VectorView (scalar_t *x)
 
scalar_toperator[] (int i)
 
scalar_toperator[] (int i) const
 
+

Detailed Description

+

template<typename T>
+class stan::VectorView< T, false, false >

+ + +

Definition at line 98 of file VectorView.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef boost::conditional<boost::is_const<T>::value, typename boost::add_const< typename scalar_type<T>::type>::type, typename scalar_type<T>::type>::type stan::VectorView< T, false, false >::scalar_t
+
+ +

Definition at line 104 of file VectorView.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
stan::VectorView< T, false, false >::VectorView (scalar_tx)
+
+inlineexplicit
+
+ +

Definition at line 106 of file VectorView.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
stan::VectorView< T, false, false >::VectorView (scalar_tx)
+
+inlineexplicit
+
+ +

Definition at line 108 of file VectorView.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< T, false, false >::operator[] (int i)
+
+inline
+
+ +

Definition at line 110 of file VectorView.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< T, false, false >::operator[] (int i) const
+
+inline
+
+ +

Definition at line 114 of file VectorView.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01is__array_00_01true_01_4-members.html b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01is__array_00_01true_01_4-members.html new file mode 100644 index 00000000000..5bf06d91b02 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01is__array_00_01true_01_4-members.html @@ -0,0 +1,119 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorView< T, is_array, true > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01is__array_00_01true_01_4.html b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01is__array_00_01true_01_4.html new file mode 100644 index 00000000000..abf3986011b --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01is__array_00_01true_01_4.html @@ -0,0 +1,276 @@ + + + + + + +Stan Math Library: stan::VectorView< T, is_array, true > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorView< T, is_array, true > Class Template Reference
+
+
+ +

#include <VectorView.hpp>

+ + + + +

+Public Types

typedef boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
 
+ + + + + + + + + + +

+Public Member Functions

 VectorView ()
 
template<typename X >
 VectorView (X x)
 
scalar_toperator[] (int i)
 
scalar_toperator[] (int i) const
 
+

Detailed Description

+

template<typename T, bool is_array>
+class stan::VectorView< T, is_array, true >

+ + +

Definition at line 75 of file VectorView.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , bool is_array>
+ + + + +
typedef boost::conditional<boost::is_const<T>::value, typename boost::add_const< typename scalar_type<T>::type>::type, typename scalar_type<T>::type>::type stan::VectorView< T, is_array, true >::scalar_t
+
+ +

Definition at line 81 of file VectorView.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , bool is_array>
+ + + + + +
+ + + + + + + +
stan::VectorView< T, is_array, true >::VectorView ()
+
+inline
+
+ +

Definition at line 82 of file VectorView.hpp.

+ +
+
+ +
+
+
+template<typename T , bool is_array>
+
+template<typename X >
+ + + + + +
+ + + + + + + + +
stan::VectorView< T, is_array, true >::VectorView (x)
+
+inlineexplicit
+
+ +

Definition at line 85 of file VectorView.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , bool is_array>
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< T, is_array, true >::operator[] (int i)
+
+inline
+
+ +

Definition at line 87 of file VectorView.hpp.

+ +
+
+ +
+
+
+template<typename T , bool is_array>
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< T, is_array, true >::operator[] (int i) const
+
+inline
+
+ +

Definition at line 91 of file VectorView.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01true_00_01false_01_4-members.html b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01true_00_01false_01_4-members.html new file mode 100644 index 00000000000..339305322e5 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01true_00_01false_01_4-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorView< T, true, false > Member List
+
+
+ +

This is the complete list of members for stan::VectorView< T, true, false >, including all inherited members.

+ + + + + +
operator[](int i)stan::VectorView< T, true, false >inline
operator[](int i) const stan::VectorView< T, true, false >inline
scalar_t typedefstan::VectorView< T, true, false >
VectorView(scalar_t *x)stan::VectorView< T, true, false >inlineexplicit
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01true_00_01false_01_4.html b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01true_00_01false_01_4.html new file mode 100644 index 00000000000..f3d1000d790 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01_t_00_01true_00_01false_01_4.html @@ -0,0 +1,244 @@ + + + + + + +Stan Math Library: stan::VectorView< T, true, false > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorView< T, true, false > Class Template Reference
+
+
+ +

#include <VectorView.hpp>

+ + + + +

+Public Types

typedef boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
 
+ + + + + + + +

+Public Member Functions

 VectorView (scalar_t *x)
 
scalar_toperator[] (int i)
 
scalar_toperator[] (int i) const
 
+

Detailed Description

+

template<typename T>
+class stan::VectorView< T, true, false >

+ + +

Definition at line 124 of file VectorView.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef boost::conditional<boost::is_const<T>::value, typename boost::add_const< typename scalar_type<T>::type>::type, typename scalar_type<T>::type>::type stan::VectorView< T, true, false >::scalar_t
+
+ +

Definition at line 130 of file VectorView.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
stan::VectorView< T, true, false >::VectorView (scalar_tx)
+
+inlineexplicit
+
+ +

Definition at line 132 of file VectorView.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< T, true, false >::operator[] (int i)
+
+inline
+
+ +

Definition at line 134 of file VectorView.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< T, true, false >::operator[] (int i) const
+
+inline
+
+ +

Definition at line 138 of file VectorView.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01const_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4-members.html b/doc/api/html/classstan_1_1_vector_view_3_01const_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4-members.html new file mode 100644 index 00000000000..42d1810a562 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01const_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorView< const Eigen::Matrix< T, R, C >, true, false > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01const_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4.html b/doc/api/html/classstan_1_1_vector_view_3_01const_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4.html new file mode 100644 index 00000000000..1ef85594a71 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01const_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01true_00_01false_01_4.html @@ -0,0 +1,217 @@ + + + + + + +Stan Math Library: stan::VectorView< const Eigen::Matrix< T, R, C >, true, false > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorView< const Eigen::Matrix< T, R, C >, true, false > Class Template Reference
+
+
+ +

#include <VectorView.hpp>

+ + + + +

+Public Types

typedef boost::add_const< typename scalar_type< T >::type >::type scalar_t
 
+ + + + + + +

+Public Member Functions

template<typename X >
 VectorView (X &x)
 
scalar_toperator[] (int i) const
 
+

Detailed Description

+

template<typename T, int R, int C>
+class stan::VectorView< const Eigen::Matrix< T, R, C >, true, false >

+ + +

Definition at line 27 of file VectorView.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + +
typedef boost::add_const<typename scalar_type<T>::type>::type stan::VectorView< const Eigen::Matrix< T, R, C >, true, false >::scalar_t
+
+ +

Definition at line 30 of file VectorView.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , int R, int C>
+
+template<typename X >
+ + + + + +
+ + + + + + + + +
stan::VectorView< const Eigen::Matrix< T, R, C >, true, false >::VectorView (X & x)
+
+inlineexplicit
+
+ +

Definition at line 33 of file VectorView.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< const Eigen::Matrix< T, R, C >, true, false >::operator[] (int i) const
+
+inline
+
+ +

Definition at line 35 of file VectorView.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01const_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4-members.html b/doc/api/html/classstan_1_1_vector_view_3_01const_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4-members.html new file mode 100644 index 00000000000..1a3ffb77b59 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01const_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorView< const std::vector< T >, true, false > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01const_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4.html b/doc/api/html/classstan_1_1_vector_view_3_01const_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4.html new file mode 100644 index 00000000000..f9b2fce4876 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01const_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4.html @@ -0,0 +1,217 @@ + + + + + + +Stan Math Library: stan::VectorView< const std::vector< T >, true, false > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorView< const std::vector< T >, true, false > Class Template Reference
+
+
+ +

#include <VectorView.hpp>

+ + + + +

+Public Types

typedef boost::add_const< typename scalar_type< T >::type >::type scalar_t
 
+ + + + + + +

+Public Member Functions

template<typename X >
 VectorView (X &x)
 
scalar_toperator[] (int i) const
 
+

Detailed Description

+

template<typename T>
+class stan::VectorView< const std::vector< T >, true, false >

+ + +

Definition at line 26 of file VectorView.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef boost::add_const<typename scalar_type<T>::type>::type stan::VectorView< const std::vector< T >, true, false >::scalar_t
+
+ +

Definition at line 29 of file VectorView.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T >
+
+template<typename X >
+ + + + + +
+ + + + + + + + +
stan::VectorView< const std::vector< T >, true, false >::VectorView (X & x)
+
+inlineexplicit
+
+ +

Definition at line 32 of file VectorView.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< const std::vector< T >, true, false >::operator[] (int i) const
+
+inline
+
+ +

Definition at line 34 of file VectorView.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4-members.html b/doc/api/html/classstan_1_1_vector_view_3_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4-members.html new file mode 100644 index 00000000000..15d05f7643e --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorView< std::vector< T >, true, false > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_3_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4.html b/doc/api/html/classstan_1_1_vector_view_3_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4.html new file mode 100644 index 00000000000..3b862a74d2b --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_3_01std_1_1vector_3_01_t_01_4_00_01true_00_01false_01_4.html @@ -0,0 +1,217 @@ + + + + + + +Stan Math Library: stan::VectorView< std::vector< T >, true, false > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorView< std::vector< T >, true, false > Class Template Reference
+
+
+ +

#include <VectorView.hpp>

+ + + + +

+Public Types

typedef scalar_type< T >::type scalar_t
 
+ + + + + + +

+Public Member Functions

template<typename X >
 VectorView (X &x)
 
scalar_toperator[] (int i)
 
+

Detailed Description

+

template<typename T>
+class stan::VectorView< std::vector< T >, true, false >

+ + +

Definition at line 10 of file VectorView.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef scalar_type<T>::type stan::VectorView< std::vector< T >, true, false >::scalar_t
+
+ +

Definition at line 12 of file VectorView.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T >
+
+template<typename X >
+ + + + + +
+ + + + + + + + +
stan::VectorView< std::vector< T >, true, false >::VectorView (X & x)
+
+inlineexplicit
+
+ +

Definition at line 15 of file VectorView.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
scalar_t& stan::VectorView< std::vector< T >, true, false >::operator[] (int i)
+
+inline
+
+ +

Definition at line 17 of file VectorView.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_mvt-members.html b/doc/api/html/classstan_1_1_vector_view_mvt-members.html new file mode 100644 index 00000000000..2983646dfa1 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_mvt-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorViewMvt< T, is_array, throw_if_accessed > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_mvt.html b/doc/api/html/classstan_1_1_vector_view_mvt.html new file mode 100644 index 00000000000..e68e622b384 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_mvt.html @@ -0,0 +1,244 @@ + + + + + + +Stan Math Library: stan::VectorViewMvt< T, is_array, throw_if_accessed > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorViewMvt< T, is_array, throw_if_accessed > Class Template Reference
+
+
+ +

#include <VectorViewMvt.hpp>

+ + + + +

+Public Types

typedef scalar_type_pre< T >::type matrix_t
 
+ + + + + + + +

+Public Member Functions

 VectorViewMvt (matrix_t &m)
 
 VectorViewMvt (std::vector< matrix_t > &vm)
 
matrix_toperator[] (int i)
 
+

Detailed Description

+

template<typename T, bool is_array = stan::is_vector_like <typename stan::math::value_type<T>::type>::value, bool throw_if_accessed = false>
+class stan::VectorViewMvt< T, is_array, throw_if_accessed >

+ + +

Definition at line 16 of file VectorViewMvt.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T, bool is_array = stan::is_vector_like <typename stan::math::value_type<T>::type>::value, bool throw_if_accessed = false>
+ + + + +
typedef scalar_type_pre<T>::type stan::VectorViewMvt< T, is_array, throw_if_accessed >::matrix_t
+
+ +

Definition at line 18 of file VectorViewMvt.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T, bool is_array = stan::is_vector_like <typename stan::math::value_type<T>::type>::value, bool throw_if_accessed = false>
+ + + + + +
+ + + + + + + + +
stan::VectorViewMvt< T, is_array, throw_if_accessed >::VectorViewMvt (matrix_tm)
+
+inlineexplicit
+
+ +

Definition at line 20 of file VectorViewMvt.hpp.

+ +
+
+ +
+
+
+template<typename T, bool is_array = stan::is_vector_like <typename stan::math::value_type<T>::type>::value, bool throw_if_accessed = false>
+ + + + + +
+ + + + + + + + +
stan::VectorViewMvt< T, is_array, throw_if_accessed >::VectorViewMvt (std::vector< matrix_t > & vm)
+
+inlineexplicit
+
+ +

Definition at line 22 of file VectorViewMvt.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T, bool is_array = stan::is_vector_like <typename stan::math::value_type<T>::type>::value, bool throw_if_accessed = false>
+ + + + + +
+ + + + + + + + +
matrix_t& stan::VectorViewMvt< T, is_array, throw_if_accessed >::operator[] (int i)
+
+inline
+
+ +

Definition at line 24 of file VectorViewMvt.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_mvt_3_01const_01_t_00_01is__array_00_01throw__if__accessed_01_4-members.html b/doc/api/html/classstan_1_1_vector_view_mvt_3_01const_01_t_00_01is__array_00_01throw__if__accessed_01_4-members.html new file mode 100644 index 00000000000..05778601f87 --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_mvt_3_01const_01_t_00_01is__array_00_01throw__if__accessed_01_4-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::VectorViewMvt< const T, is_array, throw_if_accessed > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1_vector_view_mvt_3_01const_01_t_00_01is__array_00_01throw__if__accessed_01_4.html b/doc/api/html/classstan_1_1_vector_view_mvt_3_01const_01_t_00_01is__array_00_01throw__if__accessed_01_4.html new file mode 100644 index 00000000000..9d22612cf6e --- /dev/null +++ b/doc/api/html/classstan_1_1_vector_view_mvt_3_01const_01_t_00_01is__array_00_01throw__if__accessed_01_4.html @@ -0,0 +1,248 @@ + + + + + + +Stan Math Library: stan::VectorViewMvt< const T, is_array, throw_if_accessed > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::VectorViewMvt< const T, is_array, throw_if_accessed > Class Template Reference
+
+
+ +

VectorViewMvt that has const correctness. + More...

+ +

#include <VectorViewMvt.hpp>

+ + + + +

+Public Types

typedef scalar_type_pre< T >::type matrix_t
 
+ + + + + + + +

+Public Member Functions

 VectorViewMvt (const matrix_t &m)
 
 VectorViewMvt (const std::vector< matrix_t > &vm)
 
const matrix_toperator[] (int i) const
 
+

Detailed Description

+

template<typename T, bool is_array, bool throw_if_accessed>
+class stan::VectorViewMvt< const T, is_array, throw_if_accessed >

+ +

VectorViewMvt that has const correctness.

+ +

Definition at line 41 of file VectorViewMvt.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , bool is_array, bool throw_if_accessed>
+ + + + +
typedef scalar_type_pre<T>::type stan::VectorViewMvt< const T, is_array, throw_if_accessed >::matrix_t
+
+ +

Definition at line 43 of file VectorViewMvt.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , bool is_array, bool throw_if_accessed>
+ + + + + +
+ + + + + + + + +
stan::VectorViewMvt< const T, is_array, throw_if_accessed >::VectorViewMvt (const matrix_tm)
+
+inlineexplicit
+
+ +

Definition at line 45 of file VectorViewMvt.hpp.

+ +
+
+ +
+
+
+template<typename T , bool is_array, bool throw_if_accessed>
+ + + + + +
+ + + + + + + + +
stan::VectorViewMvt< const T, is_array, throw_if_accessed >::VectorViewMvt (const std::vector< matrix_t > & vm)
+
+inlineexplicit
+
+ +

Definition at line 47 of file VectorViewMvt.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , bool is_array, bool throw_if_accessed>
+ + + + + +
+ + + + + + + + +
const matrix_t& stan::VectorViewMvt< const T, is_array, throw_if_accessed >::operator[] (int i) const
+
+inline
+
+ +

Definition at line 49 of file VectorViewMvt.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1_l_d_l_t__alloc-members.html b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__alloc-members.html new file mode 100644 index 00000000000..70522a4563d --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__alloc-members.html @@ -0,0 +1,123 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::LDLT_alloc< R, C > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1_l_d_l_t__alloc.html b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__alloc.html new file mode 100644 index 00000000000..24e2d276894 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__alloc.html @@ -0,0 +1,334 @@ + + + + + + +Stan Math Library: stan::math::LDLT_alloc< R, C > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::LDLT_alloc< R, C > Class Template Reference
+
+
+ +

This object stores the actual (double typed) LDLT factorization of an Eigen::Matrix<var> along with pointers to its vari's which allow the *_ldlt functions to save memory. + More...

+ +

#include <LDLT_alloc.hpp>

+
+Inheritance diagram for stan::math::LDLT_alloc< R, C >:
+
+
+ + +stan::math::chainable_alloc + +
+ + + + + + + + + + + + + + + + + +

+Public Member Functions

 LDLT_alloc ()
 
 LDLT_alloc (const Eigen::Matrix< var, R, C > &A)
 
void compute (const Eigen::Matrix< var, R, C > &A)
 Compute the LDLT factorization and store pointers to the vari's of the matrix entries to be used when chain() is called elsewhere. More...
 
double log_abs_det () const
 Compute the log(abs(det(A))). This is just a convenience function. More...
 
- Public Member Functions inherited from stan::math::chainable_alloc
 chainable_alloc ()
 
virtual ~chainable_alloc ()
 
+ + + + + + + +

+Public Attributes

size_t N_
 
Eigen::LDLT< Eigen::Matrix< double, R, C > > _ldlt
 
Eigen::Matrix< vari *, R, C > _variA
 
+

Detailed Description

+

template<int R, int C>
+class stan::math::LDLT_alloc< R, C >

+ +

This object stores the actual (double typed) LDLT factorization of an Eigen::Matrix<var> along with pointers to its vari's which allow the *_ldlt functions to save memory.

+

It is derived from a chainable_alloc object so that it is allocated on the stack but does not have a chain() function called.

+

This class should only be instantiated as part of an LDLT_factor object and is only used in *_ldlt functions.

+ +

Definition at line 20 of file LDLT_alloc.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + +
stan::math::LDLT_alloc< R, C >::LDLT_alloc ()
+
+inline
+
+ +

Definition at line 22 of file LDLT_alloc.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
stan::math::LDLT_alloc< R, C >::LDLT_alloc (const Eigen::Matrix< var, R, C > & A)
+
+inlineexplicit
+
+ +

Definition at line 23 of file LDLT_alloc.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
void stan::math::LDLT_alloc< R, C >::compute (const Eigen::Matrix< var, R, C > & A)
+
+inline
+
+ +

Compute the LDLT factorization and store pointers to the vari's of the matrix entries to be used when chain() is called elsewhere.

+ +

Definition at line 32 of file LDLT_alloc.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + +
double stan::math::LDLT_alloc< R, C >::log_abs_det () const
+
+inline
+
+ +

Compute the log(abs(det(A))). This is just a convenience function.

+ +

Definition at line 49 of file LDLT_alloc.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<int R, int C>
+ + + + +
Eigen::LDLT<Eigen::Matrix<double, R, C> > stan::math::LDLT_alloc< R, C >::_ldlt
+
+ +

Definition at line 54 of file LDLT_alloc.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + +
Eigen::Matrix<vari*, R, C> stan::math::LDLT_alloc< R, C >::_variA
+
+ +

Definition at line 55 of file LDLT_alloc.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + +
size_t stan::math::LDLT_alloc< R, C >::N_
+
+ +

Definition at line 53 of file LDLT_alloc.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1_l_d_l_t__alloc.png b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__alloc.png new file mode 100644 index 0000000000000000000000000000000000000000..398a5d9961099f7c79b7c7ec5a626072be612bd8 GIT binary patch literal 713 zcmeAS@N?(olHy`uVBq!ia0vp^yMZ`>gBeJco&6#Sq$C1-LR|m<{|{uoc=NTi|Ih>= z3ycpOIKbL@M;^%KC<*clW&kPzfvcxNj2IZ0B0OCjLn;{G&b_&AwE>T7xLMHu|C9CE zIc`X1RI}Z8>zZ=6t0FamY9uqlm z|0Scr3bwR*n`5o=GiqJs#p+VN-Arfr*RE#mu!jU3thv-=g$ILk)+Xj7*+9HHp}tUY zb+mTQ{y)!)-?24Frs_O!Q(iXl>GzwT&u8X5sXi5V^s2Gy@9USgeSO;<%1?P0p}s`3E)d+P&hVWGp8?ytGj@GF1(H1&{z*++f@(;b7S LtDnm{r-UW|+FDtB literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor.html b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor.html new file mode 100644 index 00000000000..3e61e661e76 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor.html @@ -0,0 +1,122 @@ + + + + + + +Stan Math Library: stan::math::LDLT_factor< T, R, C > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::LDLT_factor< T, R, C > Class Template Reference
+
+
+ +

#include <LDLT_factor.hpp>

+

Detailed Description

+

template<typename T, int R, int C>
+class stan::math::LDLT_factor< T, R, C >

+ + +

Definition at line 18 of file LDLT_factor.hpp.

+

The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01_t_00_01_r_00_01_c_01_4-members.html b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01_t_00_01_r_00_01_c_01_4-members.html new file mode 100644 index 00000000000..4131d49b3d9 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01_t_00_01_r_00_01_c_01_4-members.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::LDLT_factor< T, R, C > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01_t_00_01_r_00_01_c_01_4.html b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01_t_00_01_r_00_01_c_01_4.html new file mode 100644 index 00000000000..7bd7aa94f7c --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01_t_00_01_r_00_01_c_01_4.html @@ -0,0 +1,589 @@ + + + + + + +Stan Math Library: stan::math::LDLT_factor< T, R, C > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::LDLT_factor< T, R, C > Class Template Reference
+
+
+ +

LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodiff of things like log determinants and solutions to linear systems. + More...

+ +

#include <LDLT_factor.hpp>

+ + + + + + +

+Public Types

typedef size_t size_type
 
typedef double value_type
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 LDLT_factor ()
 
 LDLT_factor (const Eigen::Matrix< T, R, C > &A)
 
void compute (const Eigen::Matrix< T, R, C > &A)
 
bool success () const
 
log_abs_det () const
 
void inverse (Eigen::Matrix< T, R, C > &invA) const
 
template<typename Rhs >
const Eigen::internal::solve_retval< Eigen::LDLT< Eigen::Matrix< T, R, C > >, Rhs > solve (const Eigen::MatrixBase< Rhs > &b) const
 
Eigen::Matrix< T, R, C > solveRight (const Eigen::Matrix< T, R, C > &B) const
 
Eigen::Matrix< T, Eigen::Dynamic, 1 > vectorD () const
 
Eigen::LDLT< Eigen::Matrix< T, R, C > > matrixLDLT () const
 
size_t rows () const
 
size_t cols () const
 
+ + + + + +

+Public Attributes

size_t N_
 
boost::shared_ptr< Eigen::LDLT< Eigen::Matrix< T, R, C > > > _ldltP
 
+

Detailed Description

+

template<int R, int C, typename T>
+class stan::math::LDLT_factor< T, R, C >

+ +

LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodiff of things like log determinants and solutions to linear systems.

+

After the constructor and/or compute() is called users of LDLT_factor are responsible for calling success() to check whether the factorization has succeeded. Use of an LDLT_factor object (e.g., in mdivide_left_ldlt) is undefined if success() is false.

+

It's usage pattern is:

+
    +
  • ~~~ Eigen::Matrix<T, R, C> A1, A2;

    +

    LDLT_factor<T, R, C> ldlt_A1(A1); LDLT_factor<T, R, C> ldlt_A2; ldlt_A2.compute(A2);

    +
  • +
  • ~~~

    +

    Now, the caller should check that ldlt_A1.success() and ldlt_A2.success() are true or abort accordingly. Alternatively, call check_ldlt_factor().

    +

    Note that ldlt_A1 and ldlt_A2 are completely equivalent. They simply demonstrate two different ways to construct the factorization.

    +

    Now, the caller can use the LDLT_factor objects as needed. For instance

    +
  • +
  • ~~~ x1 = mdivide_left_ldlt(ldlt_A1, b1); x2 = mdivide_right_ldlt(b2, ldlt_A2);

    +

    d1 = log_determinant_ldlt(ldlt_A1); d2 = log_determinant_ldlt(ldlt_A2);

    +
  • +
  • ~~~
  • +
+ +

Definition at line 58 of file LDLT_factor.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<int R, int C, typename T >
+ + + + +
typedef size_t stan::math::LDLT_factor< T, R, C >::size_type
+
+ +

Definition at line 125 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + +
typedef double stan::math::LDLT_factor< T, R, C >::value_type
+
+ +

Definition at line 126 of file LDLT_factor.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + +
stan::math::LDLT_factor< T, R, C >::LDLT_factor ()
+
+inline
+
+ +

Definition at line 60 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + +
stan::math::LDLT_factor< T, R, C >::LDLT_factor (const Eigen::Matrix< T, R, C > & A)
+
+inlineexplicit
+
+ +

Definition at line 63 of file LDLT_factor.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + +
size_t stan::math::LDLT_factor< T, R, C >::cols () const
+
+inline
+
+ +

Definition at line 123 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + +
void stan::math::LDLT_factor< T, R, C >::compute (const Eigen::Matrix< T, R, C > & A)
+
+inline
+
+ +

Definition at line 68 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + +
void stan::math::LDLT_factor< T, R, C >::inverse (Eigen::Matrix< T, R, C > & invA) const
+
+inline
+
+ +

Definition at line 97 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + +
T stan::math::LDLT_factor< T, R, C >::log_abs_det () const
+
+inline
+
+ +

Definition at line 93 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + +
Eigen::LDLT<Eigen::Matrix<T, R, C> > stan::math::LDLT_factor< T, R, C >::matrixLDLT () const
+
+inline
+
+ +

Definition at line 118 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + +
size_t stan::math::LDLT_factor< T, R, C >::rows () const
+
+inline
+
+ +

Definition at line 122 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+
+template<typename Rhs >
+ + + + + +
+ + + + + + + + +
const Eigen::internal::solve_retval<Eigen::LDLT< Eigen::Matrix<T, R, C> >, Rhs> stan::math::LDLT_factor< T, R, C >::solve (const Eigen::MatrixBase< Rhs > & b) const
+
+inline
+
+ +

Definition at line 105 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R, C> stan::math::LDLT_factor< T, R, C >::solveRight (const Eigen::Matrix< T, R, C > & B) const
+
+inline
+
+ +

Definition at line 110 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + +
bool stan::math::LDLT_factor< T, R, C >::success () const
+
+inline
+
+ +

Definition at line 74 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::LDLT_factor< T, R, C >::vectorD () const
+
+inline
+
+ +

Definition at line 114 of file LDLT_factor.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<int R, int C, typename T >
+ + + + +
boost::shared_ptr< Eigen::LDLT< Eigen::Matrix<T, R, C> > > stan::math::LDLT_factor< T, R, C >::_ldltP
+
+ +

Definition at line 129 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + +
size_t stan::math::LDLT_factor< T, R, C >::N_
+
+ +

Definition at line 128 of file LDLT_factor.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01stan_1_1math_1_1var_00_01_r_00_01_c_01_4-members.html b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01stan_1_1math_1_1var_00_01_r_00_01_c_01_4-members.html new file mode 100644 index 00000000000..8e46ddd8018 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01stan_1_1math_1_1var_00_01_r_00_01_c_01_4-members.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::LDLT_factor< stan::math::var, R, C > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01stan_1_1math_1_1var_00_01_r_00_01_c_01_4.html b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01stan_1_1math_1_1var_00_01_r_00_01_c_01_4.html new file mode 100644 index 00000000000..2bee37cae71 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1_l_d_l_t__factor_3_01stan_1_1math_1_1var_00_01_r_00_01_c_01_4.html @@ -0,0 +1,490 @@ + + + + + + +Stan Math Library: stan::math::LDLT_factor< stan::math::var, R, C > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::LDLT_factor< stan::math::var, R, C > Class Template Reference
+
+
+ +

A template specialization of src/stan/math/matrix/LDLT_factor.hpp for stan::math::var which can be used with all the *_ldlt functions. + More...

+ +

#include <LDLT_factor.hpp>

+ + + + + + +

+Public Types

typedef size_t size_type
 
typedef stan::math::var value_type
 
+ + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 LDLT_factor ()
 Default constructor. More...
 
 LDLT_factor (const Eigen::Matrix< stan::math::var, R, C > &A)
 
void compute (const Eigen::Matrix< stan::math::var, R, C > &A)
 Use the LDLT_factor object to factorize a new matrix. More...
 
template<typename Rhs >
const Eigen::internal::solve_retval< Eigen::LDLT< Eigen::Matrix< double, R, C > >, Rhs > solve (const Eigen::MatrixBase< Rhs > &b) const
 Compute the actual numerical result of inv(A)*b. More...
 
bool success () const
 Determine whether the most recent factorization succeeded. More...
 
Eigen::VectorXd vectorD () const
 The entries of the diagonal matrix D. More...
 
size_t rows () const
 
size_t cols () const
 
+ + + + +

+Public Attributes

stan::math::LDLT_alloc< R, C > * _alloc
 The LDLT_alloc object actually contains the factorization but is derived from the chainable_alloc class so that it is allocated on the vari stack. More...
 
+

Detailed Description

+

template<int R, int C>
+class stan::math::LDLT_factor< stan::math::var, R, C >

+ +

A template specialization of src/stan/math/matrix/LDLT_factor.hpp for stan::math::var which can be used with all the *_ldlt functions.

+

The usage pattern is:

+
    +
  • ~~~ Eigen::Matrix<T, R, C> A1, A2;

    +

    LDLT_factor<T, R, C> ldlt_A1(A1); LDLT_factor<T, R, C> ldlt_A2; ldlt_A2.compute(A2);

    +
  • +
  • ~~~

    +

    Now, the caller should check that ldlt_A1.success() and ldlt_A2.success() are true or abort accordingly. Alternatively, call check_ldlt_factor(). The behaviour of using an LDLT_factor without success() returning true is undefined.

    +

    Note that ldlt_A1 and ldlt_A2 are completely equivalent. They simply demonstrate two different ways to construct the factorization.

    +

    Now, the caller can use the LDLT_factor objects as needed. For instance

    +
  • +
  • ~~~ x1 = mdivide_left_ldlt(ldlt_A1, b1); x2 = mdivide_right_ldlt(b2, ldlt_A2);

    +

    d1 = log_determinant_ldlt(ldlt_A1); d2 = log_determinant_ldlt(ldlt_A2);

    +
  • +
  • ~~~
  • +
+ +

Definition at line 45 of file LDLT_factor.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<int R, int C>
+ + + + +
typedef size_t stan::math::LDLT_factor< stan::math::var, R, C >::size_type
+
+ +

Definition at line 119 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + +
typedef stan::math::var stan::math::LDLT_factor< stan::math::var, R, C >::value_type
+
+ +

Definition at line 120 of file LDLT_factor.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + +
stan::math::LDLT_factor< stan::math::var, R, C >::LDLT_factor ()
+
+inline
+
+ +

Default constructor.

+

The caller MUST call compute() after this. Any calls which use the LDLT_factor without calling compute() run the risk of crashing Stan from within Eigen.

+ +

Definition at line 52 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
stan::math::LDLT_factor< stan::math::var, R, C >::LDLT_factor (const Eigen::Matrix< stan::math::var, R, C > & A)
+
+inlineexplicit
+
+ +

Definition at line 54 of file LDLT_factor.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + +
size_t stan::math::LDLT_factor< stan::math::var, R, C >::cols () const
+
+inline
+
+ +

Definition at line 117 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
void stan::math::LDLT_factor< stan::math::var, R, C >::compute (const Eigen::Matrix< stan::math::var, R, C > & A)
+
+inline
+
+ +

Use the LDLT_factor object to factorize a new matrix.

+

After calling this function, the user should call success() to check that the factorization was successful. If the factorization is not successful, the LDLT_factor is not valid and other functions should not be used.

+
Parameters
+ + +
AA symmetric positive definite matrix to factorize
+
+
+ +

Definition at line 67 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + +
size_t stan::math::LDLT_factor< stan::math::var, R, C >::rows () const
+
+inline
+
+ +

Definition at line 116 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+
+template<typename Rhs >
+ + + + + +
+ + + + + + + + +
const Eigen::internal::solve_retval<Eigen::LDLT<Eigen::Matrix<double, R, C> >, Rhs> stan::math::LDLT_factor< stan::math::var, R, C >::solve (const Eigen::MatrixBase< Rhs > & b) const
+
+inline
+
+ +

Compute the actual numerical result of inv(A)*b.

+

Note that this isn't meant to handle any of the autodiff. This is a convenience function for the actual implementations in mdivide_left_ldlt.

+

Precondition: success() must return true. If success() returns false, this function runs the risk of crashing Stan from within Eigen.

+
Parameters
+ + +
bThe right handside. Note that this is templated such that Eigen's expression-templating magic can work properly here.
+
+
+ +

Definition at line 87 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + +
bool stan::math::LDLT_factor< stan::math::var, R, C >::success () const
+
+inline
+
+ +

Determine whether the most recent factorization succeeded.

+

This should always be called after the object is constructed (with a matrix) or after compute() is called.

+ +

Definition at line 96 of file LDLT_factor.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + +
Eigen::VectorXd stan::math::LDLT_factor< stan::math::var, R, C >::vectorD () const
+
+inline
+
+ +

The entries of the diagonal matrix D.

+

They should be strictly positive for a positive definite matrix.

+

Precondition: success() must return true. If success() returns false, this function runs the risk of crashing Stan from within Eigen.

+ +

Definition at line 112 of file LDLT_factor.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<int R, int C>
+ + + + +
stan::math::LDLT_alloc<R, C>* stan::math::LDLT_factor< stan::math::var, R, C >::_alloc
+
+ +

The LDLT_alloc object actually contains the factorization but is derived from the chainable_alloc class so that it is allocated on the vari stack.

+

This ensures that it's lifespan is longer than the LDLT_factor object which created it. This is needed because the factorization is required during the chain() calls which happen after an LDLT_factor object will most likely have been destroyed.

+ +

Definition at line 130 of file LDLT_factor.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1accumulator-members.html b/doc/api/html/classstan_1_1math_1_1accumulator-members.html new file mode 100644 index 00000000000..4a4783a36f6 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1accumulator-members.html @@ -0,0 +1,121 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::accumulator< T > Member List
+
+
+ +

This is the complete list of members for stan::math::accumulator< T >, including all inherited members.

+ + + + + + + + +
accumulator()stan::math::accumulator< T >inline
add(S x)stan::math::accumulator< T >inline
add(const S &x)stan::math::accumulator< T >inline
add(const Eigen::Matrix< S, R, C > &m)stan::math::accumulator< T >inline
add(const std::vector< S > &xs)stan::math::accumulator< T >inline
sum() const stan::math::accumulator< T >inline
~accumulator()stan::math::accumulator< T >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1accumulator.html b/doc/api/html/classstan_1_1math_1_1accumulator.html new file mode 100644 index 00000000000..1104da602c6 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1accumulator.html @@ -0,0 +1,438 @@ + + + + + + +Stan Math Library: stan::math::accumulator< T > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::accumulator< T > Class Template Reference
+
+
+ +

Class to accumulate values and eventually return their sum. + More...

+ +

#include <accumulator.hpp>

+ + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 accumulator ()
 Construct an accumulator. More...
 
 ~accumulator ()
 Destroy an accumulator. More...
 
template<typename S >
boost::enable_if< boost::is_arithmetic< S >, void >::type add (S x)
 Add the specified arithmetic type value to the buffer after static casting it to the class type T. More...
 
template<typename S >
boost::disable_if< boost::is_arithmetic< S >, typename boost::enable_if< boost::is_same< S, T >, void >::type >::type add (const S &x)
 Add the specified non-arithmetic value to the buffer. More...
 
template<typename S , int R, int C>
void add (const Eigen::Matrix< S, R, C > &m)
 Add each entry in the specified matrix, vector, or row vector of values to the buffer. More...
 
template<typename S >
void add (const std::vector< S > &xs)
 Recursively add each entry in the specified standard vector to the buffer. More...
 
sum () const
 Return the sum of the accumulated values. More...
 
+

Detailed Description

+

template<typename T>
+class stan::math::accumulator< T >

+ +

Class to accumulate values and eventually return their sum.

+

If no values are ever added, the return value is 0.

+

This class is useful for speeding up auto-diff of long sums because it uses the sum() operation (either from stan::math or one defined by argument-dependent lookup.

+
Template Parameters
+ + +
TType of scalar added
+
+
+ +

Definition at line 25 of file accumulator.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + +
stan::math::accumulator< T >::accumulator ()
+
+inline
+
+ +

Construct an accumulator.

+ +

Definition at line 33 of file accumulator.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + +
stan::math::accumulator< T >::~accumulator ()
+
+inline
+
+ +

Destroy an accumulator.

+ +

Definition at line 40 of file accumulator.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T>
+
+template<typename S >
+ + + + + +
+ + + + + + + + +
boost::enable_if<boost::is_arithmetic<S>, void>::type stan::math::accumulator< T >::add (x)
+
+inline
+
+ +

Add the specified arithmetic type value to the buffer after static casting it to the class type T.

+

See the Boost doc for boost::is_arithmetic for information on what counts as an arithmetic type.

+
Template Parameters
+ + +
SType of argument
+
+
+
Parameters
+ + +
xValue to add
+
+
+ +

Definition at line 54 of file accumulator.hpp.

+ +
+
+ +
+
+
+template<typename T>
+
+template<typename S >
+ + + + + +
+ + + + + + + + +
boost::disable_if<boost::is_arithmetic<S>, typename boost::enable_if<boost::is_same<S, T>, void>::type >::type stan::math::accumulator< T >::add (const S & x)
+
+inline
+
+ +

Add the specified non-arithmetic value to the buffer.

+

This function is disabled if the type S is arithmetic or if it's not the same as T.

+

See the Boost doc for boost::is_arithmetic for information on what counts as an arithmetic type.

+
Template Parameters
+ + +
SType of argument
+
+
+
Parameters
+ + +
xValue to add
+
+
+ +

Definition at line 74 of file accumulator.hpp.

+ +
+
+ +
+
+
+template<typename T>
+
+template<typename S , int R, int C>
+ + + + + +
+ + + + + + + + +
void stan::math::accumulator< T >::add (const Eigen::Matrix< S, R, C > & m)
+
+inline
+
+ +

Add each entry in the specified matrix, vector, or row vector of values to the buffer.

+
Template Parameters
+ + + + +
Stype of values in matrix
Rnumber of rows in matrix
Cnumber of columns in matrix
+
+
+
Parameters
+ + +
mMatrix of values to add
+
+
+ +

Definition at line 88 of file accumulator.hpp.

+ +
+
+ +
+
+
+template<typename T>
+
+template<typename S >
+ + + + + +
+ + + + + + + + +
void stan::math::accumulator< T >::add (const std::vector< S > & xs)
+
+inline
+
+ +

Recursively add each entry in the specified standard vector to the buffer.

+

This will allow vectors of primitives, auto-diff variables to be added; if the vector entries are collections, their elements are recursively added.

+
Template Parameters
+ + +
SType of value to recursively add.
+
+
+
Parameters
+ + +
xsVector of entries to add
+
+
+ +

Definition at line 103 of file accumulator.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + +
T stan::math::accumulator< T >::sum () const
+
+inline
+
+ +

Return the sum of the accumulated values.

+
Returns
Sum of accumulated values.
+ +

Definition at line 113 of file accumulator.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1chainable__alloc-members.html b/doc/api/html/classstan_1_1math_1_1chainable__alloc-members.html new file mode 100644 index 00000000000..79abafaac51 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1chainable__alloc-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::chainable_alloc Member List
+
+
+ +

This is the complete list of members for stan::math::chainable_alloc, including all inherited members.

+ + + +
chainable_alloc()stan::math::chainable_allocinline
~chainable_alloc()stan::math::chainable_allocinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1chainable__alloc.html b/doc/api/html/classstan_1_1math_1_1chainable__alloc.html new file mode 100644 index 00000000000..f6849e98d7a --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1chainable__alloc.html @@ -0,0 +1,195 @@ + + + + + + +Stan Math Library: stan::math::chainable_alloc Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::chainable_alloc Class Reference
+
+
+ +

A chainable_alloc is an object which is constructed and destructed normally but the memory lifespan is managed along with the arena allocator for the gradient calculation. + More...

+ +

#include <chainable_alloc.hpp>

+
+Inheritance diagram for stan::math::chainable_alloc:
+
+
+ + +stan::math::LDLT_alloc< R, C > + +
+ + + + + + +

+Public Member Functions

 chainable_alloc ()
 
virtual ~chainable_alloc ()
 
+

Detailed Description

+

A chainable_alloc is an object which is constructed and destructed normally but the memory lifespan is managed along with the arena allocator for the gradient calculation.

+

A chainable_alloc instance must be created with a call to operator new for memory management.

+ +

Definition at line 16 of file chainable_alloc.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + +
stan::math::chainable_alloc::chainable_alloc ()
+
+inline
+
+ +

Definition at line 18 of file chainable_alloc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
virtual stan::math::chainable_alloc::~chainable_alloc ()
+
+inlinevirtual
+
+ +

Definition at line 21 of file chainable_alloc.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1chainable__alloc.png b/doc/api/html/classstan_1_1math_1_1chainable__alloc.png new file mode 100644 index 0000000000000000000000000000000000000000..a84b08a88b9e84962d583f1b18c83ab0a98a0f40 GIT binary patch literal 720 zcmeAS@N?(olHy`uVBq!ia0vp^yMZ`>gBeJco&6#Sq$C1-LR|m<{|{uoc=NTi|Ih>= z3ycpOIKbL@M;^%KC<*clW&kPzfvcxNj2IZ0;yqm)Ln;{G&VAkYSb@il-|f|J`%l|E z70jkDnR~a2{p8{r*@xVg4Tb+E1$lLMv20klNA@%X}A~zPOQj%dG1@mRl^VOXD_{ zJEoo5`(jqtZ|iTXou$vz9K6TM`}W(3|6PAKJ-C-R-_YvH??B^p@l3Ul*ab0nj^%hg z$??5aa54SdkMqBI4lw=FeRI24Hedfhz{d9s|G3H+>RGKD_Q&1tm=Y8f#Bl#Ib3&l* znST{)xc3|U7Osu_G4A5Y zy>E)(L{-r@N=iVR1O@9&-*~z_i92r~T*-6k^?RB8!*>fNYAZdHe8Q9V^ZT2p%dOZy z-`!MRxp!%5y>4#w{e364NM@B)CiiCic{RUnGtcoOzd!W}OU>;*JA2)hP49!Jb@ng4 zlCBI4!T)@_PhD+}N_f9<_13Ji&5ds_N*`+c-&;F>gSkuW-tuCR=Cw16W)**X^@nly zIny_7SAA^O%~X!NfAwT$-}cwV-y+X$`CS+O{_no?+8>?2WzPSZxi|XsihKRDEO&c+ zR=X;9>gd(-onPkPvMpI0Ui)m%$L+Pp;ur-dy6yk5yXyDa!UXyHI9C_F()k~{zsI^f t2|B2!^k{v8xZua@kKR~5-?Qu=1A~)#rhm)SSHR@Q;OXk;vd$@?2>^+hX2Jjf literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1cholesky__decompose__v__vari-members.html b/doc/api/html/classstan_1_1math_1_1cholesky__decompose__v__vari-members.html new file mode 100644 index 00000000000..06f1bf6ea6c --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1cholesky__decompose__v__vari-members.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
+
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+ +
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+
+
+
stan::math::cholesky_decompose_v_vari Member List
+
+
+ +

This is the complete list of members for stan::math::cholesky_decompose_v_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
adj_stan::math::vari
chain()stan::math::cholesky_decompose_v_variinlinevirtual
cholesky_decompose_v_vari(const Eigen::Matrix< var,-1,-1 > &A, const Eigen::Matrix< double,-1,-1 > &L_A)stan::math::cholesky_decompose_v_variinline
init_dependent()stan::math::variinline
M_stan::math::cholesky_decompose_v_vari
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
variRefA_stan::math::cholesky_decompose_v_vari
variRefL_stan::math::cholesky_decompose_v_vari
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1cholesky__decompose__v__vari.html b/doc/api/html/classstan_1_1math_1_1cholesky__decompose__v__vari.html new file mode 100644 index 00000000000..61d97eeb44b --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1cholesky__decompose__v__vari.html @@ -0,0 +1,293 @@ + + + + + + +Stan Math Library: stan::math::cholesky_decompose_v_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::cholesky_decompose_v_vari Class Reference
+
+
+ +

#include <cholesky_decompose.hpp>

+
+Inheritance diagram for stan::math::cholesky_decompose_v_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 cholesky_decompose_v_vari (const Eigen::Matrix< var,-1,-1 > &A, const Eigen::Matrix< double,-1,-1 > &L_A)
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + + + + + + + + +

+Public Attributes

int M_
 
vari ** variRefA_
 
vari ** variRefL_
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+ + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
+

Detailed Description

+
+

Definition at line 18 of file cholesky_decompose.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::cholesky_decompose_v_vari::cholesky_decompose_v_vari (const Eigen::Matrix< var,-1,-1 > & A,
const Eigen::Matrix< double,-1,-1 > & L_A 
)
+
+inline
+
+ +

Definition at line 41 of file cholesky_decompose.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
virtual void stan::math::cholesky_decompose_v_vari::chain ()
+
+inlinevirtual
+
+ +

Apply the chain rule to this variable based on the variables on which it depends.

+

The base implementation in this class is a no-op.

+ +

Reimplemented from stan::math::vari.

+ +

Definition at line 78 of file cholesky_decompose.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + +
int stan::math::cholesky_decompose_v_vari::M_
+
+ +

Definition at line 20 of file cholesky_decompose.hpp.

+ +
+
+ +
+
+ + + + +
vari** stan::math::cholesky_decompose_v_vari::variRefA_
+
+ +

Definition at line 21 of file cholesky_decompose.hpp.

+ +
+
+ +
+
+ + + + +
vari** stan::math::cholesky_decompose_v_vari::variRefL_
+
+ +

Definition at line 22 of file cholesky_decompose.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1cholesky__decompose__v__vari.png b/doc/api/html/classstan_1_1math_1_1cholesky__decompose__v__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..761ee2ee31e1dc640dee4fa02f542c5fa4fb33ee GIT binary patch literal 729 zcmeAS@N?(olHy`uVBq!ia0vp^Z-F>~gBeI3I?f~pq$C1-LR|m<{|{uoc=NTi|Ih>= z3ycpOIKbL@M;^%KC<*clW&kPzfvcxNj2IZ0GCW-zLn;{G&V9YZHY326|Y@StXR^L`WudeKQ zN%&V;l&6*d^2=?~hrSgqjofb(`|P%jRdvvu=(UqdW}REsYr&bNy6Sn@wo^B5pRRL% zk-z@QjM!5fPwn}ueakU-{hGDDlm12LuY3~IcYMq2jjCQ#rPtOsep{e*Jk@U5TUF2J zFWx@?rh043*7~)RypO+C@K!xucBklh^8GJHo>rdkcjl|UlzzHpQcAF&wx=1GarvU& z=}l*p8saaoCP?|ZR_{F1VlDbsv`p#F&Wye4%n?&BGu@a%Jl+$n*kaJj!7%wmCS%Si zAYQe&R_O05vrjqCtNIt;nEzw0bvsF14SP({arKVbMat)|ax z*YX=P%i^0(zSq1Zvqt;ruP@63<7)0KZQFP}_1~d;VS?L|O>W%|oYCC#&9}(q_Um^$ zYp0fl6g}P(ed}@Y?tDR(QwKU7UF^a3CtDbRvA|$f hx_hTHN21VQ=AvGsos$(mZv&=722WQ%mvv4FO#mW3Yy + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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+ + +
+ +
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+
+
+
stan::math::container_view< T1, T2 > Member List
+
+
+ +

This is the complete list of members for stan::math::container_view< T1, T2 >, including all inherited members.

+ + + +
container_view(const T1 &x, T2 *y)stan::math::container_view< T1, T2 >inline
operator[](int i)stan::math::container_view< T1, T2 >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view.html b/doc/api/html/classstan_1_1math_1_1container__view.html new file mode 100644 index 00000000000..0f9e5752d4f --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view.html @@ -0,0 +1,231 @@ + + + + + + +Stan Math Library: stan::math::container_view< T1, T2 > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::container_view< T1, T2 > Class Template Reference
+
+
+ +

Primary template class for container view of array y with same structure as T1 and size as x. + More...

+ +

#include <container_view.hpp>

+ + + + + + + + +

+Public Member Functions

 container_view (const T1 &x, T2 *y)
 Constructor. More...
 
T2 & operator[] (int i)
 operator[](int i) returns reference to view, indexed by i Specialization handle appropriate broadcasting if size of x is 1 More...
 
+

Detailed Description

+

template<typename T1, typename T2>
+class stan::math::container_view< T1, T2 >

+ +

Primary template class for container view of array y with same structure as T1 and size as x.

+
Template Parameters
+ + + +
T1type of view.
T2type of scalar returned by view.
+
+
+ +

Definition at line 22 of file container_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::container_view< T1, T2 >::container_view (const T1 & x,
T2 * y 
)
+
+inline
+
+ +

Constructor.

+
Parameters
+ + + +
xobject from which size is to be inferred
yunderlying array
+
+
+ +

Definition at line 30 of file container_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + +
T2& stan::math::container_view< T1, T2 >::operator[] (int i)
+
+inline
+
+ +

operator[](int i) returns reference to view, indexed by i Specialization handle appropriate broadcasting if size of x is 1

+
Parameters
+ + +
iindex
+
+
+ +

Definition at line 40 of file container_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_ei01a1980462c3df2fa39d131bf0f86062.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_ei01a1980462c3df2fa39d131bf0f86062.html new file mode 100644 index 00000000000..c920c103c15 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_ei01a1980462c3df2fa39d131bf0f86062.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eif0a5cd6c4f7572d0a0485f479012b4cf.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eif0a5cd6c4f7572d0a0485f479012b4cf.html new file mode 100644 index 00000000000..14ed3c4f3f0 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eif0a5cd6c4f7572d0a0485f479012b4cf.html @@ -0,0 +1,233 @@ + + + + + + +Stan Math Library: stan::math::container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > > Class Template Reference
+
+
+ +

Template specialization for Eigen::Map view of array with scalar type T2 with size inferred from input Eigen::Matrix. + More...

+ +

#include <container_view.hpp>

+ + + + + + + + +

+Public Member Functions

 container_view (const Eigen::Matrix< T1, R, C > &x, T2 *y)
 Initialize Map dimensions with input matrix dimensions. More...
 
Eigen::Map< Eigen::Matrix< T2, R, C > > & operator[] (int i)
 operator[](int i) returns Eigen::Map y More...
 
+

Detailed Description

+

template<typename T1, typename T2, int R, int C>
+class stan::math::container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >

+ +

Template specialization for Eigen::Map view of array with scalar type T2 with size inferred from input Eigen::Matrix.

+
Template Parameters
+ + + + + +
T1scalar type of input matrix
T2scalar type of view.
Rrows of input matrix and view
Ccolumns of input matrix and view
+
+
+ +

Definition at line 23 of file container_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >::container_view (const Eigen::Matrix< T1, R, C > & x,
T2 * y 
)
+
+inline
+
+ +

Initialize Map dimensions with input matrix dimensions.

+
Parameters
+ + + +
xinput matrix
yunderlying array
+
+
+ +

Definition at line 32 of file container_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Map<Eigen::Matrix<T2, R, C> >& stan::math::container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >::operator[] (int i)
+
+inline
+
+ +

operator[](int i) returns Eigen::Map y

+
Parameters
+ + +
iindex
+
+
+ +

Definition at line 40 of file container_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_t2_01_4-members.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_t2_01_4-members.html new file mode 100644 index 00000000000..fcfc60128c0 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_t2_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 > Member List
+
+
+ +

This is the complete list of members for stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 >, including all inherited members.

+ + + +
container_view(const Eigen::Matrix< T1, R, C > &x, T2 *y)stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 >inline
operator[](int i)stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_t2_01_4.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_t2_01_4.html new file mode 100644 index 00000000000..785ab7173dd --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_t2_01_4.html @@ -0,0 +1,227 @@ + + + + + + +Stan Math Library: stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 > Class Template Reference
+
+
+ +

Template specialization for scalar view of array y with scalar type T2. + More...

+ +

#include <container_view.hpp>

+ + + + + + + + +

+Public Member Functions

 container_view (const Eigen::Matrix< T1, R, C > &x, T2 *y)
 Constructor. More...
 
T2 & operator[] (int i)
 operator[](int i) returns reference to scalar of type T2 at appropriate index i in array y More...
 
+

Detailed Description

+

template<typename T1, typename T2, int R, int C>
+class stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 >

+ +

Template specialization for scalar view of array y with scalar type T2.

+
Template Parameters
+ + + + + +
T1scalar type of input matrix
T2scalar type returned by view.
Rrows of input matrix and view
Ccolumns of input matrix and view
+
+
+ +

Definition at line 58 of file container_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 >::container_view (const Eigen::Matrix< T1, R, C > & x,
T2 * y 
)
+
+inline
+
+ +

Constructor.

+
Parameters
+ + + +
xinput matrix
yunderlying array
+
+
+ +

Definition at line 66 of file container_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + +
T2& stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 >::operator[] (int i)
+
+inline
+
+ +

operator[](int i) returns reference to scalar of type T2 at appropriate index i in array y

+ +

Definition at line 73 of file container_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01dummy_00_01_t2_01_4-members.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01dummy_00_01_t2_01_4-members.html new file mode 100644 index 00000000000..3d5835e7ef9 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01dummy_00_01_t2_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::container_view< dummy, T2 > Member List
+
+
+ +

This is the complete list of members for stan::math::container_view< dummy, T2 >, including all inherited members.

+ + + + +
container_view(const T1 &x, scalar_t *y)stan::math::container_view< dummy, T2 >inline
operator[](int n) const stan::math::container_view< dummy, T2 >inline
scalar_t typedefstan::math::container_view< dummy, T2 >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01dummy_00_01_t2_01_4.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01dummy_00_01_t2_01_4.html new file mode 100644 index 00000000000..dd24ab75ab0 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01dummy_00_01_t2_01_4.html @@ -0,0 +1,256 @@ + + + + + + +Stan Math Library: stan::math::container_view< dummy, T2 > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::container_view< dummy, T2 > Class Template Reference
+
+
+ +

Dummy type specialization, used in conjunction with struct dummy as described above. + More...

+ +

#include <container_view.hpp>

+ + + + +

+Public Types

typedef stan::scalar_type< T2 >::type scalar_t
 
+ + + + + + + + +

+Public Member Functions

template<typename T1 >
 container_view (const T1 &x, scalar_t *y)
 Nothing initialized. More...
 
scalar_t operator[] (int n) const
 operator[](int i) throws exception More...
 
+

Detailed Description

+

template<typename T2>
+class stan::math::container_view< dummy, T2 >

+ +

Dummy type specialization, used in conjunction with struct dummy as described above.

+
Template Parameters
+ + +
T2type of scalar returned by view
+
+
+ +

Definition at line 63 of file container_view.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T2 >
+ + + + +
typedef stan::scalar_type<T2>::type stan::math::container_view< dummy, T2 >::scalar_t
+
+ +

Definition at line 65 of file container_view.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T2 >
+
+template<typename T1 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::container_view< dummy, T2 >::container_view (const T1 & x,
scalar_ty 
)
+
+inline
+
+ +

Nothing initialized.

+
Parameters
+ + + +
xinput object
yunderlying array
+
+
+ +

Definition at line 74 of file container_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T2 >
+ + + + + +
+ + + + + + + + +
scalar_t stan::math::container_view< dummy, T2 >::operator[] (int n) const
+
+inline
+
+ +

operator[](int i) throws exception

+
Parameters
+ + +
nindex
+
+
+ +

Definition at line 82 of file container_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_293fc31514b48bf553261266d6061c13.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_293fc31514b48bf553261266d6061c13.html new file mode 100644 index 00000000000..c4a01ad8cc1 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_293fc31514b48bf553261266d6061c13.html @@ -0,0 +1,228 @@ + + + + + + +Stan Math Library: stan::math::container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > > Class Template Reference
+
+
+ +

Template specialization for matrix view of array y with scalar type T2 with shape equal to x. + More...

+ +

#include <container_view.hpp>

+ + + + + + + + +

+Public Member Functions

 container_view (const std::vector< Eigen::Matrix< T1, R, C > > &x, T2 *y)
 Constructor assumes all matrix elements in std::vector are of same dimension. More...
 
Eigen::Map< Eigen::Matrix< T2, R, C > > & operator[] (int i)
 operator[](int i) returns matrix view of scalartype T2 at appropriate index i in array y More...
 
+

Detailed Description

+

template<typename T1, typename T2, int R, int C>
+class stan::math::container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > >

+ +

Template specialization for matrix view of array y with scalar type T2 with shape equal to x.

+
Template Parameters
+ + + + + +
T1scalar type of input vector of matrices
T2scalar type of matrix view
Rrows of input matrix and view
Ccolumns of input matrix and view
+
+
+ +

Definition at line 91 of file container_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > >::container_view (const std::vector< Eigen::Matrix< T1, R, C > > & x,
T2 * y 
)
+
+inline
+
+ +

Constructor assumes all matrix elements in std::vector are of same dimension.

+

Initializes y_view as 1x1 matrix because no nullary constructor for Eigen::Map

+
Parameters
+ + + +
xinput matrix
yunderlying array
+
+
+ +

Definition at line 104 of file container_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Map<Eigen::Matrix<T2, R, C> >& stan::math::container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > >::operator[] (int i)
+
+inline
+
+ +

operator[](int i) returns matrix view of scalartype T2 at appropriate index i in array y

+ +

Definition at line 119 of file container_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_d59ff4398db754b230f0577ac690f39e.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_d59ff4398db754b230f0577ac690f39e.html new file mode 100644 index 00000000000..995491f683b --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_d59ff4398db754b230f0577ac690f39e.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_t1_01_4_00_01_t2_01_4-members.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_t1_01_4_00_01_t2_01_4-members.html new file mode 100644 index 00000000000..4073a6297ed --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_t1_01_4_00_01_t2_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::container_view< std::vector< T1 >, T2 > Member List
+
+
+ +

This is the complete list of members for stan::math::container_view< std::vector< T1 >, T2 >, including all inherited members.

+ + + +
container_view(const std::vector< T1 > &x, T2 *y)stan::math::container_view< std::vector< T1 >, T2 >inline
operator[](int i)stan::math::container_view< std::vector< T1 >, T2 >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_t1_01_4_00_01_t2_01_4.html b/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_t1_01_4_00_01_t2_01_4.html new file mode 100644 index 00000000000..3f63be9eb07 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1container__view_3_01std_1_1vector_3_01_t1_01_4_00_01_t2_01_4.html @@ -0,0 +1,231 @@ + + + + + + +Stan Math Library: stan::math::container_view< std::vector< T1 >, T2 > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::container_view< std::vector< T1 >, T2 > Class Template Reference
+
+
+ +

Template specialization for scalar view of array y with scalar type T2 with proper indexing inferred from input vector x of scalar type T1. + More...

+ +

#include <container_view.hpp>

+ + + + + + + + +

+Public Member Functions

 container_view (const std::vector< T1 > &x, T2 *y)
 Constructor. More...
 
T2 & operator[] (int i)
 operator[](int i) returns reference to scalar view indexed at i More...
 
+

Detailed Description

+

template<typename T1, typename T2>
+class stan::math::container_view< std::vector< T1 >, T2 >

+ +

Template specialization for scalar view of array y with scalar type T2 with proper indexing inferred from input vector x of scalar type T1.

+
Template Parameters
+ + + +
T1scalar type of input vector
T2scalar type returned by view.
+
+
+ +

Definition at line 20 of file container_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::container_view< std::vector< T1 >, T2 >::container_view (const std::vector< T1 > & x,
T2 * y 
)
+
+inline
+
+ +

Constructor.

+
Parameters
+ + + +
xinput vector
yunderlying array
+
+
+ +

Definition at line 28 of file container_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + +
T2& stan::math::container_view< std::vector< T1 >, T2 >::operator[] (int i)
+
+inline
+
+ +

operator[](int i) returns reference to scalar view indexed at i

+
Parameters
+ + +
iindex of scalar element
+
+
+ +

Definition at line 37 of file container_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01double_01_4-members.html b/doc/api/html/classstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01double_01_4-members.html new file mode 100644 index 00000000000..8a5c66eb525 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01double_01_4-members.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::coupled_ode_system< F, double, double > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01double_01_4.html b/doc/api/html/classstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01double_01_4.html new file mode 100644 index 00000000000..aa75a90ae33 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01double_01_4.html @@ -0,0 +1,559 @@ + + + + + + +Stan Math Library: stan::math::coupled_ode_system< F, double, double > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::coupled_ode_system< F, double, double > Class Template Reference
+
+
+ +

The coupled ode system for known initial values and known parameters. + More...

+ +

#include <coupled_ode_system.hpp>

+ + + + + + + + + + + + + + + + + +

+Public Member Functions

 coupled_ode_system (const F &f, const std::vector< double > &y0, const std::vector< double > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
 Construct the coupled ODE system from the base system function, initial state, parameters, data and a stream for messages. More...
 
void operator() (const std::vector< double > &y, std::vector< double > &dy_dt, double t)
 Calculates the derivative of the coupled ode system with respect to the specified state at the specified time using the system state function. More...
 
int size () const
 Returns the size of the coupled system. More...
 
std::vector< double > initial_state ()
 Returns the initial state of the coupled system, which is identical to the base ODE original state in this implementation because the initial state is known. More...
 
std::vector< std::vector< double > > decouple_states (const std::vector< std::vector< double > > &y)
 Returns the base portion of the coupled state. More...
 
+ + + + + + + + + + + + + + + + + + + +

+Public Attributes

const F & f_
 
const std::vector< double > & y0_dbl_
 
const std::vector< double > & theta_dbl_
 
const std::vector< double > & x_
 
const std::vector< int > & x_int_
 
const size_t N_
 
const size_t M_
 
const size_t size_
 
std::ostream * msgs_
 
+

Detailed Description

+

template<typename F>
+class stan::math::coupled_ode_system< F, double, double >

+ +

The coupled ode system for known initial values and known parameters.

+

This coupled system does not add anything to the base system used to construct it, but is here for generality of the integration implementation.

+
Template Parameters
+ + +
Ftype of system function for the base ODE system.
+
+
+ +

Definition at line 39 of file coupled_ode_system.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::coupled_ode_system< F, double, double >::coupled_ode_system (const F & f,
const std::vector< double > & y0,
const std::vector< double > & theta,
const std::vector< double > & x,
const std::vector< int > & x_int,
std::ostream * msgs 
)
+
+inline
+
+ +

Construct the coupled ODE system from the base system function, initial state, parameters, data and a stream for messages.

+
Parameters
+ + + + + + + +
[in]fbase ode system functor.
[in]y0initial state of the base ode.
[in]thetaparameters of the base ode.
[in]xreal data.
[in]x_intinteger data.
[in,out]msgsprint stream.
+
+
+ +

Definition at line 63 of file coupled_ode_system.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + +
std::vector<std::vector<double> > stan::math::coupled_ode_system< F, double, double >::decouple_states (const std::vector< std::vector< double > > & y)
+
+inline
+
+ +

Returns the base portion of the coupled state.

+

In this class's implementation, the coupled system is equivalent to the base system, so this function just returns its input.

+
Parameters
+ + +
ythe vector of the coupled states after solving the ode
+
+
+
Returns
the decoupled states
+ +

Definition at line 143 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + +
std::vector<double> stan::math::coupled_ode_system< F, double, double >::initial_state ()
+
+inline
+
+ +

Returns the initial state of the coupled system, which is identical to the base ODE original state in this implementation because the initial state is known.

+

The return value is a vector of length size() where the first N (base ode system size) parameters are the initial conditions of the base ode system and the rest of the initial conditions is 0.

+
Returns
initial state of the coupled system
+ +

Definition at line 125 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::coupled_ode_system< F, double, double >::operator() (const std::vector< double > & y,
std::vector< double > & dy_dt,
double t 
)
+
+inline
+
+ +

Calculates the derivative of the coupled ode system with respect to the specified state at the specified time using the system state function.

+

The derivative vector created is the same length as the length as the state vector.

+
Parameters
+ + + + +
[in]ycurrent state of the coupled ode.
[out]dy_dtpopulated with derivatives of the coupled system evaluated at specified state and time.
[in]ttime.
+
+
+
Exceptions
+ + +
exceptionif the system function does not return a derivative vector of the same size as the state vector.
+
+
+ +

Definition at line 95 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + +
int stan::math::coupled_ode_system< F, double, double >::size () const
+
+inline
+
+ +

Returns the size of the coupled system.

+
Returns
size of the coupled system.
+ +

Definition at line 109 of file coupled_ode_system.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename F >
+ + + + +
const F& stan::math::coupled_ode_system< F, double, double >::f_
+
+ +

Definition at line 41 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, double, double >::M_
+
+ +

Definition at line 47 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
std::ostream* stan::math::coupled_ode_system< F, double, double >::msgs_
+
+ +

Definition at line 49 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, double, double >::N_
+
+ +

Definition at line 46 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, double, double >::size_
+
+ +

Definition at line 48 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<double>& stan::math::coupled_ode_system< F, double, double >::theta_dbl_
+
+ +

Definition at line 43 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<double>& stan::math::coupled_ode_system< F, double, double >::x_
+
+ +

Definition at line 44 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<int>& stan::math::coupled_ode_system< F, double, double >::x_int_
+
+ +

Definition at line 45 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<double>& stan::math::coupled_ode_system< F, double, double >::y0_dbl_
+
+ +

Definition at line 42 of file coupled_ode_system.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1cvodes__ode__data-members.html b/doc/api/html/classstan_1_1math_1_1cvodes__ode__data-members.html new file mode 100644 index 00000000000..0b989a326d6 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1cvodes__ode__data-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::cvodes_ode_data< F, T_initial, T_param > Member List
+
+
+ +

This is the complete list of members for stan::math::cvodes_ode_data< F, T_initial, T_param >, including all inherited members.

+ + + + + +
cvodes_ode_data(const F &f, const std::vector< T_initial > &y0, const std::vector< T_param > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)stan::math::cvodes_ode_data< F, T_initial, T_param >inline
dense_jacobian(long int N, realtype t, N_Vector y, N_Vector fy, DlsMat J, void *user_data, N_Vector tmp1, N_Vector tmp2, N_Vector tmp3)stan::math::cvodes_ode_data< F, T_initial, T_param >inlinestatic
ode_rhs(double t, N_Vector y, N_Vector ydot, void *user_data)stan::math::cvodes_ode_data< F, T_initial, T_param >inlinestatic
ode_rhs_sens(int Ns, realtype t, N_Vector y, N_Vector ydot, N_Vector *yS, N_Vector *ySdot, void *user_data, N_Vector tmp1, N_Vector tmp2)stan::math::cvodes_ode_data< F, T_initial, T_param >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1cvodes__ode__data.html b/doc/api/html/classstan_1_1math_1_1cvodes__ode__data.html new file mode 100644 index 00000000000..8f1e5f4de0a --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1cvodes__ode__data.html @@ -0,0 +1,442 @@ + + + + + + +Stan Math Library: stan::math::cvodes_ode_data< F, T_initial, T_param > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::cvodes_ode_data< F, T_initial, T_param > Class Template Reference
+
+
+ +

CVODES ode data holder object which is used during CVODES integration for CVODES callbacks. + More...

+ +

#include <cvodes_ode_data.hpp>

+ + + + + +

+Public Member Functions

 cvodes_ode_data (const F &f, const std::vector< T_initial > &y0, const std::vector< T_param > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
 Construct CVODES ode data object to enable callbacks from CVODES during ODE integration. More...
 
+ + + + + + + +

+Static Public Member Functions

static int ode_rhs (double t, N_Vector y, N_Vector ydot, void *user_data)
 
static int ode_rhs_sens (int Ns, realtype t, N_Vector y, N_Vector ydot, N_Vector *yS, N_Vector *ySdot, void *user_data, N_Vector tmp1, N_Vector tmp2)
 
static int dense_jacobian (long int N, realtype t, N_Vector y, N_Vector fy, DlsMat J, void *user_data, N_Vector tmp1, N_Vector tmp2, N_Vector tmp3)
 
+

Detailed Description

+

template<typename F, typename T_initial, typename T_param>
+class stan::math::cvodes_ode_data< F, T_initial, T_param >

+ +

CVODES ode data holder object which is used during CVODES integration for CVODES callbacks.

+
Template Parameters
+ + + + +
Ftype of functor for the base ode system.
T_initialtype of initial values
T_paramtype of parameters
+
+
+ +

Definition at line 27 of file cvodes_ode_data.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename F , typename T_initial , typename T_param >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::cvodes_ode_data< F, T_initial, T_param >::cvodes_ode_data (const F & f,
const std::vector< T_initial > & y0,
const std::vector< T_param > & theta,
const std::vector< double > & x,
const std::vector< int > & x_int,
std::ostream * msgs 
)
+
+inline
+
+ +

Construct CVODES ode data object to enable callbacks from CVODES during ODE integration.

+

Static callbacks are defined for the ODE RHS (ode_rhs), the ODE sensitivity RHS (ode_rhs_sens) and for the ODE Jacobian wrt to the states (dense_jacobian).

+
Parameters
+ + + + + + + +
[in]fode functor.
[in]y0initial state of the base ode.
[in]thetaparameters of the base ode.
[in]xcontinuous data vector for the ODE.
[in]x_intinteger data vector for the ODE.
[in]msgsstream to which messages are printed.
+
+
+ +

Definition at line 53 of file cvodes_ode_data.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F , typename T_initial , typename T_param >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static int stan::math::cvodes_ode_data< F, T_initial, T_param >::dense_jacobian (long int N,
realtype t,
N_Vector y,
N_Vector fy,
DlsMat J,
void * user_data,
N_Vector tmp1,
N_Vector tmp2,
N_Vector tmp3 
)
+
+inlinestatic
+
+ +

Definition at line 85 of file cvodes_ode_data.hpp.

+ +
+
+ +
+
+
+template<typename F , typename T_initial , typename T_param >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static int stan::math::cvodes_ode_data< F, T_initial, T_param >::ode_rhs (double t,
N_Vector y,
N_Vector ydot,
void * user_data 
)
+
+inlinestatic
+
+ +

Definition at line 66 of file cvodes_ode_data.hpp.

+ +
+
+ +
+
+
+template<typename F , typename T_initial , typename T_param >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static int stan::math::cvodes_ode_data< F, T_initial, T_param >::ode_rhs_sens (int Ns,
realtype t,
N_Vector y,
N_Vector ydot,
N_Vector * yS,
N_Vector * ySdot,
void * user_data,
N_Vector tmp1,
N_Vector tmp2 
)
+
+inlinestatic
+
+ +

Definition at line 73 of file cvodes_ode_data.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1gevv__vvv__vari-members.html b/doc/api/html/classstan_1_1math_1_1gevv__vvv__vari-members.html new file mode 100644 index 00000000000..4bf6d861e0d --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1gevv__vvv__vari-members.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::gevv_vvv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::gevv_vvv_vari, including all inherited members.

+ + + + + + + + + + + + + + + + + + + +
adj_stan::math::vari
alpha_stan::math::gevv_vvv_variprotected
chain()stan::math::gevv_vvv_variinlinevirtual
dotval_stan::math::gevv_vvv_variprotected
eval_gevv(const stan::math::var *alpha, const stan::math::var *v1, int stride1, const stan::math::var *v2, int stride2, size_t length, double *dotprod)stan::math::gevv_vvv_variinlineprotectedstatic
gevv_vvv_vari(const stan::math::var *alpha, const stan::math::var *v1, int stride1, const stan::math::var *v2, int stride2, size_t length)stan::math::gevv_vvv_variinline
init_dependent()stan::math::variinline
length_stan::math::gevv_vvv_variprotected
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
v1_stan::math::gevv_vvv_variprotected
v2_stan::math::gevv_vvv_variprotected
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~gevv_vvv_vari()stan::math::gevv_vvv_variinlinevirtual
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1gevv__vvv__vari.html b/doc/api/html/classstan_1_1math_1_1gevv__vvv__vari.html new file mode 100644 index 00000000000..64bab0ba42a --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1gevv__vvv__vari.html @@ -0,0 +1,488 @@ + + + + + + +Stan Math Library: stan::math::gevv_vvv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+ +
+ +

#include <gevv_vvv_vari.hpp>

+
+Inheritance diagram for stan::math::gevv_vvv_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 gevv_vvv_vari (const stan::math::var *alpha, const stan::math::var *v1, int stride1, const stan::math::var *v2, int stride2, size_t length)
 
virtual ~gevv_vvv_vari ()
 
void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + +

+Static Protected Member Functions

static double eval_gevv (const stan::math::var *alpha, const stan::math::var *v1, int stride1, const stan::math::var *v2, int stride2, size_t length, double *dotprod)
 
+ + + + + + + + + + + +

+Protected Attributes

stan::math::varialpha_
 
stan::math::vari ** v1_
 
stan::math::vari ** v2_
 
double dotval_
 
size_t length_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 11 of file gevv_vvv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::gevv_vvv_vari::gevv_vvv_vari (const stan::math::varalpha,
const stan::math::varv1,
int stride1,
const stan::math::varv2,
int stride2,
size_t length 
)
+
+inline
+
+ +

Definition at line 30 of file gevv_vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
virtual stan::math::gevv_vvv_vari::~gevv_vvv_vari ()
+
+inlinevirtual
+
+ +

Definition at line 46 of file gevv_vvv_vari.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::gevv_vvv_vari::chain ()
+
+inlinevirtual
+
+ +

Apply the chain rule to this variable based on the variables on which it depends.

+

The base implementation in this class is a no-op.

+ +

Reimplemented from stan::math::vari.

+ +

Definition at line 47 of file gevv_vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static double stan::math::gevv_vvv_vari::eval_gevv (const stan::math::varalpha,
const stan::math::varv1,
int stride1,
const stan::math::varv2,
int stride2,
size_t length,
double * dotprod 
)
+
+inlinestaticprotected
+
+ +

Definition at line 18 of file gevv_vvv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
stan::math::vari* stan::math::gevv_vvv_vari::alpha_
+
+protected
+
+ +

Definition at line 13 of file gevv_vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::gevv_vvv_vari::dotval_
+
+protected
+
+ +

Definition at line 16 of file gevv_vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
size_t stan::math::gevv_vvv_vari::length_
+
+protected
+
+ +

Definition at line 17 of file gevv_vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
stan::math::vari** stan::math::gevv_vvv_vari::v1_
+
+protected
+
+ +

Definition at line 14 of file gevv_vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
stan::math::vari** stan::math::gevv_vvv_vari::v2_
+
+protected
+
+ +

Definition at line 15 of file gevv_vvv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1gevv__vvv__vari.png b/doc/api/html/classstan_1_1math_1_1gevv__vvv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..52a0d5d38c0bcea6fb74780c5184a4de1fe4c5b2 GIT binary patch literal 615 zcmeAS@N?(olHy`uVBq!ia0vp^^ME*jgBeKP-)Ykeq$C1-LR|m<{|{uoc=NTi|Ih>= z3ycpOIKbL@M;^%KC<*clW&kPzfvcxNj2IXgzj?YihEy=Vo%?p(Y6TJ2cGpYa>z}Od z_!PKy*W#Tj>FR#xFSZ(_GXM4NG3?_GoaA=&tIEl)*PfH6R#!PrIyZCH+^u_VT>gJ) z@)GWtYuuk_+&*qn^K0{~HBQmpdgpb{2WfdekGUFs?7W!g!n$cGt2UfJ-J>_HU%dRK zUU?Mn)m_`oOXHU2s(Bv2qxCLoVe($x9MK}f>0d$j1@0(M{bLgCtPecx7##_AUVV8rX}he*$7jpV?LWTHzWS@nJJIsF zkAU93b2a+X*2`tF+xfq5PAmL!_SU0!uR@R7&e$8=`gqOr=eKsRynd!)bHcuJU5npL zkJEz(h4sa%=TTpap1U7q-SGL8 + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::ode_system< F > Member List
+
+
+ +

This is the complete list of members for stan::math::ode_system< F >, including all inherited members.

+ + + + + +
jacobian(const double t, const std::vector< double > &y, Eigen::MatrixBase< Derived1 > &dy_dt, Eigen::MatrixBase< Derived2 > &Jy) const stan::math::ode_system< F >inline
jacobian(const double t, const std::vector< double > &y, Eigen::MatrixBase< Derived1 > &dy_dt, Eigen::MatrixBase< Derived2 > &Jy, Eigen::MatrixBase< Derived2 > &Jtheta) const stan::math::ode_system< F >inline
ode_system(const F &f, const std::vector< double > theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)stan::math::ode_system< F >inline
operator()(const double t, const std::vector< double > &y, std::vector< double > &dy_dt) const stan::math::ode_system< F >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1ode__system.html b/doc/api/html/classstan_1_1math_1_1ode__system.html new file mode 100644 index 00000000000..66df22daf76 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1ode__system.html @@ -0,0 +1,413 @@ + + + + + + +Stan Math Library: stan::math::ode_system< F > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::ode_system< F > Class Template Reference
+
+
+ +

Internal representation of an ODE model object which provides convenient Jacobian functions to obtain gradients wrt to states and parameters. + More...

+ +

#include <ode_system.hpp>

+ + + + + + + + + + + + + + + + +

+Public Member Functions

 ode_system (const F &f, const std::vector< double > theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
 Construct an ODE model with the specified base ODE system, parameters, data, and a message stream. More...
 
void operator() (const double t, const std::vector< double > &y, std::vector< double > &dy_dt) const
 Calculate the RHS of the ODE. More...
 
template<typename Derived1 , typename Derived2 >
void jacobian (const double t, const std::vector< double > &y, Eigen::MatrixBase< Derived1 > &dy_dt, Eigen::MatrixBase< Derived2 > &Jy) const
 Calculate the Jacobian of the ODE RHS wrt to states y. More...
 
template<typename Derived1 , typename Derived2 >
void jacobian (const double t, const std::vector< double > &y, Eigen::MatrixBase< Derived1 > &dy_dt, Eigen::MatrixBase< Derived2 > &Jy, Eigen::MatrixBase< Derived2 > &Jtheta) const
 Calculate the Jacobian of the ODE RHS wrt to states y and parameters theta. More...
 
+

Detailed Description

+

template<typename F>
+class stan::math::ode_system< F >

+ +

Internal representation of an ODE model object which provides convenient Jacobian functions to obtain gradients wrt to states and parameters.

+

Can be used to provide analytic Jacobians via partial template specialisation.

+
Template Parameters
+ + +
Ftype of functor for the base ode system.
+
+
+ +

Definition at line 21 of file ode_system.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename F>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::ode_system< F >::ode_system (const F & f,
const std::vector< double > theta,
const std::vector< double > & x,
const std::vector< int > & x_int,
std::ostream * msgs 
)
+
+inline
+
+ +

Construct an ODE model with the specified base ODE system, parameters, data, and a message stream.

+
Parameters
+ + + + + + +
[in]fthe base ODE system functor.
[in]thetaparameters of the ode.
[in]xreal data.
[in]x_intinteger data.
[in]msgsstream to which messages are printed.
+
+
+ +

Definition at line 39 of file ode_system.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F>
+
+template<typename Derived1 , typename Derived2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::ode_system< F >::jacobian (const double t,
const std::vector< double > & y,
Eigen::MatrixBase< Derived1 > & dy_dt,
Eigen::MatrixBase< Derived2 > & Jy 
) const
+
+inline
+
+ +

Calculate the Jacobian of the ODE RHS wrt to states y.

+

The function expects the output objects to have correct sizes, i.e. dy_dt must be length N and Jy a NxN matrix (N states).

+
Parameters
+ + + + + +
[in]ttime.
[in]ystate of the ode system at time t.
[out]dy_dtODE RHS
[out]JyJacobian of ODE RHS wrt to y.
+
+
+ +

Definition at line 67 of file ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F>
+
+template<typename Derived1 , typename Derived2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::ode_system< F >::jacobian (const double t,
const std::vector< double > & y,
Eigen::MatrixBase< Derived1 > & dy_dt,
Eigen::MatrixBase< Derived2 > & Jy,
Eigen::MatrixBase< Derived2 > & Jtheta 
) const
+
+inline
+
+ +

Calculate the Jacobian of the ODE RHS wrt to states y and parameters theta.

+

The function expects the output objects to have correct sizes, i.e. dy_dt must be length N, Jy a NxN matrix and Jtheta a NxM matrix (N states, M parameters).

+
Parameters
+ + + + + + +
[in]ttime.
[in]ystate of the ode system at time t.
[out]dy_dtODE RHS
[out]JyJacobian of ODE RHS wrt to y.
[out]JthetaJacobian of ODE RHS wrt to theta.
+
+
+ +

Definition at line 107 of file ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::ode_system< F >::operator() (const double t,
const std::vector< double > & y,
std::vector< double > & dy_dt 
) const
+
+inline
+
+ +

Calculate the RHS of the ODE.

+
Parameters
+ + + + +
[in]ttime.
[in]ystate of the ode system at time t.
[out]dy_dtODE RHS
+
+
+ +

Definition at line 51 of file ode_system.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__ddv__vari-members.html b/doc/api/html/classstan_1_1math_1_1op__ddv__vari-members.html new file mode 100644 index 00000000000..57893753df1 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__ddv__vari-members.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_ddv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_ddv_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
ad_stan::math::op_ddv_variprotected
adj_stan::math::vari
bd_stan::math::op_ddv_variprotected
chain()stan::math::variinlinevirtual
cvi_stan::math::op_ddv_variprotected
init_dependent()stan::math::variinline
op_ddv_vari(double f, double a, double b, vari *cvi)stan::math::op_ddv_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__ddv__vari.html b/doc/api/html/classstan_1_1math_1_1op__ddv__vari.html new file mode 100644 index 00000000000..07b77099890 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__ddv__vari.html @@ -0,0 +1,298 @@ + + + + + + +Stan Math Library: stan::math::op_ddv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_ddv_vari Class Reference
+
+
+ +

#include <ddv_vari.hpp>

+
+Inheritance diagram for stan::math::op_ddv_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_ddv_vari (double f, double a, double b, vari *cvi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

double ad_
 
double bd_
 
varicvi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file ddv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_ddv_vari::op_ddv_vari (double f,
double a,
double b,
varicvi 
)
+
+inline
+
+ +

Definition at line 15 of file ddv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
double stan::math::op_ddv_vari::ad_
+
+protected
+
+ +

Definition at line 11 of file ddv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::op_ddv_vari::bd_
+
+protected
+
+ +

Definition at line 12 of file ddv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_ddv_vari::cvi_
+
+protected
+
+ +

Definition at line 13 of file ddv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__ddv__vari.png b/doc/api/html/classstan_1_1math_1_1op__ddv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..a88a3da568183bf2123d8d1bd40ea0c5e9b77cd9 GIT binary patch literal 592 zcmeAS@N?(olHy`uVBq!ia0vp^6M#5?gBeI3Ea0&NQW60^A+G=b{|7Q(y!l$%e+Z-k zj1L?*z}k679?0b=3GxeO04f53tEWPY7#JAud%8G=R4~4s`#Nup0S}wH{H1;WmBlAb zxZRW(9p(Bw;?;KLPDv>eV zt+~@bZOoI{U)C7AFoox%&o5m!)sqi`G~Ukm-aC8S{-bYaKaf}->mA46qa%7Eb=IT3 zx&JR5o1Gy)c?t8o-kkTpcLs2NoBd31=?iBk^|$u(o^QO+p)&X5Psv{%8s;y=-NN2q zco675O)p~oHu;0^UU*;9{I}j2;ue^j!WIIZ*~w7RB7VT1dpdNRXBB7P$2{N5$Mn9( zuBh7EuTxuEw$%VRer#cu9%+qV5<%nBBJQ7OOdIfB%B#yWKCDpoo}L-7drxY+)6P3LPcYOS5nfv7m|?x*=U=7^iAVpn s^D+Jr5og*^pvchuHdf4u + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_dv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_dv_vari, including all inherited members.

+ + + + + + + + + + + + + + +
ad_stan::math::op_dv_variprotected
adj_stan::math::vari
bvi_stan::math::op_dv_variprotected
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_dv_vari(double f, double a, vari *bvi)stan::math::op_dv_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__dv__vari.html b/doc/api/html/classstan_1_1math_1_1op__dv__vari.html new file mode 100644 index 00000000000..e4a3674191f --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__dv__vari.html @@ -0,0 +1,268 @@ + + + + + + +Stan Math Library: stan::math::op_dv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_dv_vari Class Reference
+
+
+ +

#include <dv_vari.hpp>

+
+Inheritance diagram for stan::math::op_dv_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_dv_vari (double f, double a, vari *bvi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + +

+Protected Attributes

double ad_
 
varibvi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file dv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_dv_vari::op_dv_vari (double f,
double a,
varibvi 
)
+
+inline
+
+ +

Definition at line 14 of file dv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
double stan::math::op_dv_vari::ad_
+
+protected
+
+ +

Definition at line 11 of file dv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_dv_vari::bvi_
+
+protected
+
+ +

Definition at line 12 of file dv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__dv__vari.png b/doc/api/html/classstan_1_1math_1_1op__dv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..7fe513971f947eb27415682ceecc049843266872 GIT binary patch literal 583 zcmeAS@N?(olHy`uVBq!ia0vp^oj@GG!3-p&PA`)IQW60^A+G=b{|7Q(y!l$%e`o@b z1;z&s9ANFdBM;MFoqy%~|0kw1 zaL#a=ZMI!|%cd)tQzbrJVXG5P?(ue*vV^rj*mKj4PL;@YGgv&U&YQitdm{Yfebb3c zB=da^?fdg{YpR#M`!nV5mW#T@KkXKox`cDRZ_%nr2C3Qim+tZ1(0|=3b)og$lg6k2 zq=l}|l)qIWyw%Y2)s72u7au8}Y@D%qYTlC}TZJ2)GT`ZDO`F(niVGjzkHrtMD?a^moI zV2EIVC|YW~bH!HP-DaOotuRVsoVZ Obp}sYKbLh*2~7Z2PYDeG literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1op__dvd__vari-members.html b/doc/api/html/classstan_1_1math_1_1op__dvd__vari-members.html new file mode 100644 index 00000000000..a5f5da206cc --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__dvd__vari-members.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_dvd_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_dvd_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
ad_stan::math::op_dvd_variprotected
adj_stan::math::vari
bvi_stan::math::op_dvd_variprotected
cd_stan::math::op_dvd_variprotected
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_dvd_vari(double f, double a, vari *bvi, double c)stan::math::op_dvd_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__dvd__vari.html b/doc/api/html/classstan_1_1math_1_1op__dvd__vari.html new file mode 100644 index 00000000000..09821f17b98 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__dvd__vari.html @@ -0,0 +1,298 @@ + + + + + + +Stan Math Library: stan::math::op_dvd_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_dvd_vari Class Reference
+
+
+ +

#include <dvd_vari.hpp>

+
+Inheritance diagram for stan::math::op_dvd_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_dvd_vari (double f, double a, vari *bvi, double c)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

double ad_
 
varibvi_
 
double cd_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file dvd_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_dvd_vari::op_dvd_vari (double f,
double a,
varibvi,
double c 
)
+
+inline
+
+ +

Definition at line 15 of file dvd_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
double stan::math::op_dvd_vari::ad_
+
+protected
+
+ +

Definition at line 11 of file dvd_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_dvd_vari::bvi_
+
+protected
+
+ +

Definition at line 12 of file dvd_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::op_dvd_vari::cd_
+
+protected
+
+ +

Definition at line 13 of file dvd_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__dvd__vari.png b/doc/api/html/classstan_1_1math_1_1op__dvd__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..44e34d16a4da5805676f33e24ada414cb2aa6798 GIT binary patch literal 599 zcmeAS@N?(olHy`uVBq!ia0vp^6M#5?gBeI3Ea0&NQW60^A+G=b{|7Q(y!l$%e+Z-k zj1L?*z}k679?0b=3GxeO04f53tEWPY7#J9zdAc};R4~4s`?~M30*@Pi{E~hDmHoXu z4otC_dGid{+o)5S>N8HShS-_+v+1K*IZP!1lkM)>j zv##}0_0-47u?F>TnRXw#xVT$<+cuf0D(&72bB}Jyi`$ZW`n35$ySUBUDs2Nce?RX=x6=dBqkygR}-*}i}7_OypWaW{~hy^7s`2BJ^o$&BHBsSaeu(3 zsy3_ss7-GhBDdCZ&swYRx%|j}KF?1aiU=Ih3UsC#(*wac24ln77hapryqM#(`h1Mr zWzM6T%pW)v8Ttj7K5!7A>ccgbPDyKGG2mBZc_8S-AUF4d@9wR)_s-ik-Fg|zbHQIH zE>tn^dB5b-N4_f`cZS#5R?Ya4;WKX|&*?4u_nPHx4(or`|Le(mmaiwhO%K}T9W%-N zBazf9b#r1s^ohmmL7x7zcx|@KF`rFts<$s!=#{YKb5B*x$%!wYou_kUdA-J!C;vGY z%9Zo~b;;P${_S$Yw}9L|T9LNSbKP}smd&u*`Z>5P$G`gUo8D(CcD2FwhFA4D_L^ty yjA!79dsBZx;J|z#pre6q|G4jTkXNSMJ_bhvc@BXW7W}|ez~JfX=d#Wzp$Pz;Z3K}3 literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1op__dvv__vari-members.html b/doc/api/html/classstan_1_1math_1_1op__dvv__vari-members.html new file mode 100644 index 00000000000..233a6cdf165 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__dvv__vari-members.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_dvv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_dvv_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
ad_stan::math::op_dvv_variprotected
adj_stan::math::vari
bvi_stan::math::op_dvv_variprotected
chain()stan::math::variinlinevirtual
cvi_stan::math::op_dvv_variprotected
init_dependent()stan::math::variinline
op_dvv_vari(double f, double a, vari *bvi, vari *cvi)stan::math::op_dvv_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__dvv__vari.html b/doc/api/html/classstan_1_1math_1_1op__dvv__vari.html new file mode 100644 index 00000000000..6447ca58e4b --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__dvv__vari.html @@ -0,0 +1,298 @@ + + + + + + +Stan Math Library: stan::math::op_dvv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_dvv_vari Class Reference
+
+
+ +

#include <dvv_vari.hpp>

+
+Inheritance diagram for stan::math::op_dvv_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_dvv_vari (double f, double a, vari *bvi, vari *cvi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

double ad_
 
varibvi_
 
varicvi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file dvv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_dvv_vari::op_dvv_vari (double f,
double a,
varibvi,
varicvi 
)
+
+inline
+
+ +

Definition at line 15 of file dvv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
double stan::math::op_dvv_vari::ad_
+
+protected
+
+ +

Definition at line 11 of file dvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_dvv_vari::bvi_
+
+protected
+
+ +

Definition at line 12 of file dvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_dvv_vari::cvi_
+
+protected
+
+ +

Definition at line 13 of file dvv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__dvv__vari.png b/doc/api/html/classstan_1_1math_1_1op__dvv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..7589bb36ed1cc5a74448e1aae5d21ce378f64ccd GIT binary patch literal 594 zcmeAS@N?(olHy`uVBq!ia0vp^6M#5?gBeI3Ea0&NQW60^A+G=b{|7Q(y!l$%e+Z-k zj1L?*z}k679?0b=3GxeO04f53tEWPY7#J8Idb&7uu}$AYuM3&cEJ0hUZuUCp|mZs&euW5Iohos&O!Ue&EC)rpJZ|^t8LtKM%%7Pdlgl<=Voh z+#Bj9pIUDkuz6|d%d+^3NBi%2N}kUCdZ|P06SwAFg(>$lg;-YDuMC;Kx4-M1f4D2!T3@NYnWdjocgQu&X%Q~loCIF2=0+j#& literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1op__matrix__vari-members.html b/doc/api/html/classstan_1_1math_1_1op__matrix__vari-members.html new file mode 100644 index 00000000000..eba1192b871 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__matrix__vari-members.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_matrix_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_matrix_vari, including all inherited members.

+ + + + + + + + + + + + + + + + +
adj_stan::math::vari
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_matrix_vari(double f, const Eigen::Matrix< stan::math::var, R, C > &vs)stan::math::op_matrix_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
operator[](size_t n) const stan::math::op_matrix_variinline
set_zero_adjoint()stan::math::variinline
size()stan::math::op_matrix_variinline
size_stan::math::op_matrix_variprotected
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
vis_stan::math::op_matrix_variprotected
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__matrix__vari.html b/doc/api/html/classstan_1_1math_1_1op__matrix__vari.html new file mode 100644 index 00000000000..4c1b43b2ac6 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__matrix__vari.html @@ -0,0 +1,321 @@ + + + + + + +Stan Math Library: stan::math::op_matrix_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_matrix_vari Class Reference
+
+
+ +

#include <matrix_vari.hpp>

+
+Inheritance diagram for stan::math::op_matrix_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

template<int R, int C>
 op_matrix_vari (double f, const Eigen::Matrix< stan::math::var, R, C > &vs)
 
varioperator[] (size_t n) const
 
size_t size ()
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + +

+Protected Attributes

const size_t size_
 
vari ** vis_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 12 of file matrix_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::op_matrix_vari::op_matrix_vari (double f,
const Eigen::Matrix< stan::math::var, R, C > & vs 
)
+
+inline
+
+ +

Definition at line 18 of file matrix_vari.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
vari* stan::math::op_matrix_vari::operator[] (size_t n) const
+
+inline
+
+ +

Definition at line 27 of file matrix_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
size_t stan::math::op_matrix_vari::size ()
+
+inline
+
+ +

Definition at line 30 of file matrix_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
const size_t stan::math::op_matrix_vari::size_
+
+protected
+
+ +

Definition at line 14 of file matrix_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari** stan::math::op_matrix_vari::vis_
+
+protected
+
+ +

Definition at line 15 of file matrix_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__matrix__vari.png b/doc/api/html/classstan_1_1math_1_1op__matrix__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..d5f776a6ff5241a1289f73794316c81932052434 GIT binary patch literal 616 zcmeAS@N?(olHy`uVBq!ia0vp^bAUL2gBeKP_Ia}bNJ#|vgt-3y{~ySF@#br3|Dg#$ z78oBmaDcV*jy#adQ4-`A%m7pb0#{Fk7%?y~e)n{745?szJNNFUCIcR}?efO^{wvEb zX#E$#QdIJ$XJ>@0=Ow)*2cwr|&T?z@oOJBSQwVKM-!z_8p%fRrcv8tJ*PT16iy~N0Wv})U%z6AX)9twVc2m7+ z({#*Moqa8zx~Josp{Laozv%7vWKO?57^Se)(9K?<{KBHT^S_I9Cw-B6J#)9}bh$h2 zw`ZkqEIgIl+Z>gh=e|u!+SBUb|9ue0uuh+>!mX$7DVDY~bJj9P#tLQrhCs>4cONBg z(}Zu?zuH<>%Tk3t18wn3*Qpw z9sO?R#-eCtb&;aNgxO45t)kbUc*6F-FI)B~Q zF0JNoC#OD)i{5^`T4y`^`x95Sw-r^--@f^xY{xFw*qw{kUVnOP-&ST(*{HaAmfbPc z)A*jeYP_-R*`BqPVzZwXw?7Inn{_v{R;x;N`lh~HTp#rB{Z0SOxbtbk@^Y~Qiq9+e pe}2MnuM_Io)4L5@1dcu7=lP~MW5=J#Wx!;?;OXk;vd$@?2>=EYAFBWW literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1op__v__vari-members.html b/doc/api/html/classstan_1_1math_1_1op__v__vari-members.html new file mode 100644 index 00000000000..4edba476277 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__v__vari-members.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_v_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_v_vari, including all inherited members.

+ + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_v_variprotected
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_v_vari(double f, vari *avi)stan::math::op_v_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__v__vari.html b/doc/api/html/classstan_1_1math_1_1op__v__vari.html new file mode 100644 index 00000000000..1b77b412dac --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__v__vari.html @@ -0,0 +1,239 @@ + + + + + + +Stan Math Library: stan::math::op_v_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_v_vari Class Reference
+
+
+ +

#include <v_vari.hpp>

+
+Inheritance diagram for stan::math::op_v_vari:
+
+
+ + +stan::math::vari +stan::math::precomp_v_vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_v_vari (double f, vari *avi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + +

+Protected Attributes

variavi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file v_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::op_v_vari::op_v_vari (double f,
variavi 
)
+
+inline
+
+ +

Definition at line 13 of file v_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_v_vari::avi_
+
+protected
+
+ +

Definition at line 11 of file v_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__v__vari.png b/doc/api/html/classstan_1_1math_1_1op__v__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..3b5608e49bd6a9f0e47b62889a381c0cfefa5684 GIT binary patch literal 912 zcmeAS@N?(olHy`uVBq!ia0vp^OM$q9gBeI}JboKUGDrmYgt-3y{~ySF@#br3|Dg#$ z78oBmaDcV*jy#adQ4-`A%m7pb0#{Fk7%?y~%X_*whEy=Vo%?XoY6TuQetF~C|L*(3 z1Q<77Gus`WZhZN&9^2uG0^juwk5yE5Oe!h76ErEOz}s`v!#$}JmLxCBbT__#=F5Ct z)t9z@k!{Z}JOJepaO+vjyDdd@~4smL_5mFv&?g>L9y|9f^y{i;Wr z+2>-{-mr7BUhz0|ORwi8Z@=&w&D;A@Ik&0pJf!(+@-*wK((>&aQ~On9KVRKxlR9(z zr|nw%$_muChuLf`f4y7g^|IqCFM0piFHyPqVA`aV=4h`;ym^|QWr<6V=CjoiRsGBn52rDh?NDvt&ErgHj%K>?04MkG{jEHTEvKCsc342w z7Nq=qX6$pBXI`24(WN?!ZF@G%xfgVPdgi~Xb1}=$Z9jY1XmMx%yP40gYZ_&qn!}KA zq)sC; zk#kdbn!Dz~zx=ph zr2b>kBZm0IslUy2=Kq~|ziYPO0mFUM;XXY4d9Sn+hdBFz8SDq1?reSfxRCv9bcEj| z^9y_0mwvZs5G5E2urT@)ds-rS%TvMRo^1lEFCXn#3JG=RbV-$$Gcs?@HdcMf{YguF z`<*wb6?(Dz)VhDBZ;aY=s>g2LqR)H&l>ZGDGTHuA`)|fh-XEvQ*iU{t|5WqzFALuDsr60A^{3u3Z3l)`#codT|GIMn z+^21OGkf=!3iHpcsd35cA5Hoq`F_8Ref8OY@~3wmKDBI{vgfOx-qo6(_MNE7=pUo; X2WPMR!a6fx_F?dJ^>bP0l+XkKf@!b^ literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1op__vd__vari-members.html b/doc/api/html/classstan_1_1math_1_1op__vd__vari-members.html new file mode 100644 index 00000000000..25baef8b1fb --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vd__vari-members.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_vd_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_vd_vari, including all inherited members.

+ + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_vd_variprotected
bd_stan::math::op_vd_variprotected
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_vd_vari(double f, vari *avi, double b)stan::math::op_vd_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vd__vari.html b/doc/api/html/classstan_1_1math_1_1op__vd__vari.html new file mode 100644 index 00000000000..831abce94d6 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vd__vari.html @@ -0,0 +1,268 @@ + + + + + + +Stan Math Library: stan::math::op_vd_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_vd_vari Class Reference
+
+
+ +

#include <vd_vari.hpp>

+
+Inheritance diagram for stan::math::op_vd_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_vd_vari (double f, vari *avi, double b)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + +

+Protected Attributes

variavi_
 
double bd_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file vd_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_vd_vari::op_vd_vari (double f,
variavi,
double b 
)
+
+inline
+
+ +

Definition at line 14 of file vd_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vd_vari::avi_
+
+protected
+
+ +

Definition at line 11 of file vd_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::op_vd_vari::bd_
+
+protected
+
+ +

Definition at line 12 of file vd_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vd__vari.png b/doc/api/html/classstan_1_1math_1_1op__vd__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..468b6ebb69e977a692bb381f3676e4d6fc575898 GIT binary patch literal 588 zcmeAS@N?(olHy`uVBq!ia0vp^oj@GG!3-p&PA`)IQW60^A+G=b{|7Q(y!l$%e`o@b z1;z&s9ANFdBM;@1PLn;{G&VAkYSxbPWd)t)n^-q$M zb26Idrfj}17}fj4>yf0MDBF*-n{-Z#Z1A|m($cA7nW*G>&RWfLQru><>Z_mh{{Nrl zaY_v!v$Prl9kcK_M~yBN`ox-07Ssw@2G zE%y9Y`TFtXX+MHLY>=6`#nk%tu4VhT{9Jw`_rkRFkh#eZ*ZH1%l0Dhzn?b}e$=P4D zZA~)6{%B90cf0nJ@Z@(sQ++dk|KQoT%FkAEuEW}MbuL!R58kx=KJUJW`vzOa{dLFd zOt07*+%!wxsrTkkB_Gq*pNq4ZJ|sh&oW8p!$SafSAM=|e*$#(}X + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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reverse mode automatic differentiation
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+ +
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+
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stan::math::op_vdd_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_vdd_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_vdd_variprotected
bd_stan::math::op_vdd_variprotected
cd_stan::math::op_vdd_variprotected
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_vdd_vari(double f, vari *avi, double b, double c)stan::math::op_vdd_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vdd__vari.html b/doc/api/html/classstan_1_1math_1_1op__vdd__vari.html new file mode 100644 index 00000000000..b95db223755 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vdd__vari.html @@ -0,0 +1,298 @@ + + + + + + +Stan Math Library: stan::math::op_vdd_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_vdd_vari Class Reference
+
+
+ +

#include <vdd_vari.hpp>

+
+Inheritance diagram for stan::math::op_vdd_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_vdd_vari (double f, vari *avi, double b, double c)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

variavi_
 
double bd_
 
double cd_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file vdd_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_vdd_vari::op_vdd_vari (double f,
variavi,
double b,
double c 
)
+
+inline
+
+ +

Definition at line 15 of file vdd_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vdd_vari::avi_
+
+protected
+
+ +

Definition at line 11 of file vdd_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::op_vdd_vari::bd_
+
+protected
+
+ +

Definition at line 12 of file vdd_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::op_vdd_vari::cd_
+
+protected
+
+ +

Definition at line 13 of file vdd_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vdd__vari.png b/doc/api/html/classstan_1_1math_1_1op__vdd__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..1690a6b8eea86f0c9a7cc98f5aeb431684d0f949 GIT binary patch literal 595 zcmeAS@N?(olHy`uVBq!ia0vp^6M#5?gBeI3Ea0&NQW60^A+G=b{|7Q(y!l$%e+Z-k zj1L?*z}k679?0b=3GxeO04f53tEWPY7#J8IdAc};R4~4sd%JJ3fdK32<3a!aPiD_) z)=!?5GA%N4w{GCc1DS8S@;`g^7_MUpoOJDAtIEkkK>Wyep@Qf4oYeBEHRC2zjaFQwsH$ur0#6Iq{Vk5m4w+*J9$eL*?};!3GI_IaQ-XT-inQ|JuGZi$%bTgD+22n+R{tvO`?u-BzJSv| ynJy%z{y)sY_(xNZCE=kHgV^s#F(;1KA6OlJ$a9EoT514H0Sun5elF{r5}E)zEe_%U literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1op__vdv__vari-members.html b/doc/api/html/classstan_1_1math_1_1op__vdv__vari-members.html new file mode 100644 index 00000000000..547d8fb2c2c --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vdv__vari-members.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_vdv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_vdv_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_vdv_variprotected
bd_stan::math::op_vdv_variprotected
chain()stan::math::variinlinevirtual
cvi_stan::math::op_vdv_variprotected
init_dependent()stan::math::variinline
op_vdv_vari(double f, vari *avi, double b, vari *cvi)stan::math::op_vdv_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vdv__vari.html b/doc/api/html/classstan_1_1math_1_1op__vdv__vari.html new file mode 100644 index 00000000000..5f5f3b979ba --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vdv__vari.html @@ -0,0 +1,298 @@ + + + + + + +Stan Math Library: stan::math::op_vdv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_vdv_vari Class Reference
+
+
+ +

#include <vdv_vari.hpp>

+
+Inheritance diagram for stan::math::op_vdv_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_vdv_vari (double f, vari *avi, double b, vari *cvi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

variavi_
 
double bd_
 
varicvi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file vdv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_vdv_vari::op_vdv_vari (double f,
variavi,
double b,
varicvi 
)
+
+inline
+
+ +

Definition at line 15 of file vdv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vdv_vari::avi_
+
+protected
+
+ +

Definition at line 11 of file vdv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::op_vdv_vari::bd_
+
+protected
+
+ +

Definition at line 12 of file vdv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vdv_vari::cvi_
+
+protected
+
+ +

Definition at line 13 of file vdv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vdv__vari.png b/doc/api/html/classstan_1_1math_1_1op__vdv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..1040772a375f7e08710dea0032b2250c8588a68b GIT binary patch literal 600 zcmeAS@N?(olHy`uVBq!ia0vp^6M#5?gBeI3Ea0&NQW60^A+G=b{|7Q(y!l$%e+Z-k zj1L?*z}k679?0b=3GxeO04f53tEWPY7#J9zd%8G=R4~4s`!?^ff(UDS^OW!PPi{$^ zIsWMNlG5;u?_Tqkd^>3Hkm;{?kKsC&z)9B*wyK;w1jLVg7bfY1(SdU3M z?^+Mpo%*?vcgDUhhd_&Hp2}wx(}FyWc8FTJoq4>>@pgLV4>g(3R@v>>nN_W=PTVz_ z`+eJA-`VDw^F1%MeD?}__BZMU&u_=#&b}{-3%g&=zh10oqU0G~v#-rg=#=mmZq?P* z86Q@tTAM|z51W>-{fp{Lq5szvJ;n4?5O{V#kD(sR0p&dmVM(S7uV))BzS?3oe{0V) z;ZLz_36Gr^#PnDa9ulDbuM6N%T*JbcAREJR;7}`r4%|MrzjJvV#J@z>D# zHs^-h9?y`+8`T1t<6}!THcgrF+Ex!Kh;-A3vUqlzgWv&2v_}$#P3(tP) zXrD7)xNSl$d+CjL%g*YjA3U||(JTAbF4b=|1hZUZ=|4%ZnEl{#x$jD>+X< z%JBMy@|L!{)5UY*Ui}TTmcKh?&AWvM7f*Y0!>9RH%JjLfH%(z*5q|QR?vEFqe_g`& zD{RrfQnQbtB;w|O17`;Nqd<29ou6cX+KD4kb{_+~iaf)gE=LbwGGOp@^>bP0l+XkK D2u= + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_vector_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_vector_vari, including all inherited members.

+ + + + + + + + + + + + + + + + +
adj_stan::math::vari
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_vector_vari(double f, const std::vector< stan::math::var > &vs)stan::math::op_vector_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
operator[](size_t n) const stan::math::op_vector_variinline
set_zero_adjoint()stan::math::variinline
size()stan::math::op_vector_variinline
size_stan::math::op_vector_variprotected
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
vis_stan::math::op_vector_variprotected
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vector__vari.html b/doc/api/html/classstan_1_1math_1_1op__vector__vari.html new file mode 100644 index 00000000000..c411e2d0e84 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vector__vari.html @@ -0,0 +1,318 @@ + + + + + + +Stan Math Library: stan::math::op_vector_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_vector_vari Class Reference
+
+
+ +

#include <vector_vari.hpp>

+
+Inheritance diagram for stan::math::op_vector_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_vector_vari (double f, const std::vector< stan::math::var > &vs)
 
varioperator[] (size_t n) const
 
size_t size ()
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + +

+Protected Attributes

const size_t size_
 
vari ** vis_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 11 of file vector_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::op_vector_vari::op_vector_vari (double f,
const std::vector< stan::math::var > & vs 
)
+
+inline
+
+ +

Definition at line 16 of file vector_vari.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
vari* stan::math::op_vector_vari::operator[] (size_t n) const
+
+inline
+
+ +

Definition at line 24 of file vector_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
size_t stan::math::op_vector_vari::size ()
+
+inline
+
+ +

Definition at line 27 of file vector_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
const size_t stan::math::op_vector_vari::size_
+
+protected
+
+ +

Definition at line 13 of file vector_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari** stan::math::op_vector_vari::vis_
+
+protected
+
+ +

Definition at line 14 of file vector_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vector__vari.png b/doc/api/html/classstan_1_1math_1_1op__vector__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..d61279168e38d706a670c88a959314cea83a825d GIT binary patch literal 619 zcmeAS@N?(olHy`uVBq!ia0vp^^MN>kgBeH~REKW{QW60^A+G=b{|7Q(y!l$%e`o@b z1;z&s9ANFdBM;6|{Y!Q;}F9rIOg7TSAm`n)WD!jkN3TUMW$t^C*A z-gDQ%+WjBql>Co+-rs&U-T0RAt_ro-?m*97&$h)2oshb?aGzN2sswrc>{%xJvN`ts0Mv!k|~-rbge*>zG$>;C&HC;NVTPLlmTS;hLDx@TF~{?y26m5e{s_!~NB z-g*CVMsz{Z{?PoagE#-~sb{o1_?O|$4*3Sz@5~z>*D;jc;Xly#oAE}WJ%jZ-_JrdI z$ zVcvg3;H?u=&kn!8!LQjrq(Z%0X&2FVdQ&MBb@0J(oU AkN^Mx literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1op__vv__vari-members.html b/doc/api/html/classstan_1_1math_1_1op__vv__vari-members.html new file mode 100644 index 00000000000..e0f20da48c2 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vv__vari-members.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_vv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_vv_vari, including all inherited members.

+ + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_vv_variprotected
bvi_stan::math::op_vv_variprotected
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_vv_vari(double f, vari *avi, vari *bvi)stan::math::op_vv_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vv__vari.html b/doc/api/html/classstan_1_1math_1_1op__vv__vari.html new file mode 100644 index 00000000000..b01d9f2ae28 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vv__vari.html @@ -0,0 +1,269 @@ + + + + + + +Stan Math Library: stan::math::op_vv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_vv_vari Class Reference
+
+
+ +

#include <vv_vari.hpp>

+
+Inheritance diagram for stan::math::op_vv_vari:
+
+
+ + +stan::math::vari +stan::math::precomp_vv_vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_vv_vari (double f, vari *avi, vari *bvi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + +

+Protected Attributes

variavi_
 
varibvi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file vv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_vv_vari::op_vv_vari (double f,
variavi,
varibvi 
)
+
+inline
+
+ +

Definition at line 14 of file vv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vv_vari::avi_
+
+protected
+
+ +

Definition at line 11 of file vv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vv_vari::bvi_
+
+protected
+
+ +

Definition at line 12 of file vv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vv__vari.png b/doc/api/html/classstan_1_1math_1_1op__vv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..4495aaf0015c9ae3e8fdd0d1f4035de5ddb48882 GIT binary patch literal 931 zcmeAS@N?(olHy`uVBq!ia0vp^Yk;_egBeKrUixqfNJ#|vgt-3y{~ySF@#br3|Dg#$ z78oBmaDcV*jy#adQ4-`A%m7pb0#{Fk7%?y~8+p1ohEy=Vo%?puW-S4>+wH6F{8yE4 zR*=s!F`T^ligoDAl+=Wb#DxDsP8^FJCM+>5i1gfaAXW8bQ-6xOr&ap9vTL7{mhD&6 z_PkyhUREWwCVsQepOZzA`EM^C750wq@w$|HZ%S;=q+pR%w--f;zImLwRXqK%QN*O> znyWf*n`g?usu0aho>X#5J$1tOPZ4Fj+nh3QPk+Im!oRI#zuULeYL%B#<=NkKZ*JLO zuh(33&H8u{+iBMeSwoS60Wo5F*%QPbQ^D^WVL^5#4h#g>>&br}1Dx(fQZsM$EnIbb7j=|KOOVQtV z>dxD0{n{BX^-nRq`Q%i#@7lcS1;47k>BK(X@MFifj7QbUN&ijOoSPC+bgu|jy(bu|=S*?Dw=nspX@%Zw z_3Ylc&0tSa!Xxf z{Y9HAALm_)oILBi>rK1&%XmJ0l0UufVDe3)e<5b?KkT~bo4jtpUFK`k4z9~F{{Hb) z-nD1UH|NedZu)y#PHggS)7#18YXPB~1nd;Du@_3NsC^(l`PbEf}T5E%6HPqVhRr#;+ + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_vvd_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_vvd_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_vvd_variprotected
bvi_stan::math::op_vvd_variprotected
cd_stan::math::op_vvd_variprotected
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
op_vvd_vari(double f, vari *avi, vari *bvi, double c)stan::math::op_vvd_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vvd__vari.html b/doc/api/html/classstan_1_1math_1_1op__vvd__vari.html new file mode 100644 index 00000000000..ea0f3b233b7 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vvd__vari.html @@ -0,0 +1,298 @@ + + + + + + +Stan Math Library: stan::math::op_vvd_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_vvd_vari Class Reference
+
+
+ +

#include <vvd_vari.hpp>

+
+Inheritance diagram for stan::math::op_vvd_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_vvd_vari (double f, vari *avi, vari *bvi, double c)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

variavi_
 
varibvi_
 
double cd_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 9 of file vvd_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_vvd_vari::op_vvd_vari (double f,
variavi,
varibvi,
double c 
)
+
+inline
+
+ +

Definition at line 15 of file vvd_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vvd_vari::avi_
+
+protected
+
+ +

Definition at line 11 of file vvd_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vvd_vari::bvi_
+
+protected
+
+ +

Definition at line 12 of file vvd_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::op_vvd_vari::cd_
+
+protected
+
+ +

Definition at line 13 of file vvd_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vvd__vari.png b/doc/api/html/classstan_1_1math_1_1op__vvd__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..f241cfbef1d2cd2c15c76e41d3c8140bd0a89d38 GIT binary patch literal 595 zcmeAS@N?(olHy`uVBq!ia0vp^6M#5?gBeI3Ea0&NQW60^A+G=b{|7Q(y!l$%e+Z-k zj1L?*z}k679?0b=3GxeO04f53tEWPY7#J8IdAc};R4~4s`#SHjf`A*pe9*oB6SJAk zravgWRT`dAzGTjhv>kKKF#PrIF7fcTN~LIuz7Id|Vx-8=e!*94Ww zJKU|cQ$J@%8`$zSIzN14c!YbWuB+5e$QTLd_zCVYszAN&e$dOap!kl=unCM_}BJ}?!rk6;x!^| zotxctBkdCQ-rC5zd#%3b^dI~AJU106BJhotq@F@W2Dyi<8-!MK?v3k~T&uR_=bF?l zb0*9;VvrVR+EAd#z)gVqQQqprk*LbS@cMxhgP0ymf+0t3#`e+!_&V_=- z{C{0CENb88z4#uGyGI-5d7tK6Po{iz`m4FR_ibe5pJjDPtKtQ2nP=^cXRumx + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::op_vvv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::op_vvv_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_vvv_variprotected
bvi_stan::math::op_vvv_variprotected
chain()stan::math::variinlinevirtual
cvi_stan::math::op_vvv_variprotected
init_dependent()stan::math::variinline
op_vvv_vari(double f, vari *avi, vari *bvi, vari *cvi)stan::math::op_vvv_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vvv__vari.html b/doc/api/html/classstan_1_1math_1_1op__vvv__vari.html new file mode 100644 index 00000000000..1b543066790 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1op__vvv__vari.html @@ -0,0 +1,299 @@ + + + + + + +Stan Math Library: stan::math::op_vvv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::op_vvv_vari Class Reference
+
+
+ +

#include <vvv_vari.hpp>

+
+Inheritance diagram for stan::math::op_vvv_vari:
+
+
+ + +stan::math::vari +stan::math::precomp_vvv_vari + +
+ + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 op_vvv_vari (double f, vari *avi, vari *bvi, vari *cvi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

variavi_
 
varibvi_
 
varicvi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 10 of file vvv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::op_vvv_vari::op_vvv_vari (double f,
variavi,
varibvi,
varicvi 
)
+
+inline
+
+ +

Definition at line 16 of file vvv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vvv_vari::avi_
+
+protected
+
+ +

Definition at line 12 of file vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vvv_vari::bvi_
+
+protected
+
+ +

Definition at line 13 of file vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari* stan::math::op_vvv_vari::cvi_
+
+protected
+
+ +

Definition at line 14 of file vvv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1op__vvv__vari.png b/doc/api/html/classstan_1_1math_1_1op__vvv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..a5d15584d06e4f17ebb008f784894a3a1af628b6 GIT binary patch literal 930 zcmeAS@N?(olHy`uVBq!ia0vp^n}N84gBeK9F4tNQq$C1-LR|m<{|{uoc=NTi|Ih>= z3ycpOIKbL@M;^%KC<*clW&kPzfvcxNj2IZ04Lw~PLn;{G&VAjt+JJ{mJ$}i)|H|@Q zoI4p>H2uv7L9_S1D&L$a`sQ)!Tk)^&pByuC zpS5z<{=W;pE$j=wXr|^FzGJp@Wpn@B>j|%?7A1Dpo&T9I|GRMd{hjWU^gegi)Sb4} z{rvuk+e)svStom!rfm84)51hObke%V|97jNlq;X6Qhg_K(wo9`&rRt?eTK(2GHiIr zXduCCWiR*GlmCT{CcnDvqRrQN8}c8VWB9hixWV=vPeQ*n^Nq*&xKFthTMjBP@U%h| z&asUDvuNeb9I$`Gv*9%N^Obyd-Q~Y3x9Rvk&-?uN)}qe$UuWK4p7-?Hv7r5x zf23dU;fX#gxFBY;ukwXsv+b_W?f$j)PQ<bOb%)I{3>bf`IhU1=jPySk! z#Wg=aSGnoiwWCErcWs;B+P$|5-}#aAxm*Kp{*%wL&-HXy-@Wg#^!*Q)yeX?Ltekcy z;*@jx{$O)Gi{%gNCP*{bA4+?ZZ()Bvbk%MK-t|cg)jzBdK0Lol-igDRG2t+Cf&p7e zoz1byau+Ityz_TOOGh7%JeDzM zy4_U + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::precomp_v_vari Member List
+
+
+ +

This is the complete list of members for stan::math::precomp_v_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_v_variprotected
chain()stan::math::precomp_v_variinlinevirtual
da_stan::math::precomp_v_variprotected
init_dependent()stan::math::variinline
op_v_vari(double f, vari *avi)stan::math::op_v_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
precomp_v_vari(double val, vari *avi, double da)stan::math::precomp_v_variinline
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1precomp__v__vari.html b/doc/api/html/classstan_1_1math_1_1precomp__v__vari.html new file mode 100644 index 00000000000..9cfd253ec00 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1precomp__v__vari.html @@ -0,0 +1,282 @@ + + + + + + +Stan Math Library: stan::math::precomp_v_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::precomp_v_vari Class Reference
+
+
+ +

#include <precomp_v_vari.hpp>

+
+Inheritance diagram for stan::math::precomp_v_vari:
+
+
+ + +stan::math::op_v_vari +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 precomp_v_vari (double val, vari *avi, double da)
 
void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
- Public Member Functions inherited from stan::math::op_v_vari
 op_v_vari (double f, vari *avi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + +

+Protected Attributes

double da_
 
- Protected Attributes inherited from stan::math::op_v_vari
variavi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 11 of file precomp_v_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::precomp_v_vari::precomp_v_vari (double val,
variavi,
double da 
)
+
+inline
+
+ +

Definition at line 15 of file precomp_v_vari.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::precomp_v_vari::chain ()
+
+inlinevirtual
+
+ +

Apply the chain rule to this variable based on the variables on which it depends.

+

The base implementation in this class is a no-op.

+ +

Reimplemented from stan::math::vari.

+ +

Definition at line 19 of file precomp_v_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
double stan::math::precomp_v_vari::da_
+
+protected
+
+ +

Definition at line 13 of file precomp_v_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1precomp__v__vari.png b/doc/api/html/classstan_1_1math_1_1precomp__v__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..f07d58d8ea69792cca4d503793e7c14eb92aaa6e GIT binary patch literal 907 zcmeAS@N?(olHy`uVBq!ia0vp^OM$q9gBeI}JboKUGDrmYgt-3y{~ySF@#br3|Dg#$ z78oBmaDcV*jy#adQ4-`A%m7pb0#{Fk7%?y~OL@9DhEy=Vo%_0PwE+*Cdi;`o|CQyv zn05+yW$vwZ$X*$2W?^yJBJICWa?kX34Nvjox~eDHwog%!J{QgAX_Yps%;fV~pZ_<5 zCf$2HCAC6tZ=J8$=hTf+d#*{w+Dv|THqf)G+jyF%^64{bU-#Zz$@T5yrv0AZmTS%1 z^z6>nuDAXf?4^6Uwi$X>oqXA)pL%7jmOS&&P`>{<29vv{*lkt z{#n~Ko$uWfucN`$+xMN`m{;X9>E40=&R&yv^E5rpb}Uu7`C!_ll*1{K$vxrh2WGGz zc)GLo>ElB7v(XWLlguydXBfU;3}!o28+dVZ|HPh_NZw=P;ed2%QD!(QH+e}V7Sk7xJ(WtdJ~BFHWppS3A}CtJVn z?peoJE*YdD;HSD%_Th4Iq zTd_l>w)Lv@7jvEYe<$AWnmtiP_Hi|h!bHGnhYd?Z_hV@I&3!ui)a5Pre->6w?T*g- zR#c^Fdw=fF*OD4apVw6GIQQbQrq%h=_1CAHI)0AWce#I>dUwoM_n%9)zN#+%q_v~> z`Jb;-%%c4+Oi9d$OxZ5#KizGoipIaQ3;Mo?WHMiwuYB6>;j%}k+uld7J6L=A)1QT@ z*TpKQ2=(ax?&8;-?fU(D(Pqtbo%WO8&OOyU{mX*)d}@8uas8=xOxuBhwC8Ti(*M)^ zRw#Q%e>=PPTZQ@O*3`J<^^X|lf2`{}ANJdRT5 + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::precomp_vv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::precomp_vv_vari, including all inherited members.

+ + + + + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_vv_variprotected
bvi_stan::math::op_vv_variprotected
chain()stan::math::precomp_vv_variinlinevirtual
da_stan::math::precomp_vv_variprotected
db_stan::math::precomp_vv_variprotected
init_dependent()stan::math::variinline
op_vv_vari(double f, vari *avi, vari *bvi)stan::math::op_vv_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
precomp_vv_vari(double val, vari *avi, vari *bvi, double da, double db)stan::math::precomp_vv_variinline
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1precomp__vv__vari.html b/doc/api/html/classstan_1_1math_1_1precomp__vv__vari.html new file mode 100644 index 00000000000..e11fa1a94d0 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1precomp__vv__vari.html @@ -0,0 +1,320 @@ + + + + + + +Stan Math Library: stan::math::precomp_vv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::precomp_vv_vari Class Reference
+
+
+ +

#include <precomp_vv_vari.hpp>

+
+Inheritance diagram for stan::math::precomp_vv_vari:
+
+
+ + +stan::math::op_vv_vari +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 precomp_vv_vari (double val, vari *avi, vari *bvi, double da, double db)
 
void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
- Public Member Functions inherited from stan::math::op_vv_vari
 op_vv_vari (double f, vari *avi, vari *bvi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + + + + +

+Protected Attributes

double da_
 
double db_
 
- Protected Attributes inherited from stan::math::op_vv_vari
variavi_
 
varibvi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 11 of file precomp_vv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::precomp_vv_vari::precomp_vv_vari (double val,
variavi,
varibvi,
double da,
double db 
)
+
+inline
+
+ +

Definition at line 16 of file precomp_vv_vari.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::precomp_vv_vari::chain ()
+
+inlinevirtual
+
+ +

Apply the chain rule to this variable based on the variables on which it depends.

+

The base implementation in this class is a no-op.

+ +

Reimplemented from stan::math::vari.

+ +

Definition at line 23 of file precomp_vv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
double stan::math::precomp_vv_vari::da_
+
+protected
+
+ +

Definition at line 13 of file precomp_vv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::precomp_vv_vari::db_
+
+protected
+
+ +

Definition at line 14 of file precomp_vv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1precomp__vv__vari.png b/doc/api/html/classstan_1_1math_1_1precomp__vv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..7f03aeeaa9f2ab9d5ee0d7c93214291060bc84c0 GIT binary patch literal 924 zcmeAS@N?(olHy`uVBq!ia0vp^Yk;_egBeKrUixqfNJ#|vgt-3y{~ySF@#br3|Dg#$ z78oBmaDcV*jy#adQ4-`A%m7pb0#{Fk7%?y~YkRslhEy=Vo%?!IvxWfM?EY1I{wuF{ zoX{=hyJ@oR6~C#n{t^;a1_l3wl6y8gOj%-C5b3$;K&tA=rv8*>mDtTCyI)lrU%o$K z>XP4kw58{<-9D}~InH(6i(K2binLtsK+j!gXKz~VTju4I8y%G0l)Pu%w^unaY}ub| zT#XC=d;ikU-P8Ha&~w+5$wnI0m3q5bs~7HhoBf4-lX`SjjPmhK%9Bd^^RvI{-rTdn zUaz_88vF4mw%4u~vZqga-?vcZ?vej@y(Y2hX?u$8Sfdj8VAG_OgG$oLJ(C#{4lpN( zrA?}}QQI`vv#fCL@iMK*{k#l01(6KgF=7Xprn7E1kjkiokE?i0BE3<=vlwJ*<7uEZ z;hP*Mt&7}s_l>5f_?)y~-J2$roZ!Cs!Q_UW*vv0lMXvd;FCOhbw&Y)B#B9yY-+U@n zUUn4UG|ly$w`7}orpZCWd%ZgqqvzUdHJ5tGS)2=;x=TOz&!yGzH_IlfzU=5W(y%T8 z`hR`uX}<5$u~Oa-YpM?X(zTtEd+LGqO+n9FAKlK@DOrakY`*XOc>1QDJg*|qx);V|8x3QS@y~FR_u}AZk|<*>!Be7_Ct40kD(t^10#P! zQ@eSzRPOf5l)q*S8x9f(5~KiY6>yrt%5*?xhfV{l9(Te)h3d;SFTY*B zKSO=CbJ_Myr**&WDgJ!iIG{FY{g=|$hR3dFyqf+$FFv{{FCtHK{k}r)0NL60uQvPL z+_uzm)&skFpZl3iqx~-Ap3=VgYL9;N*Q+zHvwTf2iNE#3W3rjU?>kduKfgP*Ky*qj~e+qx`ysK}bH|6%qUV9U9cei(D zx%%EoXHx^t|ElvmC8*oJw0Fv6>p14yxdvbMOgkGqcPit7^gHK2Ud{R6n`71TS7^Qo t)7PK!>vRtALlZ~Sb5&U + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::precomp_vvv_vari Member List
+
+
+ +

This is the complete list of members for stan::math::precomp_vvv_vari, including all inherited members.

+ + + + + + + + + + + + + + + + + + + +
adj_stan::math::vari
avi_stan::math::op_vvv_variprotected
bvi_stan::math::op_vvv_variprotected
chain()stan::math::precomp_vvv_variinlinevirtual
cvi_stan::math::op_vvv_variprotected
da_stan::math::precomp_vvv_variprotected
db_stan::math::precomp_vvv_variprotected
dc_stan::math::precomp_vvv_variprotected
init_dependent()stan::math::variinline
op_vvv_vari(double f, vari *avi, vari *bvi, vari *cvi)stan::math::op_vvv_variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
precomp_vvv_vari(double val, vari *avi, vari *bvi, vari *cvi, double da, double db, double dc)stan::math::precomp_vvv_variinline
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1precomp__vvv__vari.html b/doc/api/html/classstan_1_1math_1_1precomp__vvv__vari.html new file mode 100644 index 00000000000..4cce1509731 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1precomp__vvv__vari.html @@ -0,0 +1,358 @@ + + + + + + +Stan Math Library: stan::math::precomp_vvv_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::precomp_vvv_vari Class Reference
+
+
+ +

#include <precomp_vvv_vari.hpp>

+
+Inheritance diagram for stan::math::precomp_vvv_vari:
+
+
+ + +stan::math::op_vvv_vari +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 precomp_vvv_vari (double val, vari *avi, vari *bvi, vari *cvi, double da, double db, double dc)
 
void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
- Public Member Functions inherited from stan::math::op_vvv_vari
 op_vvv_vari (double f, vari *avi, vari *bvi, vari *cvi)
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + + + + + + + + +

+Protected Attributes

double da_
 
double db_
 
double dc_
 
- Protected Attributes inherited from stan::math::op_vvv_vari
variavi_
 
varibvi_
 
varicvi_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+
+

Definition at line 11 of file precomp_vvv_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::precomp_vvv_vari::precomp_vvv_vari (double val,
variavi,
varibvi,
varicvi,
double da,
double db,
double dc 
)
+
+inline
+
+ +

Definition at line 17 of file precomp_vvv_vari.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::precomp_vvv_vari::chain ()
+
+inlinevirtual
+
+ +

Apply the chain rule to this variable based on the variables on which it depends.

+

The base implementation in this class is a no-op.

+ +

Reimplemented from stan::math::vari.

+ +

Definition at line 25 of file precomp_vvv_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
double stan::math::precomp_vvv_vari::da_
+
+protected
+
+ +

Definition at line 13 of file precomp_vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::precomp_vvv_vari::db_
+
+protected
+
+ +

Definition at line 14 of file precomp_vvv_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::precomp_vvv_vari::dc_
+
+protected
+
+ +

Definition at line 15 of file precomp_vvv_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1precomp__vvv__vari.png b/doc/api/html/classstan_1_1math_1_1precomp__vvv__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..a7eff60ccc54b470ea9f049ede93b56d3d408169 GIT binary patch literal 926 zcmeAS@N?(olHy`uVBq!ia0vp^n}N84gBeK9F4tNQq$C1-LR|m<{|{uoc=NTi|Ih>= z3ycpOIKbL@M;^%KC<*clW&kPzfvcxNj2IZ0bv<1iLn;{G&VAjt+JJ{mJ$}i)|H|@Q zoI4q~Q(u=YPVUs?K9}kt^FBVQr_i8dl8MMW9nWt&Hmlq$zHRAo$ufBJ=4s;Yzk<(A z`XW?5=WuY!-2uv7L9_S1D&L$a`sQ)!Tk)^wpByuC zpS5z<{=W;pE$j=wXr|^FzGJp@Wpn@B>j|%?7A1Dpo%@+E|GRMd{hjWU^gj31)Sa}{ z{ajwOIHc8Y>yu+aMp3_OWM)m)^1S}>|J_L`{np--Y+(*FwmdHJID+BE2L_2A#<}wS zAD6I~%$w3aS?=P^*K7yW3(^^???@hyD`(qqd@kdgLOk5YqN5Uz69iNRuVbDbvz}9}l6jc>XU*}Q-lwy^n+LtLzBf^NsaDA zo*z%PdC53e{prIc?j_%LF@E4AGH5^nw;)Eb#Xy3kVIed~=biich~4MxzK<(2&n=u| z{@P~h-t@J8_U9cg&Wb+UpWSV@&*gd9%lE&w@m(nK&fgU+9erGL)m8bYQEBV$pA9x$ z{QaZJzeab-1veLQpL4C9Eq!|J&jurhpR<60^gZM-+luwq=lp(XzH_4a;~SN{a@N!T zEk9TJ>)W-XMP+a29W*m9n=9S=xb&XR#oFh07xsVpsruaNW7+4O=l}Tryrmia(%P>W zn0nqaJq@07K3Mi-`)+-S?7J_b;>!Gt<({$~uwB>xao){+4{hdOE<5PmEuZxNw-s{@ kA2gLzUi%^7B+*sRe8;o7TCTzqn3)(nUHx3vIVCg!0AHQW1ONa4 literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1precomputed__gradients__vari-members.html b/doc/api/html/classstan_1_1math_1_1precomputed__gradients__vari-members.html new file mode 100644 index 00000000000..58a64b6eb14 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1precomputed__gradients__vari-members.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::precomputed_gradients_vari Member List
+
+
+ +

This is the complete list of members for stan::math::precomputed_gradients_vari, including all inherited members.

+ + + + + + + + + + + + + + + + +
adj_stan::math::vari
chain()stan::math::precomputed_gradients_variinlinevirtual
gradients_stan::math::precomputed_gradients_variprotected
init_dependent()stan::math::variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
precomputed_gradients_vari(double val, size_t size, vari **varis, double *gradients)stan::math::precomputed_gradients_variinline
precomputed_gradients_vari(double val, const std::vector< var > &vars, const std::vector< double > &gradients)stan::math::precomputed_gradients_variinline
set_zero_adjoint()stan::math::variinline
size_stan::math::precomputed_gradients_variprotected
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
varis_stan::math::precomputed_gradients_variprotected
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1precomputed__gradients__vari.html b/doc/api/html/classstan_1_1math_1_1precomputed__gradients__vari.html new file mode 100644 index 00000000000..73e6c459304 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1precomputed__gradients__vari.html @@ -0,0 +1,406 @@ + + + + + + +Stan Math Library: stan::math::precomputed_gradients_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::precomputed_gradients_vari Class Reference
+
+
+ +

A variable implementation taking a sequence of operands and partial derivatives with respect to the operands. + More...

+ +

#include <precomputed_gradients.hpp>

+
+Inheritance diagram for stan::math::precomputed_gradients_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 precomputed_gradients_vari (double val, size_t size, vari **varis, double *gradients)
 Construct a precomputed vari with the specified value, operands, and gradients. More...
 
 precomputed_gradients_vari (double val, const std::vector< var > &vars, const std::vector< double > &gradients)
 Construct a precomputed vari with the specified value, operands, and gradients. More...
 
void chain ()
 Implements the chain rule for this variable, using the prestored operands and gradient. More...
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

const size_t size_
 
vari ** varis_
 
double * gradients_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+

A variable implementation taking a sequence of operands and partial derivatives with respect to the operands.

+

Stan users should use function precomputed_gradients() directly.

+ +

Definition at line 21 of file precomputed_gradients.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::precomputed_gradients_vari::precomputed_gradients_vari (double val,
size_t size,
vari ** varis,
double * gradients 
)
+
+inline
+
+ +

Construct a precomputed vari with the specified value, operands, and gradients.

+
Parameters
+ + + + + +
[in]valThe value of the variable.
[in]sizeSize of operands and gradients
[in]varisOperand implementations.
[in]gradientsGradients with respect to operands.
+
+
+ +

Definition at line 37 of file precomputed_gradients.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::precomputed_gradients_vari::precomputed_gradients_vari (double val,
const std::vector< var > & vars,
const std::vector< double > & gradients 
)
+
+inline
+
+ +

Construct a precomputed vari with the specified value, operands, and gradients.

+
Parameters
+ + + + +
[in]valThe value of the variable.
[in]varsVector of operands.
[in]gradientsVector of partial derivatives of value with respect to operands.
+
+
+
Exceptions
+ + +
std::invalid_argumentif the sizes of the vectors don't match.
+
+
+ +

Definition at line 58 of file precomputed_gradients.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::precomputed_gradients_vari::chain ()
+
+inlinevirtual
+
+ +

Implements the chain rule for this variable, using the prestored operands and gradient.

+ +

Reimplemented from stan::math::vari.

+ +

Definition at line 79 of file precomputed_gradients.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
double* stan::math::precomputed_gradients_vari::gradients_
+
+protected
+
+ +

Definition at line 25 of file precomputed_gradients.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const size_t stan::math::precomputed_gradients_vari::size_
+
+protected
+
+ +

Definition at line 23 of file precomputed_gradients.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari** stan::math::precomputed_gradients_vari::varis_
+
+protected
+
+ +

Definition at line 24 of file precomputed_gradients.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
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+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::seq_view< T, S > Member List
+
+
+ +

This is the complete list of members for stan::math::seq_view< T, S >, including all inherited members.

+ + + + +
operator[](int n) const stan::math::seq_view< T, S >inline
seq_view(typename pass_type< S >::type x)stan::math::seq_view< T, S >inlineexplicit
size() const stan::math::seq_view< T, S >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view.html b/doc/api/html/classstan_1_1math_1_1seq__view.html new file mode 100644 index 00000000000..85eae4dbbdb --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view.html @@ -0,0 +1,220 @@ + + + + + + +Stan Math Library: stan::math::seq_view< T, S > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::seq_view< T, S > Class Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + + + + + +

+Public Member Functions

 seq_view (typename pass_type< S >::type x)
 
pass_type< T >::type operator[] (int n) const
 
int size () const
 
+

Detailed Description

+

template<typename T, typename S>
+class stan::math::seq_view< T, S >

+ + +

Definition at line 42 of file seq_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
stan::math::seq_view< T, S >::seq_view (typename pass_type< S >::type x)
+
+inlineexplicit
+
+ +

Definition at line 46 of file seq_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
pass_type<T>::type stan::math::seq_view< T, S >::operator[] (int n) const
+
+inline
+
+ +

Definition at line 50 of file seq_view.hpp.

+ +
+
+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + +
int stan::math::seq_view< T, S >::size () const
+
+inline
+
+ +

Definition at line 53 of file seq_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4-members.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4-members.html new file mode 100644 index 00000000000..75ce5902596 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > > Member List
+
+
+ +

This is the complete list of members for stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >, including all inherited members.

+ + + + +
operator[](int n) const stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >inline
seq_view(typename pass_type< Eigen::Matrix< S, 1, Eigen::Dynamic > >::type x)stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >inlineexplicit
size() const stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html new file mode 100644 index 00000000000..c72f1a92955 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html @@ -0,0 +1,220 @@ + + + + + + +Stan Math Library: stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > > Class Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + + + + + +

+Public Member Functions

 seq_view (typename pass_type< Eigen::Matrix< S, 1, Eigen::Dynamic > >::type x)
 
pass_type< T >::type operator[] (int n) const
 
int size () const
 
+

Detailed Description

+

template<typename T, typename S>
+class stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >

+ + +

Definition at line 78 of file seq_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >::seq_view (typename pass_type< Eigen::Matrix< S, 1, Eigen::Dynamic > >::type x)
+
+inlineexplicit
+
+ +

Definition at line 82 of file seq_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
pass_type<T>::type stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >::operator[] (int n) const
+
+inline
+
+ +

Definition at line 87 of file seq_view.hpp.

+ +
+
+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + +
int stan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >::size () const
+
+inline
+
+ +

Definition at line 90 of file seq_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4-members.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4-members.html new file mode 100644 index 00000000000..0d086bd6da5 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > > Member List
+
+
+ +

This is the complete list of members for stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >, including all inherited members.

+ + + + +
operator[](int n) const stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >inline
seq_view(typename pass_type< Eigen::Matrix< S, Eigen::Dynamic, 1 > >::type x)stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >inlineexplicit
size() const stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html new file mode 100644 index 00000000000..0fcf8c5f8f2 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html @@ -0,0 +1,220 @@ + + + + + + +Stan Math Library: stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > > Class Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + + + + + +

+Public Member Functions

 seq_view (typename pass_type< Eigen::Matrix< S, Eigen::Dynamic, 1 > >::type x)
 
pass_type< T >::type operator[] (int n) const
 
int size () const
 
+

Detailed Description

+

template<typename T, typename S>
+class stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >

+ + +

Definition at line 59 of file seq_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >::seq_view (typename pass_type< Eigen::Matrix< S, Eigen::Dynamic, 1 > >::type x)
+
+inlineexplicit
+
+ +

Definition at line 63 of file seq_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
pass_type<T>::type stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >::operator[] (int n) const
+
+inline
+
+ +

Definition at line 68 of file seq_view.hpp.

+ +
+
+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + +
int stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >::size () const
+
+inline
+
+ +

Definition at line 71 of file seq_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html new file mode 100644 index 00000000000..56f76bf5bad --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html @@ -0,0 +1,220 @@ + + + + + + +Stan Math Library: stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > > Class Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + + + + + +

+Public Member Functions

 seq_view (typename pass_type< Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >::type x)
 
pass_type< T >::type operator[] (int n) const
 
int size () const
 
+

Detailed Description

+

template<typename T, typename S>
+class stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >

+ + +

Definition at line 99 of file seq_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >::seq_view (typename pass_type< Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >::type x)
+
+inlineexplicit
+
+ +

Definition at line 105 of file seq_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
pass_type<T>::type stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >::operator[] (int n) const
+
+inline
+
+ +

Definition at line 110 of file seq_view.hpp.

+ +
+
+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + +
int stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >::size () const
+
+inline
+
+ +

Definition at line 113 of file seq_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_085212abef8028c93e19b6c8ba8c0204d.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_085212abef8028c93e19b6c8ba8c0204d.html new file mode 100644 index 00000000000..9cc813c8230 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_085212abef8028c93e19b6c8ba8c0204d.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > > Member List
+
+
+ +

This is the complete list of members for stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >, including all inherited members.

+ + + + +
operator[](int n) const stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >inline
seq_view(typename pass_type< Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >::type x)stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >inlineexplicit
size() const stan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html new file mode 100644 index 00000000000..ad9f4d1ebce --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::seq_view< T, std::vector< S > > Member List
+
+
+ +

This is the complete list of members for stan::math::seq_view< T, std::vector< S > >, including all inherited members.

+ + + + +
operator[](int n) const stan::math::seq_view< T, std::vector< S > >inline
seq_view(typename pass_type< std::vector< S > >::type x)stan::math::seq_view< T, std::vector< S > >inlineexplicit
size() const stan::math::seq_view< T, std::vector< S > >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html new file mode 100644 index 00000000000..c2d945f7ee6 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html @@ -0,0 +1,220 @@ + + + + + + +Stan Math Library: stan::math::seq_view< T, std::vector< S > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::seq_view< T, std::vector< S > > Class Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + + + + + +

+Public Member Functions

 seq_view (typename pass_type< std::vector< S > >::type x)
 
pass_type< T >::type operator[] (int n) const
 
int size () const
 
+

Detailed Description

+

template<typename T, typename S>
+class stan::math::seq_view< T, std::vector< S > >

+ + +

Definition at line 120 of file seq_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
stan::math::seq_view< T, std::vector< S > >::seq_view (typename pass_type< std::vector< S > >::type x)
+
+inlineexplicit
+
+ +

Definition at line 125 of file seq_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
pass_type<T>::type stan::math::seq_view< T, std::vector< S > >::operator[] (int n) const
+
+inline
+
+ +

Definition at line 130 of file seq_view.hpp.

+ +
+
+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + +
int stan::math::seq_view< T, std::vector< S > >::size () const
+
+inline
+
+ +

Definition at line 133 of file seq_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_t_01_4_01_4-members.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..aa9536dd31e --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_t_01_4_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::seq_view< T, std::vector< T > > Member List
+
+
+ +

This is the complete list of members for stan::math::seq_view< T, std::vector< T > >, including all inherited members.

+ + + + +
operator[](int n) const stan::math::seq_view< T, std::vector< T > >inline
seq_view(typename pass_type< std::vector< T > >::type x)stan::math::seq_view< T, std::vector< T > >inlineexplicit
size() const stan::math::seq_view< T, std::vector< T > >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_t_01_4_01_4.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..947ac944cba --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01_t_01_4_01_4.html @@ -0,0 +1,220 @@ + + + + + + +Stan Math Library: stan::math::seq_view< T, std::vector< T > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::seq_view< T, std::vector< T > > Class Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + + + + + +

+Public Member Functions

 seq_view (typename pass_type< std::vector< T > >::type x)
 
pass_type< T >::type operator[] (int n) const
 
int size () const
 
+

Detailed Description

+

template<typename T>
+class stan::math::seq_view< T, std::vector< T > >

+ + +

Definition at line 141 of file seq_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
stan::math::seq_view< T, std::vector< T > >::seq_view (typename pass_type< std::vector< T > >::type x)
+
+inlineexplicit
+
+ +

Definition at line 145 of file seq_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
pass_type<T>::type stan::math::seq_view< T, std::vector< T > >::operator[] (int n) const
+
+inline
+
+ +

Definition at line 149 of file seq_view.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
int stan::math::seq_view< T, std::vector< T > >::size () const
+
+inline
+
+ +

Definition at line 152 of file seq_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01std_1_1vector_3_01_t_01_4_01_4_01_4-members.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01std_1_1vector_3_01_t_01_4_01_4_01_4-members.html new file mode 100644 index 00000000000..06c90748f07 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01std_1_1vector_3_01_t_01_4_01_4_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::seq_view< T, std::vector< std::vector< T > > > Member List
+
+
+ +

This is the complete list of members for stan::math::seq_view< T, std::vector< std::vector< T > > >, including all inherited members.

+ + + + +
operator[](int n) const stan::math::seq_view< T, std::vector< std::vector< T > > >inline
seq_view(typename pass_type< std::vector< std::vector< T > > >::type x)stan::math::seq_view< T, std::vector< std::vector< T > > >inlineexplicit
size() const stan::math::seq_view< T, std::vector< std::vector< T > > >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01std_1_1vector_3_01_t_01_4_01_4_01_4.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01std_1_1vector_3_01_t_01_4_01_4_01_4.html new file mode 100644 index 00000000000..4c5264a90c3 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01_t_00_01std_1_1vector_3_01std_1_1vector_3_01_t_01_4_01_4_01_4.html @@ -0,0 +1,220 @@ + + + + + + +Stan Math Library: stan::math::seq_view< T, std::vector< std::vector< T > > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::seq_view< T, std::vector< std::vector< T > > > Class Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + + + + + +

+Public Member Functions

 seq_view (typename pass_type< std::vector< std::vector< T > > >::type x)
 
pass_type< T >::type operator[] (int n) const
 
int size () const
 
+

Detailed Description

+

template<typename T>
+class stan::math::seq_view< T, std::vector< std::vector< T > > >

+ + +

Definition at line 160 of file seq_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
stan::math::seq_view< T, std::vector< std::vector< T > > >::seq_view (typename pass_type< std::vector< std::vector< T > > >::type x)
+
+inlineexplicit
+
+ +

Definition at line 165 of file seq_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
pass_type<T>::type stan::math::seq_view< T, std::vector< std::vector< T > > >::operator[] (int n) const
+
+inline
+
+ +

Definition at line 170 of file seq_view.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
int stan::math::seq_view< T, std::vector< std::vector< T > > >::size () const
+
+inline
+
+ +

Definition at line 173 of file seq_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01double_00_01std_1_1vector_3_01int_01_4_01_4-members.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01double_00_01std_1_1vector_3_01int_01_4_01_4-members.html new file mode 100644 index 00000000000..3d7260edd95 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01double_00_01std_1_1vector_3_01int_01_4_01_4-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::seq_view< double, std::vector< int > > Member List
+
+
+ +

This is the complete list of members for stan::math::seq_view< double, std::vector< int > >, including all inherited members.

+ + + + +
operator[](int n) const stan::math::seq_view< double, std::vector< int > >inline
seq_view(pass_type< std::vector< int > >::type x)stan::math::seq_view< double, std::vector< int > >inlineexplicit
size() const stan::math::seq_view< double, std::vector< int > >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1seq__view_3_01double_00_01std_1_1vector_3_01int_01_4_01_4.html b/doc/api/html/classstan_1_1math_1_1seq__view_3_01double_00_01std_1_1vector_3_01int_01_4_01_4.html new file mode 100644 index 00000000000..457ecd1446b --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1seq__view_3_01double_00_01std_1_1vector_3_01int_01_4_01_4.html @@ -0,0 +1,214 @@ + + + + + + +Stan Math Library: stan::math::seq_view< double, std::vector< int > > Class Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::seq_view< double, std::vector< int > > Class Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + + + + + +

+Public Member Functions

 seq_view (pass_type< std::vector< int > >::type x)
 
pass_type< double >::type operator[] (int n) const
 
int size () const
 
+

Detailed Description

+

template<>
+class stan::math::seq_view< double, std::vector< int > >

+ + +

Definition at line 179 of file seq_view.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::seq_view< double, std::vector< int > >::seq_view (pass_type< std::vector< int > >::type x)
+
+inlineexplicit
+
+ +

Definition at line 183 of file seq_view.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
pass_type<double>::type stan::math::seq_view< double, std::vector< int > >::operator[] (int n) const
+
+inline
+
+ +

Definition at line 186 of file seq_view.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
int stan::math::seq_view< double, std::vector< int > >::size () const
+
+inline
+
+ +

Definition at line 189 of file seq_view.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1stack__alloc-members.html b/doc/api/html/classstan_1_1math_1_1stack__alloc-members.html new file mode 100644 index 00000000000..f71da1f1f2e --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1stack__alloc-members.html @@ -0,0 +1,123 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::stack_alloc Member List
+
+
+ +

This is the complete list of members for stan::math::stack_alloc, including all inherited members.

+ + + + + + + + + + +
alloc(size_t len)stan::math::stack_allocinline
alloc_array(size_t n)stan::math::stack_allocinline
bytes_allocated()stan::math::stack_allocinline
free_all()stan::math::stack_allocinline
recover_all()stan::math::stack_allocinline
recover_nested()stan::math::stack_allocinline
stack_alloc(size_t initial_nbytes=DEFAULT_INITIAL_NBYTES)stan::math::stack_allocinlineexplicit
start_nested()stan::math::stack_allocinline
~stack_alloc()stan::math::stack_allocinline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1stack__alloc.html b/doc/api/html/classstan_1_1math_1_1stack__alloc.html new file mode 100644 index 00000000000..c66a9eb88d8 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1stack__alloc.html @@ -0,0 +1,450 @@ + + + + + + +Stan Math Library: stan::math::stack_alloc Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::stack_alloc Class Reference
+
+
+ +

An instance of this class provides a memory pool through which blocks of raw memory may be allocated and then collected simultaneously. + More...

+ +

#include <stack_alloc.hpp>

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 stack_alloc (size_t initial_nbytes=DEFAULT_INITIAL_NBYTES)
 Construct a resizable stack allocator initially holding the specified number of bytes. More...
 
 ~stack_alloc ()
 Destroy this memory allocator. More...
 
void * alloc (size_t len)
 Return a newly allocated block of memory of the appropriate size managed by the stack allocator. More...
 
template<typename T >
T * alloc_array (size_t n)
 Allocate an array on the arena of the specified size to hold values of the specified template parameter type. More...
 
void recover_all ()
 Recover all the memory used by the stack allocator. More...
 
void start_nested ()
 Store current positions before doing nested operation so can recover back to start. More...
 
void recover_nested ()
 recover memory back to the last start_nested call. More...
 
void free_all ()
 Free all memory used by the stack allocator other than the initial block allocation back to the system. More...
 
size_t bytes_allocated ()
 Return number of bytes allocated to this instance by the heap. More...
 
+

Detailed Description

+

An instance of this class provides a memory pool through which blocks of raw memory may be allocated and then collected simultaneously.

+

This class is useful in settings where large numbers of small objects are allocated and then collected all at once. This may include objects whose destructors have no effect.

+

Memory is allocated on a stack of blocks. Each block allocated is twice as large as the previous one. The memory may be recovered, with the blocks being reused, or all blocks may be freed, resetting the stack of blocks to its original state.

+

Alignment up to 8 byte boundaries guaranteed for the first malloc, and after that it's up to the caller. On 64-bit architectures, all struct values should be padded to 8-byte boundaries if they contain an 8-byte member or a virtual function.

+ +

Definition at line 74 of file stack_alloc.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::stack_alloc::stack_alloc (size_t initial_nbytes = DEFAULT_INITIAL_NBYTES)
+
+inlineexplicit
+
+ +

Construct a resizable stack allocator initially holding the specified number of bytes.

+
Parameters
+ + +
initial_nbytesInitial number of bytes for the allocator. Defaults to (1 << 16) = 64KB initial bytes.
+
+
+
Exceptions
+ + +
std::runtime_errorif the underlying malloc is not 8-byte aligned.
+
+
+ +

Definition at line 131 of file stack_alloc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
stan::math::stack_alloc::~stack_alloc ()
+
+inline
+
+ +

Destroy this memory allocator.

+

This is implemented as a no-op as there is no destruction required.

+ +

Definition at line 147 of file stack_alloc.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
void* stan::math::stack_alloc::alloc (size_t len)
+
+inline
+
+ +

Return a newly allocated block of memory of the appropriate size managed by the stack allocator.

+

The allocated pointer will be 8-byte aligned.

+

This function may call C++'s malloc() function, with any exceptions percolated throught this function.

+
Parameters
+ + +
lenNumber of bytes to allocate.
+
+
+
Returns
A pointer to the allocated memory.
+ +

Definition at line 166 of file stack_alloc.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T* stan::math::stack_alloc::alloc_array (size_t n)
+
+inline
+
+ +

Allocate an array on the arena of the specified size to hold values of the specified template parameter type.

+
Template Parameters
+ + +
Ttype of entries in allocated array.
+
+
+
Parameters
+ + +
[in]nsize of array to allocate.
+
+
+
Returns
new array allocated on the arena.
+ +

Definition at line 186 of file stack_alloc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
size_t stan::math::stack_alloc::bytes_allocated ()
+
+inline
+
+ +

Return number of bytes allocated to this instance by the heap.

+

This is not the same as the number of bytes allocated through calls to memalloc_. The latter number is not calculatable because space is wasted at the end of blocks if the next alloc request doesn't fit. (Perhaps we could trim down to what is actually used?)

+
Returns
number of bytes allocated to this instance
+ +

Definition at line 255 of file stack_alloc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::stack_alloc::free_all ()
+
+inline
+
+ +

Free all memory used by the stack allocator other than the initial block allocation back to the system.

+

Note: the destructor will free all memory.

+ +

Definition at line 235 of file stack_alloc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::stack_alloc::recover_all ()
+
+inline
+
+ +

Recover all the memory used by the stack allocator.

+

The stack of memory blocks allocated so far will be available for further allocations. To free memory back to the system, use the function free_all().

+ +

Definition at line 197 of file stack_alloc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::stack_alloc::recover_nested ()
+
+inline
+
+ +

recover memory back to the last start_nested call.

+ +

Definition at line 216 of file stack_alloc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::stack_alloc::start_nested ()
+
+inline
+
+ +

Store current positions before doing nested operation so can recover back to start.

+ +

Definition at line 207 of file stack_alloc.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1stored__gradient__vari-members.html b/doc/api/html/classstan_1_1math_1_1stored__gradient__vari-members.html new file mode 100644 index 00000000000..573171a8120 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1stored__gradient__vari-members.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::stored_gradient_vari Member List
+
+
+ +

This is the complete list of members for stan::math::stored_gradient_vari, including all inherited members.

+ + + + + + + + + + + + + + + +
adj_stan::math::vari
chain()stan::math::stored_gradient_variinlinevirtual
dtrs_stan::math::stored_gradient_variprotected
init_dependent()stan::math::variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
partials_stan::math::stored_gradient_variprotected
set_zero_adjoint()stan::math::variinline
size_stan::math::stored_gradient_variprotected
stored_gradient_vari(double value, size_t size, vari **dtrs, double *partials)stan::math::stored_gradient_variinline
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1stored__gradient__vari.html b/doc/api/html/classstan_1_1math_1_1stored__gradient__vari.html new file mode 100644 index 00000000000..fe43c941934 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1stored__gradient__vari.html @@ -0,0 +1,345 @@ + + + + + + +Stan Math Library: stan::math::stored_gradient_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::stored_gradient_vari Class Reference
+
+
+ +

A var implementation that stores the daughter variable implementation pointers and the partial derivative with respect to the result explicitly in arrays constructed on the auto-diff memory stack. + More...

+ +

#include <stored_gradient_vari.hpp>

+
+Inheritance diagram for stan::math::stored_gradient_vari:
+
+
+ + +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 stored_gradient_vari (double value, size_t size, vari **dtrs, double *partials)
 Construct a stored gradient vari with the specified value, size, daughter varis, and partial derivatives. More...
 
void chain ()
 Propagate derivatives through this vari with partial derivatives given for the daughter vari by the stored partials. More...
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Protected Attributes

size_t size_
 
vari ** dtrs_
 
double * partials_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+

A var implementation that stores the daughter variable implementation pointers and the partial derivative with respect to the result explicitly in arrays constructed on the auto-diff memory stack.

+

Like a simplified version of OperandsAndPartials.

+ +

Definition at line 18 of file stored_gradient_vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::stored_gradient_vari::stored_gradient_vari (double value,
size_t size,
vari ** dtrs,
double * partials 
)
+
+inline
+
+ +

Construct a stored gradient vari with the specified value, size, daughter varis, and partial derivatives.

+
Parameters
+ + + + + +
[in]valueValue of vari
[in]sizeNumber of daughters
[in]dtrsArray of pointers to daughters
[in]partialsPartial derivatives of value with respect to daughters.
+
+
+ +

Definition at line 35 of file stored_gradient_vari.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::stored_gradient_vari::chain ()
+
+inlinevirtual
+
+ +

Propagate derivatives through this vari with partial derivatives given for the daughter vari by the stored partials.

+ +

Reimplemented from stan::math::vari.

+ +

Definition at line 49 of file stored_gradient_vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
vari** stan::math::stored_gradient_vari::dtrs_
+
+protected
+
+ +

Definition at line 21 of file stored_gradient_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double* stan::math::stored_gradient_vari::partials_
+
+protected
+
+ +

Definition at line 22 of file stored_gradient_vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
size_t stan::math::stored_gradient_vari::size_
+
+protected
+
+ +

Definition at line 20 of file stored_gradient_vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1stored__gradient__vari.png b/doc/api/html/classstan_1_1math_1_1stored__gradient__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..1e2b6f148152afe64d2f2d6cc605dcd11c5e028c GIT binary patch literal 688 zcmeAS@N?(olHy`uVBq!ia0vp^`+zurgBeIpcw!$5q$C1-LR|m<{|{uoc=NTi|Ih@G z90(scaDcV*jy#abQ4-`A%m7pb0#{Fk7%?y~*?YP;hEy=Vo%?XoW(6Ks{_8XM{a3CJ zbL32l-hDT1roQpscV0pk4^021&RUikW9WHl1y_ydr=SPklcv|T%~yH3^Vyd4nfm8c zPX77FwNGX5!tEa~&&}L@rsDMcrs#(4J!A#*gi{FZ@YmS?wC8Gsz$DMwRxP8szo3i^X6SOp5LQ(Y$^?9?%<)63A*3+N O#o+1c=d#Wzp$P!9_fd}k literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1sum__eigen__v__vari-members.html b/doc/api/html/classstan_1_1math_1_1sum__eigen__v__vari-members.html new file mode 100644 index 00000000000..fdcc4aa54b7 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1sum__eigen__v__vari-members.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::sum_eigen_v_vari Member List
+
+
+ +

This is the complete list of members for stan::math::sum_eigen_v_vari, including all inherited members.

+ + + + + + + + + + + + + + + + + + +
adj_stan::math::vari
chain()stan::math::sum_v_variinlinevirtual
init_dependent()stan::math::variinline
length_stan::math::sum_v_variprotected
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
sum_eigen_v_vari(const Eigen::Matrix< var, R1, C1 > &v1)stan::math::sum_eigen_v_variinlineexplicit
sum_of_val(const Eigen::DenseBase< Derived > &v)stan::math::sum_eigen_v_variinlineprotectedstatic
stan::math::sum_v_vari::sum_of_val(const std::vector< var > &v)stan::math::sum_v_variinlineprotectedstatic
sum_v_vari(double value, vari **v, size_t length)stan::math::sum_v_variinlineexplicit
sum_v_vari(const std::vector< var > &v1)stan::math::sum_v_variinlineexplicit
v_stan::math::sum_v_variprotected
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1sum__eigen__v__vari.html b/doc/api/html/classstan_1_1math_1_1sum__eigen__v__vari.html new file mode 100644 index 00000000000..133aaaca4a3 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1sum__eigen__v__vari.html @@ -0,0 +1,257 @@ + + + + + + +Stan Math Library: stan::math::sum_eigen_v_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::sum_eigen_v_vari Class Reference
+
+
+ +

Class for representing sums with constructors for Eigen. + More...

+ +

#include <sum.hpp>

+
+Inheritance diagram for stan::math::sum_eigen_v_vari:
+
+
+ + +stan::math::sum_v_vari +stan::math::vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

template<int R1, int C1>
 sum_eigen_v_vari (const Eigen::Matrix< var, R1, C1 > &v1)
 
- Public Member Functions inherited from stan::math::sum_v_vari
 sum_v_vari (double value, vari **v, size_t length)
 
 sum_v_vari (const std::vector< var > &v1)
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Static Protected Member Functions

template<typename Derived >
static double sum_of_val (const Eigen::DenseBase< Derived > &v)
 
- Static Protected Member Functions inherited from stan::math::sum_v_vari
static double sum_of_val (const std::vector< var > &v)
 
+ + + + + + + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
- Protected Attributes inherited from stan::math::sum_v_vari
vari ** v_
 
size_t length_
 
+

Detailed Description

+

Class for representing sums with constructors for Eigen.

+

The chain() method and member variables are managed by the superclass sum_v_vari.

+ +

Definition at line 17 of file sum.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<int R1, int C1>
+ + + + + +
+ + + + + + + + +
stan::math::sum_eigen_v_vari::sum_eigen_v_vari (const Eigen::Matrix< var, R1, C1 > & v1)
+
+inlineexplicit
+
+ +

Definition at line 29 of file sum.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename Derived >
+ + + + + +
+ + + + + + + + +
static double stan::math::sum_eigen_v_vari::sum_of_val (const Eigen::DenseBase< Derived > & v)
+
+inlinestaticprotected
+
+ +

Definition at line 20 of file sum.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1sum__eigen__v__vari.png b/doc/api/html/classstan_1_1math_1_1sum__eigen__v__vari.png new file mode 100644 index 0000000000000000000000000000000000000000..4cd54eed0581d81d5018b4a07d8e3299cf90859b GIT binary patch literal 950 zcmeAS@N?(olHy`uVBq!ia0vp^8-TcjgBeH`I80mvq$C1-LR|m<{|{uoc=NTi|Ih>= z3ycpOIKbL@M;^%KC<*clW&kPzfvcxNj2IZ0T|HeKLn;{G&VAkY%7BMWJznMB|B3#Y zm!4hvz3EwwiZYwW+|ySI5636<6smMgGU3zH@tn3}gG%Hl=Z6ZO*M07;tGYMm<$DhA zOTzQG+qWP6WypCpzWc$V9p7F&npu+D=XHr$j$3{48&mJA*VFcD-8k-jZSr?~QnO+2@2{Km?6i&-t9? zfBPhjbcg4WUP`h8Ykz&>FzH{Wa`)K(S*j<6#HXov$3#rhDNOX-lp@q;c&w4Z;32Dl z&|=R0am|wbYBoRnQf=mJm@mYzZHGaFsvb{5CpUA%qeBeS@NrLTACquz((ruz;LxO$ zPHyi>s@D%WPFgo}*WEXop5Ze7U)@_(Gv^0C{ID&;UTxveY{3|j>vFy}f6q-hr^@*? zWTr{YJda6bmcoABPnM>w{B>(hIP32UbE8r_VZD3yx}7Fk{cF>5z(H_q>Bbx93+Co{ z-g>%8W!hOQvAE{BZoxvcXRVl8r0x5qvta+m-G_REpMUh&;XY}b&8mm$he|i*w^}d$ zv*B-$=M>`wpLJ9x@^$#x=5KB~_1nk7|4XE&$EEv^b{~3wTxYDlU)ztd`&oelnAJDQ~_+72q^ZxP$7H9W9dv3g(!L-Tp-fF|w8-6|SEGS)EeW-Nd z7GaTv%L0#^r~N*3d;Mje>nHC4Q;c*UFvV?KkT?S zXWDI++c~*GyHCDcS8zU)*Iw|Q_m>?iucYqXE4ptbd~SEtxrTF_r?^z@vHrTJk>%9y zPg8b?oI5Q$m8HRQ{{Q+JoafJn)n3Uf+Vys;EVIe`_h~=wus)cyemctmb!f6V`P*Ni dMc~*&d4C~~h*h5J5`meF!PC{xWt~$(697)Qw^#rG literal 0 HcmV?d00001 diff --git a/doc/api/html/classstan_1_1math_1_1sum__v__vari-members.html b/doc/api/html/classstan_1_1math_1_1sum__v__vari-members.html new file mode 100644 index 00000000000..ec560323268 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1sum__v__vari-members.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::sum_v_vari Member List
+
+
+ +

This is the complete list of members for stan::math::sum_v_vari, including all inherited members.

+ + + + + + + + + + + + + + + + +
adj_stan::math::vari
chain()stan::math::sum_v_variinlinevirtual
init_dependent()stan::math::variinline
length_stan::math::sum_v_variprotected
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
set_zero_adjoint()stan::math::variinline
sum_of_val(const std::vector< var > &v)stan::math::sum_v_variinlineprotectedstatic
sum_v_vari(double value, vari **v, size_t length)stan::math::sum_v_variinlineexplicit
sum_v_vari(const std::vector< var > &v1)stan::math::sum_v_variinlineexplicit
v_stan::math::sum_v_variprotected
val_stan::math::vari
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1sum__v__vari.html b/doc/api/html/classstan_1_1math_1_1sum__v__vari.html new file mode 100644 index 00000000000..38b1b481aeb --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1sum__v__vari.html @@ -0,0 +1,365 @@ + + + + + + +Stan Math Library: stan::math::sum_v_vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+ +
+ +

Class for sums of variables constructed with standard vectors. + More...

+ +

#include <sum.hpp>

+
+Inheritance diagram for stan::math::sum_v_vari:
+
+
+ + +stan::math::vari +stan::math::sum_eigen_v_vari + +
+ + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 sum_v_vari (double value, vari **v, size_t length)
 
 sum_v_vari (const std::vector< var > &v1)
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
- Public Member Functions inherited from stan::math::vari
 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + +

+Static Protected Member Functions

static double sum_of_val (const std::vector< var > &v)
 
+ + + + + +

+Protected Attributes

vari ** v_
 
size_t length_
 
+ + + + + + + + + + + + + + + +

+Additional Inherited Members

- Static Public Member Functions inherited from stan::math::vari
static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
- Public Attributes inherited from stan::math::vari
const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+

Detailed Description

+

Class for sums of variables constructed with standard vectors.

+

There's an extension for Eigen matrices.

+ +

Definition at line 14 of file sum.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::sum_v_vari::sum_v_vari (double value,
vari ** v,
size_t length 
)
+
+inlineexplicit
+
+ +

Definition at line 27 of file sum.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::sum_v_vari::sum_v_vari (const std::vector< var > & v1)
+
+inlineexplicit
+
+ +

Definition at line 31 of file sum.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
virtual void stan::math::sum_v_vari::chain ()
+
+inlinevirtual
+
+ +

Apply the chain rule to this variable based on the variables on which it depends.

+

The base implementation in this class is a no-op.

+ +

Reimplemented from stan::math::vari.

+ +

Definition at line 40 of file sum.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
static double stan::math::sum_v_vari::sum_of_val (const std::vector< var > & v)
+
+inlinestaticprotected
+
+ +

Definition at line 19 of file sum.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
size_t stan::math::sum_v_vari::length_
+
+protected
+
+ +

Definition at line 17 of file sum.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
vari** stan::math::sum_v_vari::v_
+
+protected
+
+ +

Definition at line 16 of file sum.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
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+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::var Member List
+
+
+ +

This is the complete list of members for stan::math::var, including all inherited members.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
adj() const stan::math::varinline
grad(std::vector< var > &x, std::vector< double > &g)stan::math::varinline
grad()stan::math::varinline
is_uninitialized()stan::math::varinline
operator*()stan::math::varinline
operator*=(const var &b)stan::math::varinline
operator*=(const double b)stan::math::varinline
operator+=(const var &b)stan::math::varinline
operator+=(const double b)stan::math::varinline
operator-=(const var &b)stan::math::varinline
operator-=(const double b)stan::math::varinline
operator->()stan::math::varinline
operator/=(const var &b)stan::math::varinline
operator/=(const double b)stan::math::varinline
operator<<(std::ostream &os, const var &v)stan::math::varfriend
Scalar typedefstan::math::var
val() const stan::math::varinline
var()stan::math::varinline
var(vari *vi)stan::math::varinline
var(float x)stan::math::varinline
var(double x)stan::math::varinline
var(long double x)stan::math::varinline
var(bool x)stan::math::varinline
var(char x)stan::math::varinline
var(short x)stan::math::varinline
var(int x)stan::math::varinline
var(long x)stan::math::varinline
var(unsigned char x)stan::math::varinline
var(unsigned short x)stan::math::varinline
var(unsigned int x)stan::math::varinline
var(unsigned long x)stan::math::varinline
vi_stan::math::var
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1var.html b/doc/api/html/classstan_1_1math_1_1var.html new file mode 100644 index 00000000000..00acd7dc124 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1var.html @@ -0,0 +1,1302 @@ + + + + + + +Stan Math Library: stan::math::var Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::var Class Reference
+
+
+ +

Independent (input) and dependent (output) variables for gradients. + More...

+ +

#include <var.hpp>

+ + + + +

+Public Types

typedef double Scalar
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

bool is_uninitialized ()
 Return true if this variable has been declared, but not been defined. More...
 
 var ()
 Construct a variable for later assignment. More...
 
 var (vari *vi)
 Construct a variable from a pointer to a variable implementation. More...
 
 var (float x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (double x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument as a value and a zero adjoint. More...
 
 var (long double x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (bool x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (char x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (short x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (int x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (long x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (unsigned char x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (unsigned short x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (unsigned int x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
 var (unsigned long x)
 Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint. More...
 
double val () const
 Return the value of this variable. More...
 
double adj () const
 Return the derivative of the root expression with respect to this expression. More...
 
void grad (std::vector< var > &x, std::vector< double > &g)
 Compute the gradient of this (dependent) variable with respect to the specified vector of (independent) variables, assigning the specified vector to the gradient. More...
 
void grad ()
 Compute the gradient of this (dependent) variable with respect to all (independent) variables. More...
 
varioperator* ()
 Return a reference to underlying implementation of this variable. More...
 
varioperator-> ()
 Return a pointer to the underlying implementation of this variable. More...
 
varoperator+= (const var &b)
 The compound add/assignment operator for variables (C++). More...
 
varoperator+= (const double b)
 The compound add/assignment operator for scalars (C++). More...
 
varoperator-= (const var &b)
 The compound subtract/assignment operator for variables (C++). More...
 
varoperator-= (const double b)
 The compound subtract/assignment operator for scalars (C++). More...
 
varoperator*= (const var &b)
 The compound multiply/assignment operator for variables (C++). More...
 
varoperator*= (const double b)
 The compound multiply/assignment operator for scalars (C++). More...
 
varoperator/= (const var &b)
 The compound divide/assignment operator for variables (C++). More...
 
varoperator/= (const double b)
 The compound divide/assignment operator for scalars (C++). More...
 
+ + + + +

+Public Attributes

varivi_
 Pointer to the implementation of this variable. More...
 
+ + + + +

+Friends

std::ostream & operator<< (std::ostream &os, const var &v)
 Write the value of this auto-dif variable and its adjoint to the specified output stream. More...
 
+

Detailed Description

+

Independent (input) and dependent (output) variables for gradients.

+

This class acts as a smart pointer, with resources managed by an agenda-based memory manager scoped to a single gradient calculation.

+

An var is constructed with a double and used like any other scalar. Arithmetical functions like negation, addition, and subtraction, as well as a range of mathematical functions like exponentiation and powers are overridden to operate on var values objects.

+ +

Definition at line 31 of file var.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef double stan::math::var::Scalar
+
+ +

Definition at line 34 of file var.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + +
stan::math::var::var ()
+
+inline
+
+ +

Construct a variable for later assignment.

+

This is implemented as a no-op, leaving the underlying implementation dangling. Before an assignment, the behavior is thus undefined just as for a basic double.

+ +

Definition at line 65 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (varivi)
+
+inline
+
+ +

Construct a variable from a pointer to a variable implementation.

+
Parameters
+ + +
viVariable implementation.
+
+
+ +

Definition at line 73 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (float x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 82 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (double x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument as a value and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 91 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (long double x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 100 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (bool x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 109 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (char x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 118 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (short x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 127 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (int x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 136 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (long x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 145 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (unsigned char x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 154 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (unsigned short x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 164 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (unsigned int x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 173 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::var::var (unsigned long x)
+
+inline
+
+ +

Construct a variable from the specified arithmetic argument by constructing a new vari with the argument cast to double, and a zero adjoint.

+
Parameters
+ + +
xValue of the variable.
+
+
+ +

Definition at line 183 of file var.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::var::adj () const
+
+inline
+
+ +

Return the derivative of the root expression with respect to this expression.

+

This method only works after one of the grad() methods has been called.

+
Returns
Adjoint for this variable.
+ +

Definition at line 245 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::var::grad (std::vector< var > & x,
std::vector< double > & g 
)
+
+inline
+
+ +

Compute the gradient of this (dependent) variable with respect to the specified vector of (independent) variables, assigning the specified vector to the gradient.

+

The grad() function does not recover memory. In Stan 2.4 and earlier, this function did recover memory.

+
Parameters
+ + + +
xVector of independent variables.
gGradient vector of partial derivatives of this variable with respect to x.
+
+
+ +

Definition at line 261 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::var::grad ()
+
+inline
+
+ +

Compute the gradient of this (dependent) variable with respect to all (independent) variables.

+

The grad() function does not recover memory.

+ +

Definition at line 275 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
bool stan::math::var::is_uninitialized ()
+
+inline
+
+ +

Return true if this variable has been declared, but not been defined.

+

Any attempt to use an undefined variable's value or adjoint will result in a segmentation fault.

+
Returns
true if this variable does not yet have a defined variable.
+ +

Definition at line 54 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
vari& stan::math::var::operator* ()
+
+inline
+
+ +

Return a reference to underlying implementation of this variable.

+

If x is of type var, then applying this operator, *x, has the same behavior as *(x.vi_).

+

Warning: The returned reference does not track changes to this variable.

+
Returns
variable
+ +

Definition at line 293 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var & stan::math::var::operator*= (const varb)
+
+inline
+
+ +

The compound multiply/assignment operator for variables (C++).

+

If this variable is a and the argument is the variable b, then (a *= b) behaves exactly the same way as (a = a * b). Note that the result is an assignable lvalue.

+
Parameters
+ + +
bThe variable to multiply this variable by.
+
+
+
Returns
The result of multiplying this variable by the specified variable.
+ +

Definition at line 10 of file operator_multiply_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var & stan::math::var::operator*= (const double b)
+
+inline
+
+ +

The compound multiply/assignment operator for scalars (C++).

+

If this variable is a and the argument is the scalar b, then (a *= b) behaves exactly the same way as (a = a * b). Note that the result is an assignable lvalue.

+
Parameters
+ + +
bThe scalar to multiply this variable by.
+
+
+
Returns
The result of multplying this variable by the specified variable.
+ +

Definition at line 15 of file operator_multiply_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var & stan::math::var::operator+= (const varb)
+
+inline
+
+ +

The compound add/assignment operator for variables (C++).

+

If this variable is a and the argument is the variable b, then (a += b) behaves exactly the same way as (a = a + b), creating an intermediate variable representing (a + b).

+
Parameters
+ + +
bThe variable to add to this variable.
+
+
+
Returns
The result of adding the specified variable to this variable.
+ +

Definition at line 10 of file operator_plus_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var & stan::math::var::operator+= (const double b)
+
+inline
+
+ +

The compound add/assignment operator for scalars (C++).

+

If this variable is a and the argument is the scalar b, then (a += b) behaves exactly the same way as (a = a + b). Note that the result is an assignable lvalue.

+
Parameters
+ + +
bThe scalar to add to this variable.
+
+
+
Returns
The result of adding the specified variable to this variable.
+ +

Definition at line 15 of file operator_plus_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var & stan::math::var::operator-= (const varb)
+
+inline
+
+ +

The compound subtract/assignment operator for variables (C++).

+

If this variable is a and the argument is the variable b, then (a -= b) behaves exactly the same way as (a = a - b). Note that the result is an assignable lvalue.

+
Parameters
+ + +
bThe variable to subtract from this variable.
+
+
+
Returns
The result of subtracting the specified variable from this variable.
+ +

Definition at line 10 of file operator_minus_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var & stan::math::var::operator-= (const double b)
+
+inline
+
+ +

The compound subtract/assignment operator for scalars (C++).

+

If this variable is a and the argument is the scalar b, then (a -= b) behaves exactly the same way as (a = a - b). Note that the result is an assignable lvalue.

+
Parameters
+ + +
bThe scalar to subtract from this variable.
+
+
+
Returns
The result of subtracting the specified variable from this variable.
+ +

Definition at line 15 of file operator_minus_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
vari* stan::math::var::operator-> ()
+
+inline
+
+ +

Return a pointer to the underlying implementation of this variable.

+

If x is of type var, then applying this operator, x->, behaves the same way as x.vi_->.

+

Warning: The returned result does not track changes to this variable.

+ +

Definition at line 307 of file var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var & stan::math::var::operator/= (const varb)
+
+inline
+
+ +

The compound divide/assignment operator for variables (C++).

+

If this variable is a and the argument is the variable b, then (a /= b) behaves exactly the same way as (a = a / b). Note that the result is an assignable lvalue.

+
Parameters
+ + +
bThe variable to divide this variable by.
+
+
+
Returns
The result of dividing this variable by the specified variable.
+ +

Definition at line 10 of file operator_divide_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var & stan::math::var::operator/= (const double b)
+
+inline
+
+ +

The compound divide/assignment operator for scalars (C++).

+

If this variable is a and the argument is the scalar b, then (a /= b) behaves exactly the same way as (a = a / b). Note that the result is an assignable lvalue.

+
Parameters
+ + +
bThe scalar to divide this variable by.
+
+
+
Returns
The result of dividing this variable by the specified variable.
+ +

Definition at line 15 of file operator_divide_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::var::val () const
+
+inline
+
+ +

Return the value of this variable.

+
Returns
The value of this variable.
+ +

Definition at line 233 of file var.hpp.

+ +
+
+

Friends And Related Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
std::ostream& operator<< (std::ostream & os,
const varv 
)
+
+friend
+
+ +

Write the value of this auto-dif variable and its adjoint to the specified output stream.

+
Parameters
+ + + +
osOutput stream to which to write.
vVariable to write.
+
+
+
Returns
Reference to the specified output stream.
+ +

Definition at line 422 of file var.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + +
vari* stan::math::var::vi_
+
+ +

Pointer to the implementation of this variable.

+

This value should not be modified, but may be accessed in var operators to construct vari instances.

+ +

Definition at line 43 of file var.hpp.

+ +
+
+
The documentation for this class was generated from the following files: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1vari-members.html b/doc/api/html/classstan_1_1math_1_1vari-members.html new file mode 100644 index 00000000000..dd833c36019 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1vari-members.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::vari Member List
+
+
+ +

This is the complete list of members for stan::math::vari, including all inherited members.

+ + + + + + + + + + + + + +
adj_stan::math::vari
chain()stan::math::variinlinevirtual
init_dependent()stan::math::variinline
operator delete(void *)stan::math::variinlinestatic
operator new(size_t nbytes)stan::math::variinlinestatic
operator<<(std::ostream &os, const vari *v)stan::math::varifriend
set_zero_adjoint()stan::math::variinline
val_stan::math::vari
var classstan::math::varifriend
vari(const double x)stan::math::variinlineexplicit
vari(const double x, bool stacked)stan::math::variinline
~vari()stan::math::variinlinevirtual
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1vari.html b/doc/api/html/classstan_1_1math_1_1vari.html new file mode 100644 index 00000000000..7edc448ee44 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1vari.html @@ -0,0 +1,569 @@ + + + + + + +Stan Math Library: stan::math::vari Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+ +
+ +

The variable implementation base class. + More...

+ +

#include <vari.hpp>

+
+Inheritance diagram for stan::math::vari:
+
+
+ + +stan::math::cholesky_decompose_v_vari +stan::math::gevv_vvv_vari +stan::math::op_ddv_vari +stan::math::op_dv_vari +stan::math::op_dvd_vari +stan::math::op_dvv_vari +stan::math::op_matrix_vari +stan::math::op_v_vari +stan::math::op_vd_vari +stan::math::op_vdd_vari +stan::math::op_vdv_vari +stan::math::op_vector_vari +stan::math::op_vv_vari +stan::math::op_vvd_vari +stan::math::op_vvv_vari +stan::math::precomputed_gradients_vari +stan::math::stored_gradient_vari +stan::math::sum_v_vari + +
+ + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 vari (const double x)
 Construct a variable implementation from a value. More...
 
 vari (const double x, bool stacked)
 
virtual ~vari ()
 Throw an illegal argument exception. More...
 
virtual void chain ()
 Apply the chain rule to this variable based on the variables on which it depends. More...
 
void init_dependent ()
 Initialize the adjoint for this (dependent) variable to 1. More...
 
void set_zero_adjoint ()
 Set the adjoint value of this variable to 0. More...
 
+ + + + + + + +

+Static Public Member Functions

static void * operator new (size_t nbytes)
 Allocate memory from the underlying memory pool. More...
 
static void operator delete (void *)
 Delete a pointer from the underlying memory pool. More...
 
+ + + + + + + +

+Public Attributes

const double val_
 The value of this variable. More...
 
double adj_
 The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable. More...
 
+ + + + + + +

+Friends

class var
 
std::ostream & operator<< (std::ostream &os, const vari *v)
 Insertion operator for vari. More...
 
+

Detailed Description

+

The variable implementation base class.

+

This class is complete (not abstract) and may be used for constants.

+

A variable implementation is constructed with a constant value. It also stores the adjoint for storing the partial derivative with respect to the root of the derivative tree.

+

The chain() method applies the chain rule. Concrete extensions of this class will represent base variables or the result of operations such as addition or subtraction. These extended classes will store operand variables and propagate derivative information via an implementation of chain().

+ +

Definition at line 30 of file vari.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::vari::vari (const double x)
+
+inlineexplicit
+
+ +

Construct a variable implementation from a value.

+

The adjoint is initialized to zero.

+

All constructed variables are added to the stack. Variables should be constructed before variables on which they depend to insure proper partial derivative propagation. During derivative propagation, the chain() method of each variable will be called in the reverse order of construction.

+
Parameters
+ + +
xValue of the constructed variable.
+
+
+ +

Definition at line 58 of file vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::vari::vari (const double x,
bool stacked 
)
+
+inline
+
+ +

Definition at line 64 of file vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
virtual stan::math::vari::~vari ()
+
+inlinevirtual
+
+ +

Throw an illegal argument exception.

+

Warning: Destructors should never called for var objects.

+
Exceptions
+ + +
Logicexception always.
+
+
+ +

Definition at line 80 of file vari.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
virtual void stan::math::vari::chain ()
+
+inlinevirtual
+
+ +

Apply the chain rule to this variable based on the variables on which it depends.

+

The base implementation in this class is a no-op.

+ +

Reimplemented in stan::math::precomputed_gradients_vari, stan::math::cholesky_decompose_v_vari, stan::math::stored_gradient_vari, stan::math::gevv_vvv_vari, stan::math::sum_v_vari, stan::math::precomp_vvv_vari, stan::math::precomp_vv_vari, and stan::math::precomp_v_vari.

+ +

Definition at line 89 of file vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::vari::init_dependent ()
+
+inline
+
+ +

Initialize the adjoint for this (dependent) variable to 1.

+

This operation is applied to the dependent variable before propagating derivatives, setting the derivative of the result with respect to itself to be 1.

+ +

Definition at line 98 of file vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
static void stan::math::vari::operator delete (void * )
+
+inlinestatic
+
+ +

Delete a pointer from the underlying memory pool.

+

This no-op implementation enables a subclass to throw exceptions in its constructor. An exception thrown in the constructor of a subclass will result in an error being raised, which is in turn caught and calls delete().

+

See the discussion of "plugging the memory leak" in: http://www.parashift.com/c++-faq/memory-pools.html

+ +

Definition at line 149 of file vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
static void* stan::math::vari::operator new (size_t nbytes)
+
+inlinestatic
+
+ +

Allocate memory from the underlying memory pool.

+

This memory is is managed as a whole externally.

+

Warning: Classes should not be allocated with this operator if they have non-trivial destructors.

+
Parameters
+ + +
nbytesNumber of bytes to allocate.
+
+
+
Returns
Pointer to allocated bytes.
+ +

Definition at line 134 of file vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::vari::set_zero_adjoint ()
+
+inline
+
+ +

Set the adjoint value of this variable to 0.

+

This is used to reset adjoints before propagating derivatives again (for example in a Jacobian calculation).

+ +

Definition at line 107 of file vari.hpp.

+ +
+
+

Friends And Related Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
std::ostream& operator<< (std::ostream & os,
const variv 
)
+
+friend
+
+ +

Insertion operator for vari.

+

Prints the current value and the adjoint value.

+
Parameters
+ + + +
os[in, out] ostream to modify
v[in] vari object to print.
+
+
+
Returns
The modified ostream.
+ +

Definition at line 120 of file vari.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
friend class var
+
+friend
+
+ +

Definition at line 32 of file vari.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + +
double stan::math::vari::adj_
+
+ +

The adjoint of this variable, which is the partial derivative of this variable with respect to the root variable.

+ +

Definition at line 44 of file vari.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::vari::val_
+
+ +

The value of this variable.

+ +

Definition at line 38 of file vari.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
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+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::welford_covar_estimator Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1welford__covar__estimator.html b/doc/api/html/classstan_1_1math_1_1welford__covar__estimator.html new file mode 100644 index 00000000000..3e832d8c12a --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1welford__covar__estimator.html @@ -0,0 +1,371 @@ + + + + + + +Stan Math Library: stan::math::welford_covar_estimator Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::welford_covar_estimator Class Reference
+
+
+ +

#include <welford_covar_estimator.hpp>

+ + + + + + + + + + + + + + +

+Public Member Functions

 welford_covar_estimator (int n)
 
void restart ()
 
void add_sample (const Eigen::VectorXd &q)
 
int num_samples ()
 
void sample_mean (Eigen::VectorXd &mean)
 
void sample_covariance (Eigen::MatrixXd &covar)
 
+ + + + + + + +

+Protected Attributes

double _num_samples
 
Eigen::VectorXd _m
 
Eigen::MatrixXd _m2
 
+

Detailed Description

+
+

Definition at line 11 of file welford_covar_estimator.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::welford_covar_estimator::welford_covar_estimator (int n)
+
+inlineexplicit
+
+ +

Definition at line 13 of file welford_covar_estimator.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
void stan::math::welford_covar_estimator::add_sample (const Eigen::VectorXd & q)
+
+inline
+
+ +

Definition at line 25 of file welford_covar_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
int stan::math::welford_covar_estimator::num_samples ()
+
+inline
+
+ +

Definition at line 33 of file welford_covar_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::welford_covar_estimator::restart ()
+
+inline
+
+ +

Definition at line 19 of file welford_covar_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
void stan::math::welford_covar_estimator::sample_covariance (Eigen::MatrixXd & covar)
+
+inline
+
+ +

Definition at line 37 of file welford_covar_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
void stan::math::welford_covar_estimator::sample_mean (Eigen::VectorXd & mean)
+
+inline
+
+ +

Definition at line 35 of file welford_covar_estimator.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
Eigen::VectorXd stan::math::welford_covar_estimator::_m
+
+protected
+
+ +

Definition at line 45 of file welford_covar_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
Eigen::MatrixXd stan::math::welford_covar_estimator::_m2
+
+protected
+
+ +

Definition at line 46 of file welford_covar_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::welford_covar_estimator::_num_samples
+
+protected
+
+ +

Definition at line 43 of file welford_covar_estimator.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1welford__var__estimator-members.html b/doc/api/html/classstan_1_1math_1_1welford__var__estimator-members.html new file mode 100644 index 00000000000..168585102ca --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1welford__var__estimator-members.html @@ -0,0 +1,123 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::welford_var_estimator Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/classstan_1_1math_1_1welford__var__estimator.html b/doc/api/html/classstan_1_1math_1_1welford__var__estimator.html new file mode 100644 index 00000000000..c9e2eafcab3 --- /dev/null +++ b/doc/api/html/classstan_1_1math_1_1welford__var__estimator.html @@ -0,0 +1,371 @@ + + + + + + +Stan Math Library: stan::math::welford_var_estimator Class Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::welford_var_estimator Class Reference
+
+
+ +

#include <welford_var_estimator.hpp>

+ + + + + + + + + + + + + + +

+Public Member Functions

 welford_var_estimator (int n)
 
void restart ()
 
void add_sample (const Eigen::VectorXd &q)
 
int num_samples ()
 
void sample_mean (Eigen::VectorXd &mean)
 
void sample_variance (Eigen::VectorXd &var)
 
+ + + + + + + +

+Protected Attributes

double _num_samples
 
Eigen::VectorXd _m
 
Eigen::VectorXd _m2
 
+

Detailed Description

+
+

Definition at line 11 of file welford_var_estimator.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::welford_var_estimator::welford_var_estimator (int n)
+
+inlineexplicit
+
+ +

Definition at line 13 of file welford_var_estimator.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
void stan::math::welford_var_estimator::add_sample (const Eigen::VectorXd & q)
+
+inline
+
+ +

Definition at line 25 of file welford_var_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
int stan::math::welford_var_estimator::num_samples ()
+
+inline
+
+ +

Definition at line 33 of file welford_var_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
void stan::math::welford_var_estimator::restart ()
+
+inline
+
+ +

Definition at line 19 of file welford_var_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
void stan::math::welford_var_estimator::sample_mean (Eigen::VectorXd & mean)
+
+inline
+
+ +

Definition at line 35 of file welford_var_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
void stan::math::welford_var_estimator::sample_variance (Eigen::VectorXd & var)
+
+inline
+
+ +

Definition at line 37 of file welford_var_estimator.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
Eigen::VectorXd stan::math::welford_var_estimator::_m
+
+protected
+
+ +

Definition at line 45 of file welford_var_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
Eigen::VectorXd stan::math::welford_var_estimator::_m2
+
+protected
+
+ +

Definition at line 46 of file welford_var_estimator.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
double stan::math::welford_var_estimator::_num_samples
+
+protected
+
+ +

Definition at line 43 of file welford_var_estimator.hpp.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/closed.png b/doc/api/html/closed.png new file mode 100644 index 0000000000000000000000000000000000000000..98cc2c909da37a6df914fbf67780eebd99c597f5 GIT binary patch literal 132 zcmeAS@N?(olHy`uVBq!ia0vp^oFL4>1|%O$WD@{V-kvUwAr*{o@8{^CZMh(5KoB^r_<4^zF@3)Cp&&t3hdujKf f*?bjBoY!V+E))@{xMcbjXe@)LtDnm{r-UW|*e5JT literal 0 HcmV?d00001 diff --git a/doc/api/html/col_8hpp.html b/doc/api/html/col_8hpp.html new file mode 100644 index 00000000000..adcf5222979 --- /dev/null +++ b/doc/api/html/col_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/col.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
col.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::col (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t j)
 Return the specified column of the specified matrix using start-at-1 indexing. More...
 
+
+
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diff --git a/doc/api/html/col_8hpp_source.html b/doc/api/html/col_8hpp_source.html new file mode 100644 index 00000000000..63e7cbe7707 --- /dev/null +++ b/doc/api/html/col_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/col.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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col.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_COL_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COL_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
21  template <typename T>
+
22  inline
+
23  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
24  col(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m,
+
25  size_t j) {
+
26  stan::math::check_column_index("col", "j", m, j);
+
27  return m.col(j - 1);
+
28  }
+
29 
+
30  }
+
31 }
+
32 #endif
+ + +
Eigen::Matrix< T, Eigen::Dynamic, 1 > col(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t j)
Return the specified column of the specified matrix using start-at-1 indexing.
Definition: col.hpp:24
+ +
bool check_column_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
Return true if the specified index is a valid column of the matrix.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cols_8hpp.html b/doc/api/html/cols_8hpp.html new file mode 100644 index 00000000000..818f9a5b9b5 --- /dev/null +++ b/doc/api/html/cols_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cols.hpp File Reference + + + + + + + + + + +
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cols.hpp File Reference
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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T , int R, int C>
int stan::math::cols (const Eigen::Matrix< T, R, C > &m)
 Return the number of columns in the specified matrix, vector, or row vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cols_8hpp_source.html b/doc/api/html/cols_8hpp_source.html new file mode 100644 index 00000000000..249e6649d2e --- /dev/null +++ b/doc/api/html/cols_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cols.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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cols.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_COLS_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COLS_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
19  template <typename T, int R, int C>
+
20  inline int cols(const Eigen::Matrix<T, R, C>& m) {
+
21  return m.cols();
+
22  }
+
23 
+
24  }
+
25 }
+
26 #endif
+ +
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ +
+
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diff --git a/doc/api/html/common__type_8hpp.html b/doc/api/html/common__type_8hpp.html new file mode 100644 index 00000000000..89dcbed05b7 --- /dev/null +++ b/doc/api/html/common__type_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/common_type.hpp File Reference + + + + + + + + + + +
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common_type.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <vector>
+
+

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+ + + + + + + + +

+Classes

struct  stan::math::common_type< T1, T2 >
 
struct  stan::math::common_type< std::vector< T1 >, std::vector< T2 > >
 
struct  stan::math::common_type< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/common__type_8hpp_source.html b/doc/api/html/common__type_8hpp_source.html new file mode 100644 index 00000000000..edd69c4f163 --- /dev/null +++ b/doc/api/html/common__type_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/common_type.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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common_type.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_COMMON_TYPE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COMMON_TYPE_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+
6 #include <vector>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T1, typename T2>
+
13  struct common_type {
+
14  typedef typename boost::math::tools::promote_args<T1, T2>::type type;
+
15  };
+
16 
+
17  template <typename T1, typename T2>
+
18  struct common_type<std::vector<T1>, std::vector<T2> > {
+
19  typedef std::vector<typename common_type<T1, T2>::type> type;
+
20  };
+
21 
+
22  template <typename T1, typename T2, int R, int C>
+
23  struct common_type<Eigen::Matrix<T1, R, C>, Eigen::Matrix<T2, R, C> > {
+
24  typedef Eigen::Matrix<typename common_type<T1, T2>::type, R, C> type;
+
25  };
+
26 
+
27  }
+
28 }
+
29 
+
30 
+
31 #endif
+
std::vector< typename common_type< T1, T2 >::type > type
Definition: common_type.hpp:19
+ + + +
(Expert) Numerical traits for algorithmic differentiation variables.
+
Eigen::Matrix< typename common_type< T1, T2 >::type, R, C > type
Definition: common_type.hpp:24
+ +
boost::math::tools::promote_args< T1, T2 >::type type
Definition: common_type.hpp:14
+
+
+
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diff --git a/doc/api/html/constants_8hpp.html b/doc/api/html/constants_8hpp.html new file mode 100644 index 00000000000..eb44c5f2dee --- /dev/null +++ b/doc/api/html/constants_8hpp.html @@ -0,0 +1,226 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/constants.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
constants.hpp File Reference
+
+
+
#include <boost/math/constants/constants.hpp>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

double stan::math::pi ()
 Return the value of pi. More...
 
double stan::math::e ()
 Return the base of the natural logarithm. More...
 
double stan::math::sqrt2 ()
 Return the square root of two. More...
 
double stan::math::log10 ()
 Return natural logarithm of ten. More...
 
double stan::math::positive_infinity ()
 Return positive infinity. More...
 
double stan::math::negative_infinity ()
 Return negative infinity. More...
 
double stan::math::not_a_number ()
 Return (quiet) not-a-number. More...
 
double stan::math::machine_precision ()
 Returns the difference between 1.0 and the next value representable. More...
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Variables

const double stan::math::E = boost::math::constants::e<double>()
 The base of the natural logarithm, $ e $. More...
 
const double stan::math::SQRT_2 = std::sqrt(2.0)
 The value of the square root of 2, $ \sqrt{2} $. More...
 
const double stan::math::INV_SQRT_2 = 1.0 / SQRT_2
 The value of 1 over the square root of 2, $ 1 / \sqrt{2} $. More...
 
const double stan::math::LOG_2 = std::log(2.0)
 The natural logarithm of 2, $ \log 2 $. More...
 
const double stan::math::LOG_10 = std::log(10.0)
 The natural logarithm of 10, $ \log 10 $. More...
 
const double stan::math::INFTY = std::numeric_limits<double>::infinity()
 Positive infinity. More...
 
const double stan::math::NEGATIVE_INFTY = - std::numeric_limits<double>::infinity()
 Negative infinity. More...
 
const double stan::math::NOT_A_NUMBER = std::numeric_limits<double>::quiet_NaN()
 (Quiet) not-a-number value. More...
 
const double stan::math::EPSILON = std::numeric_limits<double>::epsilon()
 Smallest positive value. More...
 
const double stan::math::NEGATIVE_EPSILON = - std::numeric_limits<double>::epsilon()
 Largest negative value (i.e., smallest absolute value). More...
 
const double stan::math::POISSON_MAX_RATE = std::pow(2.0, 30)
 Largest rate parameter allowed in Poisson RNG. More...
 
const double stan::math::LOG_PI_OVER_FOUR = std::log(boost::math::constants::pi<double>()) / 4.0
 Log pi divided by 4 $ \log \pi / 4 $. More...
 
const double stan::math::SQRT_PI = std::sqrt(boost::math::constants::pi<double>())
 
const double stan::math::SQRT_2_TIMES_SQRT_PI = SQRT_2 * SQRT_PI
 
const double stan::math::TWO_OVER_SQRT_PI = 2.0 / SQRT_PI
 
const double stan::math::NEG_TWO_OVER_SQRT_PI = -TWO_OVER_SQRT_PI
 
const double stan::math::INV_SQRT_TWO_PI = 1.0 / std::sqrt(2.0 * boost::math::constants::pi<double>())
 
const double stan::math::LOG_PI = std::log(boost::math::constants::pi<double>())
 
const double stan::math::LOG_SQRT_PI = std::log(SQRT_PI)
 
const double stan::math::LOG_ZERO = std::log(0.0)
 
const double stan::math::LOG_TWO = std::log(2.0)
 
const double stan::math::LOG_HALF = std::log(0.5)
 
const double stan::math::NEG_LOG_TWO = - LOG_TWO
 
const double stan::math::NEG_LOG_SQRT_TWO_PI = - std::log(std::sqrt(2.0 * boost::math::constants::pi<double>()))
 
const double stan::math::NEG_LOG_PI = - LOG_PI
 
const double stan::math::NEG_LOG_SQRT_PI = -std::log(std::sqrt(boost::math::constants::pi<double>()))
 
const double stan::math::NEG_LOG_TWO_OVER_TWO = - LOG_TWO / 2.0
 
const double stan::math::LOG_TWO_PI = LOG_TWO + LOG_PI
 
const double stan::math::NEG_LOG_TWO_PI = - LOG_TWO_PI
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/constants_8hpp_source.html b/doc/api/html/constants_8hpp_source.html new file mode 100644 index 00000000000..efa5e3b1494 --- /dev/null +++ b/doc/api/html/constants_8hpp_source.html @@ -0,0 +1,267 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/constants.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
constants.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_CONSTANTS_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_CONSTANTS_HPP
+
3 
+
4 #include <boost/math/constants/constants.hpp>
+
5 #include <limits>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
15  const double E = boost::math::constants::e<double>();
+
16 
+
21  const double SQRT_2 = std::sqrt(2.0);
+
22 
+
27  const double INV_SQRT_2 = 1.0 / SQRT_2;
+
28 
+
33  const double LOG_2 = std::log(2.0);
+
34 
+
39  const double LOG_10 = std::log(10.0);
+
40 
+
44  const double INFTY = std::numeric_limits<double>::infinity();
+
45 
+
49  const double NEGATIVE_INFTY
+
50  = - std::numeric_limits<double>::infinity();
+
51 
+
55  const double NOT_A_NUMBER
+
56  = std::numeric_limits<double>::quiet_NaN();
+
57 
+
61  const double EPSILON = std::numeric_limits<double>::epsilon();
+
62 
+
66  const double NEGATIVE_EPSILON
+
67  = - std::numeric_limits<double>::epsilon();
+
68 
+
72  const double POISSON_MAX_RATE = std::pow(2.0, 30);
+
73 
+
78  const double LOG_PI_OVER_FOUR
+
79  = std::log(boost::math::constants::pi<double>()) / 4.0;
+
80 
+
86  inline double pi() {
+
87  return boost::math::constants::pi<double>();
+
88  }
+
89 
+
95  inline double e() {
+
96  return E;
+
97  }
+
98 
+
104  inline double sqrt2() {
+
105  return SQRT_2;
+
106  }
+
107 
+
108 
+
114  inline double log10() {
+
115  return LOG_10;
+
116  }
+
117 
+
123  inline double positive_infinity() {
+
124  return INFTY;
+
125  }
+
126 
+
132  inline double negative_infinity() {
+
133  return NEGATIVE_INFTY;
+
134  }
+
135 
+
141  inline double not_a_number() {
+
142  return NOT_A_NUMBER;
+
143  }
+
144 
+
151  inline double machine_precision() {
+
152  return EPSILON;
+
153  }
+
154 
+
155  const double SQRT_PI
+
156  = std::sqrt(boost::math::constants::pi<double>());
+
157 
+
158  const double SQRT_2_TIMES_SQRT_PI = SQRT_2 * SQRT_PI;
+
159 
+
160  const double TWO_OVER_SQRT_PI
+
161  = 2.0 / SQRT_PI;
+
162 
+ +
164 
+
165  const double INV_SQRT_TWO_PI
+
166  = 1.0 / std::sqrt(2.0 * boost::math::constants::pi<double>());
+
167 
+
168 
+
169  const double LOG_PI
+
170  = std::log(boost::math::constants::pi<double>());
+
171 
+
172  const double LOG_SQRT_PI
+
173  = std::log(SQRT_PI);
+
174 
+
175  const double LOG_ZERO = std::log(0.0);
+
176 
+
177  const double LOG_TWO = std::log(2.0);
+
178 
+
179  const double LOG_HALF = std::log(0.5);
+
180 
+
181  const double NEG_LOG_TWO = - LOG_TWO;
+
182 
+
183  const double NEG_LOG_SQRT_TWO_PI
+
184  = - std::log(std::sqrt(2.0 * boost::math::constants::pi<double>()));
+
185 
+
186  const double NEG_LOG_PI = - LOG_PI;
+
187 
+
188  const double NEG_LOG_SQRT_PI
+
189  = -std::log(std::sqrt(boost::math::constants::pi<double>()));
+
190 
+
191  const double NEG_LOG_TWO_OVER_TWO = - LOG_TWO / 2.0;
+
192 
+
193  const double LOG_TWO_PI = LOG_TWO + LOG_PI;
+
194 
+
195  const double NEG_LOG_TWO_PI = - LOG_TWO_PI;
+
196 
+
197  }
+
198 }
+
199 
+
200 #endif
+
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:33
+
const double NEG_LOG_PI
Definition: constants.hpp:186
+
const double LOG_HALF
Definition: constants.hpp:179
+
const double INV_SQRT_TWO_PI
Definition: constants.hpp:166
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
const double LOG_PI
Definition: constants.hpp:170
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
const double NEG_LOG_SQRT_PI
Definition: constants.hpp:189
+
const double LOG_SQRT_PI
Definition: constants.hpp:173
+
const double LOG_10
The natural logarithm of 10, .
Definition: constants.hpp:39
+
fvar< T > log10(const fvar< T > &x)
Definition: log10.hpp:15
+
const double LOG_ZERO
Definition: constants.hpp:175
+
const double LOG_TWO
Definition: constants.hpp:177
+
const double LOG_TWO_PI
Definition: constants.hpp:193
+
double sqrt2()
Return the square root of two.
Definition: constants.hpp:104
+
const double TWO_OVER_SQRT_PI
Definition: constants.hpp:161
+
const double SQRT_2_TIMES_SQRT_PI
Definition: constants.hpp:158
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
const double INV_SQRT_2
The value of 1 over the square root of 2, .
Definition: constants.hpp:27
+
const double EPSILON
Smallest positive value.
Definition: constants.hpp:61
+
const double LOG_PI_OVER_FOUR
Log pi divided by 4 .
Definition: constants.hpp:79
+
double machine_precision()
Returns the difference between 1.0 and the next value representable.
Definition: constants.hpp:151
+
const double NEG_TWO_OVER_SQRT_PI
Definition: constants.hpp:163
+
const double POISSON_MAX_RATE
Largest rate parameter allowed in Poisson RNG.
Definition: constants.hpp:72
+
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+
double positive_infinity()
Return positive infinity.
Definition: constants.hpp:123
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
const double E
The base of the natural logarithm, .
Definition: constants.hpp:15
+
const double NEG_LOG_TWO
Definition: constants.hpp:181
+
const double NEG_LOG_TWO_PI
Definition: constants.hpp:195
+
const double NEG_LOG_TWO_OVER_TWO
Definition: constants.hpp:191
+
const double INFTY
Positive infinity.
Definition: constants.hpp:44
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
double not_a_number()
Return (quiet) not-a-number.
Definition: constants.hpp:141
+
const double NEGATIVE_INFTY
Negative infinity.
Definition: constants.hpp:50
+
const double NEGATIVE_EPSILON
Largest negative value (i.e., smallest absolute value).
Definition: constants.hpp:67
+
const double SQRT_PI
Definition: constants.hpp:156
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
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diff --git a/doc/api/html/constraint__tolerance_8hpp.html b/doc/api/html/constraint__tolerance_8hpp.html new file mode 100644 index 00000000000..49b70a47273 --- /dev/null +++ b/doc/api/html/constraint__tolerance_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/constraint_tolerance.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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constraint_tolerance.hpp File Reference
+
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+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Variables

const double stan::math::CONSTRAINT_TOLERANCE = 1E-8
 The tolerance for checking arithmetic bounds In rank and in simplexes. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/constraint__tolerance_8hpp_source.html b/doc/api/html/constraint__tolerance_8hpp_source.html new file mode 100644 index 00000000000..7bb8f8e3c4d --- /dev/null +++ b/doc/api/html/constraint__tolerance_8hpp_source.html @@ -0,0 +1,123 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/constraint_tolerance.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + + + + + +
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+
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+
constraint_tolerance.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_ERR_CONSTRAINT_TOLERANCE_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CONSTRAINT_TOLERANCE_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
11  const double CONSTRAINT_TOLERANCE = 1E-8;
+
12 
+
13  }
+
14 }
+
15 #endif
+ +
const double CONSTRAINT_TOLERANCE
The tolerance for checking arithmetic bounds In rank and in simplexes.
+
const double E
The base of the natural logarithm, .
Definition: constants.hpp:15
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diff --git a/doc/api/html/contains__fvar_8hpp.html b/doc/api/html/contains__fvar_8hpp.html new file mode 100644 index 00000000000..36aa047c91b --- /dev/null +++ b/doc/api/html/contains__fvar_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/contains_fvar.hpp File Reference + + + + + + + + + + +
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struct  stan::contains_fvar< T1, T2, T3, T4, T5, T6 >
 Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters. More...
 
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diff --git a/doc/api/html/contains__fvar_8hpp_source.html b/doc/api/html/contains__fvar_8hpp_source.html new file mode 100644 index 00000000000..68338b98ea4 --- /dev/null +++ b/doc/api/html/contains__fvar_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/contains_fvar.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_CONTAINS_FVAR_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_CONTAINS_FVAR_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
13  template <typename T1,
+
14  typename T2 = double,
+
15  typename T3 = double,
+
16  typename T4 = double,
+
17  typename T5 = double,
+
18  typename T6 = double>
+
19  struct contains_fvar {
+
20  enum {
+ + + + + + +
27  };
+
28  };
+
29 
+
30 }
+
31 #endif
+
32 
+ + + + +
Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of...
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diff --git a/doc/api/html/contains__nonconstant__struct_8hpp.html b/doc/api/html/contains__nonconstant__struct_8hpp.html new file mode 100644 index 00000000000..38e785c1f88 --- /dev/null +++ b/doc/api/html/contains__nonconstant__struct_8hpp.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/contains_nonconstant_struct.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/contains__nonconstant__struct_8hpp_source.html b/doc/api/html/contains__nonconstant__struct_8hpp_source.html new file mode 100644 index 00000000000..d9f249eada4 --- /dev/null +++ b/doc/api/html/contains__nonconstant__struct_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/contains_nonconstant_struct.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_CONTAINS_NONCONSTANT_STRUCT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_CONTAINS_NONCONSTANT_STRUCT_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  template <typename T1,
+
9  typename T2 = double,
+
10  typename T3 = double,
+
11  typename T4 = double,
+
12  typename T5 = double,
+
13  typename T6 = double>
+ +
15  enum {
+ + + + + + +
22  };
+
23  };
+
24 
+
25 }
+
26 #endif
+
27 
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
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diff --git a/doc/api/html/contains__vector_8hpp.html b/doc/api/html/contains__vector_8hpp.html new file mode 100644 index 00000000000..33566c42a53 --- /dev/null +++ b/doc/api/html/contains__vector_8hpp.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/contains_vector.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/contains__vector_8hpp_source.html b/doc/api/html/contains__vector_8hpp_source.html new file mode 100644 index 00000000000..85f1d980892 --- /dev/null +++ b/doc/api/html/contains__vector_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/contains_vector.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_CONTAINS_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_CONTAINS_VECTOR_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  template <typename T1,
+
9  typename T2 = double,
+
10  typename T3 = double,
+
11  typename T4 = double,
+
12  typename T5 = double,
+
13  typename T6 = double>
+
14  struct contains_vector {
+
15  enum {
+ + + + + + +
22  };
+
23  };
+
24 
+
25 }
+
26 #endif
+
27 
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diff --git a/doc/api/html/core_2grad_8hpp.html b/doc/api/html/core_2grad_8hpp.html new file mode 100644 index 00000000000..e598eba9cd4 --- /dev/null +++ b/doc/api/html/core_2grad_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/core/grad.hpp File Reference + + + + + + + + + + +
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static void stan::math::grad (vari *vi)
 Compute the gradient for all variables starting from the specified root variable implementation. More...
 
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diff --git a/doc/api/html/core_2grad_8hpp_source.html b/doc/api/html/core_2grad_8hpp_source.html new file mode 100644 index 00000000000..38073314e92 --- /dev/null +++ b/doc/api/html/core_2grad_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/rev/core/grad.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_GRAD_HPP
+
2 #define STAN_MATH_REV_CORE_GRAD_HPP
+
3 
+ + + + + +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
30  static void grad(vari* vi) {
+
31  // simple reference implementation (intended as doc):
+
32  // vi->init_dependent();
+
33  // size_t end = var_stack_.size();
+
34  // size_t begin = empty_nested() ? 0 : end - nested_size();
+
35  // for (size_t i = end; --i > begin; )
+
36  // var_stack_[i]->chain();
+
37 
+
38  typedef std::vector<vari*>::reverse_iterator it_t;
+
39  vi->init_dependent();
+
40  it_t begin = ChainableStack::var_stack_.rbegin();
+
41  it_t end = empty_nested()
+
42  ? ChainableStack::var_stack_.rend() : begin + nested_size();
+
43  for (it_t it = begin; it < end; ++it) {
+
44  (*it)->chain();
+
45  }
+
46  }
+
47 
+
48 
+
49  }
+
50 }
+
51 
+
52 #endif
+
static bool empty_nested()
Return true if there is no nested autodiff being executed.
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+ +
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+ + +
static size_t nested_size()
Definition: nested_size.hpp:10
+
void init_dependent()
Initialize the adjoint for this (dependent) variable to 1.
Definition: vari.hpp:98
+ +
static std::vector< ChainableT * > var_stack_
+
+
+
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diff --git a/doc/api/html/corr__constrain_8hpp.html b/doc/api/html/corr__constrain_8hpp.html new file mode 100644 index 00000000000..faf0d267e31 --- /dev/null +++ b/doc/api/html/corr__constrain_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/corr_constrain.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/fun/log1m.hpp>
+#include <cmath>
+
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template<typename T >
stan::math::corr_constrain (const T x)
 Return the result of transforming the specified scalar to have a valid correlation value between -1 and 1 (inclusive). More...
 
template<typename T >
stan::math::corr_constrain (const T x, T &lp)
 Return the result of transforming the specified scalar to have a valid correlation value between -1 and 1 (inclusive). More...
 
+
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diff --git a/doc/api/html/corr__constrain_8hpp_source.html b/doc/api/html/corr__constrain_8hpp_source.html new file mode 100644 index 00000000000..69bb7306fe6 --- /dev/null +++ b/doc/api/html/corr__constrain_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/corr_constrain.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_CORR_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_CORR_CONSTRAIN_HPP
+
3 
+ +
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
23  template <typename T>
+
24  inline
+
25  T corr_constrain(const T x) {
+
26  return tanh(x);
+
27  }
+
28 
+
41  template <typename T>
+
42  inline
+
43  T corr_constrain(const T x, T& lp) {
+
44  using stan::math::log1m;
+
45  T tanh_x = tanh(x);
+
46  lp += log1m(tanh_x * tanh_x);
+
47  return tanh_x;
+
48  }
+
49 
+
50  }
+
51 
+
52 }
+
53 
+
54 #endif
+ +
fvar< T > tanh(const fvar< T > &x)
Definition: tanh.hpp:14
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
T corr_constrain(const T x)
Return the result of transforming the specified scalar to have a valid correlation value between -1 a...
+
+
+
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diff --git a/doc/api/html/corr__free_8hpp.html b/doc/api/html/corr__free_8hpp.html new file mode 100644 index 00000000000..6beb806ea44 --- /dev/null +++ b/doc/api/html/corr__free_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/corr_free.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/err/check_bounded.hpp>
+#include <cmath>
+
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template<typename T >
stan::math::corr_free (const T y)
 Return the unconstrained scalar that when transformed to a valid correlation produces the specified value. More...
 
+
+
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diff --git a/doc/api/html/corr__free_8hpp_source.html b/doc/api/html/corr__free_8hpp_source.html new file mode 100644 index 00000000000..f8b75d3347a --- /dev/null +++ b/doc/api/html/corr__free_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/corr_free.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_CORR_FREE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_CORR_FREE_HPP
+
3 
+ +
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
27  template <typename T>
+
28  inline
+
29  T corr_free(const T y) {
+
30  stan::math::check_bounded<T, double, double>
+
31  ("stan::math::lub_free",
+
32  "Correlation variable", y, -1, 1);
+
33  return atanh(y);
+
34  }
+
35 
+
36  }
+
37 
+
38 }
+
39 
+
40 #endif
+
fvar< T > atanh(const fvar< T > &x)
Definition: atanh.hpp:13
+
T corr_free(const T y)
Return the unconstrained scalar that when transformed to a valid correlation produces the specified v...
Definition: corr_free.hpp:29
+ + +
+
+
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diff --git a/doc/api/html/corr__matrix__constrain_8hpp.html b/doc/api/html/corr__matrix__constrain_8hpp.html new file mode 100644 index 00000000000..1a4a32dc53a --- /dev/null +++ b/doc/api/html/corr__matrix__constrain_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/corr_matrix_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::corr_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type k)
 Return the correlation matrix of the specified dimensionality derived from the specified vector of unconstrained values. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::corr_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type k, T &lp)
 Return the correlation matrix of the specified dimensionality derived from the specified vector of unconstrained values. More...
 
+
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diff --git a/doc/api/html/corr__matrix__constrain_8hpp_source.html b/doc/api/html/corr__matrix__constrain_8hpp_source.html new file mode 100644 index 00000000000..b441210b049 --- /dev/null +++ b/doc/api/html/corr__matrix__constrain_8hpp_source.html @@ -0,0 +1,178 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/corr_matrix_constrain.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_CORR_MATRIX_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CORR_MATRIX_CONSTRAIN_HPP
+
3 
+ + + + +
8 #include <stdexcept>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
38  template <typename T>
+
39  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
40  corr_matrix_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
41  typename math::index_type
+
42  <Eigen::Matrix<T, Eigen::Dynamic, 1> >::type k) {
+
43  using Eigen::Dynamic;
+
44  using Eigen::Matrix;
+ +
46  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
47 
+
48  size_type k_choose_2 = (k * (k - 1)) / 2;
+
49  if (k_choose_2 != x.size())
+
50  throw std::invalid_argument("x is not a valid correlation matrix");
+
51  Eigen::Array<T, Eigen::Dynamic, 1> cpcs(k_choose_2);
+
52  for (size_type i = 0; i < k_choose_2; ++i)
+
53  cpcs[i] = corr_constrain(x[i]);
+
54  return read_corr_matrix(cpcs, k);
+
55  }
+
56 
+
76  template <typename T>
+
77  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
78  corr_matrix_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
79  typename math::index_type
+
80  <Eigen::Matrix<T, Eigen::Dynamic, 1> >::type k,
+
81  T& lp) {
+
82  using Eigen::Array;
+
83  using Eigen::Dynamic;
+
84  using Eigen::Matrix;
+ +
86  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
87 
+
88  size_type k_choose_2 = (k * (k - 1)) / 2;
+
89  if (k_choose_2 != x.size())
+
90  throw std::invalid_argument("x is not a valid correlation matrix");
+
91  Array<T, Dynamic, 1> cpcs(k_choose_2);
+
92  for (size_type i = 0; i < k_choose_2; ++i)
+
93  cpcs[i] = corr_constrain(x[i], lp);
+
94  return read_corr_matrix(cpcs, k, lp);
+
95  }
+
96 
+
97  }
+
98 
+
99 }
+
100 
+
101 #endif
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > corr_matrix_constrain(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type k)
Return the correlation matrix of the specified dimensionality derived from the specified vector of un...
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_matrix(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
Return the correlation matrix of the specified dimensionality corresponding to the specified canonica...
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+ + +
T corr_constrain(const T x)
Return the result of transforming the specified scalar to have a valid correlation value between -1 a...
+
+
+
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diff --git a/doc/api/html/corr__matrix__free_8hpp.html b/doc/api/html/corr__matrix__free_8hpp.html new file mode 100644 index 00000000000..33cfcafd1df --- /dev/null +++ b/doc/api/html/corr__matrix__free_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/corr_matrix_free.hpp File Reference + + + + + + + + + + +
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corr_matrix_free.hpp File Reference
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stan/math/prim/mat/err/constraint_tolerance.hpp>
+#include <stan/math/prim/mat/fun/factor_cov_matrix.hpp>
+#include <boost/throw_exception.hpp>
+#include <cmath>
+#include <sstream>
+#include <stdexcept>
+
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::corr_matrix_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return the vector of unconstrained partial correlations that define the specified correlation matrix when transformed. More...
 
+
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diff --git a/doc/api/html/corr__matrix__free_8hpp_source.html b/doc/api/html/corr__matrix__free_8hpp_source.html new file mode 100644 index 00000000000..a278517b326 --- /dev/null +++ b/doc/api/html/corr__matrix__free_8hpp_source.html @@ -0,0 +1,174 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/corr_matrix_free.hpp Source File + + + + + + + + + + +
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corr_matrix_free.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_CORR_MATRIX_FREE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CORR_MATRIX_FREE_HPP
+
3 
+ + + + +
8 #include <boost/throw_exception.hpp>
+
9 #include <cmath>
+
10 #include <sstream>
+
11 #include <stdexcept>
+
12 
+
13 namespace stan {
+
14 
+
15  namespace math {
+
16 
+
37  template <typename T>
+
38  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
39  corr_matrix_free(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>&
+
40  y) {
+
41  using Eigen::Array;
+
42  using Eigen::Dynamic;
+
43  using Eigen::Matrix;
+ +
45  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
46 
+
47  size_type k = y.rows();
+
48  if (y.cols() != k)
+
49  throw std::domain_error("y is not a square matrix");
+
50  if (k == 0)
+
51  throw std::domain_error("y has no elements");
+
52  size_type k_choose_2 = (k * (k-1)) / 2;
+
53  Array<T, Dynamic, 1> x(k_choose_2);
+
54  Array<T, Dynamic, 1> sds(k);
+
55  bool successful = factor_cov_matrix(y, x, sds);
+
56  if (!successful)
+
57  throw std::runtime_error("factor_cov_matrix failed on y");
+
58  for (size_type i = 0; i < k; ++i) {
+
59  // sds on log scale unconstrained
+
60  if (fabs(sds[i] - 0.0) >= CONSTRAINT_TOLERANCE) {
+
61  std::stringstream s;
+
62  s << "all standard deviations must be zero."
+
63  << " found log(sd[" << i << "])=" << sds[i] << std::endl;
+
64  BOOST_THROW_EXCEPTION(std::runtime_error(s.str()));
+
65  }
+
66  }
+
67  return x.matrix();
+
68  }
+
69  }
+
70 
+
71 }
+
72 
+
73 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ + +
const double CONSTRAINT_TOLERANCE
The tolerance for checking arithmetic bounds In rank and in simplexes.
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
bool factor_cov_matrix(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &Sigma, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, Eigen::Array< T, Eigen::Dynamic, 1 > &sds)
This function is intended to make starting values, given a covariance matrix Sigma.
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
Eigen::Matrix< T, Eigen::Dynamic, 1 > corr_matrix_free(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
Return the vector of unconstrained partial correlations that define the specified correlation matrix ...
+
+
+
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diff --git a/doc/api/html/coupled__ode__observer_8hpp.html b/doc/api/html/coupled__ode__observer_8hpp.html new file mode 100644 index 00000000000..25761c8e76a --- /dev/null +++ b/doc/api/html/coupled__ode__observer_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/functor/coupled_ode_observer.hpp File Reference + + + + + + + + + + +
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coupled_ode_observer.hpp File Reference
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#include <vector>
+
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+Classes

struct  stan::math::coupled_ode_observer
 Observer for the coupled states. More...
 
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 Matrices and templated mathematical functions.
 
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diff --git a/doc/api/html/coupled__ode__observer_8hpp_source.html b/doc/api/html/coupled__ode__observer_8hpp_source.html new file mode 100644 index 00000000000..2edd93551c1 --- /dev/null +++ b/doc/api/html/coupled__ode__observer_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/functor/coupled_ode_observer.hpp Source File + + + + + + + + + + +
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coupled_ode_observer.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_FUNCTOR_COUPLED_ODE_OBSERVER_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUNCTOR_COUPLED_ODE_OBSERVER_HPP
+
3 
+
4 #include <vector>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+ +
16  std::vector<std::vector<double> >& y_coupled_;
+
17  int n_;
+
18 
+
25  explicit coupled_ode_observer(std::vector<std::vector<double> >&
+
26  y_coupled)
+
27  : y_coupled_(y_coupled), n_(0) {
+
28  }
+
29 
+
36  void operator()(const std::vector<double>& coupled_state,
+
37  const double t) {
+
38  y_coupled_[n_] = coupled_state;
+
39  n_++;
+
40  }
+
41  };
+
42 
+
43  }
+
44 
+
45 }
+
46 
+
47 #endif
+ +
std::vector< std::vector< double > > & y_coupled_
+ +
Observer for the coupled states.
+
void operator()(const std::vector< double > &coupled_state, const double t)
Callback function for Boost's ODE solver to record values.
+
coupled_ode_observer(std::vector< std::vector< double > > &y_coupled)
Construct a coupled ODE observer from the specified coupled vector.
+
+
+
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diff --git a/doc/api/html/cov__matrix__constrain_8hpp.html b/doc/api/html/cov__matrix__constrain_8hpp.html new file mode 100644 index 00000000000..15c43eec147 --- /dev/null +++ b/doc/api/html/cov__matrix__constrain_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cov_matrix_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cov_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type K)
 Return the symmetric, positive-definite matrix of dimensions K by K resulting from transforming the specified finite vector of size K plus (K choose 2). More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cov_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >::type K, T &lp)
 Return the symmetric, positive-definite matrix of dimensions K by K resulting from transforming the specified finite vector of size K plus (K choose 2). More...
 
+
+
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diff --git a/doc/api/html/cov__matrix__constrain_8hpp_source.html b/doc/api/html/cov__matrix__constrain_8hpp_source.html new file mode 100644 index 00000000000..dc461ae3420 --- /dev/null +++ b/doc/api/html/cov__matrix__constrain_8hpp_source.html @@ -0,0 +1,205 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cov_matrix_constrain.hpp Source File + + + + + + + + + + +
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cov_matrix_constrain.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_COV_MATRIX_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COV_MATRIX_CONSTRAIN_HPP
+
3 
+ + + + +
8 #include <cmath>
+
9 #include <stdexcept>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15  // COVARIANCE MATRIX
+
16 
+
29  template <typename T>
+
30  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
31  cov_matrix_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
32  typename math::index_type
+
33  <Eigen::Matrix<T, Eigen::Dynamic, 1> >::type K) {
+
34  using std::exp;
+
35 
+
36  using Eigen::Dynamic;
+
37  using Eigen::Matrix;
+ + +
40  typedef typename index_type<Matrix<T, Dynamic, Dynamic> >::type size_type;
+
41 
+
42  Matrix<T, Dynamic, Dynamic> L(K, K);
+
43  if (x.size() != (K * (K + 1)) / 2)
+
44  throw std::domain_error("x.size() != K + (K choose 2)");
+
45  int i = 0;
+
46  for (size_type m = 0; m < K; ++m) {
+
47  for (int n = 0; n < m; ++n)
+
48  L(m, n) = x(i++);
+
49  L(m, m) = exp(x(i++));
+
50  for (size_type n = m + 1; n < K; ++n)
+
51  L(m, n) = 0.0;
+
52  }
+ +
54  }
+
55 
+
56 
+
69  template <typename T>
+
70  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
71  cov_matrix_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
72  typename math::index_type<Eigen::Matrix<T,
+
73  Eigen::Dynamic,
+
74  Eigen::Dynamic> >::type K,
+
75  T& lp) {
+
76  using std::exp;
+
77  using std::log;
+
78 
+
79  using Eigen::Dynamic;
+
80  using Eigen::Matrix;
+ +
82  typedef typename index_type<Matrix<T, Dynamic, Dynamic> >::type size_type;
+
83 
+
84  if (x.size() != (K * (K + 1)) / 2)
+
85  throw std::domain_error("x.size() != K + (K choose 2)");
+
86  Matrix<T, Dynamic, Dynamic> L(K, K);
+
87  int i = 0;
+
88  for (size_type m = 0; m < K; ++m) {
+
89  for (size_type n = 0; n < m; ++n)
+
90  L(m, n) = x(i++);
+
91  L(m, m) = exp(x(i++));
+
92  for (size_type n = m + 1; n < K; ++n)
+
93  L(m, n) = 0.0;
+
94  }
+
95  // Jacobian for complete transform, including exp() above
+
96  lp += (K * stan::math::LOG_2); // needless constant; want propto
+
97  for (int k = 0; k < K; ++k)
+
98  lp += (K - k + 1) * log(L(k, k)); // only +1 because index from 0
+
99  return L * L.transpose();
+
100  // return tri_multiply_transpose(L);
+
101  }
+
102 
+
103  }
+
104 
+
105 }
+
106 
+
107 #endif
+
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:33
+ +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cov_matrix_constrain(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type K)
Return the symmetric, positive-definite matrix of dimensions K by K resulting from transforming the s...
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose(const Eigen::Matrix< fvar< T >, R, C > &m)
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cov__matrix__constrain__lkj_8hpp.html b/doc/api/html/cov__matrix__constrain__lkj_8hpp.html new file mode 100644 index 00000000000..fb15dc40002 --- /dev/null +++ b/doc/api/html/cov__matrix__constrain__lkj_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cov_matrix_constrain_lkj.hpp File Reference + + + + + + + + + + +
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cov_matrix_constrain_lkj.hpp File Reference
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cov_matrix_constrain_lkj (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t k)
 Return the covariance matrix of the specified dimensionality derived from constraining the specified vector of unconstrained values. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cov_matrix_constrain_lkj (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t k, T &lp)
 Return the covariance matrix of the specified dimensionality derived from constraining the specified vector of unconstrained values and increment the specified log probability reference with the log absolute Jacobian determinant. More...
 
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diff --git a/doc/api/html/cov__matrix__constrain__lkj_8hpp_source.html b/doc/api/html/cov__matrix__constrain__lkj_8hpp_source.html new file mode 100644 index 00000000000..314bf026670 --- /dev/null +++ b/doc/api/html/cov__matrix__constrain__lkj_8hpp_source.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cov_matrix_constrain_lkj.hpp Source File + + + + + + + + + + +
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cov_matrix_constrain_lkj.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_COV_MATRIX_CONSTRAIN_LKJ_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COV_MATRIX_CONSTRAIN_LKJ_HPP
+
3 
+ + + + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
32  template <typename T>
+
33  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
34  cov_matrix_constrain_lkj(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
35  size_t k) {
+
36  size_t k_choose_2 = (k * (k - 1)) / 2;
+
37  Eigen::Array<T, Eigen::Dynamic, 1> cpcs(k_choose_2);
+
38  int pos = 0;
+
39  for (size_t i = 0; i < k_choose_2; ++i)
+
40  cpcs[i] = corr_constrain(x[pos++]);
+
41  Eigen::Array<T, Eigen::Dynamic, 1> sds(k);
+
42  for (size_t i = 0; i < k; ++i)
+
43  sds[i] = positive_constrain(x[pos++]);
+
44  return read_cov_matrix(cpcs, sds);
+
45  }
+
46 
+
71  template <typename T>
+
72  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
73  cov_matrix_constrain_lkj(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
74  size_t k,
+
75  T& lp) {
+
76  size_t k_choose_2 = (k * (k - 1)) / 2;
+
77  Eigen::Array<T, Eigen::Dynamic, 1> cpcs(k_choose_2);
+
78  int pos = 0;
+
79  for (size_t i = 0; i < k_choose_2; ++i)
+
80  cpcs[i] = corr_constrain(x[pos++], lp);
+
81  Eigen::Array<T, Eigen::Dynamic, 1> sds(k);
+
82  for (size_t i = 0; i < k; ++i)
+
83  sds[i] = positive_constrain(x[pos++], lp);
+
84  return read_cov_matrix(cpcs, sds, lp);
+
85  }
+
86 
+
87  }
+
88 
+
89 }
+
90 
+
91 #endif
+
T positive_constrain(const T x)
Return the positive value for the specified unconstrained input.
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_cov_matrix(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds, T &log_prob)
A generally worse alternative to call prior to evaluating the density of an elliptical distribution...
+ + + + + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cov_matrix_constrain_lkj(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t k)
Return the covariance matrix of the specified dimensionality derived from constraining the specified ...
+
T corr_constrain(const T x)
Return the result of transforming the specified scalar to have a valid correlation value between -1 a...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cov__matrix__free_8hpp.html b/doc/api/html/cov__matrix__free_8hpp.html new file mode 100644 index 00000000000..35bd3fc0c26 --- /dev/null +++ b/doc/api/html/cov__matrix__free_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cov_matrix_free.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <cmath>
+#include <stdexcept>
+
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::cov_matrix_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
 The covariance matrix derived from the symmetric view of the lower-triangular view of the K by K specified matrix is freed to return a vector of size K + (K choose 2). More...
 
+
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diff --git a/doc/api/html/cov__matrix__free_8hpp_source.html b/doc/api/html/cov__matrix__free_8hpp_source.html new file mode 100644 index 00000000000..cbb4ed1cc8f --- /dev/null +++ b/doc/api/html/cov__matrix__free_8hpp_source.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cov_matrix_free.hpp Source File + + + + + + + + + + +
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cov_matrix_free.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_COV_MATRIX_FREE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COV_MATRIX_FREE_HPP
+
3 
+ + +
6 #include <cmath>
+
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
35  template <typename T>
+
36  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
37  cov_matrix_free(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& y) {
+
38  using std::log;
+
39  int K = y.rows();
+
40  if (y.cols() != K)
+
41  throw std::domain_error("y is not a square matrix");
+
42  if (K == 0)
+
43  throw std::domain_error("y has no elements");
+
44  for (int k = 0; k < K; ++k)
+
45  if (!(y(k, k) > 0.0))
+
46  throw std::domain_error("y has non-positive diagonal");
+
47  Eigen::Matrix<T, Eigen::Dynamic, 1> x((K * (K + 1)) / 2);
+
48  // FIXME: see Eigen LDLT for rank-revealing version -- use that
+
49  // even if less efficient?
+
50  Eigen::LLT<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
+
51  llt(y.rows());
+
52  llt.compute(y);
+
53  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> L = llt.matrixL();
+
54  int i = 0;
+
55  for (int m = 0; m < K; ++m) {
+
56  for (int n = 0; n < m; ++n)
+
57  x(i++) = L(m, n);
+
58  x(i++) = log(L(m, m));
+
59  }
+
60  return x;
+
61  }
+
62 
+
63  }
+
64 
+
65 }
+
66 
+
67 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
Eigen::Matrix< T, Eigen::Dynamic, 1 > cov_matrix_free(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
The covariance matrix derived from the symmetric view of the lower-triangular view of the K by K spec...
+
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diff --git a/doc/api/html/cov__matrix__free__lkj_8hpp.html b/doc/api/html/cov__matrix__free__lkj_8hpp.html new file mode 100644 index 00000000000..659e6f4a47b --- /dev/null +++ b/doc/api/html/cov__matrix__free__lkj_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cov_matrix_free_lkj.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stdexcept>
+
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::cov_matrix_free_lkj (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return the vector of unconstrained partial correlations and deviations that transform to the specified covariance matrix. More...
 
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diff --git a/doc/api/html/cov__matrix__free__lkj_8hpp_source.html b/doc/api/html/cov__matrix__free__lkj_8hpp_source.html new file mode 100644 index 00000000000..4221d20a65e --- /dev/null +++ b/doc/api/html/cov__matrix__free__lkj_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cov_matrix_free_lkj.hpp Source File + + + + + + + + + + +
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cov_matrix_free_lkj.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_COV_MATRIX_FREE_LKJ_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COV_MATRIX_FREE_LKJ_HPP
+
3 
+ + +
6 #include <stdexcept>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
30  template <typename T>
+
31  Eigen::Matrix<T, Eigen::Dynamic, 1>
+ +
33  const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& y) {
+
34  using Eigen::Array;
+
35  using Eigen::Dynamic;
+
36  using Eigen::Matrix;
+ +
38  typedef typename index_type<Matrix<T, Dynamic, Dynamic> >::type size_type;
+
39 
+
40  size_type k = y.rows();
+
41  if (y.cols() != k)
+
42  throw std::domain_error("y is not a square matrix");
+
43  if (k == 0)
+
44  throw std::domain_error("y has no elements");
+
45  size_type k_choose_2 = (k * (k-1)) / 2;
+
46  Array<T, Dynamic, 1> cpcs(k_choose_2);
+
47  Array<T, Dynamic, 1> sds(k);
+
48  bool successful = factor_cov_matrix(y, cpcs, sds);
+
49  if (!successful)
+
50  throw std::runtime_error("factor_cov_matrix failed on y");
+
51  Matrix<T, Dynamic, 1> x(k_choose_2 + k);
+
52  size_type pos = 0;
+
53  for (size_type i = 0; i < k_choose_2; ++i)
+
54  x[pos++] = cpcs[i];
+
55  for (size_type i = 0; i < k; ++i)
+
56  x[pos++] = sds[i];
+
57  return x;
+
58  }
+
59 
+
60  }
+
61 
+
62 }
+
63 
+
64 #endif
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
bool factor_cov_matrix(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &Sigma, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, Eigen::Array< T, Eigen::Dynamic, 1 > &sds)
This function is intended to make starting values, given a covariance matrix Sigma.
+ +
Eigen::Matrix< T, Eigen::Dynamic, 1 > cov_matrix_free_lkj(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
Return the vector of unconstrained partial correlations and deviations that transform to the specifie...
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
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diff --git a/doc/api/html/csr__extract__u_8hpp.html b/doc/api/html/csr__extract__u_8hpp.html new file mode 100644 index 00000000000..976f820e5f2 --- /dev/null +++ b/doc/api/html/csr__extract__u_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_extract_u.hpp File Reference + + + + + + + + + + +
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csr_extract_u.hpp File Reference
+
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+
#include <stan/math/prim/scal/meta/error_index.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <Eigen/Sparse>
+#include <vector>
+#include <numeric>
+
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template<typename T >
const std::vector< int > stan::math::csr_extract_u (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 Extract the NZE index for each entry from a sparse matrix. More...
 
template<typename T , int R, int C>
const std::vector< int > stan::math::csr_extract_u (const Eigen::Matrix< T, R, C > &A)
 Extract the NZE index for each entry from a sparse matrix. More...
 
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diff --git a/doc/api/html/csr__extract__u_8hpp_source.html b/doc/api/html/csr__extract__u_8hpp_source.html new file mode 100644 index 00000000000..797e7a015fc --- /dev/null +++ b/doc/api/html/csr__extract__u_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_extract_u.hpp Source File + + + + + + + + + + +
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csr_extract_u.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CSR_EXTRACT_U_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CSR_EXTRACT_U_HPP
+
3 
+ + +
6 #include <Eigen/Sparse>
+
7 #include <vector>
+
8 #include <numeric>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
25  template <typename T>
+
26  const std::vector<int>
+
27  csr_extract_u(const Eigen::SparseMatrix<T, Eigen::RowMajor>& A) {
+
28  std::vector<int> u(A.outerSize() + 1); // last entry is garbage.
+
29  for (int nze = 0; nze <= A.outerSize(); ++nze)
+
30  u[nze] = *(A.outerIndexPtr() + nze) + stan::error_index::value;
+
31  return u;
+
32  }
+
33 
+
41  template <typename T, int R, int C>
+
42  const std::vector<int>
+
43  csr_extract_u(const Eigen::Matrix<T, R, C>& A) {
+
44  Eigen::SparseMatrix<T, Eigen::RowMajor> B = A.sparseView();
+
45  std::vector<int> u = csr_extract_u(B);
+
46  return u;
+
47  }
+
48  // end of csr_format group
+
50 
+
51  }
+
52 }
+
53 
+
54 #endif
+ + + + +
const std::vector< int > csr_extract_u(const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
Extract the NZE index for each entry from a sparse matrix.
+
+
+
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diff --git a/doc/api/html/csr__extract__v_8hpp.html b/doc/api/html/csr__extract__v_8hpp.html new file mode 100644 index 00000000000..a16141d70a0 --- /dev/null +++ b/doc/api/html/csr__extract__v_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_extract_v.hpp File Reference + + + + + + + + + + +
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+
+
+
#include <stan/math/prim/scal/meta/error_index.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <Eigen/Sparse>
+#include <vector>
+#include <numeric>
+
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template<typename T >
const std::vector< int > stan::math::csr_extract_v (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 Extract the column indexes for non-zero value from a sparse matrix. More...
 
template<typename T , int R, int C>
const std::vector< int > stan::math::csr_extract_v (const Eigen::Matrix< T, R, C > &A)
 Extract the column indexes for non-zero values from a dense matrix by converting to sparse and calling the sparse matrix extractor. More...
 
+
+
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diff --git a/doc/api/html/csr__extract__v_8hpp_source.html b/doc/api/html/csr__extract__v_8hpp_source.html new file mode 100644 index 00000000000..18b7990c5aa --- /dev/null +++ b/doc/api/html/csr__extract__v_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_extract_v.hpp Source File + + + + + + + + + + +
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csr_extract_v.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CSR_EXTRACT_V_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CSR_EXTRACT_V_HPP
+
3 
+ + +
6 #include <Eigen/Sparse>
+
7 #include <vector>
+
8 #include <numeric>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
26  template <typename T>
+
27  const std::vector<int>
+
28  csr_extract_v(const Eigen::SparseMatrix<T, Eigen::RowMajor>& A) {
+
29  std::vector<int> v(A.nonZeros());
+
30  for (int nze = 0; nze < A.nonZeros(); ++nze)
+
31  v[nze] = *(A.innerIndexPtr() + nze) + stan::error_index::value;
+
32  return v;
+
33  }
+
34 
+
44  template <typename T, int R, int C>
+
45  const std::vector<int>
+
46  csr_extract_v(const Eigen::Matrix<T, R, C>& A) {
+
47  Eigen::SparseMatrix<T, Eigen::RowMajor> B = A.sparseView();
+
48  std::vector<int> v = csr_extract_v(B);
+
49  return v;
+
50  }
+
51  // end of csr_format group
+
53  }
+
54 }
+
55 
+
56 #endif
+ + +
const std::vector< int > csr_extract_v(const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
Extract the column indexes for non-zero value from a sparse matrix.
+ + +
+
+
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diff --git a/doc/api/html/csr__extract__w_8hpp.html b/doc/api/html/csr__extract__w_8hpp.html new file mode 100644 index 00000000000..19178d29fef --- /dev/null +++ b/doc/api/html/csr__extract__w_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_extract_w.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <Eigen/Sparse>
+
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template<typename T >
const Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::csr_extract_w (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 
template<typename T , int R, int C>
const Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::csr_extract_w (const Eigen::Matrix< T, R, C > &A)
 
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diff --git a/doc/api/html/csr__extract__w_8hpp_source.html b/doc/api/html/csr__extract__w_8hpp_source.html new file mode 100644 index 00000000000..f512eef0364 --- /dev/null +++ b/doc/api/html/csr__extract__w_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_extract_w.hpp Source File + + + + + + + + + + +
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csr_extract_w.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CSR_EXTRACT_W_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CSR_EXTRACT_W_HPP
+
3 
+ +
5 #include <Eigen/Sparse>
+
6 // #include <numeric>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
16  /* Extract the non-zero values from a sparse matrix.
+
17  *
+
18  * @tparam T Type of matrix entries.
+
19  * @param[in] A sparse matrix.
+
20  * @return Vector of non-zero entries of A.
+
21  */
+
22  template <typename T>
+
23  const Eigen::Matrix<T, Eigen::Dynamic, 1>
+
24  csr_extract_w(const Eigen::SparseMatrix<T, Eigen::RowMajor>& A) {
+
25  Eigen::Matrix<T, Eigen::Dynamic, 1> w(A.nonZeros());
+
26  w.setZero();
+
27  for (int nze = 0; nze < A.nonZeros(); ++nze)
+
28  w[nze] = *(A.valuePtr() + nze);
+
29  return w;
+
30  }
+
31 
+
32  /* Extract the non-zero values from a dense matrix by converting
+
33  * to sparse and calling the sparse matrix extractor.
+
34  *
+
35  * @tparam T Type of matrix entries.
+
36  * @param[in] A dense matrix.
+
37  * @return Vector of non-zero entries of A.
+
38  */
+
39  template <typename T, int R, int C>
+
40  const Eigen::Matrix<T, Eigen::Dynamic, 1>
+
41  csr_extract_w(const Eigen::Matrix<T, R, C>& A) {
+
42  Eigen::SparseMatrix<T, Eigen::RowMajor> B = A.sparseView();
+
43  return csr_extract_w(B);
+
44  }
+
45  // end of csr_format group
+
47 
+
48  }
+
49 }
+
50 #endif
+
const Eigen::Matrix< T, Eigen::Dynamic, 1 > csr_extract_w(const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
+ + +
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diff --git a/doc/api/html/csr__matrix__times__vector_8hpp.html b/doc/api/html/csr__matrix__times__vector_8hpp.html new file mode 100644 index 00000000000..0833b95867a --- /dev/null +++ b/doc/api/html/csr__matrix__times__vector_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_matrix_times_vector.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, Eigen::Dynamic, 1 > stan::math::csr_matrix_times_vector (const int &m, const int &n, const Eigen::Matrix< T1, Eigen::Dynamic, 1 > &w, const std::vector< int > &v, const std::vector< int > &u, const Eigen::Matrix< T2, Eigen::Dynamic, 1 > &b)
 
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diff --git a/doc/api/html/csr__matrix__times__vector_8hpp_source.html b/doc/api/html/csr__matrix__times__vector_8hpp_source.html new file mode 100644 index 00000000000..6c0400e8a7b --- /dev/null +++ b/doc/api/html/csr__matrix__times__vector_8hpp_source.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_matrix_times_vector.hpp Source File + + + + + + + + + + +
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csr_matrix_times_vector.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_CSR_MATRIX_TIMES_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CSR_MATRIX_TIMES_VECTOR_HPP
+
3 
+ + + + + + +
10 #include <boost/math/tools/promotion.hpp>
+
11 #include <vector>
+
12 
+
13 namespace stan {
+
14 
+
15  namespace math {
+
75  template <typename T1, typename T2>
+
76  inline
+
77  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
78  Eigen::Dynamic, 1>
+ +
80  const int& n,
+
81  const Eigen::Matrix<T1, Eigen::Dynamic, 1>& w,
+
82  const std::vector<int>& v,
+
83  const std::vector<int>& u,
+
84  const Eigen::Matrix<T2, Eigen::Dynamic, 1>& b) {
+
85  typedef typename boost::math::tools::promote_args<T1, T2>::type
+
86  result_t;
+
87 
+
88  check_positive("csr_matrix_times_vector", "m", m);
+
89  check_positive("csr_matrix_times_vector", "n", n);
+
90  check_size_match("csr_matrix_times_vector", "n", n, "b", b.size());
+
91  check_size_match("csr_matrix_times_vector", "m", m, "u", u.size() - 1);
+
92  check_size_match("csr_matrix_times_vector", "w", w.size(), "v", v.size());
+
93  check_size_match("csr_matrix_times_vector", "u/z",
+
94  u[m - 1] + csr_u_to_z(u, m - 1) - 1, "v", v.size());
+
95  for (unsigned int i = 0; i < v.size(); ++i)
+
96  check_range("csr_matrix_times_vector", "v[]", n, v[i]);
+
97 
+
98  Eigen::Matrix<result_t, Eigen::Dynamic, 1> result(m);
+
99  result.setZero();
+
100  for (int row = 0; row < m; ++row) {
+
101  int idx = csr_u_to_z(u, row);
+
102  int row_end_in_w = (u[row] - stan::error_index::value) + idx;
+
103  int i = 0; // index into dot-product segment entries.
+
104  Eigen::Matrix<result_t, Eigen::Dynamic, 1> b_sub(idx);
+
105  b_sub.setZero();
+
106  for (int nze = u[row] - stan::error_index::value;
+
107  nze < row_end_in_w; ++nze, ++i) {
+
108  check_range("csr_matrix_times_vector", "j", n, v[nze]);
+
109  b_sub.coeffRef(i) = b.coeffRef(v[nze] - stan::error_index::value);
+
110  } // loop skipped when z is zero.
+
111  Eigen::Matrix<T1, Eigen::Dynamic, 1>
+
112  w_sub(w.segment(u[row] - stan::error_index::value, idx));
+
113  result.coeffRef(row) = dot_product(w_sub, b_sub);
+
114  }
+
115  return result;
+
116  }
+
117  // end of csr_format group
+
119 
+
120  }
+
121 
+
122 }
+
123 
+
124 #endif
+ + + +
int csr_u_to_z(const std::vector< int > &u, int i)
Return the z vector computed from the specified u vector at the index for the z vector.
Definition: csr_u_to_z.hpp:24
+
bool check_range(const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
Return true if specified index is within range.
Definition: check_range.hpp:29
+
Eigen::Matrix< T, 1, Eigen::Dynamic > row(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i)
Return the specified row of the specified matrix, using start-at-1 indexing.
Definition: row.hpp:25
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ + + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, Eigen::Dynamic, 1 > csr_matrix_times_vector(const int &m, const int &n, const Eigen::Matrix< T1, Eigen::Dynamic, 1 > &w, const std::vector< int > &v, const std::vector< int > &u, const Eigen::Matrix< T2, Eigen::Dynamic, 1 > &b)
+ +
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diff --git a/doc/api/html/csr__to__dense__matrix_8hpp.html b/doc/api/html/csr__to__dense__matrix_8hpp.html new file mode 100644 index 00000000000..a7307315ecf --- /dev/null +++ b/doc/api/html/csr__to__dense__matrix_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_to_dense_matrix.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::csr_to_dense_matrix (const int &m, const int &n, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &w, const std::vector< int > &v, const std::vector< int > &u)
 Construct a dense Eigen matrix from the CSR format components. More...
 
+
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diff --git a/doc/api/html/csr__to__dense__matrix_8hpp_source.html b/doc/api/html/csr__to__dense__matrix_8hpp_source.html new file mode 100644 index 00000000000..21d6546c52f --- /dev/null +++ b/doc/api/html/csr__to__dense__matrix_8hpp_source.html @@ -0,0 +1,178 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_to_dense_matrix.hpp Source File + + + + + + + + + + +
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csr_to_dense_matrix.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CSR_TO_DENSE_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CSR_TO_DENSE_MATRIX_HPP
+
3 
+ + + + + + +
10 #include <vector>
+
11 
+
12 namespace stan {
+
13 
+
14  namespace math {
+
15 
+
33  template <typename T>
+
34  inline Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
35  csr_to_dense_matrix(const int& m,
+
36  const int& n,
+
37  const Eigen::Matrix<T, Eigen::Dynamic, 1>& w,
+
38  const std::vector<int>& v,
+
39  const std::vector<int>& u) {
+
40  using Eigen::Dynamic;
+
41  using Eigen::Matrix;
+
42 
+
43  check_positive("csr_to_dense_matrix", "m", m);
+
44  check_positive("csr_to_dense_matrix", "n", n);
+
45  check_size_match("csr_to_dense_matrix", "m", m, "u", u.size()-1);
+
46  check_size_match("csr_to_dense_matrix", "w", w.size(), "v", v.size());
+
47  check_size_match("csr_to_dense_matrix", "u/z",
+
48  u[m-1] + csr_u_to_z(u, m - 1) - 1,
+
49  "v", v.size());
+
50  for (size_t i = 0; i < v.size(); ++i)
+
51  check_range("csr_to_dense_matrix", "v[]", n, v[i]);
+
52 
+
53  Matrix<T, Dynamic, Dynamic> result(m, n);
+
54  result.setZero();
+
55  for (int row = 0; row < m; ++row) {
+
56  int row_end_in_w = (u[row] - stan::error_index::value)
+
57  + csr_u_to_z(u, row);
+
58  check_range("csr_to_dense_matrix", "w", w.size(), row_end_in_w);
+
59  for (int nze = u[row] - stan::error_index::value;
+
60  nze < row_end_in_w; ++nze) {
+
61  // row is row index, v[nze] is column index. w[nze] is entry value.
+
62  check_range("csr_to_dense_matrix", "j", n, v[nze]);
+
63  result(row, v[nze] - stan::error_index::value) = w(nze);
+
64  }
+
65  }
+
66  return result;
+
67  }
+
68  // end of csr_format group
+
70 
+
71  }
+
72 }
+
73 #endif
+ + + +
int csr_u_to_z(const std::vector< int > &u, int i)
Return the z vector computed from the specified u vector at the index for the z vector.
Definition: csr_u_to_z.hpp:24
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > csr_to_dense_matrix(const int &m, const int &n, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &w, const std::vector< int > &v, const std::vector< int > &u)
Construct a dense Eigen matrix from the CSR format components.
+
bool check_range(const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
Return true if specified index is within range.
Definition: check_range.hpp:29
+
Eigen::Matrix< T, 1, Eigen::Dynamic > row(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i)
Return the specified row of the specified matrix, using start-at-1 indexing.
Definition: row.hpp:25
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/csr__u__to__z_8hpp.html b/doc/api/html/csr__u__to__z_8hpp.html new file mode 100644 index 00000000000..186d73d42c9 --- /dev/null +++ b/doc/api/html/csr__u__to__z_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_u_to_z.hpp File Reference + + + + + + + + + + +
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csr_u_to_z.hpp File Reference
+
+
+
#include <stan/math/prim/mat/err/check_range.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stdexcept>
+#include <vector>
+
+

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 Matrices and templated mathematical functions.
 
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int stan::math::csr_u_to_z (const std::vector< int > &u, int i)
 Return the z vector computed from the specified u vector at the index for the z vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/csr__u__to__z_8hpp_source.html b/doc/api/html/csr__u__to__z_8hpp_source.html new file mode 100644 index 00000000000..9eb7ec905b6 --- /dev/null +++ b/doc/api/html/csr__u__to__z_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/csr_u_to_z.hpp Source File + + + + + + + + + + +
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+
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csr_u_to_z.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CSR_U_TO_Z
+
2 #define STAN_MATH_PRIM_MAT_FUN_CSR_U_TO_Z
+
3 
+ + +
6 #include <stdexcept>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
24  int csr_u_to_z(const std::vector<int>& u, int i) {
+
25  check_positive("csr_u_to_z", "u.size()", u.size());
+
26  check_range("csr_u_to_z", "i", u.size(), i + 1, "index out of range");
+
27  return u[i + 1] - u[i];
+
28  }
+
29 
+
30  }
+
31 }
+
32 #endif
+ + +
int csr_u_to_z(const std::vector< int > &u, int i)
Return the z vector computed from the specified u vector at the index for the z vector.
Definition: csr_u_to_z.hpp:24
+
bool check_range(const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
Return true if specified index is within range.
Definition: check_range.hpp:29
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cumulative__sum_8hpp.html b/doc/api/html/cumulative__sum_8hpp.html new file mode 100644 index 00000000000..14276aed43c --- /dev/null +++ b/doc/api/html/cumulative__sum_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cumulative_sum.hpp File Reference + + + + + + + + + + +
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+
cumulative_sum.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
+

Go to the source code of this file.

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 stan
 
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 Matrices and templated mathematical functions.
 
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+Functions

template<typename T >
std::vector< T > stan::math::cumulative_sum (const std::vector< T > &x)
 Return the cumulative sum of the specified vector. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > stan::math::cumulative_sum (const Eigen::Matrix< T, R, C > &m)
 Return the cumulative sum of the specified matrix. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/cumulative__sum_8hpp_source.html b/doc/api/html/cumulative__sum_8hpp_source.html new file mode 100644 index 00000000000..ba33b5f401c --- /dev/null +++ b/doc/api/html/cumulative__sum_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cumulative_sum.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
cumulative_sum.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_CUMULATIVE_SUM_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CUMULATIVE_SUM_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
21  template <typename T>
+
22  inline std::vector<T>
+
23  cumulative_sum(const std::vector<T>& x) {
+
24  std::vector<T> result(x.size());
+
25  if (x.size() == 0)
+
26  return result;
+
27  result[0] = x[0];
+
28  for (size_t i = 1; i < result.size(); ++i)
+
29  result[i] = x[i] + result[i-1];
+
30  return result;
+
31  }
+
32 
+
47  template <typename T, int R, int C>
+
48  inline Eigen::Matrix<T, R, C>
+
49  cumulative_sum(const Eigen::Matrix<T, R, C>& m) {
+
50  Eigen::Matrix<T, R, C> result(m.rows(), m.cols());
+
51  if (m.size() == 0)
+
52  return result;
+
53  result(0) = m(0);
+
54  for (int i = 1; i < result.size(); ++i)
+
55  result(i) = m(i) + result(i-1);
+
56  return result;
+
57  }
+
58  }
+
59 }
+
60 #endif
+
std::vector< T > cumulative_sum(const std::vector< T > &x)
Return the cumulative sum of the specified vector.
+ + +
+
+
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diff --git a/doc/api/html/cvodes__ode__data_8hpp.html b/doc/api/html/cvodes__ode__data_8hpp.html new file mode 100644 index 00000000000..bd1549cd457 --- /dev/null +++ b/doc/api/html/cvodes__ode__data_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/cvodes_ode_data.hpp File Reference + + + + + + + + + + +
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cvodes_ode_data.hpp File Reference
+
+
+
#include <stan/math/rev/mat/functor/ode_system.hpp>
+#include <stan/math/rev/scal/meta/is_var.hpp>
+#include <cvodes/cvodes.h>
+#include <cvodes/cvodes_band.h>
+#include <cvodes/cvodes_dense.h>
+#include <nvector/nvector_serial.h>
+#include <algorithm>
+#include <vector>
+
+

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+ + + + + +

+Classes

class  stan::math::cvodes_ode_data< F, T_initial, T_param >
 CVODES ode data holder object which is used during CVODES integration for CVODES callbacks. More...
 
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+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
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+
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diff --git a/doc/api/html/cvodes__ode__data_8hpp_source.html b/doc/api/html/cvodes__ode__data_8hpp_source.html new file mode 100644 index 00000000000..a2c9fda77d1 --- /dev/null +++ b/doc/api/html/cvodes__ode__data_8hpp_source.html @@ -0,0 +1,272 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/cvodes_ode_data.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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+
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cvodes_ode_data.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUNCTOR_CVODES_ODE_DATA_HPP
+
2 #define STAN_MATH_REV_MAT_FUNCTOR_CVODES_ODE_DATA_HPP
+
3 
+ + +
6 #include <cvodes/cvodes.h>
+
7 #include <cvodes/cvodes_band.h>
+
8 #include <cvodes/cvodes_dense.h>
+
9 #include <nvector/nvector_serial.h>
+
10 #include <algorithm>
+
11 #include <vector>
+
12 
+
13 namespace stan {
+
14 
+
15  namespace math {
+
16 
+
26  template<typename F, typename T_initial, typename T_param>
+ +
28  const std::vector<T_initial>& y0_;
+
29  const std::vector<T_param>& theta_;
+
30  const size_t N_;
+
31  const size_t M_;
+
32  const size_t param_var_ind_;
+
33  const ode_system<F> ode_system_;
+
34 
+ + +
37 
+
38  public:
+
53  cvodes_ode_data(const F& f,
+
54  const std::vector<T_initial>& y0,
+
55  const std::vector<T_param>& theta,
+
56  const std::vector<double>& x,
+
57  const std::vector<int>& x_int,
+
58  std::ostream* msgs)
+
59  : y0_(y0),
+
60  theta_(theta),
+
61  N_(y0.size()),
+
62  M_(theta.size()),
+
63  param_var_ind_(initial_var::value ? N_ : 0),
+
64  ode_system_(f, stan::math::value_of(theta), x, x_int, msgs) { }
+
65 
+
66  static int ode_rhs(double t, N_Vector y, N_Vector ydot, void* user_data) {
+
67  const ode_data* explicit_ode
+
68  = static_cast<const ode_data*>(user_data);
+
69  explicit_ode->rhs(NV_DATA_S(y), NV_DATA_S(ydot), t);
+
70  return 0;
+
71  }
+
72 
+
73  static int ode_rhs_sens(int Ns, realtype t,
+
74  N_Vector y, N_Vector ydot,
+
75  N_Vector *yS, N_Vector *ySdot, void *user_data,
+
76  N_Vector tmp1, N_Vector tmp2) {
+
77  const ode_data* explicit_ode = static_cast<const ode_data*>(user_data);
+
78  const std::vector<double> y_vec(NV_DATA_S(y),
+
79  NV_DATA_S(y) + explicit_ode->N_);
+
80  explicit_ode->rhs_sens(explicit_ode->y0_, explicit_ode->theta_,
+
81  t, y_vec, yS, ySdot);
+
82  return 0;
+
83  }
+
84 
+
85  static int dense_jacobian(long int N, // NOLINT(runtime/int)
+
86  realtype t, N_Vector y, N_Vector fy,
+
87  DlsMat J, void *user_data,
+
88  N_Vector tmp1, N_Vector tmp2, N_Vector tmp3) {
+
89  const ode_data* explicit_ode = static_cast<const ode_data*>(user_data);
+
90  return explicit_ode->dense_jacobian(NV_DATA_S(y), J, t);
+
91  }
+
92 
+
93  private:
+
94  void rhs(const double y[], double dy_dt[], double t) const {
+
95  const std::vector<double> y_vec(y, y + N_);
+
96  std::vector<double> dy_dt_vec(N_);
+
97  ode_system_(t, y_vec, dy_dt_vec);
+
98  std::copy(dy_dt_vec.begin(), dy_dt_vec.end(), dy_dt);
+
99  }
+
100 
+
101  int dense_jacobian(const double* y, DlsMat J, double t) const {
+
102  const std::vector<double> y_vec(y, y + N_);
+
103  Eigen::VectorXd fy(N_);
+
104  // Eigen and CVODES use column major addressing
+
105  Eigen::Map<Eigen::MatrixXd> Jy_map(J->data, N_, N_);
+
106  ode_system_.jacobian(t, y_vec, fy, Jy_map);
+
107  return 0;
+
108  }
+
109 
+
110  inline void rhs_sens_initial(const Eigen::MatrixXd& Jy,
+
111  N_Vector *yS, N_Vector *ySdot) const {
+
112  for (size_t m = 0; m < N_; ++m) {
+
113  Eigen::Map<Eigen::VectorXd> yS_eig(NV_DATA_S(yS[m]), N_);
+
114  Eigen::Map<Eigen::VectorXd> ySdot_eig(NV_DATA_S(ySdot[m]), N_);
+
115  ySdot_eig = Jy * yS_eig;
+
116  }
+
117  }
+
118 
+
119  inline void rhs_sens_param(const Eigen::MatrixXd& Jy,
+
120  const Eigen::MatrixXd& Jtheta,
+
121  N_Vector *yS, N_Vector *ySdot) const {
+
122  using Eigen::Map;
+
123  using Eigen::VectorXd;
+
124  for (size_t m = 0; m < M_; ++m) {
+
125  Map<VectorXd> yS_eig(NV_DATA_S(yS[param_var_ind_ + m]), N_);
+
126  Map<VectorXd> ySdot_eig(NV_DATA_S(ySdot[param_var_ind_ + m]), N_);
+
127  ySdot_eig = Jy * yS_eig + Jtheta.col(m);
+
128  }
+
129  }
+
130 
+
142  void rhs_sens(const std::vector<stan::math::var>& initial,
+
143  const std::vector<stan::math::var>& param,
+
144  const double t, const std::vector<double>& y,
+
145  N_Vector *yS, N_Vector *ySdot) const {
+
146  Eigen::VectorXd dy_dt(N_);
+
147  Eigen::MatrixXd Jy(N_, N_);
+
148  Eigen::MatrixXd Jtheta(N_, M_);
+
149  ode_system_.jacobian(t, y, dy_dt, Jy, Jtheta);
+
150  rhs_sens_initial(Jy, yS, ySdot);
+
151  rhs_sens_param(Jy, Jtheta, yS, ySdot);
+
152  }
+
153 
+
165  void rhs_sens(const std::vector<double>& initial,
+
166  const std::vector<stan::math::var>& param,
+
167  const double t, const std::vector<double>& y,
+
168  N_Vector *yS, N_Vector *ySdot) const {
+
169  Eigen::VectorXd dy_dt(N_);
+
170  Eigen::MatrixXd Jy(N_, N_);
+
171  Eigen::MatrixXd Jtheta(N_, M_);
+
172  ode_system_.jacobian(t, y, dy_dt, Jy, Jtheta);
+
173  rhs_sens_param(Jy, Jtheta, yS, ySdot);
+
174  }
+
175 
+
187  void rhs_sens(const std::vector<stan::math::var>& initial,
+
188  const std::vector<double>& param,
+
189  const double t, const std::vector<double>& y,
+
190  N_Vector *yS, N_Vector *ySdot) const {
+
191  Eigen::VectorXd dy_dt(N_);
+
192  Eigen::MatrixXd Jy(N_, N_);
+
193  ode_system_.jacobian(t, y, dy_dt, Jy);
+
194  rhs_sens_initial(Jy, yS, ySdot);
+
195  }
+
196 
+
208  void rhs_sens(const std::vector<double>& initial,
+
209  const std::vector<double>& param,
+
210  const double t, const std::vector<double>& y,
+
211  N_Vector *yS, N_Vector *ySdot) const {
+
212  }
+
213  };
+
214 
+
215  }
+
216 }
+
217 #endif
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ + +
static int ode_rhs_sens(int Ns, realtype t, N_Vector y, N_Vector ydot, N_Vector *yS, N_Vector *ySdot, void *user_data, N_Vector tmp1, N_Vector tmp2)
+
void jacobian(const double t, const std::vector< double > &y, Eigen::MatrixBase< Derived1 > &dy_dt, Eigen::MatrixBase< Derived2 > &Jy) const
Calculate the Jacobian of the ODE RHS wrt to states y.
Definition: ode_system.hpp:67
+
CVODES ode data holder object which is used during CVODES integration for CVODES callbacks.
+
static int dense_jacobian(long int N, realtype t, N_Vector y, N_Vector fy, DlsMat J, void *user_data, N_Vector tmp1, N_Vector tmp2, N_Vector tmp3)
+
Internal representation of an ODE model object which provides convenient Jacobian functions to obtain...
Definition: ode_system.hpp:21
+
cvodes_ode_data(const F &f, const std::vector< T_initial > &y0, const std::vector< T_param > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
Construct CVODES ode data object to enable callbacks from CVODES during ODE integration.
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
static int ode_rhs(double t, N_Vector y, N_Vector ydot, void *user_data)
+
+
+
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diff --git a/doc/api/html/cvodes__utils_8hpp.html b/doc/api/html/cvodes__utils_8hpp.html new file mode 100644 index 00000000000..5e0c838bdf6 --- /dev/null +++ b/doc/api/html/cvodes__utils_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/cvodes_utils.hpp File Reference + + + + + + + + + + +
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cvodes_utils.hpp File Reference
+
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#include <cvodes/cvodes.h>
+#include <cvodes/cvodes_band.h>
+#include <cvodes/cvodes_dense.h>
+#include <nvector/nvector_serial.h>
+#include <sstream>
+#include <string>
+
+

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void stan::math::cvodes_silent_err_handler (int error_code, const char *module, const char *function, char *msg, void *eh_data)
 
void stan::math::cvodes_check_flag (int flag, const std::string &func_name)
 
void stan::math::cvodes_set_options (void *cvodes_mem, double rel_tol, double abs_tol, long int max_num_steps)
 
+
+
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diff --git a/doc/api/html/cvodes__utils_8hpp_source.html b/doc/api/html/cvodes__utils_8hpp_source.html new file mode 100644 index 00000000000..6d77d1cf736 --- /dev/null +++ b/doc/api/html/cvodes__utils_8hpp_source.html @@ -0,0 +1,173 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/cvodes_utils.hpp Source File + + + + + + + + + + +
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cvodes_utils.hpp
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1 #ifndef STAN_MATH_REV_MAT_FUNCTOR_CVODES_UTILS_HPP
+
2 #define STAN_MATH_REV_MAT_FUNCTOR_CVODES_UTILS_HPP
+
3 
+
4 #include <cvodes/cvodes.h>
+
5 #include <cvodes/cvodes_band.h>
+
6 #include <cvodes/cvodes_dense.h>
+
7 #include <nvector/nvector_serial.h>
+
8 #include <sstream>
+
9 #include <string>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15  // no-op error handler to silence CVodes error output; errors handled
+
16  // directly by Stan
+
17  extern "C"
+
18  inline void cvodes_silent_err_handler(int error_code, const char *module,
+
19  const char *function, char *msg,
+
20  void *eh_data) {
+
21  }
+
22 
+
23  inline void cvodes_check_flag(int flag, const std::string& func_name) {
+
24  if (flag < 0) {
+
25  std::ostringstream ss;
+
26  ss << func_name << " failed with error flag " << flag;
+
27  throw std::runtime_error(ss.str());
+
28  }
+
29  }
+
30 
+
31  inline void cvodes_set_options(void* cvodes_mem,
+
32  double rel_tol, double abs_tol,
+
33  // NOLINTNEXTLINE(runtime/int)
+
34  long int max_num_steps) {
+
35  // forward CVode errors to noop error handler
+
36  CVodeSetErrHandlerFn(cvodes_mem, cvodes_silent_err_handler, 0);
+
37 
+
38  // Initialize solver parameters
+
39  cvodes_check_flag(CVodeSStolerances(cvodes_mem, rel_tol, abs_tol),
+
40  "CVodeSStolerances");
+
41 
+
42  cvodes_check_flag(CVodeSetMaxNumSteps(cvodes_mem, max_num_steps),
+
43  "CVodeSetMaxNumSteps");
+
44 
+
45  double init_step = 0;
+
46  cvodes_check_flag(CVodeSetInitStep(cvodes_mem, init_step),
+
47  "CVodeSetInitStep");
+
48 
+
49  long int max_err_test_fails = 20; // NOLINT(runtime/int)
+
50  cvodes_check_flag(CVodeSetMaxErrTestFails(cvodes_mem, max_err_test_fails),
+
51  "CVodeSetMaxErrTestFails");
+
52 
+
53  long int max_conv_fails = 50; // NOLINT(runtime/int)
+
54  cvodes_check_flag(CVodeSetMaxConvFails(cvodes_mem, max_conv_fails),
+
55  "CVodeSetMaxConvFails");
+
56  }
+
57 
+
58  }
+
59 }
+
60 #endif
+
void cvodes_set_options(void *cvodes_mem, double rel_tol, double abs_tol, long int max_num_steps)
+ +
void cvodes_check_flag(int flag, const std::string &func_name)
+
void cvodes_silent_err_handler(int error_code, const char *module, const char *function, char *msg, void *eh_data)
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/ddv__vari_8hpp.html b/doc/api/html/ddv__vari_8hpp.html new file mode 100644 index 00000000000..07d529c43b0 --- /dev/null +++ b/doc/api/html/ddv__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/ddv_vari.hpp File Reference + + + + + + + + + + +
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ddv_vari.hpp File Reference
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class  stan::math::op_ddv_vari
 
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diff --git a/doc/api/html/ddv__vari_8hpp_source.html b/doc/api/html/ddv__vari_8hpp_source.html new file mode 100644 index 00000000000..efdb9857c82 --- /dev/null +++ b/doc/api/html/ddv__vari_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/rev/core/ddv_vari.hpp Source File + + + + + + + + + + +
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ddv_vari.hpp
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1 #ifndef STAN_MATH_REV_CORE_DDV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_DDV_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_ddv_vari : public vari {
+
10  protected:
+
11  double ad_;
+
12  double bd_;
+ +
14  public:
+
15  op_ddv_vari(double f, double a, double b, vari* cvi) :
+
16  vari(f),
+
17  ad_(a),
+
18  bd_(b),
+
19  cvi_(cvi) {
+
20  }
+
21  };
+
22 
+
23  }
+
24 }
+
25 #endif
+ +
op_ddv_vari(double f, double a, double b, vari *cvi)
Definition: ddv_vari.hpp:15
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/decouple__ode__states_8hpp.html b/doc/api/html/decouple__ode__states_8hpp.html new file mode 100644 index 00000000000..4981fc09513 --- /dev/null +++ b/doc/api/html/decouple__ode__states_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/fun/decouple_ode_states.hpp File Reference + + + + + + + + + + +
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decouple_ode_states.hpp File Reference
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+Functions

template<typename T_initial , typename T_param >
std::vector< std::vector< typename stan::return_type< T_initial, T_param >::type > > stan::math::decouple_ode_states (const std::vector< std::vector< double > > &y, const std::vector< T_initial > &y0, const std::vector< T_param > &theta)
 Takes sensitivity output from integrators and returns results in precomputed_gradients format. More...
 
template<>
std::vector< std::vector< double > > stan::math::decouple_ode_states (const std::vector< std::vector< double > > &y, const std::vector< double > &y0, const std::vector< double > &theta)
 The decouple ODE states operation for the case of no sensitivities is equal to the indentity operation. More...
 
+
+
+
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diff --git a/doc/api/html/decouple__ode__states_8hpp_source.html b/doc/api/html/decouple__ode__states_8hpp_source.html new file mode 100644 index 00000000000..9ca5fe5d9cb --- /dev/null +++ b/doc/api/html/decouple__ode__states_8hpp_source.html @@ -0,0 +1,185 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/fun/decouple_ode_states.hpp Source File + + + + + + + + + + +
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decouple_ode_states.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_ARR_FUN_DECOUPLE_ODE_STATES_HPP
+
2 #define STAN_MATH_REV_ARR_FUN_DECOUPLE_ODE_STATES_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
34  template <typename T_initial, typename T_param>
+
35  inline
+
36  std::vector<std::vector<typename stan::return_type<T_initial,
+
37  T_param>::type> >
+
38  decouple_ode_states(const std::vector<std::vector<double> >& y,
+
39  const std::vector<T_initial>& y0,
+
40  const std::vector<T_param>& theta) {
+
41  using std::vector;
+
42  using stan::math::var;
+ +
44 
+
45  vector<typename stan::return_type<T_initial, T_param>::type> vars;
+
46  typedef stan::is_var<T_initial> initial_var;
+
47  typedef stan::is_var<T_param> param_var;
+
48 
+
49  const size_t N = y0.size();
+
50  const size_t M = theta.size();
+
51  const size_t S = (initial_var::value ? N : 0)
+
52  + (param_var::value ? M : 0);
+
53 
+
54  vars.reserve(S);
+
55  if (initial_var::value)
+
56  vars.insert(vars.end(), y0.begin(), y0.end());
+
57  if (param_var::value)
+
58  vars.insert(vars.end(), theta.begin(), theta.end());
+
59 
+
60  vector<var> temp_vars(N);
+
61  vector<double> temp_gradients(S);
+
62  vector<vector<var> > y_return(y.size());
+
63 
+
64  for (size_t i = 0; i < y.size(); ++i) {
+
65  for (size_t j = 0; j < N; ++j) {
+
66  for (size_t k = 0; k < S; ++k) {
+
67  temp_gradients[k] = y[i][N + N * k + j];
+
68  }
+
69  temp_vars[j] = precomputed_gradients(y[i][j],
+
70  vars, temp_gradients);
+
71  }
+
72  y_return[i] = temp_vars;
+
73  }
+
74  return y_return;
+
75  }
+
76 
+
86  template <>
+
87  inline
+
88  std::vector<std::vector<double> >
+
89  decouple_ode_states(const std::vector<std::vector<double> >& y,
+
90  const std::vector<double>& y0,
+
91  const std::vector<double>& theta) {
+
92  return y;
+
93  }
+
94 
+
95  }
+
96 }
+
97 #endif
+
var precomputed_gradients(const double value, const std::vector< var > &operands, const std::vector< double > &gradients)
This function returns a var for an expression that has the specified value, vector of operands...
+ + + +
Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of...
Definition: return_type.hpp:19
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
std::vector< std::vector< typename stan::return_type< T_initial, T_param >::type > > decouple_ode_states(const std::vector< std::vector< double > > &y, const std::vector< T_initial > &y0, const std::vector< T_param > &theta)
Takes sensitivity output from integrators and returns results in precomputed_gradients format...
+ +
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diff --git a/doc/api/html/derivative_8hpp.html b/doc/api/html/derivative_8hpp.html new file mode 100644 index 00000000000..beb071f3911 --- /dev/null +++ b/doc/api/html/derivative_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/derivative.hpp File Reference + + + + + + + + + + +
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derivative.hpp File Reference
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#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <vector>
+
+

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template<typename T , typename F >
void stan::math::derivative (const F &f, const T &x, T &fx, T &dfx_dx)
 Return the derivative of the specified univariate function at the specified argument. More...
 
+
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diff --git a/doc/api/html/derivative_8hpp_source.html b/doc/api/html/derivative_8hpp_source.html new file mode 100644 index 00000000000..e64e1248632 --- /dev/null +++ b/doc/api/html/derivative_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/derivative.hpp Source File + + + + + + + + + + +
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derivative.hpp
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1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_DERIVATIVE_HPP
+
2 #define STAN_MATH_MIX_MAT_FUNCTOR_DERIVATIVE_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <stan/math/rev/core.hpp>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
24  template <typename T, typename F>
+
25  void
+
26  derivative(const F& f,
+
27  const T& x,
+
28  T& fx,
+
29  T& dfx_dx) {
+
30  fvar<T> x_fvar = fvar<T>(x, 1.0);
+
31  fvar<T> fx_fvar = f(x_fvar);
+
32  fx = fx_fvar.val_;
+
33  dfx_dx = fx_fvar.d_;
+
34  }
+
35 
+
36  } // namespace math
+
37 } // namespace stan
+
38 #endif
+ + + + + +
void derivative(const F &f, const T &x, T &fx, T &dfx_dx)
Return the derivative of the specified univariate function at the specified argument.
Definition: derivative.hpp:26
+ + +
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diff --git a/doc/api/html/diag__matrix_8hpp.html b/doc/api/html/diag__matrix_8hpp.html new file mode 100644 index 00000000000..eea2baec1d2 --- /dev/null +++ b/doc/api/html/diag__matrix_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/diag_matrix.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::diag_matrix (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v)
 Return a square diagonal matrix with the specified vector of coefficients as the diagonal values. More...
 
+
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diff --git a/doc/api/html/diag__matrix_8hpp_source.html b/doc/api/html/diag__matrix_8hpp_source.html new file mode 100644 index 00000000000..4c267aa21a2 --- /dev/null +++ b/doc/api/html/diag__matrix_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/diag_matrix.hpp Source File + + + + + + + + + + +
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diag_matrix.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DIAG_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DIAG_MATRIX_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
15  template <typename T>
+
16  inline
+
17  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
18  diag_matrix(const Eigen::Matrix<T, Eigen::Dynamic, 1>& v) {
+
19  return v.asDiagonal();
+
20  }
+
21 
+
22  }
+
23 }
+
24 #endif
+ +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > diag_matrix(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v)
Return a square diagonal matrix with the specified vector of coefficients as the diagonal values...
Definition: diag_matrix.hpp:18
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diff --git a/doc/api/html/diag__post__multiply_8hpp.html b/doc/api/html/diag__post__multiply_8hpp.html new file mode 100644 index 00000000000..b5e186bad38 --- /dev/null +++ b/doc/api/html/diag__post__multiply_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/diag_post_multiply.hpp File Reference + + + + + + + + + + +
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diag_post_multiply.hpp File Reference
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <stdexcept>
+
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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C1 > stan::math::diag_post_multiply (const Eigen::Matrix< T1, R1, C1 > &m1, const Eigen::Matrix< T2, R2, C2 > &m2)
 
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diff --git a/doc/api/html/diag__post__multiply_8hpp_source.html b/doc/api/html/diag__post__multiply_8hpp_source.html new file mode 100644 index 00000000000..840f176d32b --- /dev/null +++ b/doc/api/html/diag__post__multiply_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/diag_post_multiply.hpp Source File + + + + + + + + + + +
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diag_post_multiply.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DIAG_POST_MULTIPLY_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DIAG_POST_MULTIPLY_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+
6 #include <stdexcept>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
12  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
13  R1, C1>
+
14  diag_post_multiply(const Eigen::Matrix<T1, R1, C1>& m1,
+
15  const Eigen::Matrix<T2, R2, C2>& m2) {
+
16  if (m2.cols() != 1 && m2.rows() != 1)
+
17  throw std::domain_error("m2 must be a vector");
+
18  int m1_cols = m1.cols();
+
19  if (m2.size() != m1_cols)
+
20  throw std::domain_error("m2 must have same length as m1 has columns");
+
21  int m1_rows = m1.rows();
+
22  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
23  R1, C1>
+
24  result(m1_rows, m1_cols);
+
25 
+
26  for (int j = 0; j < m1_cols; ++j)
+
27  for (int i = 0; i < m1_rows; ++i)
+
28  result(i, j) = m2(j) * m1(i, j);
+
29  return result;
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C1 > diag_post_multiply(const Eigen::Matrix< T1, R1, C1 > &m1, const Eigen::Matrix< T2, R2, C2 > &m2)
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diff --git a/doc/api/html/diag__pre__multiply_8hpp.html b/doc/api/html/diag__pre__multiply_8hpp.html new file mode 100644 index 00000000000..680e4b67aea --- /dev/null +++ b/doc/api/html/diag__pre__multiply_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/diag_pre_multiply.hpp File Reference + + + + + + + + + + +
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diag_pre_multiply.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <stdexcept>
+
+

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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R2, C2 > stan::math::diag_pre_multiply (const Eigen::Matrix< T1, R1, C1 > &m1, const Eigen::Matrix< T2, R2, C2 > &m2)
 
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diff --git a/doc/api/html/diag__pre__multiply_8hpp_source.html b/doc/api/html/diag__pre__multiply_8hpp_source.html new file mode 100644 index 00000000000..ebc33ad0df1 --- /dev/null +++ b/doc/api/html/diag__pre__multiply_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/diag_pre_multiply.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DIAG_PRE_MULTIPLY_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DIAG_PRE_MULTIPLY_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+
6 #include <stdexcept>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
12  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
13  R2, C2>
+
14  diag_pre_multiply(const Eigen::Matrix<T1, R1, C1>& m1,
+
15  const Eigen::Matrix<T2, R2, C2>& m2) {
+
16  if (m1.cols() != 1 && m1.rows() != 1)
+
17  throw std::domain_error("m1 must be a vector");
+
18  int m2_rows = m2.rows();
+
19  if (m1.size() != m2_rows)
+
20  throw std::domain_error("m1 must have same length as m2 has rows");
+
21  int m2_cols = m2.cols();
+
22  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
23  R2, C2>
+
24  result(m2_rows, m2_cols);
+
25  for (int j = 0; j < m2_cols; ++j)
+
26  for (int i = 0; i < m2_rows; ++i)
+
27  result(i, j) = m1(i) * m2(i, j);
+
28  return result;
+
29  }
+
30 
+
31  }
+
32 }
+
33 #endif
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R2, C2 > diag_pre_multiply(const Eigen::Matrix< T1, R1, C1 > &m1, const Eigen::Matrix< T2, R2, C2 > &m2)
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diff --git a/doc/api/html/diagonal_8hpp.html b/doc/api/html/diagonal_8hpp.html new file mode 100644 index 00000000000..f37927b98ae --- /dev/null +++ b/doc/api/html/diagonal_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/diagonal.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::diagonal (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Return a column vector of the diagonal elements of the specified matrix. More...
 
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diff --git a/doc/api/html/diagonal_8hpp_source.html b/doc/api/html/diagonal_8hpp_source.html new file mode 100644 index 00000000000..2c5f6dcd04b --- /dev/null +++ b/doc/api/html/diagonal_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/diagonal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DIAGONAL_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DIAGONAL_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
15  template <typename T>
+
16  inline
+
17  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
18  diagonal(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
19  return m.diagonal();
+
20  }
+
21 
+
22  }
+
23 }
+
24 #endif
+ +
Eigen::Matrix< T, Eigen::Dynamic, 1 > diagonal(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Return a column vector of the diagonal elements of the specified matrix.
Definition: diagonal.hpp:18
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diff --git a/doc/api/html/dims_8hpp.html b/doc/api/html/dims_8hpp.html new file mode 100644 index 00000000000..a647fa1938a --- /dev/null +++ b/doc/api/html/dims_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/dims.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
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template<typename T >
void stan::math::dims (const T &x, std::vector< int > &result)
 
template<typename T , int R, int C>
void stan::math::dims (const Eigen::Matrix< T, R, C > &x, std::vector< int > &result)
 
template<typename T >
void stan::math::dims (const std::vector< T > &x, std::vector< int > &result)
 
template<typename T >
std::vector< int > stan::math::dims (const T &x)
 
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diff --git a/doc/api/html/dims_8hpp_source.html b/doc/api/html/dims_8hpp_source.html new file mode 100644 index 00000000000..aa1c1a17c2f --- /dev/null +++ b/doc/api/html/dims_8hpp_source.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/dims.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DIMS_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DIMS_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline
+
12  void
+
13  dims(const T& x, std::vector<int>& result) {
+
14  /* no op */
+
15  }
+
16  template <typename T, int R, int C>
+
17  inline void
+
18  dims(const Eigen::Matrix<T, R, C>& x,
+
19  std::vector<int>& result) {
+
20  result.push_back(x.rows());
+
21  result.push_back(x.cols());
+
22  }
+
23  template <typename T>
+
24  inline void
+
25  dims(const std::vector<T>& x,
+
26  std::vector<int>& result) {
+
27  result.push_back(x.size());
+
28  if (x.size() > 0)
+
29  dims(x[0], result);
+
30  }
+
31 
+
32  template <typename T>
+
33  inline std::vector<int>
+
34  dims(const T& x) {
+
35  std::vector<int> result;
+
36  dims(x, result);
+
37  return result;
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+ +
void dims(const T &x, std::vector< int > &result)
Definition: dims.hpp:13
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diff --git a/doc/api/html/dir_1dcd98e7c4f45b41e0c83c911c6e550e.html b/doc/api/html/dir_1dcd98e7c4f45b41e0c83c911c6e550e.html new file mode 100644 index 00000000000..ee86ac323f4 --- /dev/null +++ b/doc/api/html/dir_1dcd98e7c4f45b41e0c83c911c6e550e.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: stan/math/rev/mat Directory Reference + + + + + + + + + + +
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file  accumulator.hpp [code]
 
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file  cov_matrix_constrain_lkj.hpp [code]
 
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file  distance.hpp [code]
 
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file  log_determinant_spd.hpp [code]
 
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file  log_sum_exp.hpp [code]
 
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file  mdivide_left.hpp [code]
 
file  mdivide_left_ldlt.hpp [code]
 
file  mdivide_left_spd.hpp [code]
 
file  mdivide_left_tri.hpp [code]
 
file  mdivide_left_tri_low.hpp [code]
 
file  mdivide_right.hpp [code]
 
file  mdivide_right_ldlt.hpp [code]
 
file  mdivide_right_spd.hpp [code]
 
file  mdivide_right_tri.hpp [code]
 
file  mdivide_right_tri_low.hpp [code]
 
file  mean.hpp [code]
 
file  min.hpp [code]
 
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file  multiply.hpp [code]
 
file  multiply_lower_tri_self_transpose.hpp [code]
 
file  num_elements.hpp [code]
 
file  ordered_constrain.hpp [code]
 
file  ordered_free.hpp [code]
 
file  positive_ordered_constrain.hpp [code]
 
file  positive_ordered_free.hpp [code]
 
file  prod.hpp [code]
 
file  promote_common.hpp [code]
 
file  promote_scalar.hpp [code]
 
file  promote_scalar_type.hpp [code]
 
file  promoter.hpp [code]
 
file  qr_Q.hpp [code]
 
file  qr_R.hpp [code]
 
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file  resize.hpp [code]
 
file  row.hpp [code]
 
file  rows.hpp [code]
 
file  rows_dot_product.hpp [code]
 
file  rows_dot_self.hpp [code]
 
file  sd.hpp [code]
 
file  segment.hpp [code]
 
file  simplex_constrain.hpp [code]
 
file  simplex_free.hpp [code]
 
file  singular_values.hpp [code]
 
file  size.hpp [code]
 
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file  tail.hpp [code]
 
file  tcrossprod.hpp [code]
 
file  to_array_1d.hpp [code]
 
file  to_array_2d.hpp [code]
 
file  to_matrix.hpp [code]
 
file  to_row_vector.hpp [code]
 
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file  trace_gen_quad_form.hpp [code]
 
file  trace_inv_quad_form_ldlt.hpp [code]
 
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file  operator_greater_than.hpp [code]
 
file  operator_greater_than_or_equal.hpp [code]
 
file  operator_less_than.hpp [code]
 
file  operator_less_than_or_equal.hpp [code]
 
file  operator_minus_equal.hpp [code]
 
file  operator_multiplication.hpp [code]
 
file  operator_multiply_equal.hpp [code]
 
file  operator_not_equal.hpp [code]
 
file  operator_plus_equal.hpp [code]
 
file  operator_subtraction.hpp [code]
 
file  operator_unary_decrement.hpp [code]
 
file  operator_unary_increment.hpp [code]
 
file  operator_unary_negative.hpp [code]
 
file  operator_unary_not.hpp [code]
 
file  operator_unary_plus.hpp [code]
 
file  precomp_v_vari.hpp [code]
 
file  precomp_vv_vari.hpp [code]
 
file  precomp_vvv_vari.hpp [code]
 
file  precomputed_gradients.hpp [code]
 
file  print_stack.hpp [code]
 
file  recover_memory.hpp [code]
 
file  recover_memory_nested.hpp [code]
 
file  set_zero_all_adjoints.hpp [code]
 
file  set_zero_all_adjoints_nested.hpp [code]
 
file  start_nested.hpp [code]
 
file  std_isinf.hpp [code]
 
file  std_isnan.hpp [code]
 
file  std_numeric_limits.hpp [code]
 
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file  abs.hpp [code]
 
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file  atan.hpp [code]
 
file  atan2.hpp [code]
 
file  atanh.hpp [code]
 
file  bessel_first_kind.hpp [code]
 
file  bessel_second_kind.hpp [code]
 
file  binary_log_loss.hpp [code]
 
file  binomial_coefficient_log.hpp [code]
 
file  cbrt.hpp [code]
 
file  ceil.hpp [code]
 
file  cos.hpp [code]
 
file  cosh.hpp [code]
 
file  digamma.hpp [code]
 
file  erf.hpp [code]
 
file  erfc.hpp [code]
 
file  exp.hpp [code]
 
file  exp2.hpp [code]
 
file  expm1.hpp [code]
 
file  fabs.hpp [code]
 
file  falling_factorial.hpp [code]
 
file  fdim.hpp [code]
 
file  floor.hpp [code]
 
file  fma.hpp [code]
 
file  fmax.hpp [code]
 
file  fmin.hpp [code]
 
file  fmod.hpp [code]
 
file  gamma_p.hpp [code]
 
file  gamma_q.hpp [code]
 
file  grad_inc_beta.hpp [code]
 
file  hypot.hpp [code]
 
file  inc_beta.hpp [code]
 
file  inv.hpp [code]
 
file  inv_cloglog.hpp [code]
 
file  inv_logit.hpp [code]
 
file  inv_Phi.hpp [code]
 
file  inv_sqrt.hpp [code]
 
file  inv_square.hpp [code]
 
file  is_inf.hpp [code]
 
file  is_nan.hpp [code]
 
file  lbeta.hpp [code]
 
file  lgamma.hpp [code]
 
file  lmgamma.hpp [code]
 
file  log.hpp [code]
 
file  log10.hpp [code]
 
file  log1m.hpp [code]
 
file  log1m_exp.hpp [code]
 
file  log1m_inv_logit.hpp [code]
 
file  log1p.hpp [code]
 
file  log1p_exp.hpp [code]
 
file  log2.hpp [code]
 
file  log_diff_exp.hpp [code]
 
file  log_falling_factorial.hpp [code]
 
file  log_inv_logit.hpp [code]
 
file  log_mix.hpp [code]
 
file  log_rising_factorial.hpp [code]
 
file  log_sum_exp.hpp [code]
 
file  logit.hpp [code]
 
file  modified_bessel_first_kind.hpp [code]
 
file  modified_bessel_second_kind.hpp [code]
 
file  multiply_log.hpp [code]
 
file  owens_t.hpp [code]
 
file  Phi.hpp [code]
 
file  pow.hpp [code]
 
file  primitive_value.hpp [code]
 
file  rising_factorial.hpp [code]
 
file  round.hpp [code]
 
file  sin.hpp [code]
 
file  sinh.hpp [code]
 
file  sqrt.hpp [code]
 
file  square.hpp [code]
 
file  tan.hpp [code]
 
file  tanh.hpp [code]
 
file  tgamma.hpp [code]
 
file  to_fvar.hpp [code]
 
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file  bernoulli_ccdf_log.hpp [code]
 
file  bernoulli_cdf.hpp [code]
 
file  bernoulli_cdf_log.hpp [code]
 
file  bernoulli_log.hpp [code]
 
file  bernoulli_logit_log.hpp [code]
 
file  bernoulli_rng.hpp [code]
 
file  beta_binomial_ccdf_log.hpp [code]
 
file  beta_binomial_cdf.hpp [code]
 
file  beta_binomial_cdf_log.hpp [code]
 
file  beta_binomial_log.hpp [code]
 
file  beta_binomial_rng.hpp [code]
 
file  beta_ccdf_log.hpp [code]
 
file  beta_cdf.hpp [code]
 
file  beta_cdf_log.hpp [code]
 
file  beta_log.hpp [code]
 
file  beta_rng.hpp [code]
 
file  binomial_ccdf_log.hpp [code]
 
file  binomial_cdf.hpp [code]
 
file  binomial_cdf_log.hpp [code]
 
file  binomial_log.hpp [code]
 
file  binomial_logit_log.hpp [code]
 
file  binomial_rng.hpp [code]
 
file  cauchy_ccdf_log.hpp [code]
 
file  cauchy_cdf.hpp [code]
 
file  cauchy_cdf_log.hpp [code]
 
file  cauchy_log.hpp [code]
 
file  cauchy_rng.hpp [code]
 
file  chi_square_ccdf_log.hpp [code]
 
file  chi_square_cdf.hpp [code]
 
file  chi_square_cdf_log.hpp [code]
 
file  chi_square_log.hpp [code]
 
file  chi_square_rng.hpp [code]
 
file  double_exponential_ccdf_log.hpp [code]
 
file  double_exponential_cdf.hpp [code]
 
file  double_exponential_cdf_log.hpp [code]
 
file  double_exponential_log.hpp [code]
 
file  double_exponential_rng.hpp [code]
 
file  exp_mod_normal_ccdf_log.hpp [code]
 
file  exp_mod_normal_cdf.hpp [code]
 
file  exp_mod_normal_cdf_log.hpp [code]
 
file  exp_mod_normal_log.hpp [code]
 
file  exp_mod_normal_rng.hpp [code]
 
file  exponential_ccdf_log.hpp [code]
 
file  exponential_cdf.hpp [code]
 
file  exponential_cdf_log.hpp [code]
 
file  exponential_log.hpp [code]
 
file  exponential_rng.hpp [code]
 
file  frechet_ccdf_log.hpp [code]
 
file  frechet_cdf.hpp [code]
 
file  frechet_cdf_log.hpp [code]
 
file  frechet_log.hpp [code]
 
file  frechet_rng.hpp [code]
 
file  gamma_ccdf_log.hpp [code]
 
file  gamma_cdf.hpp [code]
 
file  gamma_cdf_log.hpp [code]
 
file  gamma_log.hpp [code]
 
file  gamma_rng.hpp [code]
 
file  gumbel_ccdf_log.hpp [code]
 
file  gumbel_cdf.hpp [code]
 
file  gumbel_cdf_log.hpp [code]
 
file  gumbel_log.hpp [code]
 
file  gumbel_rng.hpp [code]
 
file  hypergeometric_log.hpp [code]
 
file  hypergeometric_rng.hpp [code]
 
file  inv_chi_square_ccdf_log.hpp [code]
 
file  inv_chi_square_cdf.hpp [code]
 
file  inv_chi_square_cdf_log.hpp [code]
 
file  inv_chi_square_log.hpp [code]
 
file  inv_chi_square_rng.hpp [code]
 
file  inv_gamma_ccdf_log.hpp [code]
 
file  inv_gamma_cdf.hpp [code]
 
file  inv_gamma_cdf_log.hpp [code]
 
file  inv_gamma_log.hpp [code]
 
file  inv_gamma_rng.hpp [code]
 
file  logistic_ccdf_log.hpp [code]
 
file  logistic_cdf.hpp [code]
 
file  logistic_cdf_log.hpp [code]
 
file  logistic_log.hpp [code]
 
file  logistic_rng.hpp [code]
 
file  lognormal_ccdf_log.hpp [code]
 
file  lognormal_cdf.hpp [code]
 
file  lognormal_cdf_log.hpp [code]
 
file  lognormal_log.hpp [code]
 
file  lognormal_rng.hpp [code]
 
file  neg_binomial_2_ccdf_log.hpp [code]
 
file  neg_binomial_2_cdf.hpp [code]
 
file  neg_binomial_2_cdf_log.hpp [code]
 
file  neg_binomial_2_log.hpp [code]
 
file  neg_binomial_2_log_log.hpp [code]
 
file  neg_binomial_2_log_rng.hpp [code]
 
file  neg_binomial_2_rng.hpp [code]
 
file  neg_binomial_ccdf_log.hpp [code]
 
file  neg_binomial_cdf.hpp [code]
 
file  neg_binomial_cdf_log.hpp [code]
 
file  neg_binomial_log.hpp [code]
 
file  neg_binomial_rng.hpp [code]
 
file  normal_ccdf_log.hpp [code]
 
file  normal_cdf.hpp [code]
 
file  normal_cdf_log.hpp [code]
 
file  normal_log.hpp [code]
 
file  normal_rng.hpp [code]
 
file  pareto_ccdf_log.hpp [code]
 
file  pareto_cdf.hpp [code]
 
file  pareto_cdf_log.hpp [code]
 
file  pareto_log.hpp [code]
 
file  pareto_rng.hpp [code]
 
file  pareto_type_2_ccdf_log.hpp [code]
 
file  pareto_type_2_cdf.hpp [code]
 
file  pareto_type_2_cdf_log.hpp [code]
 
file  pareto_type_2_log.hpp [code]
 
file  pareto_type_2_rng.hpp [code]
 
file  poisson_ccdf_log.hpp [code]
 
file  poisson_cdf.hpp [code]
 
file  poisson_cdf_log.hpp [code]
 
file  poisson_log.hpp [code]
 
file  poisson_log_log.hpp [code]
 
file  poisson_log_rng.hpp [code]
 
file  poisson_rng.hpp [code]
 
file  rayleigh_ccdf_log.hpp [code]
 
file  rayleigh_cdf.hpp [code]
 
file  rayleigh_cdf_log.hpp [code]
 
file  rayleigh_log.hpp [code]
 
file  rayleigh_rng.hpp [code]
 
file  scaled_inv_chi_square_ccdf_log.hpp [code]
 
file  scaled_inv_chi_square_cdf.hpp [code]
 
file  scaled_inv_chi_square_cdf_log.hpp [code]
 
file  scaled_inv_chi_square_log.hpp [code]
 
file  scaled_inv_chi_square_rng.hpp [code]
 
file  skew_normal_ccdf_log.hpp [code]
 
file  skew_normal_cdf.hpp [code]
 
file  skew_normal_cdf_log.hpp [code]
 
file  skew_normal_log.hpp [code]
 
file  skew_normal_rng.hpp [code]
 
file  student_t_ccdf_log.hpp [code]
 
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file  quad_form_sym.hpp [code]
 
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file  to_var.hpp [code]
 
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file  abs.hpp [code]
 
file  as_bool.hpp [code]
 
file  bessel_first_kind.hpp [code]
 
file  bessel_second_kind.hpp [code]
 
file  binary_log_loss.hpp [code]
 
file  binomial_coefficient_log.hpp [code]
 
file  constants.hpp [code]
 
file  corr_constrain.hpp [code]
 
file  corr_free.hpp [code]
 
file  digamma.hpp [code]
 
file  divide.hpp [code]
 
file  exp2.hpp [code]
 
file  F32.hpp [code]
 
file  falling_factorial.hpp [code]
 
file  fdim.hpp [code]
 
file  fill.hpp [code]
 
file  gamma_p.hpp [code]
 
file  gamma_q.hpp [code]
 
file  grad_2F1.hpp [code]
 
file  grad_F32.hpp [code]
 
file  grad_inc_beta.hpp [code]
 
file  grad_reg_inc_beta.hpp [code]
 
file  grad_reg_inc_gamma.hpp [code]
 
file  ibeta.hpp [code]
 
file  identity_constrain.hpp [code]
 
file  identity_free.hpp [code]
 
file  if_else.hpp [code]
 
file  inc_beta.hpp [code]
 
file  inc_beta_dda.hpp [code]
 
file  inc_beta_ddb.hpp [code]
 
file  inc_beta_ddz.hpp [code]
 
file  int_step.hpp [code]
 
file  inv.hpp [code]
 
file  inv_cloglog.hpp [code]
 
file  inv_logit.hpp [code]
 
file  inv_Phi.hpp [code]
 
file  inv_sqrt.hpp [code]
 
file  inv_square.hpp [code]
 
file  inverse_softmax.hpp [code]
 
file  is_inf.hpp [code]
 
file  is_nan.hpp [code]
 
file  is_uninitialized.hpp [code]
 
file  lb_constrain.hpp [code]
 
file  lb_free.hpp [code]
 
file  lbeta.hpp [code]
 
file  lgamma.hpp [code]
 
file  lmgamma.hpp [code]
 
file  log1m.hpp [code]
 
file  log1m_exp.hpp [code]
 
file  log1m_inv_logit.hpp [code]
 
file  log1p.hpp [code]
 
file  log1p_exp.hpp [code]
 
file  log2.hpp [code]
 
file  log_diff_exp.hpp [code]
 
file  log_falling_factorial.hpp [code]
 
file  log_inv_logit.hpp [code]
 
file  log_mix.hpp [code]
 
file  log_rising_factorial.hpp [code]
 
file  log_sum_exp.hpp [code]
 
file  logical_and.hpp [code]
 
file  logical_eq.hpp [code]
 
file  logical_gt.hpp [code]
 
file  logical_gte.hpp [code]
 
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file  logical_lte.hpp [code]
 
file  logical_negation.hpp [code]
 
file  logical_neq.hpp [code]
 
file  logical_or.hpp [code]
 
file  logit.hpp [code]
 
file  lub_constrain.hpp [code]
 
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file  modified_bessel_first_kind.hpp [code]
 
file  modified_bessel_second_kind.hpp [code]
 
file  modulus.hpp [code]
 
file  multiply_log.hpp [code]
 
file  owens_t.hpp [code]
 
file  Phi.hpp [code]
 
file  Phi_approx.hpp [code]
 
file  positive_constrain.hpp [code]
 
file  positive_free.hpp [code]
 
file  primitive_value.hpp [code]
 
file  prob_constrain.hpp [code]
 
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file  promote_scalar.hpp [code]
 
file  promote_scalar_type.hpp [code]
 
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file  step.hpp [code]
 
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diff --git a/doc/api/html/dirichlet__log_8hpp.html b/doc/api/html/dirichlet__log_8hpp.html new file mode 100644 index 00000000000..56207a3ad5d --- /dev/null +++ b/doc/api/html/dirichlet__log_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/dirichlet_log.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/gamma.hpp>
+#include <boost/random/gamma_distribution.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <stan/math/prim/mat/err/check_simplex.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+
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template<bool propto, typename T_prob , typename T_prior_sample_size >
boost::math::tools::promote_args< T_prob, T_prior_sample_size >::type stan::math::dirichlet_log (const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta, const Eigen::Matrix< T_prior_sample_size, Eigen::Dynamic, 1 > &alpha)
 The log of the Dirichlet density for the given theta and a vector of prior sample sizes, alpha. More...
 
template<typename T_prob , typename T_prior_sample_size >
boost::math::tools::promote_args< T_prob, T_prior_sample_size >::type stan::math::dirichlet_log (const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta, const Eigen::Matrix< T_prior_sample_size, Eigen::Dynamic, 1 > &alpha)
 
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diff --git a/doc/api/html/dirichlet__log_8hpp_source.html b/doc/api/html/dirichlet__log_8hpp_source.html new file mode 100644 index 00000000000..972c8be2f45 --- /dev/null +++ b/doc/api/html/dirichlet__log_8hpp_source.html @@ -0,0 +1,184 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/dirichlet_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_DIRICHLET_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_DIRICHLET_LOG_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 #include <boost/random/gamma_distribution.hpp>
+
6 #include <boost/random/variate_generator.hpp>
+ + + + + + +
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
17 
+
43  template <bool propto,
+
44  typename T_prob, typename T_prior_sample_size>
+
45  typename boost::math::tools::promote_args<T_prob, T_prior_sample_size>::type
+
46  dirichlet_log(const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta,
+
47  const Eigen::Matrix
+
48  <T_prior_sample_size, Eigen::Dynamic, 1>& alpha) {
+
49  static const char* function("stan::math::dirichlet_log");
+
50  using boost::math::lgamma;
+
51  using boost::math::tools::promote_args;
+ + + + +
56 
+
57  typename promote_args<T_prob, T_prior_sample_size>::type lp(0.0);
+
58  check_consistent_sizes(function,
+
59  "probabilities", theta,
+
60  "prior sample sizes", alpha);
+
61  check_positive(function, "prior sample sizes", alpha);
+
62  check_simplex(function, "probabilities", theta);
+
63 
+ +
65  lp += lgamma(alpha.sum());
+
66  for (int k = 0; k < alpha.rows(); ++k)
+
67  lp -= lgamma(alpha[k]);
+
68  }
+ +
70  for (int k = 0; k < theta.rows(); ++k)
+
71  lp += multiply_log(alpha[k]-1, theta[k]);
+
72  }
+
73  return lp;
+
74  }
+
75 
+
76  template <typename T_prob, typename T_prior_sample_size>
+
77  inline
+
78  typename boost::math::tools::promote_args<T_prob, T_prior_sample_size>::type
+
79  dirichlet_log(const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta,
+
80  const Eigen::Matrix
+
81  <T_prior_sample_size, Eigen::Dynamic, 1>& alpha) {
+
82  return dirichlet_log<false>(theta, alpha);
+
83  }
+
84  }
+
85 }
+
86 #endif
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + +
boost::math::tools::promote_args< T_prob, T_prior_sample_size >::type dirichlet_log(const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta, const Eigen::Matrix< T_prior_sample_size, Eigen::Dynamic, 1 > &alpha)
The log of the Dirichlet density for the given theta and a vector of prior sample sizes...
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_simplex(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is simplex.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/dirichlet__rng_8hpp.html b/doc/api/html/dirichlet__rng_8hpp.html new file mode 100644 index 00000000000..5fa62f6073f --- /dev/null +++ b/doc/api/html/dirichlet__rng_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/dirichlet_rng.hpp File Reference + + + + + + + + + + +
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+
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+
#include <boost/math/special_functions/gamma.hpp>
+#include <boost/random/gamma_distribution.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/mat/err/check_simplex.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/mat/fun/log_sum_exp.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <cmath>
+
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template<class RNG >
Eigen::VectorXd stan::math::dirichlet_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &alpha, RNG &rng)
 Return a draw from a Dirichlet distribution with specified parameters and pseudo-random number generator. More...
 
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diff --git a/doc/api/html/dirichlet__rng_8hpp_source.html b/doc/api/html/dirichlet__rng_8hpp_source.html new file mode 100644 index 00000000000..2d8d5cfd97f --- /dev/null +++ b/doc/api/html/dirichlet__rng_8hpp_source.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/dirichlet_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_DIRICHLET_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_DIRICHLET_RNG_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 #include <boost/random/gamma_distribution.hpp>
+
6 #include <boost/random/uniform_real_distribution.hpp>
+
7 #include <boost/random/variate_generator.hpp>
+
8 
+ + + + + + + +
16 
+
17 #include <cmath>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
44  template <class RNG>
+
45  inline Eigen::VectorXd
+
46  dirichlet_rng(const Eigen::Matrix<double, Eigen::Dynamic, 1>& alpha,
+
47  RNG& rng) {
+
48  using boost::variate_generator;
+
49  using boost::gamma_distribution;
+
50  using boost::random::uniform_real_distribution;
+
51  using Eigen::VectorXd;
+
52  using std::exp;
+
53  using std::log;
+
54 
+
55  // separate algorithm if any parameter is less than 1
+
56  if (alpha.minCoeff() < 1) {
+
57  variate_generator<RNG&, uniform_real_distribution<> >
+
58  uniform_rng(rng, uniform_real_distribution<>(0.0, 1.0));
+
59  VectorXd log_y(alpha.size());
+
60  for (int i = 0; i < alpha.size(); ++i) {
+
61  variate_generator<RNG&, gamma_distribution<> >
+
62  gamma_rng(rng, gamma_distribution<>(alpha(i) + 1, 1));
+
63  double log_u = log(uniform_rng());
+
64  log_y(i) = log(gamma_rng()) + log_u / alpha(i);
+
65  }
+
66  double log_sum_y = log_sum_exp(log_y);
+
67  VectorXd theta(alpha.size());
+
68  for (int i = 0; i < alpha.size(); ++i)
+
69  theta(i) = exp(log_y(i) - log_sum_y);
+
70  return theta;
+
71  }
+
72 
+
73  // standard normalized gamma algorithm
+
74  Eigen::VectorXd y(alpha.rows());
+
75  for (int i = 0; i < alpha.rows(); i++) {
+
76  variate_generator<RNG&, gamma_distribution<> >
+
77  gamma_rng(rng, gamma_distribution<>(alpha(i, 0), 1e-7));
+
78  y(i) = gamma_rng();
+
79  }
+
80  return y / y.sum();
+
81  }
+
82 
+
83  }
+
84 }
+
85 #endif
+ +
double gamma_rng(const double alpha, const double beta, RNG &rng)
Definition: gamma_rng.hpp:30
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+ + +
Eigen::VectorXd dirichlet_rng(const Eigen::Matrix< double, Eigen::Dynamic, 1 > &alpha, RNG &rng)
Return a draw from a Dirichlet distribution with specified parameters and pseudo-random number genera...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
double uniform_rng(const double alpha, const double beta, RNG &rng)
Definition: uniform_rng.hpp:21
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+ + + +
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diff --git a/doc/api/html/dist_8hpp.html b/doc/api/html/dist_8hpp.html new file mode 100644 index 00000000000..26863c6f24f --- /dev/null +++ b/doc/api/html/dist_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/dist.hpp File Reference + + + + + + + + + + +
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double stan::math::dist (const std::vector< double > &x, const std::vector< double > &y)
 
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diff --git a/doc/api/html/dist_8hpp_source.html b/doc/api/html/dist_8hpp_source.html new file mode 100644 index 00000000000..c5b3cc7d9a2 --- /dev/null +++ b/doc/api/html/dist_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/dist.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_DIST_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_DIST_HPP
+
3 
+
4 #include <vector>
+
5 #include <cstddef>
+
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  inline double dist(const std::vector<double>& x,
+
12  const std::vector<double>& y) {
+
13  using std::sqrt;
+
14  double result = 0;
+
15  for (size_t i = 0; i < x.size(); ++i) {
+
16  double diff = x[i] - y[i];
+
17  result += diff * diff;
+
18  }
+
19  return sqrt(result);
+
20  }
+
21 
+
22  }
+
23 }
+
24 
+
25 #endif
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
double dist(const std::vector< double > &x, const std::vector< double > &y)
Definition: dist.hpp:11
+
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diff --git a/doc/api/html/distance_8hpp.html b/doc/api/html/distance_8hpp.html new file mode 100644 index 00000000000..9378af28aa0 --- /dev/null +++ b/doc/api/html/distance_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/distance.hpp File Reference + + + + + + + + + + +
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template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::math::tools::promote_args< T1, T2 >::type stan::math::distance (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 Returns the distance between the specified vectors. More...
 
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diff --git a/doc/api/html/distance_8hpp_source.html b/doc/api/html/distance_8hpp_source.html new file mode 100644 index 00000000000..6f69ebc80ff --- /dev/null +++ b/doc/api/html/distance_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/distance.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_DISTANCE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DISTANCE_HPP
+
3 
+ +
5 
+
6 #include <boost/math/tools/promotion.hpp>
+ + + +
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
23  template<typename T1, int R1, int C1, typename T2, int R2, int C2>
+
24  inline typename boost::math::tools::promote_args<T1, T2>::type
+
25  distance(const Eigen::Matrix<T1, R1, C1>& v1,
+
26  const Eigen::Matrix<T2, R2, C2>& v2) {
+
27  using std::sqrt;
+
28  stan::math::check_vector("distance", "v1", v1);
+
29  stan::math::check_vector("distance", "v2", v2);
+ +
31  "v1", v1,
+
32  "v2", v2);
+
33  return sqrt(squared_distance(v1, v2));
+
34  }
+
35  }
+
36 }
+
37 #endif
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ +
boost::math::tools::promote_args< T1, T2 >::type squared_distance(const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
Returns the squared distance between the specified vectors.
+ + +
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ + +
boost::math::tools::promote_args< T1, T2 >::type distance(const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
Returns the distance between the specified vectors.
Definition: distance.hpp:25
+
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diff --git a/doc/api/html/doc.png b/doc/api/html/doc.png new file mode 100644 index 0000000000000000000000000000000000000000..17edabff95f7b8da13c9516a04efe05493c29501 GIT binary patch literal 746 zcmV7=@pnbNXRFEm&G8P!&WHG=d)>K?YZ1bzou)2{$)) zumDct!>4SyxL;zgaG>wy`^Hv*+}0kUfCrz~BCOViSb$_*&;{TGGn2^x9K*!Sf0=lV zpP=7O;GA0*Jm*tTYj$IoXvimpnV4S1Z5f$p*f$Db2iq2zrVGQUz~yq`ahn7ck(|CE z7Gz;%OP~J6)tEZWDzjhL9h2hdfoU2)Nd%T<5Kt;Y0XLt&<@6pQx!nw*5`@bq#?l*?3z{Hlzoc=Pr>oB5(9i6~_&-}A(4{Q$>c>%rV&E|a(r&;?i5cQB=} zYSDU5nXG)NS4HEs0it2AHe2>shCyr7`6@4*6{r@8fXRbTA?=IFVWAQJL&H5H{)DpM#{W(GL+Idzf^)uRV@oB8u$ z8v{MfJbTiiRg4bza<41NAzrl{=3fl_D+$t+^!xlQ8S}{UtY`e z;;&9UhyZqQRN%2pot{*Ei0*4~hSF_3AH2@fKU!$NSflS>{@tZpDT4`M2WRTTVH+D? z)GFlEGGHe?koB}i|1w45!BF}N_q&^HJ&-tyR{(afC6H7|aml|tBBbv}55C5DNP8p3 z)~jLEO4Z&2hZmP^i-e%(@d!(E|KRafiU8Q5u(wU((j8un3OR*Hvj+t literal 0 HcmV?d00001 diff --git a/doc/api/html/domain__error_8hpp.html b/doc/api/html/domain__error_8hpp.html new file mode 100644 index 00000000000..a95c890366b --- /dev/null +++ b/doc/api/html/domain__error_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/domain_error.hpp File Reference + + + + + + + + + + +
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+#include <stdexcept>
+
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template<typename T >
void stan::math::domain_error (const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
 Throw a domain error with a consistently formatted message. More...
 
template<typename T >
void stan::math::domain_error (const char *function, const char *name, const T &y, const char *msg1)
 Throw a domain error with a consistently formatted message. More...
 
+
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diff --git a/doc/api/html/domain__error_8hpp_source.html b/doc/api/html/domain__error_8hpp_source.html new file mode 100644 index 00000000000..bae750f47e9 --- /dev/null +++ b/doc/api/html/domain__error_8hpp_source.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/domain_error.hpp Source File + + + + + + + + + + +
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domain_error.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_ERR_DOMAIN_ERROR_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_DOMAIN_ERROR_HPP
+
3 
+
4 #include <typeinfo>
+
5 #include <string>
+
6 #include <sstream>
+
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
31  template <typename T>
+
32  inline void domain_error(const char* function,
+
33  const char* name,
+
34  const T& y,
+
35  const char* msg1,
+
36  const char* msg2) {
+
37  std::ostringstream message;
+
38 
+
39  message << function << ": "
+
40  << name << " "
+
41  << msg1
+
42  << y
+
43  << msg2;
+
44 
+
45  throw std::domain_error(message.str());
+
46  }
+
47 
+
66  template <typename T>
+
67  inline void domain_error(const char* function,
+
68  const char* name,
+
69  const T& y,
+
70  const char* msg1) {
+
71  domain_error(function, name, y, msg1, "");
+
72  }
+
73 
+
74  }
+
75 }
+
76 #endif
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1)
Throw a domain error with a consistently formatted message.
+
+
+
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diff --git a/doc/api/html/domain__error__vec_8hpp.html b/doc/api/html/domain__error__vec_8hpp.html new file mode 100644 index 00000000000..24cff0abade --- /dev/null +++ b/doc/api/html/domain__error__vec_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/domain_error_vec.hpp File Reference + + + + + + + + + + +
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template<typename T >
void stan::math::domain_error_vec (const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
 Throw a domain error with a consistently formatted message. More...
 
template<typename T >
void stan::math::domain_error_vec (const char *function, const char *name, const T &y, const size_t i, const char *msg)
 Throw a domain error with a consistently formatted message. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/domain__error__vec_8hpp_source.html b/doc/api/html/domain__error__vec_8hpp_source.html new file mode 100644 index 00000000000..676389f4569 --- /dev/null +++ b/doc/api/html/domain__error__vec_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/domain_error_vec.hpp Source File + + + + + + + + + + +
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domain_error_vec.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_DOMAIN_ERROR_VEC_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_DOMAIN_ERROR_VEC_HPP
+
3 
+ + + + +
8 #include <sstream>
+
9 #include <string>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
37  template <typename T>
+
38  inline void domain_error_vec(const char* function,
+
39  const char* name,
+
40  const T& y,
+
41  const size_t i,
+
42  const char* msg1,
+
43  const char* msg2) {
+
44  std::ostringstream vec_name_stream;
+
45  vec_name_stream << name
+
46  << "[" << stan::error_index::value + i << "]";
+
47  std::string vec_name(vec_name_stream.str());
+
48  domain_error(function, vec_name.c_str(), stan::get(y, i), msg1, msg2);
+
49  }
+
50 
+
72  template <typename T>
+
73  inline void domain_error_vec(const char* function,
+
74  const char* name,
+
75  const T& y,
+
76  const size_t i,
+
77  const char* msg) {
+
78  domain_error_vec(function, name, y, i, msg, "");
+
79  }
+
80 
+
81  }
+
82 }
+
83 #endif
+ + + +
void domain_error_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + + +
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diff --git a/doc/api/html/dot_8hpp.html b/doc/api/html/dot_8hpp.html new file mode 100644 index 00000000000..049798344e4 --- /dev/null +++ b/doc/api/html/dot_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/dot.hpp File Reference + + + + + + + + + + +
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double stan::math::dot (const std::vector< double > &x, const std::vector< double > &y)
 
+
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diff --git a/doc/api/html/dot_8hpp_source.html b/doc/api/html/dot_8hpp_source.html new file mode 100644 index 00000000000..8186a20b0eb --- /dev/null +++ b/doc/api/html/dot_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/dot.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_DOT_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_DOT_HPP
+
3 
+
4 #include <vector>
+
5 #include <cstddef>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  // x' * y
+
11  inline double dot(const std::vector<double>& x,
+
12  const std::vector<double>& y) {
+
13  double sum = 0.0;
+
14  for (size_t i = 0; i < x.size(); ++i)
+
15  sum += x[i] * y[i];
+
16  return sum;
+
17  }
+
18 
+
19  }
+
20 }
+
21 
+
22 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
double dot(const std::vector< double > &x, const std::vector< double > &y)
Definition: dot.hpp:11
+
+
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diff --git a/doc/api/html/double__exponential__ccdf__log_8hpp.html b/doc/api/html/double__exponential__ccdf__log_8hpp.html new file mode 100644 index 00000000000..e6a45dd535d --- /dev/null +++ b/doc/api/html/double__exponential__ccdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::double_exponential_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
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diff --git a/doc/api/html/double__exponential__ccdf__log_8hpp_source.html b/doc/api/html/double__exponential__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..13824791f35 --- /dev/null +++ b/doc/api/html/double__exponential__ccdf__log_8hpp_source.html @@ -0,0 +1,246 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_ccdf_log.hpp Source File + + + + + + + + + + +
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double_exponential_ccdf_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/uniform_01.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <typename T_y, typename T_loc, typename T_scale>
+
25  typename return_type<T_y, T_loc, T_scale>::type
+
26  double_exponential_ccdf_log(const T_y& y, const T_loc& mu,
+
27  const T_scale& sigma) {
+
28  static const char* function("stan::math::double_exponential_ccdf_log");
+ +
30  T_partials_return;
+
31 
+ + + + + +
37 
+
38  T_partials_return ccdf_log(0.0);
+
39 
+
40  // check if any vectors are zero length
+
41  if (!(stan::length(y)
+
42  && stan::length(mu)
+
43  && stan::length(sigma)))
+
44  return ccdf_log;
+
45 
+
46  check_not_nan(function, "Random variable", y);
+
47  check_finite(function, "Location parameter", mu);
+
48  check_positive_finite(function, "Scale parameter", sigma);
+
49  check_consistent_sizes(function,
+
50  "Random variable", y,
+
51  "Location parameter", mu,
+
52  "Scale Parameter", sigma);
+
53 
+
54  using std::log;
+
55  using std::exp;
+
56  using stan::math::log1m;
+
57  using std::exp;
+
58 
+ +
60  operands_and_partials(y, mu, sigma);
+
61 
+
62  VectorView<const T_y> y_vec(y);
+
63  VectorView<const T_loc> mu_vec(mu);
+
64  VectorView<const T_scale> sigma_vec(sigma);
+
65  const double log_half = std::log(0.5);
+
66  size_t N = max_size(y, mu, sigma);
+
67 
+
68  for (size_t n = 0; n < N; n++) {
+
69  const T_partials_return y_dbl = value_of(y_vec[n]);
+
70  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
71  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
72  const T_partials_return scaled_diff = (y_dbl - mu_dbl) / sigma_dbl;
+
73  const T_partials_return inv_sigma = 1.0 / sigma_dbl;
+
74  if (y_dbl < mu_dbl) {
+
75  // log ccdf
+
76  ccdf_log += log1m(0.5 * exp(scaled_diff));
+
77 
+
78  // gradients
+
79  const T_partials_return rep_deriv = 1.0
+
80  / (2.0 * exp(-scaled_diff) - 1.0);
+ +
82  operands_and_partials.d_x1[n] -= rep_deriv * inv_sigma;
+ +
84  operands_and_partials.d_x2[n] += rep_deriv * inv_sigma;
+ +
86  operands_and_partials.d_x3[n] += rep_deriv * scaled_diff
+
87  * inv_sigma;
+
88  } else {
+
89  // log ccdf
+
90  ccdf_log += log_half - scaled_diff;
+
91 
+
92  // gradients
+ +
94  operands_and_partials.d_x1[n] -= inv_sigma;
+ +
96  operands_and_partials.d_x2[n] += inv_sigma;
+ +
98  operands_and_partials.d_x3[n] += scaled_diff * inv_sigma;
+
99  }
+
100  }
+
101  return operands_and_partials.value(ccdf_log);
+
102  }
+
103  }
+
104 }
+
105 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
return_type< T_y, T_loc, T_scale >::type double_exponential_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/double__exponential__cdf_8hpp.html b/doc/api/html/double__exponential__cdf_8hpp.html new file mode 100644 index 00000000000..f3c877858b9 --- /dev/null +++ b/doc/api/html/double__exponential__cdf_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_cdf.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::double_exponential_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 Calculates the double exponential cumulative density function. More...
 
+
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diff --git a/doc/api/html/double__exponential__cdf_8hpp_source.html b/doc/api/html/double__exponential__cdf_8hpp_source.html new file mode 100644 index 00000000000..fd8df488abc --- /dev/null +++ b/doc/api/html/double__exponential__cdf_8hpp_source.html @@ -0,0 +1,241 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_cdf.hpp Source File + + + + + + + + + + +
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double_exponential_cdf.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_CDF_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/uniform_01.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
38  template <typename T_y, typename T_loc, typename T_scale>
+
39  typename return_type<T_y, T_loc, T_scale>::type
+
40  double_exponential_cdf(const T_y& y,
+
41  const T_loc& mu, const T_scale& sigma) {
+
42  static const char* function("stan::math::double_exponential_cdf");
+ +
44  T_partials_return;
+
45 
+
46  // Size checks
+
47  if ( !( stan::length(y) && stan::length(mu)
+
48  && stan::length(sigma) ) )
+
49  return 1.0;
+
50 
+ + + + +
55  using boost::math::tools::promote_args;
+
56  using std::exp;
+
57 
+
58  T_partials_return cdf(1.0);
+
59 
+
60  check_not_nan(function, "Random variable", y);
+
61  check_finite(function, "Location parameter", mu);
+
62  check_positive_finite(function, "Scale parameter", sigma);
+
63 
+ +
65  operands_and_partials(y, mu, sigma);
+
66 
+
67  VectorView<const T_y> y_vec(y);
+
68  VectorView<const T_loc> mu_vec(mu);
+
69  VectorView<const T_scale> sigma_vec(sigma);
+
70  size_t N = max_size(y, mu, sigma);
+
71 
+
72  // cdf
+
73  for (size_t n = 0; n < N; n++) {
+
74  const T_partials_return y_dbl = value_of(y_vec[n]);
+
75  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
76  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
77  const T_partials_return scaled_diff = (y_dbl - mu_dbl) / (sigma_dbl);
+
78  const T_partials_return exp_scaled_diff = exp(scaled_diff);
+
79 
+
80  if (y_dbl < mu_dbl)
+
81  cdf *= exp_scaled_diff * 0.5;
+
82  else
+
83  cdf *= 1.0 - 0.5 / exp_scaled_diff;
+
84  }
+
85 
+
86  // gradients
+
87  for (size_t n = 0; n < N; n++) {
+
88  const T_partials_return y_dbl = value_of(y_vec[n]);
+
89  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
90  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
91  const T_partials_return scaled_diff = (y_dbl - mu_dbl) / sigma_dbl;
+
92  const T_partials_return exp_scaled_diff = exp(scaled_diff);
+
93  const T_partials_return inv_sigma = 1.0 / sigma_dbl;
+
94 
+
95  if (y_dbl < mu_dbl) {
+ +
97  operands_and_partials.d_x1[n] += inv_sigma * cdf;
+ +
99  operands_and_partials.d_x2[n] -= inv_sigma * cdf;
+ +
101  operands_and_partials.d_x3[n] -= scaled_diff * inv_sigma * cdf;
+
102  } else {
+
103  const T_partials_return rep_deriv = cdf * inv_sigma
+
104  / (2.0 * exp_scaled_diff - 1.0);
+ +
106  operands_and_partials.d_x1[n] += rep_deriv;
+ +
108  operands_and_partials.d_x2[n] -= rep_deriv;
+ +
110  operands_and_partials.d_x3[n] -= rep_deriv * scaled_diff;
+
111  }
+
112  }
+
113  return operands_and_partials.value(cdf);
+
114  }
+
115  }
+
116 }
+
117 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_y, T_loc, T_scale >::type double_exponential_cdf(const T_y &y, const T_loc &mu, const T_scale &sigma)
Calculates the double exponential cumulative density function.
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/double__exponential__cdf__log_8hpp.html b/doc/api/html/double__exponential__cdf__log_8hpp.html new file mode 100644 index 00000000000..45ac74df9c5 --- /dev/null +++ b/doc/api/html/double__exponential__cdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
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+
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+
+
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+
double_exponential_cdf_log.hpp File Reference
+
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::double_exponential_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/double__exponential__cdf__log_8hpp_source.html b/doc/api/html/double__exponential__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..e6e03f63c32 --- /dev/null +++ b/doc/api/html/double__exponential__cdf__log_8hpp_source.html @@ -0,0 +1,246 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
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+
double_exponential_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/uniform_01.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <typename T_y, typename T_loc, typename T_scale>
+
25  typename return_type<T_y, T_loc, T_scale>::type
+
26  double_exponential_cdf_log(const T_y& y, const T_loc& mu,
+
27  const T_scale& sigma) {
+
28  static const char* function("stan::math::double_exponential_cdf_log");
+ +
30  T_partials_return;
+
31 
+ + + + + +
37 
+
38  T_partials_return cdf_log(0.0);
+
39 
+
40  // check if any vectors are zero length
+
41  if (!(stan::length(y)
+
42  && stan::length(mu)
+
43  && stan::length(sigma)))
+
44  return cdf_log;
+
45 
+
46  check_not_nan(function, "Random variable", y);
+
47  check_finite(function, "Location parameter", mu);
+
48  check_positive_finite(function, "Scale parameter", sigma);
+
49  check_consistent_sizes(function,
+
50  "Random variable", y,
+
51  "Location parameter", mu,
+
52  "Scale Parameter", sigma);
+
53 
+
54  using std::log;
+
55  using std::exp;
+
56  using stan::math::log1m;
+
57  using std::exp;
+
58 
+ +
60  operands_and_partials(y, mu, sigma);
+
61 
+
62  VectorView<const T_y> y_vec(y);
+
63  VectorView<const T_loc> mu_vec(mu);
+
64  VectorView<const T_scale> sigma_vec(sigma);
+
65  const double log_half = std::log(0.5);
+
66  size_t N = max_size(y, mu, sigma);
+
67 
+
68  for (size_t n = 0; n < N; n++) {
+
69  const T_partials_return y_dbl = value_of(y_vec[n]);
+
70  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
71  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
72  const T_partials_return scaled_diff = (y_dbl - mu_dbl) / sigma_dbl;
+
73  const T_partials_return inv_sigma = 1.0 / sigma_dbl;
+
74  if (y_dbl < mu_dbl) {
+
75  // log cdf
+
76  cdf_log += log_half + scaled_diff;
+
77 
+
78  // gradients
+ +
80  operands_and_partials.d_x1[n] += inv_sigma;
+ +
82  operands_and_partials.d_x2[n] -= inv_sigma;
+ +
84  operands_and_partials.d_x3[n] -= scaled_diff * inv_sigma;
+
85  } else {
+
86  // log cdf
+
87  cdf_log += log1m(0.5 * exp(-scaled_diff));
+
88 
+
89  // gradients
+
90  const T_partials_return rep_deriv = 1.0
+
91  / (2.0 * exp(scaled_diff) - 1.0);
+ +
93  operands_and_partials.d_x1[n] += rep_deriv * inv_sigma;
+ +
95  operands_and_partials.d_x2[n] -= rep_deriv * inv_sigma;
+ +
97  operands_and_partials.d_x3[n] -= rep_deriv * scaled_diff
+
98  * inv_sigma;
+
99  }
+
100  }
+
101  return operands_and_partials.value(cdf_log);
+
102  }
+
103  }
+
104 }
+
105 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
return_type< T_y, T_loc, T_scale >::type double_exponential_cdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/double__exponential__log_8hpp.html b/doc/api/html/double__exponential__log_8hpp.html new file mode 100644 index 00000000000..1470ebf4f35 --- /dev/null +++ b/doc/api/html/double__exponential__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
double_exponential_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::double_exponential_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::double_exponential_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/double__exponential__log_8hpp_source.html b/doc/api/html/double__exponential__log_8hpp_source.html new file mode 100644 index 00000000000..c0f8ceb29a4 --- /dev/null +++ b/doc/api/html/double__exponential__log_8hpp_source.html @@ -0,0 +1,283 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
double_exponential_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/random/uniform_01.hpp>
+
19 #include <boost/random/variate_generator.hpp>
+
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  // DoubleExponential(y|mu, sigma) [sigma > 0]
+
27  // FIXME: add documentation
+
28  template <bool propto,
+
29  typename T_y, typename T_loc, typename T_scale>
+
30  typename return_type<T_y, T_loc, T_scale>::type
+
31  double_exponential_log(const T_y& y,
+
32  const T_loc& mu, const T_scale& sigma) {
+
33  static const char* function("stan::math::double_exponential_log");
+ +
35  T_partials_return;
+
36 
+ + + + + + +
43  using std::log;
+
44  using std::fabs;
+
45  using stan::math::sign;
+
46  using std::log;
+
47 
+
48  // check if any vectors are zero length
+
49  if (!(stan::length(y)
+
50  && stan::length(mu)
+
51  && stan::length(sigma)))
+
52  return 0.0;
+
53 
+
54  // set up return value accumulator
+
55  T_partials_return logp(0.0);
+
56  check_finite(function, "Random variable", y);
+
57  check_finite(function, "Location parameter", mu);
+
58  check_positive_finite(function, "Scale parameter", sigma);
+
59  check_consistent_sizes(function,
+
60  "Random variable", y,
+
61  "Location parameter", mu,
+
62  "Shape parameter", sigma);
+
63 
+
64  // check if no variables are involved and prop-to
+ +
66  return 0.0;
+
67 
+
68  // set up template expressions wrapping scalars into vector views
+
69  VectorView<const T_y> y_vec(y);
+
70  VectorView<const T_loc> mu_vec(mu);
+
71  VectorView<const T_scale> sigma_vec(sigma);
+
72  size_t N = max_size(y, mu, sigma);
+ +
74  operands_and_partials(y, mu, sigma);
+
75 
+ +
77  T_partials_return, T_scale> inv_sigma(length(sigma));
+ +
79  T_partials_return, T_scale>
+
80  inv_sigma_squared(length(sigma));
+ +
82  T_partials_return, T_scale> log_sigma(length(sigma));
+
83  for (size_t i = 0; i < length(sigma); i++) {
+
84  const T_partials_return sigma_dbl = value_of(sigma_vec[i]);
+ +
86  inv_sigma[i] = 1.0 / sigma_dbl;
+ +
88  log_sigma[i] = log(value_of(sigma_vec[i]));
+ +
90  inv_sigma_squared[i] = inv_sigma[i] * inv_sigma[i];
+
91  }
+
92 
+
93 
+
94  for (size_t n = 0; n < N; n++) {
+
95  const T_partials_return y_dbl = value_of(y_vec[n]);
+
96  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
97 
+
98  // reusable subexpressions values
+
99  const T_partials_return y_m_mu = y_dbl - mu_dbl;
+
100  const T_partials_return fabs_y_m_mu = fabs(y_m_mu);
+
101 
+
102  // log probability
+ +
104  logp += NEG_LOG_TWO;
+ +
106  logp -= log_sigma[n];
+ +
108  logp -= fabs_y_m_mu * inv_sigma[n];
+
109 
+
110  // gradients
+
111  T_partials_return sign_y_m_mu_times_inv_sigma(0);
+ +
113  sign_y_m_mu_times_inv_sigma = sign(y_m_mu) * inv_sigma[n];
+ +
115  operands_and_partials.d_x1[n] -= sign_y_m_mu_times_inv_sigma;
+
116  }
+ +
118  operands_and_partials.d_x2[n] += sign_y_m_mu_times_inv_sigma;
+
119  }
+ +
121  operands_and_partials.d_x3[n] += -inv_sigma[n] + fabs_y_m_mu
+
122  * inv_sigma_squared[n];
+
123  }
+
124  return operands_and_partials.value(logp);
+
125  }
+
126 
+
127 
+
128  template <typename T_y, typename T_loc, typename T_scale>
+ +
130  double_exponential_log(const T_y& y, const T_loc& mu,
+
131  const T_scale& sigma) {
+
132  return double_exponential_log<false>(y, mu, sigma);
+
133  }
+
134  }
+
135 }
+
136 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
int sign(const T &z)
Definition: sign.hpp:9
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
return_type< T_y, T_loc, T_scale >::type double_exponential_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
const double NEG_LOG_TWO
Definition: constants.hpp:181
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ + +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
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diff --git a/doc/api/html/double__exponential__rng_8hpp.html b/doc/api/html/double__exponential__rng_8hpp.html new file mode 100644 index 00000000000..cb4e71e5fc9 --- /dev/null +++ b/doc/api/html/double__exponential__rng_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::double_exponential_rng (const double mu, const double sigma, RNG &rng)
 
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diff --git a/doc/api/html/double__exponential__rng_8hpp_source.html b/doc/api/html/double__exponential__rng_8hpp_source.html new file mode 100644 index 00000000000..65d1d26f28a --- /dev/null +++ b/doc/api/html/double__exponential__rng_8hpp_source.html @@ -0,0 +1,176 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/double_exponential_rng.hpp Source File + + + + + + + + + + +
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double_exponential_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_DOUBLE_EXPONENTIAL_RNG_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + +
12 
+ + + +
16 
+
17 namespace stan {
+
18 
+
19  namespace math {
+
20 
+
21  template <class RNG>
+
22  inline double
+
23  double_exponential_rng(const double mu,
+
24  const double sigma,
+
25  RNG& rng) {
+
26  static const char* function("stan::math::double_exponential_rng");
+
27 
+
28  using boost::variate_generator;
+
29  using boost::random::uniform_01;
+
30  using std::log;
+
31  using std::abs;
+ + +
34  using stan::math::log1m;
+
35 
+
36  check_finite(function, "Location parameter", mu);
+
37  check_positive_finite(function, "Scale parameter", sigma);
+
38 
+
39  variate_generator<RNG&, uniform_01<> >
+
40  rng_unit_01(rng, uniform_01<>());
+
41  double a = 0;
+
42  double laplaceRN = rng_unit_01();
+
43  if (0.5 - laplaceRN > 0)
+
44  a = 1.0;
+
45  else if (0.5 - laplaceRN < 0)
+
46  a = -1.0;
+
47  return mu - sigma * a * log1m(2 * abs(0.5 - laplaceRN));
+
48  }
+
49  }
+
50 }
+
51 #endif
+ +
fvar< T > abs(const fvar< T > &x)
Definition: abs.hpp:15
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + +
double double_exponential_rng(const double mu, const double sigma, RNG &rng)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
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+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
dv_vari.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::op_dv_vari
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/dv__vari_8hpp_source.html b/doc/api/html/dv__vari_8hpp_source.html new file mode 100644 index 00000000000..0e048473e2d --- /dev/null +++ b/doc/api/html/dv__vari_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/core/dv_vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
dv_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_DV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_DV_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_dv_vari : public vari {
+
10  protected:
+
11  double ad_;
+ +
13  public:
+
14  op_dv_vari(double f, double a, vari* bvi) :
+
15  vari(f),
+
16  ad_(a),
+
17  bvi_(bvi) {
+
18  }
+
19  };
+
20 
+
21  }
+
22 }
+
23 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+ +
op_dv_vari(double f, double a, vari *bvi)
Definition: dv_vari.hpp:14
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/dvd__vari_8hpp.html b/doc/api/html/dvd__vari_8hpp.html new file mode 100644 index 00000000000..e0e68c1a495 --- /dev/null +++ b/doc/api/html/dvd__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/dvd_vari.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
dvd_vari.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::op_dvd_vari
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/dvd__vari_8hpp_source.html b/doc/api/html/dvd__vari_8hpp_source.html new file mode 100644 index 00000000000..fef707c2323 --- /dev/null +++ b/doc/api/html/dvd__vari_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/rev/core/dvd_vari.hpp Source File + + + + + + + + + + +
+
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1 #ifndef STAN_MATH_REV_CORE_DVD_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_DVD_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_dvd_vari : public vari {
+
10  protected:
+
11  double ad_;
+ +
13  double cd_;
+
14  public:
+
15  op_dvd_vari(double f, double a, vari* bvi, double c) :
+
16  vari(f),
+
17  ad_(a),
+
18  bvi_(bvi),
+
19  cd_(c) {
+
20  }
+
21  };
+
22 
+
23  }
+
24 }
+
25 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+
op_dvd_vari(double f, double a, vari *bvi, double c)
Definition: dvd_vari.hpp:15
+ + + +
+
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diff --git a/doc/api/html/dvv__vari_8hpp.html b/doc/api/html/dvv__vari_8hpp.html new file mode 100644 index 00000000000..aa0f6af2eaa --- /dev/null +++ b/doc/api/html/dvv__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/dvv_vari.hpp File Reference + + + + + + + + + + +
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class  stan::math::op_dvv_vari
 
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diff --git a/doc/api/html/dvv__vari_8hpp_source.html b/doc/api/html/dvv__vari_8hpp_source.html new file mode 100644 index 00000000000..bba7427cb0a --- /dev/null +++ b/doc/api/html/dvv__vari_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/rev/core/dvv_vari.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_DVV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_DVV_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_dvv_vari : public vari {
+
10  protected:
+
11  double ad_;
+ + +
14  public:
+
15  op_dvv_vari(double f, double a, vari* bvi, vari* cvi) :
+
16  vari(f),
+
17  ad_(a),
+
18  bvi_(bvi),
+
19  cvi_(cvi) {
+
20  }
+
21  };
+
22 
+
23  }
+
24 }
+
25 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+ + +
op_dvv_vari(double f, double a, vari *bvi, vari *cvi)
Definition: dvv_vari.hpp:15
+ +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::eigenvalues_sym (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Return the eigenvalues of the specified symmetric matrix in descending order of magnitude. More...
 
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diff --git a/doc/api/html/eigenvalues__sym_8hpp_source.html b/doc/api/html/eigenvalues__sym_8hpp_source.html new file mode 100644 index 00000000000..a02420cd755 --- /dev/null +++ b/doc/api/html/eigenvalues__sym_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/eigenvalues_sym.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_EIGENVALUES_SYM_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_EIGENVALUES_SYM_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
20  template <typename T>
+
21  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
22  eigenvalues_sym(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
23  stan::math::check_nonzero_size("eigenvalues_sym", "m", m);
+
24  stan::math::check_symmetric("eigenvalues_sym", "m", m);
+
25 
+
26  Eigen::SelfAdjointEigenSolver
+
27  <Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
+
28  solver(m, Eigen::EigenvaluesOnly);
+
29  return solver.eigenvalues();
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+ + +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+ +
Eigen::Matrix< T, Eigen::Dynamic, 1 > eigenvalues_sym(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Return the eigenvalues of the specified symmetric matrix in descending order of magnitude.
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+ +
+
+
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diff --git a/doc/api/html/eigenvectors__sym_8hpp.html b/doc/api/html/eigenvectors__sym_8hpp.html new file mode 100644 index 00000000000..e4cc2a22838 --- /dev/null +++ b/doc/api/html/eigenvectors__sym_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/eigenvectors_sym.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::eigenvectors_sym (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 
+
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diff --git a/doc/api/html/eigenvectors__sym_8hpp_source.html b/doc/api/html/eigenvectors__sym_8hpp_source.html new file mode 100644 index 00000000000..2573436e739 --- /dev/null +++ b/doc/api/html/eigenvectors__sym_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/eigenvectors_sym.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_EIGENVECTORS_SYM_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_EIGENVECTORS_SYM_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
13  eigenvectors_sym(const Eigen::Matrix
+
14  <T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
15  stan::math::check_nonzero_size("eigenvectors_sym", "m", m);
+
16  stan::math::check_symmetric("eigenvalues_sym", "m", m);
+
17 
+
18  Eigen::SelfAdjointEigenSolver
+
19  <Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
+
20  solver(m);
+
21  return solver.eigenvectors();
+
22  }
+
23 
+
24  }
+
25 }
+
26 #endif
+ + +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+ +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > eigenvectors_sym(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/elt__divide_8hpp.html b/doc/api/html/elt__divide_8hpp.html new file mode 100644 index 00000000000..3d0aed96f4f --- /dev/null +++ b/doc/api/html/elt__divide_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/elt_divide.hpp File Reference + + + + + + + + + + +
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+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/divide.hpp>
+#include <stan/math/prim/mat/err/check_matching_dims.hpp>
+
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template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::elt_divide (const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
 Return the elementwise division of the specified matrices. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::elt_divide (const Eigen::Matrix< T1, R, C > &m, T2 s)
 Return the elementwise division of the specified matrix by the specified scalar. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::elt_divide (T1 s, const Eigen::Matrix< T2, R, C > &m)
 Return the elementwise division of the specified scalar by the specified matrix. More...
 
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diff --git a/doc/api/html/elt__divide_8hpp_source.html b/doc/api/html/elt__divide_8hpp_source.html new file mode 100644 index 00000000000..9167ae4a191 --- /dev/null +++ b/doc/api/html/elt__divide_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/elt_divide.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_ELT_DIVIDE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ELT_DIVIDE_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
23  template <typename T1, typename T2, int R, int C>
+
24  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
25  elt_divide(const Eigen::Matrix<T1, R, C>& m1,
+
26  const Eigen::Matrix<T2, R, C>& m2) {
+ +
28  "m1", m1,
+
29  "m2", m2);
+
30  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
31  R, C> result(m1.rows(), m2.cols());
+
32  for (int i = 0; i < m1.size(); ++i)
+
33  result(i) = m1(i) / m2(i);
+
34  return result;
+
35  }
+
36 
+
49  template <typename T1, typename T2, int R, int C>
+
50  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
51  elt_divide(const Eigen::Matrix<T1, R, C>& m, T2 s) {
+
52  return divide(m, s); // TODO(carp): stan::math::divide(m, s);
+
53  }
+
54 
+
67  template <typename T1, typename T2, int R, int C>
+
68  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
69  elt_divide(T1 s,
+
70  const Eigen::Matrix<T2, R, C>& m) {
+
71  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
72  R, C> result(m.rows(), m.cols());
+
73  for (int i = 0; i < m.size(); ++i)
+
74  result(i) = s / m(i);
+
75  return result;
+
76  }
+
77 
+
78  }
+
79 }
+
80 #endif
+ + + +
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
+
Eigen::Matrix< fvar< T >, R, C > divide(const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
Definition: divide.hpp:16
+ +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > elt_divide(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the elementwise division of the specified matrices.
Definition: elt_divide.hpp:25
+
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diff --git a/doc/api/html/elt__multiply_8hpp.html b/doc/api/html/elt__multiply_8hpp.html new file mode 100644 index 00000000000..9ec82a7091f --- /dev/null +++ b/doc/api/html/elt__multiply_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/elt_multiply.hpp File Reference + + + + + + + + + + +
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#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/err/check_matching_dims.hpp>
+
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template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::elt_multiply (const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
 Return the elementwise multiplication of the specified matrices. More...
 
+
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diff --git a/doc/api/html/elt__multiply_8hpp_source.html b/doc/api/html/elt__multiply_8hpp_source.html new file mode 100644 index 00000000000..dc8e3aefa16 --- /dev/null +++ b/doc/api/html/elt__multiply_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/elt_multiply.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_ELT_MULTIPLY_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ELT_MULTIPLY_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
23  template <typename T1, typename T2, int R, int C>
+
24  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
25  elt_multiply(const Eigen::Matrix<T1, R, C>& m1,
+
26  const Eigen::Matrix<T2, R, C>& m2) {
+
27  stan::math::check_matching_dims("elt_multiply",
+
28  "m1", m1,
+
29  "m2", m2);
+
30  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
31  R, C> result(m1.rows(), m2.cols());
+
32  for (int i = 0; i < m1.size(); ++i)
+
33  result(i) = m1(i) * m2(i);
+
34  return result;
+
35  }
+
36 
+
37  }
+
38 }
+
39 #endif
+ + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > elt_multiply(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the elementwise multiplication of the specified matrices.
+
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
+ +
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diff --git a/doc/api/html/empty__nested_8hpp.html b/doc/api/html/empty__nested_8hpp.html new file mode 100644 index 00000000000..9bc9bb5febb --- /dev/null +++ b/doc/api/html/empty__nested_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/empty_nested.hpp File Reference + + + + + + + + + + +
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static bool stan::math::empty_nested ()
 Return true if there is no nested autodiff being executed. More...
 
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diff --git a/doc/api/html/empty__nested_8hpp_source.html b/doc/api/html/empty__nested_8hpp_source.html new file mode 100644 index 00000000000..e6f66811640 --- /dev/null +++ b/doc/api/html/empty__nested_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/empty_nested.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_EMPTY_NESTED_HPP
+
2 #define STAN_MATH_REV_CORE_EMPTY_NESTED_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
12  static inline bool empty_nested() {
+ +
14  }
+
15 
+
16 
+
17  }
+
18 }
+
19 #endif
+
static bool empty_nested()
Return true if there is no nested autodiff being executed.
+ +
static std::vector< size_t > nested_var_stack_sizes_
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/error__index_8hpp.html b/doc/api/html/error__index_8hpp.html new file mode 100644 index 00000000000..309dd98ffb0 --- /dev/null +++ b/doc/api/html/error__index_8hpp.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/error_index.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
error_index.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + +

+Classes

struct  stan::error_index
 
+ + + +

+Namespaces

 stan
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/error__index_8hpp_source.html b/doc/api/html/error__index_8hpp_source.html new file mode 100644 index 00000000000..eb44a7f62fd --- /dev/null +++ b/doc/api/html/error__index_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/error_index.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
error_index.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_ERROR_INDEX_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_ERROR_INDEX_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  struct error_index {
+
7  enum { value =
+
8 #ifdef ERROR_INDEX
+
9 ERROR_INDEX
+
10 #else
+
11 1
+
12 #endif
+
13  };
+
14  };
+
15 
+
16 }
+
17 #endif
+
18 
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exp__mod__normal__ccdf__log_8hpp.html b/doc/api/html/exp__mod__normal__ccdf__log_8hpp.html new file mode 100644 index 00000000000..a8811135d16 --- /dev/null +++ b/doc/api/html/exp__mod__normal__ccdf__log_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_ccdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
exp_mod_normal_ccdf_log.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <stan/math/prim/scal/meta/partials_return_type.hpp>
+#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/err/check_positive_finite.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/random/normal_distribution.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type stan::math::exp_mod_normal_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exp__mod__normal__ccdf__log_8hpp_source.html b/doc/api/html/exp__mod__normal__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..4d572e68049 --- /dev/null +++ b/doc/api/html/exp__mod__normal__ccdf__log_8hpp_source.html @@ -0,0 +1,285 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_ccdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
exp_mod_normal_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + +
14 #include <boost/random/normal_distribution.hpp>
+
15 #include <boost/math/special_functions/fpclassify.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_loc, typename T_scale,
+
24  typename T_inv_scale>
+
25  typename return_type<T_y, T_loc, T_scale, T_inv_scale>::type
+
26  exp_mod_normal_ccdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
27  const T_inv_scale& lambda) {
+
28  static const char* function("stan::math::exp_mod_normal_ccdf_log");
+
29  typedef typename stan::partials_return_type<T_y, T_loc, T_scale,
+
30  T_inv_scale>::type
+
31  T_partials_return;
+
32 
+ + + + + +
38 
+
39  T_partials_return ccdf_log(0.0);
+
40  // check if any vectors are zero length
+
41  if (!(stan::length(y)
+
42  && stan::length(mu)
+
43  && stan::length(sigma)
+
44  && stan::length(lambda)))
+
45  return ccdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_finite(function, "Location parameter", mu);
+
49  check_not_nan(function, "Scale parameter", sigma);
+
50  check_positive_finite(function, "Scale parameter", sigma);
+
51  check_positive_finite(function, "Inv_scale parameter", lambda);
+
52  check_not_nan(function, "Inv_scale parameter", lambda);
+
53  check_consistent_sizes(function,
+
54  "Random variable", y,
+
55  "Location parameter", mu,
+
56  "Scale parameter", sigma,
+
57  "Inv_scale paramter", lambda);
+
58 
+
59 
+ +
61  operands_and_partials(y, mu, sigma, lambda);
+
62 
+
63  using stan::math::SQRT_2;
+
64  using std::log;
+
65  using std::log;
+
66  using std::exp;
+
67 
+
68  VectorView<const T_y> y_vec(y);
+
69  VectorView<const T_loc> mu_vec(mu);
+
70  VectorView<const T_scale> sigma_vec(sigma);
+
71  VectorView<const T_inv_scale> lambda_vec(lambda);
+
72  size_t N = max_size(y, mu, sigma, lambda);
+
73  const double sqrt_pi = std::sqrt(stan::math::pi());
+
74  for (size_t n = 0; n < N; n++) {
+
75  if (boost::math::isinf(y_vec[n])) {
+
76  if (y_vec[n] > 0.0)
+
77  return operands_and_partials.value(stan::math::negative_infinity());
+
78  else
+
79  return operands_and_partials.value(0.0);
+
80  }
+
81 
+
82  const T_partials_return y_dbl = value_of(y_vec[n]);
+
83  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
84  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
85  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
+
86  const T_partials_return u = lambda_dbl * (y_dbl - mu_dbl);
+
87  const T_partials_return v = lambda_dbl * sigma_dbl;
+
88  const T_partials_return v_sq = v * v;
+
89  const T_partials_return scaled_diff = (y_dbl - mu_dbl)
+
90  / (SQRT_2 * sigma_dbl);
+
91  const T_partials_return scaled_diff_sq = scaled_diff * scaled_diff;
+
92  const T_partials_return erf_calc1 = 0.5 * (1 + erf(u / (v * SQRT_2)));
+
93  const T_partials_return erf_calc2 = 0.5 * (1 + erf(u / (v * SQRT_2)
+
94  - v / SQRT_2));
+
95 
+
96  const T_partials_return deriv_1 = lambda_dbl * exp(0.5 * v_sq - u)
+
97  * erf_calc2;
+
98  const T_partials_return deriv_2 = SQRT_2 / sqrt_pi * 0.5
+
99  * exp(0.5 * v_sq
+
100  - (-scaled_diff + (v / SQRT_2)) * (-scaled_diff
+
101  + (v / SQRT_2)) - u)
+
102  / sigma_dbl;
+
103  const T_partials_return deriv_3 = SQRT_2 / sqrt_pi * 0.5
+
104  * exp(-scaled_diff_sq) / sigma_dbl;
+
105 
+
106  const T_partials_return ccdf_ = 1.0 - erf_calc1 + exp(-u + v_sq * 0.5)
+
107  * (erf_calc2);
+
108 
+
109  ccdf_log += log(ccdf_);
+
110 
+ +
112  operands_and_partials.d_x1[n]
+
113  -= (deriv_1 - deriv_2 + deriv_3) / ccdf_;
+ +
115  operands_and_partials.d_x2[n]
+
116  -= (-deriv_1 + deriv_2 - deriv_3) / ccdf_;
+ +
118  operands_and_partials.d_x3[n]
+
119  -= (-deriv_1 * v - deriv_3 * scaled_diff * SQRT_2 - deriv_2
+
120  * sigma_dbl * SQRT_2
+
121  * (-SQRT_2 * 0.5 * (-lambda_dbl + scaled_diff * SQRT_2
+
122  / sigma_dbl)
+
123  - SQRT_2 * lambda_dbl))
+
124  / ccdf_;
+ +
126  operands_and_partials.d_x4[n] -= exp(0.5 * v_sq - u)
+
127  * (SQRT_2 / sqrt_pi * 0.5 * sigma_dbl
+
128  * exp(-(v / SQRT_2 - scaled_diff) * (v / SQRT_2 - scaled_diff))
+
129  - (v * sigma_dbl + mu_dbl - y_dbl) * erf_calc2)
+
130  / ccdf_;
+
131  }
+
132 
+
133  return operands_and_partials.value(ccdf_log);
+
134  }
+
135  }
+
136 }
+
137 #endif
+
138 
+
139 
+
140 
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exp__mod__normal__cdf_8hpp.html b/doc/api/html/exp__mod__normal__cdf_8hpp.html new file mode 100644 index 00000000000..a2351cf9734 --- /dev/null +++ b/doc/api/html/exp__mod__normal__cdf_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
exp_mod_normal_cdf.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <stan/math/prim/scal/meta/partials_return_type.hpp>
+#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/err/check_positive_finite.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/random/normal_distribution.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type stan::math::exp_mod_normal_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exp__mod__normal__cdf_8hpp_source.html b/doc/api/html/exp__mod__normal__cdf_8hpp_source.html new file mode 100644 index 00000000000..acd7c455518 --- /dev/null +++ b/doc/api/html/exp__mod__normal__cdf_8hpp_source.html @@ -0,0 +1,290 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
exp_mod_normal_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_CDF_HPP
+
3 
+ + + + + + + + + + +
14 #include <boost/random/normal_distribution.hpp>
+
15 #include <boost/math/special_functions/fpclassify.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_loc, typename T_scale,
+
24  typename T_inv_scale>
+
25  typename return_type<T_y, T_loc, T_scale, T_inv_scale>::type
+
26  exp_mod_normal_cdf(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
27  const T_inv_scale& lambda) {
+
28  static const char* function("stan::math::exp_mod_normal_cdf");
+
29  typedef typename stan::partials_return_type<T_y, T_loc, T_scale,
+
30  T_inv_scale>::type
+
31  T_partials_return;
+
32 
+ + + + + +
38 
+
39  T_partials_return cdf(1.0);
+
40  // check if any vectors are zero length
+
41  if (!(stan::length(y)
+
42  && stan::length(mu)
+
43  && stan::length(sigma)
+
44  && stan::length(lambda)))
+
45  return cdf;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_finite(function, "Location parameter", mu);
+
49  check_not_nan(function, "Scale parameter", sigma);
+
50  check_positive_finite(function, "Scale parameter", sigma);
+
51  check_positive_finite(function, "Inv_scale parameter", lambda);
+
52  check_not_nan(function, "Inv_scale parameter", lambda);
+
53  check_consistent_sizes(function,
+
54  "Random variable", y,
+
55  "Location parameter", mu,
+
56  "Scale parameter", sigma,
+
57  "Inv_scale paramter", lambda);
+
58 
+ +
60  operands_and_partials(y, mu, sigma, lambda);
+
61 
+
62  using stan::math::SQRT_2;
+
63  using std::exp;
+
64 
+
65  VectorView<const T_y> y_vec(y);
+
66  VectorView<const T_loc> mu_vec(mu);
+
67  VectorView<const T_scale> sigma_vec(sigma);
+
68  VectorView<const T_inv_scale> lambda_vec(lambda);
+
69  size_t N = max_size(y, mu, sigma, lambda);
+
70  const double sqrt_pi = std::sqrt(stan::math::pi());
+
71  for (size_t n = 0; n < N; n++) {
+
72  if (boost::math::isinf(y_vec[n])) {
+
73  if (y_vec[n] < 0.0)
+
74  return operands_and_partials.value(0.0);
+
75  }
+
76 
+
77  const T_partials_return y_dbl = value_of(y_vec[n]);
+
78  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
79  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
80  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
+
81  const T_partials_return u = lambda_dbl * (y_dbl - mu_dbl);
+
82  const T_partials_return v = lambda_dbl * sigma_dbl;
+
83  const T_partials_return v_sq = v * v;
+
84  const T_partials_return scaled_diff = (y_dbl - mu_dbl) / (SQRT_2
+
85  * sigma_dbl);
+
86  const T_partials_return scaled_diff_sq = scaled_diff * scaled_diff;
+
87  const T_partials_return erf_calc = 0.5 * (1 + erf(-v / SQRT_2
+
88  + scaled_diff));
+
89  const T_partials_return deriv_1 = lambda_dbl * exp(0.5 * v_sq - u)
+
90  * erf_calc;
+
91  const T_partials_return deriv_2 = SQRT_2 / sqrt_pi * 0.5
+
92  * exp(0.5 * v_sq - (scaled_diff - (v / SQRT_2))
+
93  * (scaled_diff - (v / SQRT_2)) - u) / sigma_dbl;
+
94  const T_partials_return deriv_3 = SQRT_2 / sqrt_pi * 0.5
+
95  * exp(-scaled_diff_sq) / sigma_dbl;
+
96 
+
97  const T_partials_return cdf_ = 0.5 * (1 + erf(u / (v * SQRT_2)))
+
98  - exp(-u + v_sq * 0.5) * (erf_calc);
+
99 
+
100  cdf *= cdf_;
+
101 
+ +
103  operands_and_partials.d_x1[n] += (deriv_1 - deriv_2 + deriv_3)
+
104  / cdf_;
+ +
106  operands_and_partials.d_x2[n] += (-deriv_1 + deriv_2 - deriv_3)
+
107  / cdf_;
+ +
109  operands_and_partials.d_x3[n] += (-deriv_1 * v - deriv_3
+
110  * scaled_diff * SQRT_2 - deriv_2
+
111  * sigma_dbl * SQRT_2
+
112  * (-SQRT_2 * 0.5
+
113  * (-lambda_dbl + scaled_diff
+
114  * SQRT_2 / sigma_dbl) - SQRT_2
+
115  * lambda_dbl)) / cdf_;
+ +
117  operands_and_partials.d_x4[n] += exp(0.5 * v_sq - u)
+
118  * (SQRT_2 / sqrt_pi * 0.5 * sigma_dbl
+
119  * exp(-(v / SQRT_2 - scaled_diff) * (v / SQRT_2 - scaled_diff))
+
120  - (v * sigma_dbl + mu_dbl - y_dbl) * erf_calc) / cdf_;
+
121  }
+
122 
+ +
124  for (size_t n = 0; n < stan::length(y); ++n)
+
125  operands_and_partials.d_x1[n] *= cdf;
+
126  }
+ +
128  for (size_t n = 0; n < stan::length(mu); ++n)
+
129  operands_and_partials.d_x2[n] *= cdf;
+
130  }
+ +
132  for (size_t n = 0; n < stan::length(sigma); ++n)
+
133  operands_and_partials.d_x3[n] *= cdf;
+
134  }
+ +
136  for (size_t n = 0; n < stan::length(lambda); ++n)
+
137  operands_and_partials.d_x4[n] *= cdf;
+
138  }
+
139 
+
140  return operands_and_partials.value(cdf);
+
141  }
+
142  }
+
143 }
+
144 #endif
+
145 
+
146 
+
147 
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_cdf(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exp__mod__normal__cdf__log_8hpp.html b/doc/api/html/exp__mod__normal__cdf__log_8hpp.html new file mode 100644 index 00000000000..1fcfb12fe4e --- /dev/null +++ b/doc/api/html/exp__mod__normal__cdf__log_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
exp_mod_normal_cdf_log.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <stan/math/prim/scal/meta/partials_return_type.hpp>
+#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/err/check_positive_finite.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/random/normal_distribution.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type stan::math::exp_mod_normal_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exp__mod__normal__cdf__log_8hpp_source.html b/doc/api/html/exp__mod__normal__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..f01a59d14e1 --- /dev/null +++ b/doc/api/html/exp__mod__normal__cdf__log_8hpp_source.html @@ -0,0 +1,285 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
exp_mod_normal_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + +
14 #include <boost/random/normal_distribution.hpp>
+
15 #include <boost/math/special_functions/fpclassify.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_loc, typename T_scale,
+
24  typename T_inv_scale>
+
25  typename return_type<T_y, T_loc, T_scale, T_inv_scale>::type
+
26  exp_mod_normal_cdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
27  const T_inv_scale& lambda) {
+
28  static const char* function("stan::math::exp_mod_normal_cdf_log");
+
29  typedef typename stan::partials_return_type<T_y, T_loc, T_scale,
+
30  T_inv_scale>::type
+
31  T_partials_return;
+
32 
+ + + + + +
38 
+
39  T_partials_return cdf_log(0.0);
+
40  // check if any vectors are zero length
+
41  if (!(stan::length(y)
+
42  && stan::length(mu)
+
43  && stan::length(sigma)
+
44  && stan::length(lambda)))
+
45  return cdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_finite(function, "Location parameter", mu);
+
49  check_not_nan(function, "Scale parameter", sigma);
+
50  check_positive_finite(function, "Scale parameter", sigma);
+
51  check_positive_finite(function, "Inv_scale parameter", lambda);
+
52  check_not_nan(function, "Inv_scale parameter", lambda);
+
53  check_consistent_sizes(function,
+
54  "Random variable", y,
+
55  "Location parameter", mu,
+
56  "Scale parameter", sigma,
+
57  "Inv_scale paramter", lambda);
+
58 
+ +
60  operands_and_partials(y, mu, sigma, lambda);
+
61 
+
62  using stan::math::SQRT_2;
+
63  using std::log;
+
64  using std::log;
+
65  using std::exp;
+
66 
+
67  VectorView<const T_y> y_vec(y);
+
68  VectorView<const T_loc> mu_vec(mu);
+
69  VectorView<const T_scale> sigma_vec(sigma);
+
70  VectorView<const T_inv_scale> lambda_vec(lambda);
+
71  size_t N = max_size(y, mu, sigma, lambda);
+
72  const double sqrt_pi = std::sqrt(stan::math::pi());
+
73  for (size_t n = 0; n < N; n++) {
+
74  if (boost::math::isinf(y_vec[n])) {
+
75  if (y_vec[n] < 0.0)
+
76  return operands_and_partials.value(stan::math::negative_infinity());
+
77  else
+
78  return operands_and_partials.value(0.0);
+
79  }
+
80 
+
81  const T_partials_return y_dbl = value_of(y_vec[n]);
+
82  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
83  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
84  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
+
85  const T_partials_return u = lambda_dbl * (y_dbl - mu_dbl);
+
86  const T_partials_return v = lambda_dbl * sigma_dbl;
+
87  const T_partials_return v_sq = v * v;
+
88  const T_partials_return scaled_diff = (y_dbl - mu_dbl)
+
89  / (SQRT_2 * sigma_dbl);
+
90  const T_partials_return scaled_diff_sq = scaled_diff * scaled_diff;
+
91  const T_partials_return erf_calc1 = 0.5 * (1 + erf(u / (v * SQRT_2)));
+
92  const T_partials_return erf_calc2 = 0.5 * (1 + erf(u / (v * SQRT_2) - v
+
93  / SQRT_2));
+
94  const T_partials_return deriv_1 = lambda_dbl * exp(0.5 * v_sq - u)
+
95  * erf_calc2;
+
96  const T_partials_return deriv_2 = SQRT_2 / sqrt_pi * 0.5
+
97  * exp(0.5 * v_sq - (-scaled_diff + (v / SQRT_2))
+
98  * (-scaled_diff + (v / SQRT_2)) - u) / sigma_dbl;
+
99  const T_partials_return deriv_3 = SQRT_2 / sqrt_pi * 0.5
+
100  * exp(-scaled_diff_sq) / sigma_dbl;
+
101 
+
102  const T_partials_return denom = erf_calc1 - erf_calc2
+
103  * exp(0.5 * v_sq - u);
+
104  const T_partials_return cdf_ = erf_calc1 - exp(-u + v_sq * 0.5)
+
105  * (erf_calc2);
+
106 
+
107  cdf_log += log(cdf_);
+
108 
+ +
110  operands_and_partials.d_x1[n] += (deriv_1 - deriv_2 + deriv_3)
+
111  / denom;
+ +
113  operands_and_partials.d_x2[n] += (-deriv_1 + deriv_2 - deriv_3)
+
114  / denom;
+ +
116  operands_and_partials.d_x3[n]
+
117  += (-deriv_1 * v - deriv_3 * scaled_diff
+
118  * SQRT_2 - deriv_2 * sigma_dbl * SQRT_2
+
119  * (-SQRT_2 * 0.5 * (-lambda_dbl + scaled_diff * SQRT_2
+
120  / sigma_dbl)
+
121  - SQRT_2 * lambda_dbl))
+
122  / denom;
+ +
124  operands_and_partials.d_x4[n]
+
125  += exp(0.5 * v_sq - u)
+
126  * (SQRT_2 / sqrt_pi * 0.5 * sigma_dbl
+
127  * exp(-(v / SQRT_2 - scaled_diff)
+
128  * (v / SQRT_2 - scaled_diff))
+
129  - (v * sigma_dbl + mu_dbl - y_dbl) * erf_calc2)
+
130  / denom;
+
131  }
+
132 
+
133  return operands_and_partials.value(cdf_log);
+
134  }
+
135  }
+
136 }
+
137 #endif
+
138 
+
139 
+
140 
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_cdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exp__mod__normal__log_8hpp.html b/doc/api/html/exp__mod__normal__log_8hpp.html new file mode 100644 index 00000000000..a20a4195e80 --- /dev/null +++ b/doc/api/html/exp__mod__normal__log_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
exp_mod_normal_log.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <stan/math/prim/scal/meta/partials_return_type.hpp>
+#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/err/check_positive_finite.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/random/normal_distribution.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type stan::math::exp_mod_normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type stan::math::exp_mod_normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exp__mod__normal__log_8hpp_source.html b/doc/api/html/exp__mod__normal__log_8hpp_source.html new file mode 100644 index 00000000000..70cd0f913aa --- /dev/null +++ b/doc/api/html/exp__mod__normal__log_8hpp_source.html @@ -0,0 +1,293 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
exp_mod_normal_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_LOG_HPP
+
3 
+ + + + + + + + + + +
14 #include <boost/random/normal_distribution.hpp>
+
15 #include <boost/math/special_functions/fpclassify.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  template <bool propto,
+
24  typename T_y, typename T_loc, typename T_scale,
+
25  typename T_inv_scale>
+
26  typename return_type<T_y, T_loc, T_scale, T_inv_scale>::type
+
27  exp_mod_normal_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
28  const T_inv_scale& lambda) {
+
29  static const char* function("stan::math::exp_mod_normal_log");
+
30  typedef typename stan::partials_return_type<T_y, T_loc, T_scale,
+
31  T_inv_scale>::type
+
32  T_partials_return;
+
33 
+ + + + + + + +
41  using std::log;
+
42 
+
43  // check if any vectors are zero length
+
44  if (!(stan::length(y)
+
45  && stan::length(mu)
+
46  && stan::length(sigma)
+
47  && stan::length(lambda)))
+
48  return 0.0;
+
49 
+
50  // set up return value accumulator
+
51  T_partials_return logp(0.0);
+
52 
+
53  // validate args (here done over var, which should be OK)
+
54  check_not_nan(function, "Random variable", y);
+
55  check_finite(function, "Location parameter", mu);
+
56  check_positive_finite(function, "Inv_scale parameter", lambda);
+
57  check_positive_finite(function, "Scale parameter", sigma);
+
58  check_consistent_sizes(function,
+
59  "Random variable", y,
+
60  "Location parameter", mu,
+
61  "Scale parameter", sigma,
+
62  "Inv_scale paramter", lambda);
+
63 
+
64  // check if no variables are involved and prop-to
+ +
66  return 0.0;
+
67 
+
68  using boost::math::erfc;
+
69  using std::sqrt;
+
70  using std::log;
+
71  using std::exp;
+
72 
+
73  // set up template expressions wrapping scalars into vector views
+ +
75  operands_and_partials(y, mu, sigma, lambda);
+
76 
+
77  VectorView<const T_y> y_vec(y);
+
78  VectorView<const T_loc> mu_vec(mu);
+
79  VectorView<const T_scale> sigma_vec(sigma);
+
80  VectorView<const T_inv_scale> lambda_vec(lambda);
+
81  size_t N = max_size(y, mu, sigma, lambda);
+
82 
+
83  for (size_t n = 0; n < N; n++) {
+
84  // pull out values of arguments
+
85  const T_partials_return y_dbl = value_of(y_vec[n]);
+
86  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
87  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
88  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
+
89 
+
90  const T_partials_return pi_dbl = boost::math::constants::pi<double>();
+
91 
+
92  // log probability
+ +
94  logp -= log(2.0);
+ +
96  logp += log(lambda_dbl);
+ +
98  logp += lambda_dbl
+
99  * (mu_dbl + 0.5 * lambda_dbl * sigma_dbl * sigma_dbl - y_dbl)
+
100  + log(erfc((mu_dbl + lambda_dbl * sigma_dbl
+
101  * sigma_dbl - y_dbl)
+
102  / (sqrt(2.0) * sigma_dbl)));
+
103 
+
104  // gradients
+
105  const T_partials_return deriv_logerfc
+
106  = -2.0 / sqrt(pi_dbl)
+
107  * exp(-(mu_dbl + lambda_dbl * sigma_dbl * sigma_dbl - y_dbl)
+
108  / (std::sqrt(2.0) * sigma_dbl)
+
109  * (mu_dbl + lambda_dbl * sigma_dbl * sigma_dbl - y_dbl)
+
110  / (sigma_dbl * std::sqrt(2.0)))
+
111  / erfc((mu_dbl + lambda_dbl * sigma_dbl * sigma_dbl
+
112  - y_dbl) / (sigma_dbl * std::sqrt(2.0)));
+
113 
+ +
115  operands_and_partials.d_x1[n]
+
116  += -lambda_dbl
+
117  + deriv_logerfc * -1.0 / (sigma_dbl * std::sqrt(2.0));
+ +
119  operands_and_partials.d_x2[n]
+
120  += lambda_dbl
+
121  + deriv_logerfc / (sigma_dbl * std::sqrt(2.0));
+ +
123  operands_and_partials.d_x3[n]
+
124  += sigma_dbl * lambda_dbl * lambda_dbl
+
125  + deriv_logerfc
+
126  * (-mu_dbl / (sigma_dbl * sigma_dbl * std::sqrt(2.0))
+
127  + lambda_dbl / std::sqrt(2.0)
+
128  + y_dbl / (sigma_dbl * sigma_dbl * std::sqrt(2.0)));
+ +
130  operands_and_partials.d_x4[n]
+
131  += 1 / lambda_dbl + lambda_dbl * sigma_dbl * sigma_dbl
+
132  + mu_dbl - y_dbl + deriv_logerfc * sigma_dbl / std::sqrt(2.0);
+
133  }
+
134  return operands_and_partials.value(logp);
+
135  }
+
136 
+
137  template <typename T_y, typename T_loc, typename T_scale,
+
138  typename T_inv_scale>
+
139  inline
+ +
141  exp_mod_normal_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
142  const T_inv_scale& lambda) {
+
143  return exp_mod_normal_log<false>(y, mu, sigma, lambda);
+
144  }
+
145  }
+
146 }
+
147 #endif
+
148 
+
149 
+
150 
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_log(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
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diff --git a/doc/api/html/exp__mod__normal__rng_8hpp.html b/doc/api/html/exp__mod__normal__rng_8hpp.html new file mode 100644 index 00000000000..31a15cf39db --- /dev/null +++ b/doc/api/html/exp__mod__normal__rng_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::exp_mod_normal_rng (const double mu, const double sigma, const double lambda, RNG &rng)
 
+
+
+
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diff --git a/doc/api/html/exp__mod__normal__rng_8hpp_source.html b/doc/api/html/exp__mod__normal__rng_8hpp_source.html new file mode 100644 index 00000000000..cf18ba473ac --- /dev/null +++ b/doc/api/html/exp__mod__normal__rng_8hpp_source.html @@ -0,0 +1,174 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exp_mod_normal_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXP_MOD_NORMAL_RNG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/normal_distribution.hpp>
+
17 #include <boost/math/special_functions/fpclassify.hpp>
+
18 #include <boost/random/variate_generator.hpp>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <class RNG>
+
25  inline double
+
26  exp_mod_normal_rng(const double mu,
+
27  const double sigma,
+
28  const double lambda,
+
29  RNG& rng) {
+
30  static const char* function("stan::math::exp_mod_normal_rng");
+
31 
+ + +
34 
+
35  check_finite(function, "Location parameter", mu);
+
36  check_positive_finite(function, "Inv_scale parameter", lambda);
+
37  check_positive_finite(function, "Scale parameter", sigma);
+
38 
+
39  return stan::math::normal_rng(mu, sigma, rng)
+
40  + stan::math::exponential_rng(lambda, rng);
+
41  }
+
42  }
+
43 }
+
44 #endif
+
45 
+
46 
+
47 
+ + + + + +
double exponential_rng(const double beta, RNG &rng)
+ +
double exp_mod_normal_rng(const double mu, const double sigma, const double lambda, RNG &rng)
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
double normal_rng(const double mu, const double sigma, RNG &rng)
Definition: normal_rng.hpp:19
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exponential__ccdf__log_8hpp.html b/doc/api/html/exponential__ccdf__log_8hpp.html new file mode 100644 index 00000000000..4d1825fc7c5 --- /dev/null +++ b/doc/api/html/exponential__ccdf__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type stan::math::exponential_ccdf_log (const T_y &y, const T_inv_scale &beta)
 
+
+
+
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diff --git a/doc/api/html/exponential__ccdf__log_8hpp_source.html b/doc/api/html/exponential__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..80b93928074 --- /dev/null +++ b/doc/api/html/exponential__ccdf__log_8hpp_source.html @@ -0,0 +1,210 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_ccdf_log.hpp Source File + + + + + + + + + + +
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exponential_ccdf_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_CCDF_LOG_HPP
+
3 
+
4 #include <boost/random/exponential_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <typename T_y, typename T_inv_scale>
+
26  typename return_type<T_y, T_inv_scale>::type
+
27  exponential_ccdf_log(const T_y& y, const T_inv_scale& beta) {
+ +
29  T_partials_return;
+
30 
+
31  static const char* function("stan::math::exponential_ccdf_log");
+
32 
+ + + +
36  using boost::math::tools::promote_args;
+ +
38 
+
39  T_partials_return ccdf_log(0.0);
+
40  // check if any vectors are zero length
+
41  if (!(stan::length(y)
+
42  && stan::length(beta)))
+
43  return ccdf_log;
+
44 
+
45  check_not_nan(function, "Random variable", y);
+
46  check_nonnegative(function, "Random variable", y);
+
47  check_positive_finite(function, "Inverse scale parameter", beta);
+
48 
+ +
50  operands_and_partials(y, beta);
+
51 
+
52  VectorView<const T_y> y_vec(y);
+
53  VectorView<const T_inv_scale> beta_vec(beta);
+
54  size_t N = max_size(y, beta);
+
55  for (size_t n = 0; n < N; n++) {
+
56  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
57  const T_partials_return y_dbl = value_of(y_vec[n]);
+
58  // log ccdf
+
59  ccdf_log += -beta_dbl * y_dbl;
+
60 
+
61  // gradients
+ +
63  operands_and_partials.d_x1[n] -= beta_dbl;
+ +
65  operands_and_partials.d_x2[n] -= y_dbl;
+
66  }
+
67  return operands_and_partials.value(ccdf_log);
+
68  }
+
69  }
+
70 }
+
71 
+
72 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
return_type< T_y, T_inv_scale >::type exponential_ccdf_log(const T_y &y, const T_inv_scale &beta)
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/exponential__cdf_8hpp.html b/doc/api/html/exponential__cdf_8hpp.html new file mode 100644 index 00000000000..b48cccf621c --- /dev/null +++ b/doc/api/html/exponential__cdf_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_cdf.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type stan::math::exponential_cdf (const T_y &y, const T_inv_scale &beta)
 Calculates the exponential cumulative distribution function for the given y and beta. More...
 
+
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diff --git a/doc/api/html/exponential__cdf_8hpp_source.html b/doc/api/html/exponential__cdf_8hpp_source.html new file mode 100644 index 00000000000..05d369287a7 --- /dev/null +++ b/doc/api/html/exponential__cdf_8hpp_source.html @@ -0,0 +1,223 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_cdf.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_CDF_HPP
+
3 
+
4 #include <boost/random/exponential_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
38  template <typename T_y, typename T_inv_scale>
+
39  typename return_type<T_y, T_inv_scale>::type
+
40  exponential_cdf(const T_y& y, const T_inv_scale& beta) {
+ +
42  T_partials_return;
+
43 
+
44  static const char* function("stan::math::exponential_cdf");
+
45 
+ + + +
49  using boost::math::tools::promote_args;
+ +
51  using std::exp;
+
52 
+
53  T_partials_return cdf(1.0);
+
54  // check if any vectors are zero length
+
55  if (!(stan::length(y)
+
56  && stan::length(beta)))
+
57  return cdf;
+
58 
+
59  check_not_nan(function, "Random variable", y);
+
60  check_nonnegative(function, "Random variable", y);
+
61  check_positive_finite(function, "Inverse scale parameter", beta);
+
62 
+ +
64  operands_and_partials(y, beta);
+
65 
+
66  VectorView<const T_y> y_vec(y);
+
67  VectorView<const T_inv_scale> beta_vec(beta);
+
68  size_t N = max_size(y, beta);
+
69  for (size_t n = 0; n < N; n++) {
+
70  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
71  const T_partials_return y_dbl = value_of(y_vec[n]);
+
72  const T_partials_return one_m_exp = 1.0 - exp(-beta_dbl * y_dbl);
+
73 
+
74  // cdf
+
75  cdf *= one_m_exp;
+
76  }
+
77 
+
78  for (size_t n = 0; n < N; n++) {
+
79  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
80  const T_partials_return y_dbl = value_of(y_vec[n]);
+
81  const T_partials_return one_m_exp = 1.0 - exp(-beta_dbl * y_dbl);
+
82 
+
83  // gradients
+
84  T_partials_return rep_deriv = exp(-beta_dbl * y_dbl) / one_m_exp;
+ +
86  operands_and_partials.d_x1[n] += rep_deriv * beta_dbl * cdf;
+ +
88  operands_and_partials.d_x2[n] += rep_deriv * y_dbl * cdf;
+
89  }
+
90 
+
91  return operands_and_partials.value(cdf);
+
92  }
+
93  }
+
94 }
+
95 
+
96 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_inv_scale >::type exponential_cdf(const T_y &y, const T_inv_scale &beta)
Calculates the exponential cumulative distribution function for the given y and beta.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/exponential__cdf__log_8hpp.html b/doc/api/html/exponential__cdf__log_8hpp.html new file mode 100644 index 00000000000..e10a4fa928c --- /dev/null +++ b/doc/api/html/exponential__cdf__log_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_cdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type stan::math::exponential_cdf_log (const T_y &y, const T_inv_scale &beta)
 
+
+
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diff --git a/doc/api/html/exponential__cdf__log_8hpp_source.html b/doc/api/html/exponential__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..c096641472c --- /dev/null +++ b/doc/api/html/exponential__cdf__log_8hpp_source.html @@ -0,0 +1,218 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_cdf_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_CDF_LOG_HPP
+
3 
+
4 #include <boost/random/exponential_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <typename T_y, typename T_inv_scale>
+
27  typename return_type<T_y, T_inv_scale>::type
+
28  exponential_cdf_log(const T_y& y, const T_inv_scale& beta) {
+
29  typedef
+ +
31  T_partials_return;
+
32 
+
33  static const char* function("stan::math::exponential_cdf_log");
+
34 
+ + + +
38  using boost::math::tools::promote_args;
+ +
40  using std::log;
+
41  using std::exp;
+
42 
+
43  T_partials_return cdf_log(0.0);
+
44  // check if any vectors are zero length
+
45  if (!(stan::length(y)
+
46  && stan::length(beta)))
+
47  return cdf_log;
+
48 
+
49  check_not_nan(function, "Random variable", y);
+
50  check_nonnegative(function, "Random variable", y);
+
51  check_positive_finite(function, "Inverse scale parameter", beta);
+
52 
+ +
54  operands_and_partials(y, beta);
+
55 
+
56  VectorView<const T_y> y_vec(y);
+
57  VectorView<const T_inv_scale> beta_vec(beta);
+
58  size_t N = max_size(y, beta);
+
59  for (size_t n = 0; n < N; n++) {
+
60  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
61  const T_partials_return y_dbl = value_of(y_vec[n]);
+
62  T_partials_return one_m_exp = 1.0 - exp(-beta_dbl * y_dbl);
+
63  // log cdf
+
64  cdf_log += log(one_m_exp);
+
65 
+
66  // gradients
+
67  T_partials_return rep_deriv = -exp(-beta_dbl * y_dbl) / one_m_exp;
+ +
69  operands_and_partials.d_x1[n] -= rep_deriv * beta_dbl;
+ +
71  operands_and_partials.d_x2[n] -= rep_deriv * y_dbl;
+
72  }
+
73  return operands_and_partials.value(cdf_log);
+
74  }
+
75  }
+
76 }
+
77 
+
78 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
return_type< T_y, T_inv_scale >::type exponential_cdf_log(const T_y &y, const T_inv_scale &beta)
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/exponential__log_8hpp.html b/doc/api/html/exponential__log_8hpp.html new file mode 100644 index 00000000000..9e1ee1ca61d --- /dev/null +++ b/doc/api/html/exponential__log_8hpp.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type stan::math::exponential_log (const T_y &y, const T_inv_scale &beta)
 The log of an exponential density for y with the specified inverse scale parameter. More...
 
template<typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type stan::math::exponential_log (const T_y &y, const T_inv_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exponential__log_8hpp_source.html b/doc/api/html/exponential__log_8hpp_source.html new file mode 100644 index 00000000000..4766cc4b5a6 --- /dev/null +++ b/doc/api/html/exponential__log_8hpp_source.html @@ -0,0 +1,234 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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+
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exponential_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/random/exponential_distribution.hpp>
+
19 #include <boost/random/variate_generator.hpp>
+
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
52  template <bool propto, typename T_y, typename T_inv_scale>
+
53  typename return_type<T_y, T_inv_scale>::type
+
54  exponential_log(const T_y& y, const T_inv_scale& beta) {
+
55  static const char* function("stan::math::exponential_log");
+ +
57  T_partials_return;
+
58 
+
59  // check if any vectors are zero length
+
60  if (!(stan::length(y)
+
61  && stan::length(beta)))
+
62  return 0.0;
+
63 
+ + + + +
68  using std::log;
+
69 
+
70  T_partials_return logp(0.0);
+
71  check_nonnegative(function, "Random variable", y);
+
72  check_positive_finite(function, "Inverse scale parameter", beta);
+
73  check_consistent_sizes(function,
+
74  "Random variable", y,
+
75  "Inverse scale parameter", beta);
+
76 
+
77 
+
78  // set up template expressions wrapping scalars into vector views
+
79  VectorView<const T_y> y_vec(y);
+
80  VectorView<const T_inv_scale> beta_vec(beta);
+
81  size_t N = max_size(y, beta);
+
82 
+ +
84  T_partials_return, T_inv_scale> log_beta(length(beta));
+
85  for (size_t i = 0; i < length(beta); i++)
+ +
87  log_beta[i] = log(value_of(beta_vec[i]));
+
88 
+ +
90  operands_and_partials(y, beta);
+
91 
+
92  for (size_t n = 0; n < N; n++) {
+
93  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
94  const T_partials_return y_dbl = value_of(y_vec[n]);
+ +
96  logp += log_beta[n];
+ +
98  logp -= beta_dbl * y_dbl;
+
99 
+ +
101  operands_and_partials.d_x1[n] -= beta_dbl;
+ +
103  operands_and_partials.d_x2[n] += 1 / beta_dbl - y_dbl;
+
104  }
+
105  return operands_and_partials.value(logp);
+
106  }
+
107 
+
108  template <typename T_y, typename T_inv_scale>
+
109  inline
+ +
111  exponential_log(const T_y& y, const T_inv_scale& beta) {
+
112  return exponential_log<false>(y, beta);
+
113  }
+
114  }
+
115 }
+
116 
+
117 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
return_type< T_y, T_inv_scale >::type exponential_log(const T_y &y, const T_inv_scale &beta)
The log of an exponential density for y with the specified inverse scale parameter.
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exponential__rng_8hpp.html b/doc/api/html/exponential__rng_8hpp.html new file mode 100644 index 00000000000..82da9c0d483 --- /dev/null +++ b/doc/api/html/exponential__rng_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_rng.hpp File Reference + + + + + + + + + + +
+
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+
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+
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+
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+
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<class RNG >
double stan::math::exponential_rng (const double beta, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/exponential__rng_8hpp_source.html b/doc/api/html/exponential__rng_8hpp_source.html new file mode 100644 index 00000000000..da616b383ce --- /dev/null +++ b/doc/api/html/exponential__rng_8hpp_source.html @@ -0,0 +1,165 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/exponential_rng.hpp Source File + + + + + + + + + + +
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exponential_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_EXPONENTIAL_RNG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/exponential_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  template <class RNG>
+
23  inline double
+
24  exponential_rng(const double beta,
+
25  RNG& rng) {
+
26  using boost::variate_generator;
+
27  using boost::exponential_distribution;
+
28 
+
29  static const char* function("stan::math::exponential_rng");
+
30 
+ +
32 
+
33  check_positive_finite(function, "Inverse scale parameter", beta);
+
34 
+
35  variate_generator<RNG&, exponential_distribution<> >
+
36  exp_rng(rng, exponential_distribution<>(beta));
+
37  return exp_rng();
+
38  }
+
39  }
+
40 }
+
41 
+
42 #endif
+ + + + +
double exponential_rng(const double beta, RNG &rng)
+ + + + + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/factor___u_8hpp.html b/doc/api/html/factor___u_8hpp.html new file mode 100644 index 00000000000..aa63f23f268 --- /dev/null +++ b/doc/api/html/factor___u_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/factor_U.hpp File Reference + + + + + + + + + + +
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+
factor_U.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <cmath>
+#include <cstddef>
+#include <iostream>
+#include <limits>
+#include <stdexcept>
+#include <sstream>
+#include <vector>
+
+

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+Functions

template<typename T >
void stan::math::factor_U (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &U, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs)
 This function is intended to make starting values, given a unit upper-triangular matrix U such that U'DU is a correlation matrix. More...
 
+
+
+
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diff --git a/doc/api/html/factor___u_8hpp_source.html b/doc/api/html/factor___u_8hpp_source.html new file mode 100644 index 00000000000..2879c00f8b1 --- /dev/null +++ b/doc/api/html/factor___u_8hpp_source.html @@ -0,0 +1,171 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/factor_U.hpp Source File + + + + + + + + + + +
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factor_U.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_FACTOR_U_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_FACTOR_U_HPP
+
3 
+ + +
6 
+
7 #include <cmath>
+
8 #include <cstddef>
+
9 #include <iostream>
+
10 #include <limits>
+
11 #include <stdexcept>
+
12 #include <sstream>
+
13 #include <vector>
+
14 
+
15 
+
16 namespace stan {
+
17 
+
18  namespace math {
+
19 
+
27  template<typename T>
+
28  void
+
29  factor_U(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& U,
+
30  Eigen::Array<T, Eigen::Dynamic, 1>& CPCs) {
+
31  size_t K = U.rows();
+
32  size_t position = 0;
+
33  size_t pull = K - 1;
+
34 
+
35  if (K == 2) {
+
36  CPCs(0) = atanh(U(0, 1));
+
37  return;
+
38  }
+
39 
+
40  Eigen::Array<T, 1, Eigen::Dynamic> temp = U.row(0).tail(pull);
+
41 
+
42  CPCs.head(pull) = temp;
+
43 
+
44  Eigen::Array<T, Eigen::Dynamic, 1> acc(K);
+
45  acc(0) = -0.0;
+
46  acc.tail(pull) = 1.0 - temp.square();
+
47  for (size_t i = 1; i < (K - 1); i++) {
+
48  position += pull;
+
49  pull--;
+
50  temp = U.row(i).tail(pull);
+
51  temp /= sqrt(acc.tail(pull) / acc(i));
+
52  CPCs.segment(position, pull) = temp;
+
53  acc.tail(pull) *= 1.0 - temp.square();
+
54  }
+
55  CPCs = 0.5 * ( (1.0 + CPCs) / (1.0 - CPCs) ).log(); // now unbounded
+
56  }
+
57 
+
58  }
+
59 
+
60 }
+
61 
+
62 #endif
+
fvar< T > atanh(const fvar< T > &x)
Definition: atanh.hpp:13
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
void factor_U(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &U, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs)
This function is intended to make starting values, given a unit upper-triangular matrix U such that U...
Definition: factor_U.hpp:29
+ + +
+
+
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diff --git a/doc/api/html/factor__cov__matrix_8hpp.html b/doc/api/html/factor__cov__matrix_8hpp.html new file mode 100644 index 00000000000..579b7f6cfbd --- /dev/null +++ b/doc/api/html/factor__cov__matrix_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/factor_cov_matrix.hpp File Reference + + + + + + + + + + +
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factor_cov_matrix.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/factor_U.hpp>
+#include <cstddef>
+
+

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template<typename T >
bool stan::math::factor_cov_matrix (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &Sigma, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, Eigen::Array< T, Eigen::Dynamic, 1 > &sds)
 This function is intended to make starting values, given a covariance matrix Sigma. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/factor__cov__matrix_8hpp_source.html b/doc/api/html/factor__cov__matrix_8hpp_source.html new file mode 100644 index 00000000000..fb16a00cad9 --- /dev/null +++ b/doc/api/html/factor__cov__matrix_8hpp_source.html @@ -0,0 +1,159 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/factor_cov_matrix.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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factor_cov_matrix.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_FACTOR_COV_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_FACTOR_COV_MATRIX_HPP
+
3 
+ + +
6 #include <cstddef>
+
7 
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
25  template<typename T>
+
26  bool
+
27  factor_cov_matrix(const Eigen::Matrix
+
28  <T, Eigen::Dynamic, Eigen::Dynamic>& Sigma,
+
29  Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
+
30  Eigen::Array<T, Eigen::Dynamic, 1>& sds) {
+
31  size_t K = sds.rows();
+
32 
+
33  sds = Sigma.diagonal().array();
+
34  if ( (sds <= 0.0).any() ) return false;
+
35  sds = sds.sqrt();
+
36 
+
37  Eigen::DiagonalMatrix<T, Eigen::Dynamic> D(K);
+
38  D.diagonal() = sds.inverse();
+
39  sds = sds.log(); // now unbounded
+
40 
+
41  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> R = D * Sigma * D;
+
42  // to hopefully prevent pivoting due to floating point error
+
43  R.diagonal().setOnes();
+
44  Eigen::LDLT<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> > ldlt;
+
45  ldlt = R.ldlt();
+
46  if (!ldlt.isPositive())
+
47  return false;
+
48  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> U = ldlt.matrixU();
+
49  factor_U(U, CPCs);
+
50  return true;
+
51  }
+
52 
+
53  }
+
54 
+
55 }
+
56 
+
57 #endif
+ + +
bool factor_cov_matrix(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &Sigma, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, Eigen::Array< T, Eigen::Dynamic, 1 > &sds)
This function is intended to make starting values, given a covariance matrix Sigma.
+
void factor_U(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &U, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs)
This function is intended to make starting values, given a unit upper-triangular matrix U such that U...
Definition: factor_U.hpp:29
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diff --git a/doc/api/html/finite__diff__grad__hessian_8hpp.html b/doc/api/html/finite__diff__grad__hessian_8hpp.html new file mode 100644 index 00000000000..89270142e7f --- /dev/null +++ b/doc/api/html/finite__diff__grad__hessian_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/finite_diff_grad_hessian.hpp File Reference + + + + + + + + + + +
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template<typename F >
void stan::math::finite_diff_grad_hessian (const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1,-1 > &hess, std::vector< Eigen::Matrix< double,-1,-1 > > &grad_hess_fx, const double epsilon=1e-04)
 Calculate the value and the gradient of the hessian of the specified function at the specified argument using second-order autodiff and first-order finite difference. More...
 
+
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diff --git a/doc/api/html/finite__diff__grad__hessian_8hpp_source.html b/doc/api/html/finite__diff__grad__hessian_8hpp_source.html new file mode 100644 index 00000000000..dc1b7c55c37 --- /dev/null +++ b/doc/api/html/finite__diff__grad__hessian_8hpp_source.html @@ -0,0 +1,179 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/finite_diff_grad_hessian.hpp Source File + + + + + + + + + + +
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finite_diff_grad_hessian.hpp
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1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_FINITE_DIFF_GRAD_HESSIAN_HPP
+
2 #define STAN_MATH_MIX_MAT_FUNCTOR_FINITE_DIFF_GRAD_HESSIAN_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+ +
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
41  template <typename F>
+
42  void
+ +
44  const Eigen::Matrix<double, -1, 1>& x,
+
45  double& fx,
+
46  Eigen::Matrix<double, -1, -1>& hess,
+
47  std::vector<Eigen::Matrix<double, -1, -1> >&
+
48  grad_hess_fx,
+
49  const double epsilon = 1e-04) {
+
50  using Eigen::Matrix;
+
51  using Eigen::Dynamic;
+
52 
+
53  int d = x.size();
+
54  double dummy_fx_eval;
+
55 
+
56  Matrix<double, Dynamic, 1> x_temp(x);
+
57  Matrix<double, Dynamic, 1> grad_auto(d);
+
58  Matrix<double, Dynamic, Dynamic> hess_auto(d, d);
+
59  Matrix<double, Dynamic, Dynamic> hess_diff(d, d);
+
60 
+
61  hessian(f, x, fx, grad_auto, hess);
+
62  for (int i = 0; i < d; ++i) {
+
63  hess_diff.setZero();
+
64 
+
65  x_temp(i) = x(i) + 2.0 * epsilon;
+
66  hessian(f, x_temp, dummy_fx_eval, grad_auto, hess_auto);
+
67  hess_diff = -hess_auto;
+
68 
+
69  x_temp(i) = x(i) + -2.0 * epsilon;
+
70  hessian(f, x_temp, dummy_fx_eval, grad_auto, hess_auto);
+
71  hess_diff += hess_auto;
+
72 
+
73  x_temp(i) = x(i) + epsilon;
+
74  hessian(f, x_temp, dummy_fx_eval, grad_auto, hess_auto);
+
75  hess_diff += 8.0 * hess_auto;
+
76 
+
77  x_temp(i) = x(i) + -epsilon;
+
78  hessian(f, x_temp, dummy_fx_eval, grad_auto, hess_auto);
+
79  hess_diff -= 8.0 * hess_auto;
+
80 
+
81  x_temp(i) = x(i);
+
82  hess_diff /= 12.0 * epsilon;
+
83 
+
84  grad_hess_fx.push_back(hess_diff);
+
85  }
+
86  fx = f(x);
+
87  }
+
88 
+
89  }
+
90 }
+
91 #endif
+
void hessian(const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &H)
Calculate the value, the gradient, and the Hessian, of the specified function at the specified argume...
Definition: hessian.hpp:45
+ + +
void finite_diff_grad_hessian(const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1,-1 > &hess, std::vector< Eigen::Matrix< double,-1,-1 > > &grad_hess_fx, const double epsilon=1e-04)
Calculate the value and the gradient of the hessian of the specified function at the specified argume...
+ + +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
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diff --git a/doc/api/html/finite__diff__gradient_8hpp.html b/doc/api/html/finite__diff__gradient_8hpp.html new file mode 100644 index 00000000000..62ef31ea1c6 --- /dev/null +++ b/doc/api/html/finite__diff__gradient_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/functor/finite_diff_gradient.hpp File Reference + + + + + + + + + + +
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template<typename F >
void stan::math::finite_diff_gradient (const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1, 1 > &grad_fx, const double epsilon=1e-03)
 Calculate the value and the gradient of the specified function at the specified argument using finite difference. More...
 
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diff --git a/doc/api/html/finite__diff__gradient_8hpp_source.html b/doc/api/html/finite__diff__gradient_8hpp_source.html new file mode 100644 index 00000000000..28afdd5cfac --- /dev/null +++ b/doc/api/html/finite__diff__gradient_8hpp_source.html @@ -0,0 +1,168 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/functor/finite_diff_gradient.hpp Source File + + + + + + + + + + +
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finite_diff_gradient.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUNCTOR_FINITE_DIFF_GRADIENT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUNCTOR_FINITE_DIFF_GRADIENT_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
37  template <typename F>
+
38  void
+ +
40  const Eigen::Matrix<double, -1, 1>& x,
+
41  double& fx,
+
42  Eigen::Matrix<double, -1, 1>& grad_fx,
+
43  const double epsilon = 1e-03) {
+
44  using Eigen::Matrix;
+
45  using Eigen::Dynamic;
+
46  Matrix<double, Dynamic, 1> x_temp(x);
+
47 
+
48  int d = x.size();
+
49  grad_fx.resize(d);
+
50 
+
51  fx = f(x);
+
52 
+
53  for (int i = 0; i < d; ++i) {
+
54  double delta_f = 0.0;
+
55 
+
56  x_temp(i) = x(i) + 3.0 * epsilon;
+
57  delta_f = f(x_temp);
+
58 
+
59  x_temp(i) = x(i) + 2.0 * epsilon;
+
60  delta_f -= 9.0 * f(x_temp);
+
61 
+
62  x_temp(i) = x(i) + epsilon;
+
63  delta_f += 45.0 * f(x_temp);
+
64 
+
65  x_temp(i) = x(i) + -3.0 * epsilon;
+
66  delta_f -= f(x_temp);
+
67 
+
68  x_temp(i) = x(i) + -2.0 * epsilon;
+
69  delta_f += 9.0 * f(x_temp);
+
70 
+
71  x_temp(i) = x(i) + -epsilon;
+
72  delta_f -= 45.0 * f(x_temp);
+
73 
+
74  delta_f /= 60 * epsilon;
+
75 
+
76  x_temp(i) = x(i);
+
77  grad_fx(i) = delta_f;
+
78  }
+
79  }
+
80  }
+
81 }
+
82 #endif
+ + +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
void finite_diff_gradient(const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1, 1 > &grad_fx, const double epsilon=1e-03)
Calculate the value and the gradient of the specified function at the specified argument using finite...
+
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diff --git a/doc/api/html/finite__diff__hessian_8hpp.html b/doc/api/html/finite__diff__hessian_8hpp.html new file mode 100644 index 00000000000..f4f4a0ad8f5 --- /dev/null +++ b/doc/api/html/finite__diff__hessian_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/functor/finite_diff_hessian.hpp File Reference + + + + + + + + + + +
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template<typename F >
double stan::math::finite_diff_hess_helper (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const int lambda, const double epsilon=1e-03)
 
template<typename F >
void stan::math::finite_diff_hessian (const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1, 1 > &grad_fx, Eigen::Matrix< double,-1,-1 > &hess_fx, const double epsilon=1e-03)
 Calculate the value and the Hessian of the specified function at the specified argument using second-order finite difference. More...
 
+
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diff --git a/doc/api/html/finite__diff__hessian_8hpp_source.html b/doc/api/html/finite__diff__hessian_8hpp_source.html new file mode 100644 index 00000000000..59350904313 --- /dev/null +++ b/doc/api/html/finite__diff__hessian_8hpp_source.html @@ -0,0 +1,206 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/functor/finite_diff_hessian.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUNCTOR_FINITE_DIFF_HESSIAN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUNCTOR_FINITE_DIFF_HESSIAN_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename F>
+
12  double
+ +
14  const Eigen::Matrix<double, Eigen::Dynamic, 1>& x,
+
15  const int lambda,
+
16  const double epsilon = 1e-03) {
+
17  using Eigen::Matrix;
+
18  using Eigen::Dynamic;
+
19 
+
20  Matrix<double, Dynamic, 1> x_temp(x);
+
21 
+
22  double grad = 0.0;
+
23  x_temp(lambda) = x(lambda) + 2.0 * epsilon;
+
24  grad = -f(x_temp);
+
25 
+
26  x_temp(lambda) = x(lambda) + -2.0 * epsilon;
+
27  grad += f(x_temp);
+
28 
+
29  x_temp(lambda) = x(lambda) + epsilon;
+
30  grad += 8.0 * f(x_temp);
+
31 
+
32  x_temp(lambda) = x(lambda) + -epsilon;
+
33  grad -= 8.0 * f(x_temp);
+
34 
+
35  return grad;
+
36  }
+
37 
+
65  template <typename F>
+
66  void
+
67  finite_diff_hessian(const F& f,
+
68  const Eigen::Matrix<double, -1, 1>& x,
+
69  double& fx,
+
70  Eigen::Matrix<double, -1, 1>& grad_fx,
+
71  Eigen::Matrix<double, -1, -1>& hess_fx,
+
72  const double epsilon = 1e-03) {
+
73  using Eigen::Matrix;
+
74  using Eigen::Dynamic;
+
75 
+
76  int d = x.size();
+
77 
+
78  Matrix<double, Dynamic, 1> x_temp(x);
+
79  hess_fx.resize(d, d);
+
80 
+
81  finite_diff_gradient(f, x, fx, grad_fx);
+
82  double f_diff(0.0);
+
83  for (int i = 0; i < d; ++i) {
+
84  for (int j = i; j < d; ++j) {
+
85  x_temp(i) += 2.0 * epsilon;
+
86  if (i != j) {
+
87  f_diff = -finite_diff_hess_helper(f, x_temp, j);
+
88  x_temp(i) = x(i) + -2.0 * epsilon;
+
89  f_diff += finite_diff_hess_helper(f, x_temp, j);
+
90  x_temp(i) = x(i) + epsilon;
+
91  f_diff += 8.0 * finite_diff_hess_helper(f, x_temp, j);
+
92  x_temp(i) = x(i) + -epsilon;
+
93  f_diff -= 8.0 * finite_diff_hess_helper(f, x_temp, j);
+
94  f_diff /= 12.0 * epsilon * 12.0 * epsilon;
+
95  } else {
+
96  f_diff = -f(x_temp);
+
97  f_diff -= 30 * fx;
+
98  x_temp(i) = x(i) + -2.0 * epsilon;
+
99  f_diff -= f(x_temp);
+
100  x_temp(i) = x(i) + epsilon;
+
101  f_diff += 16.0 * f(x_temp);
+
102  x_temp(i) = x(i) - epsilon;
+
103  f_diff += 16.0 * f(x_temp);
+
104  f_diff /= 12 * epsilon * epsilon;
+
105  }
+
106 
+
107  x_temp(i) = x(i);
+
108 
+
109  hess_fx(j, i) = f_diff;
+
110  hess_fx(i, j) = hess_fx(j, i);
+
111  }
+
112  }
+
113  }
+
114  }
+
115 }
+
116 #endif
+ + +
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
void finite_diff_gradient(const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1, 1 > &grad_fx, const double epsilon=1e-03)
Calculate the value and the gradient of the specified function at the specified argument using finite...
+
void finite_diff_hessian(const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1, 1 > &grad_fx, Eigen::Matrix< double,-1,-1 > &hess_fx, const double epsilon=1e-03)
Calculate the value and the Hessian of the specified function at the specified argument using second-...
+
double finite_diff_hess_helper(const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const int lambda, const double epsilon=1e-03)
+
+
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zcmeAS@N?(olHy`uVBq!ia0vp@K+Mg-3?wJ#d=Cav1_3@Hu0Wb35M?jJ4b&h|666=m zpyv^r-_SpA&Ca8j?!Nr;e^vU1_dq!}PZ!6K3dXl{H}W<(@G$G2RNuj{>Hjtne*KIY z4^`&pyl42}J+< 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#31:\[ \frac{\partial\, \mbox{bessel\_second\_kind}(v, x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0 \\ \frac{\partial\, Y_v(x)}{\partial x} & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#32:\[ Y_v(x)=\frac{J_v(x)\cos(v\pi)-J_{-v}(x)}{\sin(v\pi)} \] +\form#33:\[ \frac{\partial \, Y_v(x)}{\partial x} = \frac{v}{x}Y_v(x)-Y_{v+1}(x) \] +\form#34:$\hat{y} \in [0, 1]$ +\form#35:$y \in \{ 0, 1 \}$ +\form#36:$\mbox{logloss}(1, \hat{y}) = -\log \hat{y} $ +\form#37:$\mbox{logloss}(0, \hat{y}) = -\log (1 - \hat{y}) $ +\form#38:${N \choose n}$ +\form#39:$0 \leq n \leq N$ +\form#40:${N \choose n} = \frac{N!}{n! (N-n)!}$ +\form#41:$ \log {N \choose n} = \log \ \Gamma(N+1) - \log \Gamma(n+1) - \log \Gamma(N-n+1)$ +\form#42:\[ \mbox{binomial\_coefficient\_log}(x, y) = \begin{cases} \textrm{error} & \mbox{if } y > x \textrm{ or } y < 0\\ \ln\Gamma(x+1) & \mbox{if } 0\leq y \leq x \\ \quad -\ln\Gamma(y+1)& \\ \quad -\ln\Gamma(x-y+1)& \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#43:\[ \frac{\partial\, \mbox{binomial\_coefficient\_log}(x, y)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } y > x \textrm{ or } y < 0\\ \Psi(x+1) & \mbox{if } 0\leq y \leq x \\ \quad -\Psi(x-y+1)& \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#44:\[ \frac{\partial\, \mbox{binomial\_coefficient\_log}(x, y)}{\partial y} = \begin{cases} \textrm{error} & \mbox{if } y > x \textrm{ or } y < 0\\ -\Psi(y+1) & \mbox{if } 0\leq y \leq x \\ \quad +\Psi(x-y+1)& \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#45:$ e $ +\form#46:$ \sqrt{2} $ +\form#47:$ 1 / \sqrt{2} $ +\form#48:$ \log 2 $ +\form#49:$ \log 10 $ +\form#50:$ \log \pi / 4 $ +\form#51:$f(x) = \tanh x = \frac{\exp(2x) - 1}{\exp(2x) + 1}$ +\form#52:$\log | \frac{d}{dx} \tanh x | = \log (1 - \tanh^2 x)$ +\form#53:$ f^{-1}(y) = \mbox{atanh}\, y = \frac{1}{2} \log \frac{y + 1}{y - 1}$ +\form#54:\[ \mbox{digamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#55:\[ \frac{\partial\, \mbox{digamma}(x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \frac{\partial\, \Psi(x)}{\partial x} & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#56:\[ \Psi(x)=\frac{\Gamma'(x)}{\Gamma(x)} \] +\form#57:\[ \frac{\partial \, \Psi(x)}{\partial x} = \frac{\Gamma''(x)\Gamma(x)-(\Gamma'(x))^2}{\Gamma^2(x)} \] +\form#58:\[ \mbox{falling\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ (x)_n & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#59:\[ \frac{\partial\, \mbox{falling\_factorial}(x, n)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \frac{\partial\, (x)_n}{\partial x} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#60:\[ \frac{\partial\, \mbox{falling\_factorial}(x, n)}{\partial n} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \frac{\partial\, (x)_n}{\partial n} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#61:\[ (x)_n=\frac{\Gamma(x+1)}{\Gamma(x-n+1)} \] +\form#62:\[ \frac{\partial \, (x)_n}{\partial x} = (x)_n\Psi(x+1) \] +\form#63:\[ \frac{\partial \, (x)_n}{\partial n} = -(x)_n\Psi(n+1) \] +\form#64:\[ \mbox{gamma\_p}(a, z) = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ P(a, z) & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +\form#65:\[ \frac{\partial\, \mbox{gamma\_p}(a, z)}{\partial a} = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ \frac{\partial\, P(a, z)}{\partial a} & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +\form#66:\[ \frac{\partial\, \mbox{gamma\_p}(a, z)}{\partial z} = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ \frac{\partial\, P(a, z)}{\partial z} & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +\form#67:\[ P(a, z)=\frac{1}{\Gamma(a)}\int_0^zt^{a-1}e^{-t}dt \] +\form#68:\[ \frac{\partial \, P(a, z)}{\partial a} = -\frac{\Psi(a)}{\Gamma^2(a)}\int_0^zt^{a-1}e^{-t}dt + \frac{1}{\Gamma(a)}\int_0^z (a-1)t^{a-2}e^{-t}dt \] +\form#69:\[ \frac{\partial \, P(a, z)}{\partial z} = \frac{z^{a-1}e^{-z}}{\Gamma(a)} \] +\form#70:\[ \mbox{gamma\_q}(a, z) = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ Q(a, z) & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +\form#71:\[ \frac{\partial\, \mbox{gamma\_q}(a, z)}{\partial a} = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ \frac{\partial\, Q(a, z)}{\partial a} & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +\form#72:\[ \frac{\partial\, \mbox{gamma\_q}(a, z)}{\partial z} = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ \frac{\partial\, Q(a, z)}{\partial z} & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +\form#73:\[ Q(a, z)=\frac{1}{\Gamma(a)}\int_z^\infty t^{a-1}e^{-t}dt \] +\form#74:\[ \frac{\partial \, Q(a, z)}{\partial a} = -\frac{\Psi(a)}{\Gamma^2(a)}\int_z^\infty t^{a-1}e^{-t}dt + \frac{1}{\Gamma(a)}\int_z^\infty (a-1)t^{a-2}e^{-t}dt \] +\form#75:\[ \frac{\partial \, Q(a, z)}{\partial z} = -\frac{z^{a-1}e^{-z}}{\Gamma(a)} \] +\form#76:\[ \mbox{int\_step}(x) = \begin{cases} 0 & \mbox{if } x \leq 0 \\ 1 & \mbox{if } x > 0 \\[6pt] 0 & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#77:\[ \mbox{inv\_cloglog}(y) = \begin{cases} \mbox{cloglog}^{-1}(y) & \mbox{if } -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \] +\form#78:\[ \frac{\partial\, \mbox{inv\_cloglog}(y)}{\partial y} = \begin{cases} \frac{\partial\, \mbox{cloglog}^{-1}(y)}{\partial y} & \mbox{if } -\infty\leq y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \] +\form#79:\[ \mbox{cloglog}^{-1}(y) = 1 - \exp \left( - \exp(y) \right) \] +\form#80:\[ \frac{\partial \, \mbox{cloglog}^{-1}(y)}{\partial y} = \exp(y-\exp(y)) \] +\form#81:$\mbox{logit}^{-1}(x) = \frac{1}{1 + \exp(-x)}$ +\form#82:\[ \mbox{inv\_logit}(y) = \begin{cases} \mbox{logit}^{-1}(y) & \mbox{if } -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \] +\form#83:\[ \frac{\partial\, \mbox{inv\_logit}(y)}{\partial y} = \begin{cases} \frac{\partial\, \mbox{logit}^{-1}(y)}{\partial y} & \mbox{if } -\infty\leq y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \] +\form#84:\[ \mbox{logit}^{-1}(y) = \frac{1}{1 + \exp(-y)} \] +\form#85:\[ \frac{\partial \, \mbox{logit}^{-1}(y)}{\partial y} = \frac{\exp(y)}{(\exp(y)+1)^2} \] +\form#86:$\Phi(x) = \int_{-\infty}^x \mbox{\sf Norm}(x|0, 1) \ dx = p$ +\form#87:$\mbox{inverse\_softmax}(x)[i] = \log x[i]$ +\form#88:$f(x) = \exp(x) + L$ +\form#89:$a > 0$ +\form#90:$b > 0$ +\form#91:$\mbox{B}(a, b) = \frac{\Gamma(a) \Gamma(b)}{\Gamma(a+b)}$ +\form#92:$\log \mbox{B}(a, b) = \log \Gamma(a) + \log \Gamma(b) - \log \Gamma(a+b)$ +\form#93:\[ \mbox{lbeta}(\alpha, \beta) = \begin{cases} \ln\int_0^1 u^{\alpha - 1} (1 - u)^{\beta - 1} \, du & \mbox{if } \alpha, \beta>0 \\[6pt] \textrm{NaN} & \mbox{if } \alpha = \textrm{NaN or } \beta = \textrm{NaN} \end{cases} \] +\form#94:\[ \frac{\partial\, \mbox{lbeta}(\alpha, \beta)}{\partial \alpha} = \begin{cases} \Psi(\alpha)-\Psi(\alpha+\beta) & \mbox{if } \alpha, \beta>0 \\[6pt] \textrm{NaN} & \mbox{if } \alpha = \textrm{NaN or } \beta = \textrm{NaN} \end{cases} \] +\form#95:\[ \frac{\partial\, \mbox{lbeta}(\alpha, \beta)}{\partial \beta} = \begin{cases} \Psi(\beta)-\Psi(\alpha+\beta) & \mbox{if } \alpha, \beta>0 \\[6pt] \textrm{NaN} & \mbox{if } \alpha = \textrm{NaN or } \beta = \textrm{NaN} \end{cases} \] +\form#96:\[ \mbox{lgamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \ln\Gamma(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#97:\[ \frac{\partial\, \mbox{lgamma}(x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#98:$\Gamma_k(x)$ +\form#99:$x$ +\form#100:$\Gamma_k(x) = \pi^{k(k-1)/4} \, \prod_{j=1}^k \Gamma(x + (1 - j)/2)$ +\form#101:$\Gamma()$ +\form#102:\[ \mbox{lmgamma}(n, x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \ln\Gamma_n(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#103:\[ \frac{\partial\, \mbox{lmgamma}(n, x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \frac{\partial\, \ln\Gamma_n(x)}{\partial x} & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#104:\[ \ln\Gamma_n(x) = \pi^{n(n-1)/4} \, \prod_{j=1}^n \Gamma(x + (1 - j)/2) \] +\form#105:\[ \frac{\partial \, \ln\Gamma_n(x)}{\partial x} = \sum_{j=1}^n \Psi(x + (1 - j) / 2) \] +\form#106:\[ \mbox{log1m}(x) = \begin{cases} \ln(1-x) & \mbox{if } x \leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#107:\[ \frac{\partial\, \mbox{log1m}(x)}{\partial x} = \begin{cases} -\frac{1}{1-x} & \mbox{if } x \leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#108:\[ \mbox{log1m\_exp}(x) = \begin{cases} \ln(1-\exp(x)) & \mbox{if } x < 0 \\ \textrm{NaN} & \mbox{if } x \geq 0\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#109:\[ \frac{\partial\, \mbox{asinh}(x)}{\partial x} = \begin{cases} -\frac{\exp(x)}{1-\exp(x)} & \mbox{if } x < 0 \\ \textrm{NaN} & \mbox{if } x \geq 0\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#110:\[ \mbox{log1m\_inv\_logit}(x) = \begin{cases} -\ln(\exp(x)+1) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#111:\[ \frac{\partial\, \mbox{log1m\_inv\_logit}(x)}{\partial x} = \begin{cases} -\frac{\exp(x)}{\exp(x)+1} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#112:\[ \mbox{log1p}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \ln(1+x)& \mbox{if } x\geq -1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#113:\[ \frac{\partial\, \mbox{log1p}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \frac{1}{1+x} & \mbox{if } x\geq -1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#114:\[ \mbox{log1p\_exp}(x) = \begin{cases} \ln(1+\exp(x)) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#115:\[ \frac{\partial\, \mbox{log1p\_exp}(x)}{\partial x} = \begin{cases} \frac{\exp(x)}{1+\exp(x)} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#116:\[ \mbox{log\_diff\_exp}(x, y) = \begin{cases} \textrm{NaN} & \mbox{if } x \leq y\\ \ln(\exp(x)-\exp(y)) & \mbox{if } x > y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#117:\[ \frac{\partial\, \mbox{log\_diff\_exp}(x, y)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x \leq y\\ \frac{\exp(x)}{\exp(x)-\exp(y)} & \mbox{if } x > y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#118:\[ \frac{\partial\, \mbox{log\_diff\_exp}(x, y)}{\partial y} = \begin{cases} \textrm{NaN} & \mbox{if } x \leq y\\ -\frac{\exp(y)}{\exp(x)-\exp(y)} & \mbox{if } x > y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#119:\[ \mbox{log\_falling\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \ln (x)_n & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#120:\[ \frac{\partial\, \mbox{log\_falling\_factorial}(x, n)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \Psi(x) & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#121:\[ \frac{\partial\, \mbox{log\_falling\_factorial}(x, n)}{\partial n} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ -\Psi(n) & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#122:\[ \mbox{log\_inv\_logit}(x) = \begin{cases} \ln\left(\frac{1}{1+\exp(-x)}\right)& \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#123:\[ \frac{\partial\, \mbox{log\_inv\_logit}(x)}{\partial x} = \begin{cases} \frac{1}{1+\exp(x)} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#124:\[ \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \log \left( \theta \lambda_1 + (1 - \theta) \lambda_2 \right). \] +\form#125:\[ \frac{\partial}{\partial \theta} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = FIXME \] +\form#126:\[ \frac{\partial}{\partial \lambda_1} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = FIXME \] +\form#127:\[ \frac{\partial}{\partial \lambda_2} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = FIXME \] +\form#128:\[ \mbox{log\_rising\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \ln x^{(n)} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#129:\[ \frac{\partial\, \mbox{log\_rising\_factorial}(x, n)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \Psi(x+n) - \Psi(x) & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#130:\[ \frac{\partial\, \mbox{log\_rising\_factorial}(x, n)}{\partial n} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \Psi(x+n) & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#131:$\log (\exp(a) + \exp(b)) = m + \log(\exp(a-m) + \exp(b-m))$ +\form#132:$m = max(a, b)$ +\form#133:\[ \mbox{log\_sum\_exp}(x, y) = \begin{cases} \ln(\exp(x)+\exp(y)) & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#134:\[ \frac{\partial\, \mbox{log\_sum\_exp}(x, y)}{\partial x} = \begin{cases} \frac{\exp(x)}{\exp(x)+\exp(y)} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#135:\[ \frac{\partial\, \mbox{log\_sum\_exp}(x, y)}{\partial y} = \begin{cases} \frac{\exp(y)}{\exp(x)+\exp(y)} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#136:\[ \mbox{operator\&\&}(x, y) = \begin{cases} 0 & \mbox{if } x = 0 \textrm{ or } y=0 \\ 1 & \mbox{if } x, y \neq 0 \\[6pt] 1 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#137:\[ \mbox{operator||}(x, y) = \begin{cases} 0 & \mbox{if } x, y=0 \\ 1 & \mbox{if } x \neq 0 \textrm{ or } y\neq0\\[6pt] 1 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#138:$x \in [0, 1]$ +\form#139:$\mbox{logit}(x) = \log \left( \frac{x}{1 - x} \right)$ +\form#140:\[ \mbox{logit}(x) = \begin{cases} \textrm{NaN}& \mbox{if } x < 0 \textrm{ or } x > 1\\ \ln\frac{x}{1-x} & \mbox{if } 0\leq x \leq 1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#141:\[ \frac{\partial\, \mbox{logit}(x)}{\partial x} = \begin{cases} \textrm{NaN}& \mbox{if } x < 0 \textrm{ or } x > 1\\ \frac{1}{x-x^2}& \mbox{if } 0\leq x\leq 1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#142:$f(x) = L + (U - L) \mbox{logit}^{-1}(x)$ +\form#143:$\log \left| \frac{d}{dx} \left( L + (U-L) \mbox{logit}^{-1}(x) \right) \right|$ +\form#144:$ {} = \log | (U-L) \, (\mbox{logit}^{-1}(x)) \, (1 - \mbox{logit}^{-1}(x)) |$ +\form#145:$ {} = \log (U - L) + \log (\mbox{logit}^{-1}(x)) + \log (1 - \mbox{logit}^{-1}(x))$ +\form#146:$f^{-1}(y) = \mbox{logit}(\frac{y - L}{U - L})$ +\form#147:$U$ +\form#148:\[ \mbox{modified\_bessel\_first\_kind}(v, z) = \begin{cases} I_v(z) & \mbox{if } -\infty\leq z \leq \infty \\[6pt] \textrm{error} & \mbox{if } z = \textrm{NaN} \end{cases} \] +\form#149:\[ \frac{\partial\, \mbox{modified\_bessel\_first\_kind}(v, z)}{\partial z} = \begin{cases} \frac{\partial\, I_v(z)}{\partial z} & \mbox{if } -\infty\leq z\leq \infty \\[6pt] \textrm{error} & \mbox{if } z = \textrm{NaN} \end{cases} \] +\form#150:\[ {I_v}(z) = \left(\frac{1}{2}z\right)^v\sum_{k=0}^\infty \frac{\left(\frac{1}{4}z^2\right)^k}{k!\Gamma(v+k+1)} \] +\form#151:\[ \frac{\partial \, I_v(z)}{\partial z} = I_{v-1}(z)-\frac{v}{z}I_v(z) \] +\form#152:\[ \mbox{modified\_bessel\_second\_kind}(v, z) = \begin{cases} \textrm{error} & \mbox{if } z \leq 0 \\ K_v(z) & \mbox{if } z > 0 \\[6pt] \textrm{NaN} & \mbox{if } z = \textrm{NaN} \end{cases} \] +\form#153:\[ \frac{\partial\, \mbox{modified\_bessel\_second\_kind}(v, z)}{\partial z} = \begin{cases} \textrm{error} & \mbox{if } z \leq 0 \\ \frac{\partial\, K_v(z)}{\partial z} & \mbox{if } z > 0 \\[6pt] \textrm{NaN} & \mbox{if } z = \textrm{NaN} \end{cases} \] +\form#154:\[ {K_v}(z) = \frac{\pi}{2}\cdot\frac{I_{-v}(z) - I_{v}(z)}{\sin(v\pi)} \] +\form#155:\[ \frac{\partial \, K_v(z)}{\partial z} = -\frac{v}{z}K_v(z)-K_{v-1}(z) \] +\form#156:$ a * \log b $ +\form#157:\[ \mbox{multiply\_log}(x, y) = \begin{cases} 0 & \mbox{if } x=y=0\\ x\ln y & \mbox{if } x, y\neq0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#158:\[ \frac{\partial\, \mbox{multiply\_log}(x, y)}{\partial x} = \begin{cases} \infty & \mbox{if } x=y=0\\ \ln y & \mbox{if } x, y\neq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#159:\[ \frac{\partial\, \mbox{multiply\_log}(x, y)}{\partial y} = \begin{cases} \infty & \mbox{if } x=y=0\\ \frac{x}{y} & \mbox{if } x, y\neq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#160:\[ \mbox{owens\_t}(h, a) = \begin{cases} \mbox{owens\_t}(h, a) & \mbox{if } -\infty\leq h, a \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } h = \textrm{NaN or } a = \textrm{NaN} \end{cases} \] +\form#161:\[ \frac{\partial\, \mbox{owens\_t}(h, a)}{\partial h} = \begin{cases} \frac{\partial\, \mbox{owens\_t}(h, a)}{\partial h} & \mbox{if } -\infty\leq h, a\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } h = \textrm{NaN or } a = \textrm{NaN} \end{cases} \] +\form#162:\[ \frac{\partial\, \mbox{owens\_t}(h, a)}{\partial a} = \begin{cases} \frac{\partial\, \mbox{owens\_t}(h, a)}{\partial a} & \mbox{if } -\infty\leq h, a\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } h = \textrm{NaN or } a = \textrm{NaN} \end{cases} \] +\form#163:\[ \mbox{owens\_t}(h, a) = \frac{1}{2\pi} \int_0^a \frac{\exp(-\frac{1}{2}h^2(1+x^2))}{1+x^2}dx \] +\form#164:\[ \frac{\partial \, \mbox{owens\_t}(h, a)}{\partial h} = -\frac{1}{2\sqrt{2\pi}} \operatorname{erf}\left(\frac{ha}{\sqrt{2}}\right) \exp\left(-\frac{h^2}{2}\right) \] +\form#165:\[ \frac{\partial \, \mbox{owens\_t}(h, a)}{\partial a} = \frac{\exp\left(-\frac{1}{2}h^2(1+a^2)\right)}{2\pi (1+a^2)} \] +\form#166:$\Phi(x) = \int_{-\infty}^x \mbox{\sf Norm}(x|0, 1) \ dx$ +\form#167:$f(x) = \exp(x)$ +\form#168:$\log | \frac{d}{dx} \mbox{exp}(x) | = \log | \mbox{exp}(x) | = x$ +\form#169:$f$ +\form#170:$f^{-1}(x) = \log(x)$ +\form#171:$f(x) = \mbox{logit}^{-1}(x) = \frac{1}{1 + \exp(x)}$ +\form#172:$\log | \frac{d}{dx} \mbox{logit}^{-1}(x) |$ +\form#173:$\log ((\mbox{logit}^{-1}(x)) (1 - \mbox{logit}^{-1}(x))$ +\form#174:$\log (\mbox{logit}^{-1}(x)) + \log (1 - \mbox{logit}^{-1}(x))$ +\form#175:$f^{-1}(y) = \mbox{logit}(y) = \frac{1 - y}{y}$ +\form#176:\[ \mbox{rising\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ x^{(n)} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#177:\[ \frac{\partial\, \mbox{rising\_factorial}(x, n)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \frac{\partial\, x^{(n)}}{\partial x} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#178:\[ \frac{\partial\, \mbox{rising\_factorial}(x, n)}{\partial n} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \frac{\partial\, x^{(n)}}{\partial n} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +\form#179:\[ x^{(n)}=\frac{\Gamma(x+n)}{\Gamma(x)} \] +\form#180:\[ \frac{\partial \, x^{(n)}}{\partial x} = x^{(n)}(\Psi(x+n)-\Psi(x)) \] +\form#181:\[ \frac{\partial \, x^{(n)}}{\partial n} = (x)_n\Psi(x+n) \] +\form#182:$\mbox{square}(x) = x^2$ +\form#183:\[ \mbox{step}(x) = \begin{cases} 0 & \mbox{if } x \leq 0 \\ 1 & \mbox{if } x > 0 \\[6pt] 0 & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#184:\[ \mbox{trigamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi_1(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#185:\[ \frac{\partial\, \mbox{trigamma}(x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \frac{\partial\, \Psi_1(x)}{\partial x} & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#186:\[ \Psi_1(x)=\sum_{n=0}^\infty \frac{1}{(x+n)^2} \] +\form#187:\[ \frac{\partial \, \Psi_1(x)}{\partial x} = -2\sum_{n=0}^\infty \frac{1}{(x+n)^3} \] +\form#188:$f(x) = U - \exp(x)$ +\form#189:$ \log | \frac{d}{dx} -\mbox{exp}(x) + U | = \log | -\mbox{exp}(x) + 0 | = x$ +\form#190:$f^{-1}(y) = \log -(y - U)$ +\form#191:$\frac{1}{\pi}\arctan\left(\frac{y-\mu}{\sigma}\right) + \frac{1}{2}$ +\form#192:\begin{eqnarray*} y &\sim& \chi^2_\nu \\ \log (p (y \, |\, \nu)) &=& \log \left( \frac{2^{-\nu / 2}}{\Gamma (\nu / 2)} y^{\nu / 2 - 1} \exp^{- y / 2} \right) \\ &=& - \frac{\nu}{2} \log(2) - \log (\Gamma (\nu / 2)) + (\frac{\nu}{2} - 1) \log(y) - \frac{y}{2} \\ & & \mathrm{ where } \; y \ge 0 \end{eqnarray*} +\form#193:$ f(y|\mu, \sigma) = \begin{cases} \ \frac{1}{2} \exp\left(\frac{y-\mu}{\sigma}\right), \mbox{if } y < \mu \\ 1 - \frac{1}{2} \exp\left(-\frac{y-\mu}{\sigma}\right), \mbox{if } y \ge \mu \ \end{cases}$ +\form#194:\begin{eqnarray*} y &\sim& \mbox{\sf{Expon}}(\beta) \\ \log (p (y \, |\, \beta) ) &=& \log \left( \beta \exp^{-\beta y} \right) \\ &=& \log (\beta) - \beta y \\ & & \mathrm{where} \; y > 0 \end{eqnarray*} +\form#195:\begin{eqnarray*} y &\sim& \mbox{\sf{Gamma}}(\alpha, \beta) \\ \log (p (y \, |\, \alpha, \beta) ) &=& \log \left( \frac{\beta^\alpha}{\Gamma(\alpha)} y^{\alpha - 1} \exp^{- \beta y} \right) \\ &=& \alpha \log(\beta) - \log(\Gamma(\alpha)) + (\alpha - 1) \log(y) - \beta y\\ & & \mathrm{where} \; y > 0 \end{eqnarray*} +\form#196:\begin{eqnarray*} y &\sim& \mbox{\sf{Inv-}}\chi^2_\nu \\ \log (p (y \, |\, \nu)) &=& \log \left( \frac{2^{-\nu / 2}}{\Gamma (\nu / 2)} y^{- (\nu / 2 + 1)} \exp^{-1 / (2y)} \right) \\ &=& - \frac{\nu}{2} \log(2) - \log (\Gamma (\nu / 2)) - (\frac{\nu}{2} + 1) \log(y) - \frac{1}{2y} \\ & & \mathrm{ where } \; y > 0 \end{eqnarray*} +\form#197:$\Phi(x) = \frac{1}{\sqrt{2 \pi}} \int_{-\inf}^x e^{-t^2/2} dt$ +\form#198:\begin{eqnarray*} y &\sim& \mbox{\sf{Inv-}}\chi^2(\nu, s^2) \\ \log (p (y \, |\, \nu, s)) &=& \log \left( \frac{(\nu / 2)^{\nu / 2}}{\Gamma (\nu / 2)} s^\nu y^{- (\nu / 2 + 1)} \exp^{-\nu s^2 / (2y)} \right) \\ &=& \frac{\nu}{2} \log(\frac{\nu}{2}) - \log (\Gamma (\nu / 2)) + \nu \log(s) - (\frac{\nu}{2} + 1) \log(y) - \frac{\nu s^2}{2y} \\ & & \mathrm{ where } \; y > 0 \end{eqnarray*} +\form#199:\begin{eqnarray*} y &\sim& t_{\nu} (\mu, \sigma^2) \\ \log (p (y \, |\, \nu, \mu, \sigma) ) &=& \log \left( \frac{\Gamma((\nu + 1) /2)} {\Gamma(\nu/2)\sqrt{\nu \pi} \sigma} \left( 1 + \frac{1}{\nu} (\frac{y - \mu}{\sigma})^2 \right)^{-(\nu + 1)/2} \right) \\ &=& \log( \Gamma( (\nu+1)/2 )) - \log (\Gamma (\nu/2) - \frac{1}{2} \log(\nu \pi) - \log(\sigma) -\frac{\nu + 1}{2} \log (1 + \frac{1}{\nu} (\frac{y - \mu}{\sigma})^2) \end{eqnarray*} +\form#200:\begin{eqnarray*} y &\sim& \mbox{\sf{U}}(\alpha, \beta) \\ \log (p (y \, |\, \alpha, \beta)) &=& \log \left( \frac{1}{\beta-\alpha} \right) \\ &=& \log (1) - \log (\beta - \alpha) \\ &=& -\log (\beta - \alpha) \\ & & \mathrm{ where } \; y \in [\alpha, \beta], \log(0) \; \mathrm{otherwise} \end{eqnarray*} +\form#201:$y$ +\form#202:$\alpha$ +\form#203:$\tau$ +\form#204:$\beta$ +\form#205:$\delta$ +\form#206:$ \frac{d x_n}{dt} $ +\form#207:\[ \frac{d x_{N+m}}{dt} = \frac{d}{dt} \frac{\partial x_1}{\partial \theta_m} \] +\form#208:\[ \frac{d x_{N+n}}{dt} = \frac{d}{dt} \frac{\partial x_1}{\partial y0_n} \] +\form#209:\[ \frac{d x_{N + n}}{dt} = \frac{d}{dt} \frac{\partial x_1}{\partial y0_n} \] +\form#210:\[ \frac{d x_{N+N+m}}{dt} = \frac{d}{dt} \frac{\partial x_1}{\partial \theta_m} \] +\form#211:$\frac{\partial}{\partial x} (x+y) = 1$ +\form#212:$\frac{\partial}{\partial y} (x+y) = 1$ +\form#213:\[ \mbox{operator+}(x, y) = \begin{cases} x+y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#214:\[ \frac{\partial\, \mbox{operator+}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#215:\[ \frac{\partial\, \mbox{operator+}(x, y)}{\partial y} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#216:$\frac{d}{dx} (x + c) = 1$ +\form#217:$\frac{d}{dy} (c + y) = 1$ +\form#218:$\frac{\partial}{\partial x} (x/y) = 1/y$ +\form#219:$\frac{\partial}{\partial y} (x/y) = -x / y^2$ +\form#220:\[ \mbox{operator/}(x, y) = \begin{cases} \frac{x}{y} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#221:\[ \frac{\partial\, \mbox{operator/}(x, y)}{\partial x} = \begin{cases} \frac{1}{y} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#222:\[ \frac{\partial\, \mbox{operator/}(x, y)}{\partial y} = \begin{cases} -\frac{x}{y^2} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#223:$\frac{\partial}{\partial x} (x/c) = 1/c$ +\form#224:$\frac{d}{d y} (c/y) = -c / y^2$ +\form#225:\[ \mbox{operator==}(x, y) = \begin{cases} 0 & \mbox{if } x \neq y\\ 1 & \mbox{if } x = y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#226:\[ \mbox{operator\textgreater}(x, y) = \begin{cases} 0 & \mbox{if } x \leq y\\ 1 & \mbox{if } x > y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#227:\[ \mbox{operator\textgreater=}(x, y) = \begin{cases} 0 & \mbox{if } x < y\\ 1 & \mbox{if } x \geq y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#228:\[ \mbox{operator\textless}(x, y) = \begin{cases} 0 & \mbox{if } x \geq y \\ 1 & \mbox{if } x < y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#229:\[ \mbox{operator\textless=}(x, y) = \begin{cases} 0 & \mbox{if } x > y\\ 1 & \mbox{if } x \leq y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#230:$\frac{\partial}{\partial x} (x * y) = y$ +\form#231:$\frac{\partial}{\partial y} (x * y) = x$ +\form#232:\[ \mbox{operator*}(x, y) = \begin{cases} xy & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#233:\[ \frac{\partial\, \mbox{operator*}(x, y)}{\partial x} = \begin{cases} y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#234:\[ \frac{\partial\, \mbox{operator*}(x, y)}{\partial y} = \begin{cases} x & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#235:$\frac{\partial}{\partial x} (x * c) = c$ +\form#236:$\frac{\partial}{\partial y} (c * y) = c$ +\form#237:\[ \mbox{operator!=}(x, y) = \begin{cases} 0 & \mbox{if } x = y\\ 1 & \mbox{if } x \neq y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#238:$\frac{\partial}{\partial x} (x-y) = 1$ +\form#239:$\frac{\partial}{\partial y} (x-y) = -1$ +\form#240:\[ \mbox{operator-}(x, y) = \begin{cases} x-y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#241:\[ \frac{\partial\, \mbox{operator-}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#242:\[ \frac{\partial\, \mbox{operator-}(x, y)}{\partial y} = \begin{cases} -1 & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#243:$\frac{\partial}{\partial x} (x-c) = 1$ +\form#244:$\frac{\partial}{\partial y} (c-y) = -1$ +\form#245:$\frac{d}{dx} -x = -1$ +\form#246:\[ \mbox{operator-}(x) = \begin{cases} -x & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#247:\[ \frac{\partial\, \mbox{operator-}(x)}{\partial x} = \begin{cases} -1 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#248:\[ \mbox{operator!}(x) = \begin{cases} 0 & \mbox{if } x \neq 0 \\ 1 & \mbox{if } x = 0 \\[6pt] 0 & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#249:$\frac{d}{dx} +x = \frac{d}{dx} x = 1$ +\form#250:\[ \mbox{operator+}(x) = \begin{cases} x & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#251:\[ \frac{\partial\, \mbox{operator+}(x)}{\partial x} = \begin{cases} 1 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#252:\[ \mbox{abs}(x) = \begin{cases} |x| & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#253:\[ \frac{\partial\, \mbox{abs}(x)}{\partial x} = \begin{cases} -1 & \mbox{if } x < 0 \\ 0 & \mbox{if } x = 0 \\ 1 & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#254:$\frac{d}{dx} \arccos x = \frac{-1}{\sqrt{1 - x^2}}$ +\form#255:\[ \mbox{acos}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \arccos(x) & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#256:\[ \frac{\partial\, \mbox{acos}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \frac{\partial\, \arccos(x)}{\partial x} & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x < -1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#257:\[ \frac{\partial \, \arccos(x)}{\partial x} = -\frac{1}{\sqrt{1-x^2}} \] +\form#258:$\frac{d}{dx} \mbox{acosh}(x) = \frac{x}{x^2 - 1}$ +\form#259:\[ \mbox{acosh}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < 1 \\ \cosh^{-1}(x) & \mbox{if } x \geq 1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#260:\[ \frac{\partial\, \mbox{acosh}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 1 \\ \frac{\partial\, \cosh^{-1}(x)}{\partial x} & \mbox{if } x \geq 1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#261:\[ \cosh^{-1}(x)=\ln\left(x+\sqrt{x^2-1}\right) \] +\form#262:\[ \frac{\partial \, \cosh^{-1}(x)}{\partial x} = \frac{1}{\sqrt{x^2-1}} \] +\form#263:$\frac{d}{dx} \arcsin x = \frac{1}{\sqrt{1 - x^2}}$ +\form#264:\[ \mbox{asin}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \arcsin(x) & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#265:\[ \frac{\partial\, \mbox{asin}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \frac{\partial\, \arcsin(x)}{\partial x} & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x < -1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#266:\[ \frac{\partial \, \arcsin(x)}{\partial x} = \frac{1}{\sqrt{1-x^2}} \] +\form#267:$\frac{d}{dx} \mbox{asinh}(x) = \frac{x}{x^2 + 1}$ +\form#268:\[ \mbox{asinh}(x) = \begin{cases} \sinh^{-1}(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#269:\[ \frac{\partial\, \mbox{asinh}(x)}{\partial x} = \begin{cases} \frac{\partial\, \sinh^{-1}(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#270:\[ \sinh^{-1}(x)=\ln\left(x+\sqrt{x^2+1}\right) \] +\form#271:\[ \frac{\partial \, \sinh^{-1}(x)}{\partial x} = \frac{1}{\sqrt{x^2+1}} \] +\form#272:$\frac{d}{dx} \arctan x = \frac{1}{1 + x^2}$ +\form#273:\[ \mbox{atan}(x) = \begin{cases} \arctan(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#274:\[ \frac{\partial\, \mbox{atan}(x)}{\partial x} = \begin{cases} \frac{\partial\, \arctan(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#275:\[ \frac{\partial \, \arctan(x)}{\partial x} = \frac{1}{x^2+1} \] +\form#276:$ \frac{\partial}{\partial x} \arctan \frac{x}{y} = \frac{y}{x^2 + y^2}$ +\form#277:$ \frac{\partial}{\partial y} \arctan \frac{x}{y} = \frac{-x}{x^2 + y^2}$ +\form#278:$ \frac{d}{d x} \arctan \frac{x}{c} = \frac{c}{x^2 + c^2}$ +\form#279:$ \frac{\partial}{\partial y} \arctan \frac{c}{y} = \frac{-c}{c^2 + y^2}$ +\form#280:\[ \mbox{atan2}(x, y) = \begin{cases} \arctan\left(\frac{x}{y}\right) & \mbox{if } -\infty\leq x \leq \infty, -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#281:\[ \frac{\partial\, \mbox{atan2}(x, y)}{\partial x} = \begin{cases} \frac{y}{x^2+y^2} & \mbox{if } -\infty\leq x\leq \infty, -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#282:\[ \frac{\partial\, \mbox{atan2}(x, y)}{\partial y} = \begin{cases} -\frac{x}{x^2+y^2} & \mbox{if } -\infty\leq x\leq \infty, -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#283:$\frac{d}{dx} \mbox{atanh}(x) = \frac{1}{1 - x^2}$ +\form#284:\[ \mbox{atanh}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \tanh^{-1}(x) & \mbox{if } -1\leq x \leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#285:\[ \frac{\partial\, \mbox{atanh}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \frac{\partial\, \tanh^{-1}(x)}{\partial x} & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#286:\[ \tanh^{-1}(x)=\frac{1}{2}\ln\left(\frac{1+x}{1-x}\right) \] +\form#287:\[ \frac{\partial \, \tanh^{-1}(x)}{\partial x} = \frac{1}{1-x^2} \] +\form#288:$\hat{y}$ +\form#289:$\frac{d}{d\hat{y}} \mbox{logloss}(1, \hat{y}) = - \frac{1}{\hat{y}}$ +\form#290:$\frac{d}{d\hat{y}} \mbox{logloss}(0, \hat{y}) = \frac{1}{1 - \hat{y}}$ +\form#291:\[ \mbox{binary\_log\_loss}(y, \hat{y}) = \begin{cases} y \log \hat{y} + (1 - y) \log (1 - \hat{y}) & \mbox{if } 0\leq \hat{y}\leq 1, y\in\{ 0, 1 \}\\[6pt] \textrm{NaN} & \mbox{if } \hat{y} = \textrm{NaN} \end{cases} \] +\form#292:\[ \frac{\partial\, \mbox{binary\_log\_loss}(y, \hat{y})}{\partial \hat{y}} = \begin{cases} \frac{y}{\hat{y}}-\frac{1-y}{1-\hat{y}} & \mbox{if } 0\leq \hat{y}\leq 1, y\in\{ 0, 1 \}\\[6pt] \textrm{NaN} & \mbox{if } \hat{y} = \textrm{NaN} \end{cases} \] +\form#293:$\frac{d}{dx} x^{1/3} = \frac{1}{3 x^{2/3}}$ +\form#294:\[ \mbox{cbrt}(x) = \begin{cases} \sqrt[3]{x} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#295:\[ \frac{\partial\, \mbox{cbrt}(x)}{\partial x} = \begin{cases} \frac{1}{3x^{2/3}} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#296:$\frac{d}{dx} {\lceil x \rceil} = 0$ +\form#297:\[ \mbox{ceil}(x) = \begin{cases} \lceil x\rceil & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#298:\[ \frac{\partial\, \mbox{ceil}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#299:$\frac{d}{dx} \cos x = - \sin x$ +\form#300:\[ \mbox{cos}(x) = \begin{cases} \cos(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#301:\[ \frac{\partial\, \mbox{cos}(x)}{\partial x} = \begin{cases} -\sin(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#302:$\frac{d}{dx} \cosh x = \sinh x$ +\form#303:\[ \mbox{cosh}(x) = \begin{cases} \cosh(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#304:\[ \frac{\partial\, \mbox{cosh}(x)}{\partial x} = \begin{cases} \sinh(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#305:$\frac{d}{dx} \mbox{erf}(x) = \frac{2}{\sqrt{\pi}} \exp(-x^2)$ +\form#306:\[ \mbox{erf}(x) = \begin{cases} \operatorname{erf}(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#307:\[ \frac{\partial\, \mbox{erf}(x)}{\partial x} = \begin{cases} \frac{\partial\, \operatorname{erf}(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#308:\[ \operatorname{erf}(x)=\frac{2}{\sqrt{\pi}}\int_0^x e^{-t^2}dt \] +\form#309:\[ \frac{\partial \, \operatorname{erf}(x)}{\partial x} = \frac{2}{\sqrt{\pi}} e^{-x^2} \] +\form#310:$\frac{d}{dx} \mbox{erfc}(x) = - \frac{2}{\sqrt{\pi}} \exp(-x^2)$ +\form#311:\[ \mbox{erfc}(x) = \begin{cases} \operatorname{erfc}(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#312:\[ \frac{\partial\, \mbox{erfc}(x)}{\partial x} = \begin{cases} \frac{\partial\, \operatorname{erfc}(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#313:\[ \operatorname{erfc}(x)=\frac{2}{\sqrt{\pi}}\int_x^\infty e^{-t^2}dt \] +\form#314:\[ \frac{\partial \, \operatorname{erfc}(x)}{\partial x} = -\frac{2}{\sqrt{\pi}} e^{-x^2} \] +\form#315:\[ \mbox{exp}(x) = \begin{cases} e^x & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#316:\[ \frac{\partial\, \mbox{exp}(x)}{\partial x} = \begin{cases} e^x & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#317:$\frac{d}{dx} 2^x = (\log 2) 2^x$ +\form#318:\[ \mbox{exp2}(x) = \begin{cases} 2^x & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#319:\[ \frac{\partial\, \mbox{exp2}(x)}{\partial x} = \begin{cases} 2^x\ln2 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#320:$\frac{d}{dx} \exp(a) - 1 = \exp(a)$ +\form#321:\[ \mbox{expm1}(x) = \begin{cases} e^x-1 & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#322:\[ \frac{\partial\, \mbox{expm1}(x)}{\partial x} = \begin{cases} e^x & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#323:$\frac{d}{dx}|x| = \mbox{sgn}(x)$ +\form#324:$\mbox{sgn}(x)$ +\form#325:$x < 0$ +\form#326:$x == 0$ +\form#327:$x == 1$ +\form#328:\[ \mbox{fabs}(x) = \begin{cases} |x| & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#329:\[ \frac{\partial\, \mbox{fabs}(x)}{\partial x} = \begin{cases} -1 & \mbox{if } x < 0 \\ 0 & \mbox{if } x = 0 \\ 1 & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#330:$\frac{\partial}{\partial x} \mbox{fdim}(x, y) = 0.0$ +\form#331:$x < y$ +\form#332:$\frac{\partial}{\partial x} \mbox{fdim}(x, y) = 1.0$ +\form#333:$x \geq y$ +\form#334:$\frac{\partial}{\partial y} \mbox{fdim}(x, y) = 0.0$ +\form#335:$\frac{\partial}{\partial y} \mbox{fdim}(x, y) = -\lfloor\frac{x}{y}\rfloor$ +\form#336:\[ \mbox{fdim}(x, y) = \begin{cases} 0 & \mbox{if } x < y\\ x-y & \mbox{if } x \geq y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#337:\[ \frac{\partial\, \mbox{fdim}(x, y)}{\partial x} = \begin{cases} 0 & \mbox{if } x < y \\ 1 & \mbox{if } x \geq y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#338:\[ \frac{\partial\, \mbox{fdim}(x, y)}{\partial y} = \begin{cases} 0 & \mbox{if } x < y \\ -\lfloor\frac{x}{y}\rfloor & \mbox{if } x \geq y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#339:$\frac{d}{d y} \mbox{fdim}(c, y) = 0.0$ +\form#340:$c < y$ +\form#341:$\frac{d}{d y} \mbox{fdim}(c, y) = -\lfloor\frac{c}{y}\rfloor$ +\form#342:$c \geq y$ +\form#343:$\frac{d}{d x} \mbox{fdim}(x, c) = 0.0$ +\form#344:$x < c$ +\form#345:$\frac{d}{d x} \mbox{fdim}(x, c) = 1.0$ +\form#346:$x \geq yc$ +\form#347:$\frac{d}{dx} {\lfloor x \rfloor} = 0$ +\form#348:\[ \mbox{floor}(x) = \begin{cases} \lfloor x \rfloor & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#349:\[ \frac{\partial\, \mbox{floor}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#350:$\frac{\partial}{\partial x} (x * y) + z = y$ +\form#351:$\frac{\partial}{\partial y} (x * y) + z = x$ +\form#352:$\frac{\partial}{\partial z} (x * y) + z = 1$ +\form#353:$\frac{\partial}{\partial x} (x * y) + c = y$ +\form#354:$\frac{\partial}{\partial y} (x * y) + c = x$ +\form#355:$\frac{\partial}{\partial x} (x * c) + z = c$ +\form#356:$\frac{\partial}{\partial z} (x * c) + z = 1$ +\form#357:$\frac{d}{d x} (x * c) + d = c$ +\form#358:$\frac{d}{d y} (c * y) + d = c$ +\form#359:$\frac{\partial}{\partial z} (c * d) + z = 1$ +\form#360:$\frac{\partial}{\partial y} (c * y) + z = c$ +\form#361:$\frac{\partial}{\partial z} (c * y) + z = 1$ +\form#362:\[ \mbox{fmax}(x, y) = \begin{cases} x & \mbox{if } x \geq y \\ y & \mbox{if } x < y \\[6pt] x & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ y & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +\form#363:\[ \frac{\partial\, \mbox{fmax}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } x \geq y \\ 0 & \mbox{if } x < y \\[6pt] 1 & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ 0 & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +\form#364:\[ \frac{\partial\, \mbox{fmax}(x, y)}{\partial y} = \begin{cases} 0 & \mbox{if } x \geq y \\ 1 & \mbox{if } x < y \\[6pt] 0 & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ 1 & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +\form#365:\[ \mbox{fmin}(x, y) = \begin{cases} x & \mbox{if } x \leq y \\ y & \mbox{if } x > y \\[6pt] x & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ y & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +\form#366:\[ \frac{\partial\, \mbox{fmin}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } x \leq y \\ 0 & \mbox{if } x > y \\[6pt] 1 & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ 0 & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +\form#367:\[ \frac{\partial\, \mbox{fmin}(x, y)}{\partial y} = \begin{cases} 0 & \mbox{if } x \leq y \\ 1 & \mbox{if } x > y \\[6pt] 0 & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ 1 & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +\form#368:$x = y$ +\form#369:$\frac{\partial}{\partial x} \mbox{fmod}(x, y) = 1$ +\form#370:$\frac{\partial}{\partial y} \mbox{fmod}(x, y) = -\lfloor \frac{x}{y} \rfloor$ +\form#371:\[ \mbox{fmod}(x, y) = \begin{cases} x - \lfloor \frac{x}{y}\rfloor y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#372:\[ \frac{\partial\, \mbox{fmod}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#373:\[ \frac{\partial\, \mbox{fmod}(x, y)}{\partial y} = \begin{cases} -\lfloor \frac{x}{y}\rfloor & \mbox{if } -\infty\leq x, y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#374:$\frac{d}{d x} \mbox{fmod}(x, c) = \frac{1}{c}$ +\form#375:$\frac{d}{d y} \mbox{fmod}(c, y) = -\lfloor \frac{c}{y} \rfloor$ +\form#376:$\frac{\partial}{\partial x} \sqrt{x^2 + y^2} = \frac{x}{\sqrt{x^2 + y^2}}$ +\form#377:$\frac{\partial}{\partial y} \sqrt{x^2 + y^2} = \frac{y}{\sqrt{x^2 + y^2}}$ +\form#378:$\frac{d}{d x} \sqrt{x^2 + c^2} = \frac{x}{\sqrt{x^2 + c^2}}$ +\form#379:$\frac{d}{d y} \sqrt{c^2 + y^2} = \frac{y}{\sqrt{c^2 + y^2}}$ +\form#380:\[ \mbox{hypot}(x, y) = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \text{ or } y < 0 \\ \sqrt{x^2+y^2} & \mbox{if } x, y\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#381:\[ \frac{\partial\, \mbox{hypot}(x, y)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \text{ or } y < 0 \\ \frac{x}{\sqrt{x^2+y^2}} & \mbox{if } x, y\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#382:\[ \frac{\partial\, \mbox{hypot}(x, y)}{\partial y} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \text{ or } y < 0 \\ \frac{y}{\sqrt{x^2+y^2}} & \mbox{if } x, y\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#383:\[ \mbox{inv}(x) = \begin{cases} \frac{1}{x} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#384:\[ \frac{\partial\, \mbox{inv}(x)}{\partial x} = \begin{cases} -\frac{1}{x^2} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#385:$\frac{d}{dx} \mbox{cloglog}^{-1}(x) = \exp (x - \exp (x))$ +\form#386:$\frac{d}{dx} \mbox{logit}^{-1}(x) = \mbox{logit}^{-1}(x) (1 - \mbox{logit}^{-1}(x))$ +\form#387:\[ \mbox{inv\_sqrt}(x) = \begin{cases} \frac{1}{\sqrt{x}} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#388:\[ \frac{\partial\, \mbox{inv\_sqrt}(x)}{\partial x} = \begin{cases} -\frac{1}{2\sqrt{x^3}} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#389:\[ \mbox{inv\_square}(x) = \begin{cases} \frac{1}{x^2} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#390:\[ \frac{\partial\, \mbox{inv\_square}(x)}{\partial x} = \begin{cases} -\frac{2}{x^3} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#391:$\frac{d}{dx} \Gamma(x) = \psi^{(0)}(x)$ +\form#392:$\frac{d}{dx} \log x = \frac{1}{x}$ +\form#393:\[ \mbox{log}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < 0\\ \ln(x) & \mbox{if } x \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#394:\[ \frac{\partial\, \mbox{log}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0\\ \frac{1}{x} & \mbox{if } x\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#395:$\frac{d}{dx} \log_{10} x = \frac{1}{x \log 10}$ +\form#396:\[ \mbox{log10}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < 0\\ \log_{10}(x) & \mbox{if } x \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#397:\[ \frac{\partial\, \mbox{log10}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0\\ \frac{1}{x \ln10} & \mbox{if } x\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#398:$\frac{d}{dx} \log (1 - x) = -\frac{1}{1 - x}$ +\form#399:$\frac{d}{dx} \log (1 + x) = \frac{1}{1 + x}$ +\form#400:$\frac{d}{dx} \log_2 x = \frac{1}{x \log 2}$ +\form#401:\[ \mbox{log2}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \\ \log_2(x) & \mbox{if } x\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#402:\[ \frac{\partial\, \mbox{log2}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \\ \frac{1}{x\ln2} & \mbox{if } x\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#403:$\frac{d}{dx} \Phi(x) = \mbox{\sf Norm}(x|0, 1) = \frac{1}{\sqrt{2\pi}} \exp(-\frac{1}{2} x^2)$ +\form#404:\[ \mbox{Phi}(x) = \begin{cases} 0 & \mbox{if } x < -37.5 \\ \Phi(x) & \mbox{if } -37.5 \leq x \leq 8.25 \\ 1 & \mbox{if } x > 8.25 \\[6pt] \textrm{error} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#405:\[ \frac{\partial\, \mbox{Phi}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } x < -27.5 \\ \frac{\partial\, \Phi(x)}{\partial x} & \mbox{if } -27.5 \leq x \leq 27.5 \\ 0 & \mbox{if } x > 27.5 \\[6pt] \textrm{error} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#406:\[ \Phi(x) = \frac{1}{\sqrt{2\pi}} \int_{0}^{x} e^{-t^2/2} dt \] +\form#407:\[ \frac{\partial \, \Phi(x)}{\partial x} = \frac{e^{-x^2/2}}{\sqrt{2\pi}} \] +\form#408:\[ \mbox{Phi\_approx}(x) = \begin{cases} \Phi_{\mbox{\footnotesize approx}}(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#409:\[ \frac{\partial\, \mbox{Phi\_approx}(x)}{\partial x} = \begin{cases} \frac{\partial\, \Phi_{\mbox{\footnotesize approx}}(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#410:\[ \Phi_{\mbox{\footnotesize approx}}(x) = \mbox{logit}^{-1}(0.07056 \, x^3 + 1.5976 \, x) \] +\form#411:\[ \frac{\partial \, \Phi_{\mbox{\footnotesize approx}}(x)}{\partial x} = -\Phi_{\mbox{\footnotesize approx}}^2(x) e^{-0.07056x^3 - 1.5976x}(-0.21168x^2-1.5976) \] +\form#412:$\frac{\partial}{\partial x} \mbox{pow}(x, y) = y x^{y-1}$ +\form#413:$\frac{\partial}{\partial y} \mbox{pow}(x, y) = x^y \ \log x$ +\form#414:\[ \mbox{pow}(x, y) = \begin{cases} x^y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#415:\[ \frac{\partial\, \mbox{pow}(x, y)}{\partial x} = \begin{cases} yx^{y-1} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#416:\[ \frac{\partial\, \mbox{pow}(x, y)}{\partial y} = \begin{cases} x^y\ln x & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +\form#417:$\frac{d}{dx} \mbox{pow}(x, c) = c x^{c-1}$ +\form#418:$\frac{d}{d y} \mbox{pow}(c, y) = c^y \log c $ +\form#419:$\frac{d}{dx} \mbox{round}(x) = 0$ +\form#420:\[ \mbox{round}(x) = \begin{cases} \lceil x \rceil & \mbox{if } x-\lfloor x\rfloor \geq 0.5 \\ \lfloor x \rfloor & \mbox{if } x-\lfloor x\rfloor < 0.5 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#421:\[ \frac{\partial\, \mbox{round}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#422:$\frac{d}{dx} \sin x = \cos x$ +\form#423:\[ \mbox{sin}(x) = \begin{cases} \sin(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#424:\[ \frac{\partial\, \mbox{sin}(x)}{\partial x} = \begin{cases} \cos(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#425:$\frac{d}{dx} \sinh x = \cosh x$ +\form#426:\[ \mbox{sinh}(x) = \begin{cases} \sinh(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#427:\[ \frac{\partial\, \mbox{sinh}(x)}{\partial x} = \begin{cases} \cosh(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#428:$\frac{d}{dx} \sqrt{x} = \frac{1}{2 \sqrt{x}}$ +\form#429:\[ \mbox{sqrt}(x) = \begin{cases} \textrm{NaN} & x < 0 \\ \sqrt{x} & \mbox{if } x\geq 0\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#430:\[ \frac{\partial\, \mbox{sqrt}(x)}{\partial x} = \begin{cases} \textrm{NaN} & x < 0 \\ \frac{1}{2\sqrt{x}} & x\geq 0\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#431:\[ \mbox{square}(x) = \begin{cases} x^2 & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#432:\[ \frac{\partial\, \mbox{square}(x)}{\partial x} = \begin{cases} 2x & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#433:$\mbox{step}(x) = 0$ +\form#434:$\frac{d}{dx} \tan x = \sec^2 x$ +\form#435:\[ \mbox{tan}(x) = \begin{cases} \tan(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#436:\[ \frac{\partial\, \mbox{tan}(x)}{\partial x} = \begin{cases} \sec^2(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#437:$\frac{d}{dx} \tanh x = \frac{1}{\cosh^2 x}$ +\form#438:\[ \mbox{tanh}(x) = \begin{cases} \tanh(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#439:\[ \frac{\partial\, \mbox{tanh}(x)}{\partial x} = \begin{cases} \mbox{sech}^2(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#440:$\frac{d}{dx} \Gamma(x) = \Gamma(x) \Psi^{(0)}(x)$ +\form#441:$\Psi^{(0)}(x)$ +\form#442:\[ \mbox{tgamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Gamma(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#443:\[ \frac{\partial\, \mbox{tgamma}(x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \frac{\partial\, \Gamma(x)}{\partial x} & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#444:\[ \Gamma(x)=\int_0^{\infty} u^{x - 1} \exp(-u) \, du \] +\form#445:\[ \frac{\partial \, \Gamma(x)}{\partial x} = \Gamma(x)\Psi(x) \] +\form#446:$\frac{d}{dx} \mbox{trunc}(x) = 0$ +\form#447:\[ \mbox{trunc}(x) = \begin{cases} \lfloor x \rfloor & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +\form#448:\[ \frac{\partial\, \mbox{trunc}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] diff --git a/doc/api/html/frechet__ccdf__log_8hpp.html b/doc/api/html/frechet__ccdf__log_8hpp.html new file mode 100644 index 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template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::frechet_ccdf_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
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frechet_ccdf_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_FRECHET_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_FRECHET_CCDF_LOG_HPP
+
3 
+
4 #include <boost/random/weibull_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + +
23 #include <cmath>
+
24 
+
25 namespace stan {
+
26 
+
27  namespace math {
+
28 
+
29  template <typename T_y, typename T_shape, typename T_scale>
+
30  typename return_type<T_y, T_shape, T_scale>::type
+
31  frechet_ccdf_log(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+ +
33  T_partials_return;
+
34 
+
35  static const char* function("stan::math::frechet_ccdf_log");
+
36 
+ + + +
40  using boost::math::tools::promote_args;
+ +
42 
+
43  // check if any vectors are zero length
+
44  if (!(stan::length(y)
+
45  && stan::length(alpha)
+
46  && stan::length(sigma)))
+
47  return 0.0;
+
48 
+
49  T_partials_return ccdf_log(0.0);
+
50  check_positive(function, "Random variable", y);
+
51  check_positive_finite(function, "Shape parameter", alpha);
+
52  check_positive_finite(function, "Scale parameter", sigma);
+
53 
+ +
55  operands_and_partials(y, alpha, sigma);
+
56 
+
57  using stan::math::log1m;
+
58  using std::log;
+
59  using std::exp;
+
60  VectorView<const T_y> y_vec(y);
+
61  VectorView<const T_scale> sigma_vec(sigma);
+
62  VectorView<const T_shape> alpha_vec(alpha);
+
63  size_t N = max_size(y, sigma, alpha);
+
64 
+
65  for (size_t n = 0; n < N; n++) {
+
66  const T_partials_return y_dbl = value_of(y_vec[n]);
+
67  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
68  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
69  const T_partials_return pow_ = pow(sigma_dbl / y_dbl, alpha_dbl);
+
70  const T_partials_return exp_ = exp(-pow_);
+
71 
+
72  // ccdf_log
+
73  ccdf_log += log1m(exp_);
+
74 
+
75  // gradients
+
76  const T_partials_return rep_deriv_ = pow_ / (1.0 / exp_ - 1);
+ +
78  operands_and_partials.d_x1[n] -= alpha_dbl / y_dbl * rep_deriv_;
+ +
80  operands_and_partials.d_x2[n] -= log(y_dbl / sigma_dbl) * rep_deriv_;
+ +
82  operands_and_partials.d_x3[n] += alpha_dbl / sigma_dbl * rep_deriv_;
+
83  }
+
84 
+
85  return operands_and_partials.value(ccdf_log);
+
86  }
+
87  }
+
88 }
+
89 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
return_type< T_y, T_shape, T_scale >::type frechet_ccdf_log(const T_y &y, const T_shape &alpha, const T_scale &sigma)
+ +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/frechet__cdf_8hpp.html b/doc/api/html/frechet__cdf_8hpp.html new file mode 100644 index 00000000000..68c8eb828c6 --- /dev/null +++ b/doc/api/html/frechet__cdf_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/frechet_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+
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template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::frechet_cdf (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/frechet__cdf_8hpp_source.html b/doc/api/html/frechet__cdf_8hpp_source.html new file mode 100644 index 00000000000..6d0e6742bd6 --- /dev/null +++ b/doc/api/html/frechet__cdf_8hpp_source.html @@ -0,0 +1,244 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/frechet_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
frechet_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_FRECHET_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_FRECHET_CDF_HPP
+
3 
+
4 #include <boost/random/weibull_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + +
23 #include <cmath>
+
24 
+
25 namespace stan {
+
26 
+
27  namespace math {
+
28 
+
29  template <typename T_y, typename T_shape, typename T_scale>
+
30  typename return_type<T_y, T_shape, T_scale>::type
+
31  frechet_cdf(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+ +
33  T_partials_return;
+
34 
+
35  static const char* function("stan::math::frechet_cdf");
+
36 
+ + + +
40  using boost::math::tools::promote_args;
+ +
42  using std::log;
+
43  using std::exp;
+
44 
+
45  // check if any vectors are zero length
+
46  if (!(stan::length(y)
+
47  && stan::length(alpha)
+
48  && stan::length(sigma)))
+
49  return 1.0;
+
50 
+
51  T_partials_return cdf(1.0);
+
52  check_positive(function, "Random variable", y);
+
53  check_positive_finite(function, "Shape parameter", alpha);
+
54  check_positive_finite(function, "Scale parameter", sigma);
+
55 
+ +
57  operands_and_partials(y, alpha, sigma);
+
58 
+
59  VectorView<const T_y> y_vec(y);
+
60  VectorView<const T_scale> sigma_vec(sigma);
+
61  VectorView<const T_shape> alpha_vec(alpha);
+
62  size_t N = max_size(y, sigma, alpha);
+
63  for (size_t n = 0; n < N; n++) {
+
64  const T_partials_return y_dbl = value_of(y_vec[n]);
+
65  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
66  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
67  const T_partials_return pow_ = pow(sigma_dbl / y_dbl, alpha_dbl);
+
68  const T_partials_return cdf_ = exp(-pow_);
+
69 
+
70  // cdf
+
71  cdf *= cdf_;
+
72 
+
73  // gradients
+ +
75  operands_and_partials.d_x1[n] += pow_ * alpha_dbl / y_dbl;
+ +
77  operands_and_partials.d_x2[n] += pow_ * log(y_dbl / sigma_dbl);
+ +
79  operands_and_partials.d_x3[n] -= pow_ * alpha_dbl / sigma_dbl;
+
80  }
+
81 
+ +
83  for (size_t n = 0; n < stan::length(y); ++n)
+
84  operands_and_partials.d_x1[n] *= cdf;
+
85  }
+ +
87  for (size_t n = 0; n < stan::length(alpha); ++n)
+
88  operands_and_partials.d_x2[n] *= cdf;
+
89  }
+ +
91  for (size_t n = 0; n < stan::length(sigma); ++n)
+
92  operands_and_partials.d_x3[n] *= cdf;
+
93  }
+
94 
+
95  return operands_and_partials.value(cdf);
+
96  }
+
97  }
+
98 }
+
99 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
return_type< T_y, T_shape, T_scale >::type frechet_cdf(const T_y &y, const T_shape &alpha, const T_scale &sigma)
Definition: frechet_cdf.hpp:31
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/frechet__cdf__log_8hpp.html b/doc/api/html/frechet__cdf__log_8hpp.html new file mode 100644 index 00000000000..f2304ded705 --- /dev/null +++ b/doc/api/html/frechet__cdf__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/frechet_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
frechet_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::frechet_cdf_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/frechet__cdf__log_8hpp_source.html b/doc/api/html/frechet__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..d6cb5b65cbb --- /dev/null +++ b/doc/api/html/frechet__cdf__log_8hpp_source.html @@ -0,0 +1,228 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/frechet_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+
+
frechet_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_FRECHET_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_FRECHET_CDF_LOG_HPP
+
3 
+
4 #include <boost/random/weibull_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + +
23 #include <cmath>
+
24 
+
25 namespace stan {
+
26 
+
27  namespace math {
+
28 
+
29  template <typename T_y, typename T_shape, typename T_scale>
+
30  typename return_type<T_y, T_shape, T_scale>::type
+
31  frechet_cdf_log(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+ +
33  T_partials_return;
+
34 
+
35  static const char* function("stan::math::frechet_cdf_log");
+
36 
+ + + +
40  using boost::math::tools::promote_args;
+ +
42  using std::log;
+
43 
+
44  // check if any vectors are zero length
+
45  if (!(stan::length(y)
+
46  && stan::length(alpha)
+
47  && stan::length(sigma)))
+
48  return 0.0;
+
49 
+
50  T_partials_return cdf_log(0.0);
+
51  check_positive(function, "Random variable", y);
+
52  check_positive_finite(function, "Shape parameter", alpha);
+
53  check_positive_finite(function, "Scale parameter", sigma);
+
54 
+ +
56  operands_and_partials(y, alpha, sigma);
+
57 
+
58  VectorView<const T_y> y_vec(y);
+
59  VectorView<const T_scale> sigma_vec(sigma);
+
60  VectorView<const T_shape> alpha_vec(alpha);
+
61  size_t N = max_size(y, sigma, alpha);
+
62  for (size_t n = 0; n < N; n++) {
+
63  const T_partials_return y_dbl = value_of(y_vec[n]);
+
64  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
65  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
66  const T_partials_return pow_ = pow(sigma_dbl / y_dbl, alpha_dbl);
+
67 
+
68  // cdf_log
+
69  cdf_log -= pow_;
+
70 
+
71  // gradients
+ +
73  operands_and_partials.d_x1[n] += pow_ * alpha_dbl / y_dbl;
+ +
75  operands_and_partials.d_x2[n] += pow_ * log(y_dbl / sigma_dbl);
+ +
77  operands_and_partials.d_x3[n] -= pow_ * alpha_dbl / sigma_dbl;
+
78  }
+
79 
+
80  return operands_and_partials.value(cdf_log);
+
81  }
+
82  }
+
83 }
+
84 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + + +
return_type< T_y, T_shape, T_scale >::type frechet_cdf_log(const T_y &y, const T_shape &alpha, const T_scale &sigma)
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/frechet__log_8hpp.html b/doc/api/html/frechet__log_8hpp.html new file mode 100644 index 00000000000..c1504c6eab1 --- /dev/null +++ b/doc/api/html/frechet__log_8hpp.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/frechet_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
frechet_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::frechet_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::frechet_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/frechet__log_8hpp_source.html b/doc/api/html/frechet__log_8hpp_source.html new file mode 100644 index 00000000000..f65b353730b --- /dev/null +++ b/doc/api/html/frechet__log_8hpp_source.html @@ -0,0 +1,294 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/frechet_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
+
frechet_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_FRECHET_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_FRECHET_LOG_HPP
+
3 
+
4 #include <boost/random/weibull_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + +
23 #include <cmath>
+
24 
+
25 namespace stan {
+
26 
+
27  namespace math {
+
28 
+
29  // Frechet(y|alpha, sigma) [y > 0; alpha > 0; sigma > 0]
+
30  // FIXME: document
+
31  template <bool propto,
+
32  typename T_y, typename T_shape, typename T_scale>
+
33  typename return_type<T_y, T_shape, T_scale>::type
+
34  frechet_log(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+
35  static const char* function("stan::math::frechet_log");
+ +
37  T_partials_return;
+
38 
+ + + + + + +
45  using std::log;
+
46 
+
47  // check if any vectors are zero length
+
48  if (!(stan::length(y)
+
49  && stan::length(alpha)
+
50  && stan::length(sigma)))
+
51  return 0.0;
+
52 
+
53  // set up return value accumulator
+
54  T_partials_return logp(0.0);
+
55  check_positive(function, "Random variable", y);
+
56  check_positive_finite(function, "Shape parameter", alpha);
+
57  check_positive_finite(function, "Scale parameter", sigma);
+
58  check_consistent_sizes(function,
+
59  "Random variable", y,
+
60  "Shape parameter", alpha,
+
61  "Scale parameter", sigma);
+
62 
+
63  // check if no variables are involved and prop-to
+ +
65  return 0.0;
+
66 
+
67  VectorView<const T_y> y_vec(y);
+
68  VectorView<const T_shape> alpha_vec(alpha);
+
69  VectorView<const T_scale> sigma_vec(sigma);
+
70  size_t N = max_size(y, alpha, sigma);
+
71 
+ +
73  T_partials_return, T_shape> log_alpha(length(alpha));
+
74  for (size_t i = 0; i < length(alpha); i++)
+ +
76  log_alpha[i] = log(value_of(alpha_vec[i]));
+
77 
+ +
79  T_partials_return, T_y> log_y(length(y));
+
80  for (size_t i = 0; i < length(y); i++)
+ +
82  log_y[i] = log(value_of(y_vec[i]));
+
83 
+ +
85  T_partials_return, T_scale> log_sigma(length(sigma));
+
86  for (size_t i = 0; i < length(sigma); i++)
+ +
88  log_sigma[i] = log(value_of(sigma_vec[i]));
+
89 
+ +
91  T_partials_return, T_y> inv_y(length(y));
+
92  for (size_t i = 0; i < length(y); i++)
+ +
94  inv_y[i] = 1.0 / value_of(y_vec[i]);
+
95 
+ +
97  T_partials_return, T_y, T_shape, T_scale>
+
98  sigma_div_y_pow_alpha(N);
+
99  for (size_t i = 0; i < N; i++)
+ +
101  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
102  sigma_div_y_pow_alpha[i] = pow(inv_y[i] * value_of(sigma_vec[i]),
+
103  alpha_dbl);
+
104  }
+
105 
+ +
107  operands_and_partials(y, alpha, sigma);
+
108  for (size_t n = 0; n < N; n++) {
+
109  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+ +
111  logp += log_alpha[n];
+ +
113  logp -= (alpha_dbl+1.0)*log_y[n];
+ +
115  logp += alpha_dbl*log_sigma[n];
+ +
117  logp -= sigma_div_y_pow_alpha[n];
+
118 
+ +
120  const T_partials_return inv_y_dbl = value_of(inv_y[n]);
+
121  operands_and_partials.d_x1[n]
+
122  += -(alpha_dbl+1.0) * inv_y_dbl
+
123  + alpha_dbl * sigma_div_y_pow_alpha[n] * inv_y_dbl;
+
124  }
+ +
126  operands_and_partials.d_x2[n]
+
127  += 1.0/alpha_dbl
+
128  + (1.0 - sigma_div_y_pow_alpha[n]) * (log_sigma[n] - log_y[n]);
+ +
130  operands_and_partials.d_x3[n]
+
131  += alpha_dbl / value_of(sigma_vec[n])
+
132  * (1 - sigma_div_y_pow_alpha[n]);
+
133  }
+
134  return operands_and_partials.value(logp);
+
135  }
+
136 
+
137  template <typename T_y, typename T_shape, typename T_scale>
+
138  inline
+ +
140  frechet_log(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+
141  return frechet_log<false>(y, alpha, sigma);
+
142  }
+
143  }
+
144 }
+
145 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_y, T_shape, T_scale >::type frechet_log(const T_y &y, const T_shape &alpha, const T_scale &sigma)
Definition: frechet_log.hpp:34
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
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+
+
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diff --git a/doc/api/html/frechet__rng_8hpp.html b/doc/api/html/frechet__rng_8hpp.html new file mode 100644 index 00000000000..2081e7aa6f0 --- /dev/null +++ b/doc/api/html/frechet__rng_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/frechet_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::frechet_rng (const double alpha, const double sigma, RNG &rng)
 
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diff --git a/doc/api/html/frechet__rng_8hpp_source.html b/doc/api/html/frechet__rng_8hpp_source.html new file mode 100644 index 00000000000..af9a9a370c9 --- /dev/null +++ b/doc/api/html/frechet__rng_8hpp_source.html @@ -0,0 +1,179 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/frechet_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_FRECHET_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_FRECHET_RNG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/random/weibull_distribution.hpp>
+
19 #include <boost/random/variate_generator.hpp>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <class RNG>
+
26  inline double
+
27  frechet_rng(const double alpha,
+
28  const double sigma,
+
29  RNG& rng) {
+
30  using boost::variate_generator;
+
31  using boost::random::weibull_distribution;
+
32 
+
33  static const char* function("stan::math::frechet_rng");
+
34 
+ + + +
38 
+
39  check_finite(function, "Shape parameter", alpha);
+
40  check_positive(function, "Shape parameter", alpha);
+
41  check_not_nan(function, "Scale parameter", sigma);
+
42  check_positive(function, "Scale parameter", sigma);
+
43 
+
44  variate_generator<RNG&, weibull_distribution<> >
+
45  weibull_rng(rng, weibull_distribution<>(alpha, 1.0/sigma));
+
46  return 1.0 / weibull_rng();
+
47  }
+
48  }
+
49 }
+
50 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + + + + +
double frechet_rng(const double alpha, const double sigma, RNG &rng)
Definition: frechet_rng.hpp:27
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ + +
double weibull_rng(const double alpha, const double sigma, RNG &rng)
Definition: weibull_rng.hpp:23
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
+
+
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diff --git a/doc/api/html/fun_8hpp.html b/doc/api/html/fun_8hpp.html new file mode 100644 index 00000000000..6aa714d1d6b --- /dev/null +++ b/doc/api/html/fun_8hpp.html @@ -0,0 +1,203 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun.hpp File Reference + + + + + + + + + + +
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+
#include <stan/math/prim/scal/fun/abs.hpp>
+#include <stan/math/prim/scal/fun/as_bool.hpp>
+#include <stan/math/prim/scal/fun/bessel_first_kind.hpp>
+#include <stan/math/prim/scal/fun/bessel_second_kind.hpp>
+#include <stan/math/prim/scal/fun/binary_log_loss.hpp>
+#include <stan/math/prim/scal/fun/binomial_coefficient_log.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/corr_constrain.hpp>
+#include <stan/math/prim/scal/fun/corr_free.hpp>
+#include <stan/math/prim/scal/fun/digamma.hpp>
+#include <stan/math/prim/scal/fun/divide.hpp>
+#include <stan/math/prim/scal/fun/exp2.hpp>
+#include <stan/math/prim/scal/fun/F32.hpp>
+#include <stan/math/prim/scal/fun/falling_factorial.hpp>
+#include <stan/math/prim/scal/fun/fdim.hpp>
+#include <stan/math/prim/scal/fun/gamma_p.hpp>
+#include <stan/math/prim/scal/fun/gamma_q.hpp>
+#include <stan/math/prim/scal/fun/grad_2F1.hpp>
+#include <stan/math/prim/scal/fun/grad_F32.hpp>
+#include <stan/math/prim/scal/fun/grad_inc_beta.hpp>
+#include <stan/math/prim/scal/fun/grad_reg_inc_beta.hpp>
+#include <stan/math/prim/scal/fun/grad_reg_inc_gamma.hpp>
+#include <stan/math/prim/scal/fun/ibeta.hpp>
+#include <stan/math/prim/scal/fun/identity_constrain.hpp>
+#include <stan/math/prim/scal/fun/identity_free.hpp>
+#include <stan/math/prim/scal/fun/if_else.hpp>
+#include <stan/math/prim/scal/fun/inc_beta.hpp>
+#include <stan/math/prim/scal/fun/inc_beta_dda.hpp>
+#include <stan/math/prim/scal/fun/inc_beta_ddb.hpp>
+#include <stan/math/prim/scal/fun/inc_beta_ddz.hpp>
+#include <stan/math/prim/scal/fun/int_step.hpp>
+#include <stan/math/prim/scal/fun/inv.hpp>
+#include <stan/math/prim/scal/fun/inv_cloglog.hpp>
+#include <stan/math/prim/scal/fun/inv_logit.hpp>
+#include <stan/math/prim/scal/fun/inv_sqrt.hpp>
+#include <stan/math/prim/scal/fun/inv_square.hpp>
+#include <stan/math/prim/scal/fun/inverse_softmax.hpp>
+#include <stan/math/prim/scal/fun/is_inf.hpp>
+#include <stan/math/prim/scal/fun/is_nan.hpp>
+#include <stan/math/prim/scal/fun/is_uninitialized.hpp>
+#include <stan/math/prim/scal/fun/lb_constrain.hpp>
+#include <stan/math/prim/scal/fun/lb_free.hpp>
+#include <stan/math/prim/scal/fun/lbeta.hpp>
+#include <stan/math/prim/scal/fun/lgamma.hpp>
+#include <stan/math/prim/scal/fun/lmgamma.hpp>
+#include <stan/math/prim/scal/fun/log1m.hpp>
+#include <stan/math/prim/scal/fun/log1m_exp.hpp>
+#include <stan/math/prim/scal/fun/log1m_inv_logit.hpp>
+#include <stan/math/prim/scal/fun/log1p.hpp>
+#include <stan/math/prim/scal/fun/log1p_exp.hpp>
+#include <stan/math/prim/scal/fun/log2.hpp>
+#include <stan/math/prim/scal/fun/log_diff_exp.hpp>
+#include <stan/math/prim/scal/fun/log_falling_factorial.hpp>
+#include <stan/math/prim/scal/fun/log_inv_logit.hpp>
+#include <stan/math/prim/scal/fun/log_mix.hpp>
+#include <stan/math/prim/scal/fun/log_rising_factorial.hpp>
+#include <stan/math/prim/scal/fun/log_sum_exp.hpp>
+#include <stan/math/prim/scal/fun/logical_and.hpp>
+#include <stan/math/prim/scal/fun/logical_eq.hpp>
+#include <stan/math/prim/scal/fun/logical_gt.hpp>
+#include <stan/math/prim/scal/fun/logical_gte.hpp>
+#include <stan/math/prim/scal/fun/logical_lt.hpp>
+#include <stan/math/prim/scal/fun/logical_lte.hpp>
+#include <stan/math/prim/scal/fun/logical_negation.hpp>
+#include <stan/math/prim/scal/fun/logical_neq.hpp>
+#include <stan/math/prim/scal/fun/logical_or.hpp>
+#include <stan/math/prim/scal/fun/logit.hpp>
+#include <stan/math/prim/scal/fun/lub_constrain.hpp>
+#include <stan/math/prim/scal/fun/lub_free.hpp>
+#include <stan/math/prim/scal/fun/modified_bessel_first_kind.hpp>
+#include <stan/math/prim/scal/fun/modified_bessel_second_kind.hpp>
+#include <stan/math/prim/scal/fun/modulus.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/owens_t.hpp>
+#include <stan/math/prim/scal/fun/Phi.hpp>
+#include <stan/math/prim/scal/fun/Phi_approx.hpp>
+#include <stan/math/prim/scal/fun/positive_constrain.hpp>
+#include <stan/math/prim/scal/fun/positive_free.hpp>
+#include <stan/math/prim/scal/fun/primitive_value.hpp>
+#include <stan/math/prim/scal/fun/prob_constrain.hpp>
+#include <stan/math/prim/scal/fun/prob_free.hpp>
+#include <stan/math/prim/scal/fun/promote_scalar.hpp>
+#include <stan/math/prim/scal/fun/promote_scalar_type.hpp>
+#include <stan/math/prim/scal/fun/rising_factorial.hpp>
+#include <stan/math/prim/scal/fun/sign.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <stan/math/prim/scal/fun/step.hpp>
+#include <stan/math/prim/scal/fun/trigamma.hpp>
+#include <stan/math/prim/scal/fun/ub_constrain.hpp>
+#include <stan/math/prim/scal/fun/ub_free.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <stan/math/prim/scal/fun/value_of_rec.hpp>
+
+

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diff --git a/doc/api/html/fun_8hpp_source.html b/doc/api/html/fun_8hpp_source.html new file mode 100644 index 00000000000..3d4131a7f93 --- /dev/null +++ b/doc/api/html/fun_8hpp_source.html @@ -0,0 +1,298 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_HPP
+
3 
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diff --git a/doc/api/html/functor_8hpp_source.html b/doc/api/html/functor_8hpp_source.html new file mode 100644 index 00000000000..917c7f9a8b0 --- /dev/null +++ b/doc/api/html/functor_8hpp_source.html @@ -0,0 +1,122 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_MAT_FUNCTOR_HPP
+
2 #define STAN_MATH_REV_MAT_FUNCTOR_HPP
+
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diff --git a/doc/api/html/fvar_8hpp.html b/doc/api/html/fvar_8hpp.html new file mode 100644 index 00000000000..67233fd87e4 --- /dev/null +++ b/doc/api/html/fvar_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/fvar.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/meta/likely.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <ostream>
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struct  stan::math::fvar< T >
 
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diff --git a/doc/api/html/fvar_8hpp_source.html b/doc/api/html/fvar_8hpp_source.html new file mode 100644 index 00000000000..850f4b48d67 --- /dev/null +++ b/doc/api/html/fvar_8hpp_source.html @@ -0,0 +1,280 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/fvar.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_FVAR_HPP
+
2 #define STAN_MATH_FWD_CORE_FVAR_HPP
+
3 
+ +
5 #include <boost/math/special_functions/fpclassify.hpp>
+
6 #include <ostream>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  struct fvar {
+
14  T val_; // value
+
15  T d_; // tangent (aka derivative)
+
16 
+
17  T val() const { return val_; }
+
18  T tangent() const { return d_; }
+
19 
+
20  typedef fvar value_type;
+
21 
+
22  fvar() : val_(0.0), d_(0.0) { }
+
23 
+
24  fvar(const fvar<T>& x)
+
25  : val_(x.val_), d_(x.d_) {
+
26  }
+
27 
+
28  // TV and TD must be assignable to T
+
29  template <typename TV, typename TD>
+
30  fvar(const TV& val, const TD& deriv) : val_(val), d_(deriv) {
+
31  if (unlikely(boost::math::isnan(val)))
+
32  d_ = val;
+
33  }
+
34 
+
35  // TV must be assignable to T
+
36  template <typename TV>
+
37  fvar(const TV& val) // NOLINT
+
38  : val_(val), d_(0.0) {
+
39  if (unlikely(boost::math::isnan(val)))
+
40  d_ = val;
+
41  }
+
42 
+
43 
+
44  inline
+
45  fvar<T>&
+
46  operator+=(const fvar<T>& x2) {
+
47  val_ += x2.val_;
+
48  d_ += x2.d_;
+
49  return *this;
+
50  }
+
51 
+
52  inline
+
53  fvar<T>&
+
54  operator+=(double x2) {
+
55  val_ += x2;
+
56  return *this;
+
57  }
+
58 
+
59  inline
+
60  fvar<T>&
+
61  operator-=(const fvar<T>& x2) {
+
62  val_ -= x2.val_;
+
63  d_ -= x2.d_;
+
64  return *this;
+
65  }
+
66 
+
67  inline
+
68  fvar<T>&
+
69  operator-=(double x2) {
+
70  val_ -= x2;
+
71  return *this;
+
72  }
+
73 
+
74  inline
+
75  fvar<T>&
+
76  operator*=(const fvar<T>& x2) {
+
77  d_ = d_ * x2.val_ + val_ * x2.d_;
+
78  val_ *= x2.val_;
+
79  return *this;
+
80  }
+
81 
+
82  inline
+
83  fvar<T>&
+
84  operator*=(double x2) {
+
85  val_ *= x2;
+
86  d_ *= x2;
+
87  return *this;
+
88  }
+
89 
+
90  // SPEEDUP: specialize for T2 == var with d_ function
+
91 
+
92  inline
+
93  fvar<T>&
+
94  operator/=(const fvar<T>& x2) {
+
95  d_ = (d_ * x2.val_ - val_ * x2.d_) / (x2.val_ * x2.val_);
+
96  val_ /= x2.val_;
+
97  return *this;
+
98  }
+
99 
+
100  inline
+
101  fvar<T>&
+
102  operator/=(double x2) {
+
103  val_ /= x2;
+
104  d_ /= x2;
+
105  return *this;
+
106  }
+
107 
+
108  inline
+
109  fvar<T>&
+ +
111  ++val_;
+
112  return *this;
+
113  }
+
114 
+
115  inline
+
116  fvar<T>
+
117  operator++(int /*dummy*/) {
+
118  fvar<T> result(val_, d_);
+
119  ++val_;
+
120  return result;
+
121  }
+
122 
+
123  inline
+
124  fvar<T>&
+ +
126  --val_;
+
127  return *this;
+
128  }
+
129  inline
+
130  fvar<T>
+
131  operator--(int /*dummy*/) {
+
132  fvar<T> result(val_, d_);
+
133  --val_;
+
134  return result;
+
135  }
+
136 
+
137  friend
+
138  std::ostream&
+
139  operator<<(std::ostream& os, const fvar<T>& v) {
+
140  return os << v.val_;
+
141  }
+
142  };
+
143  }
+
144 }
+
145 #endif
+ + +
fvar< T > & operator-=(const fvar< T > &x2)
Definition: fvar.hpp:61
+
fvar< T > & operator/=(double x2)
Definition: fvar.hpp:102
+
T tangent() const
Definition: fvar.hpp:18
+
fvar< T > operator--(int)
Definition: fvar.hpp:131
+
fvar(const fvar< T > &x)
Definition: fvar.hpp:24
+
fvar< T > & operator+=(const fvar< T > &x2)
Definition: fvar.hpp:46
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
fvar< T > & operator++()
Definition: fvar.hpp:110
+ +
fvar value_type
Definition: fvar.hpp:20
+
fvar< T > & operator--()
Definition: fvar.hpp:125
+
fvar< T > operator++(int)
Definition: fvar.hpp:117
+ +
fvar< T > & operator-=(double x2)
Definition: fvar.hpp:69
+
fvar(const TV &val)
Definition: fvar.hpp:37
+
T val() const
Definition: fvar.hpp:17
+
fvar< T > & operator+=(double x2)
Definition: fvar.hpp:54
+
fvar< T > & operator*=(const fvar< T > &x2)
Definition: fvar.hpp:76
+ +
fvar< T > & operator*=(double x2)
Definition: fvar.hpp:84
+
fvar(const TV &val, const TD &deriv)
Definition: fvar.hpp:30
+
fvar< T > & operator/=(const fvar< T > &x2)
Definition: fvar.hpp:94
+ +
+
+
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diff --git a/doc/api/html/fwd_2arr_2fun_2log__sum__exp_8hpp.html b/doc/api/html/fwd_2arr_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..733d90f8057 --- /dev/null +++ b/doc/api/html/fwd_2arr_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/arr/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
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log_sum_exp.hpp File Reference
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#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/arr/fun/log_sum_exp.hpp>
+#include <vector>
+
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template<typename T >
fvar< T > stan::math::log_sum_exp (const std::vector< fvar< T > > &v)
 
+
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diff --git a/doc/api/html/fwd_2arr_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/fwd_2arr_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..d2ebade256f --- /dev/null +++ b/doc/api/html/fwd_2arr_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/fwd/arr/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_ARR_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_FWD_ARR_FUN_LOG_SUM_EXP_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  fvar<T>
+
14  log_sum_exp(const std::vector<fvar<T> >& v) {
+ +
16  using std::exp;
+
17  std::vector<T> vals(v.size());
+
18  for (size_t i = 0; i < v.size(); ++i)
+
19  vals[i] = v[i].val_;
+
20  T deriv(0.0);
+
21  T denominator(0.0);
+
22  for (size_t i = 0; i < v.size(); ++i) {
+
23  T exp_vi = exp(vals[i]);
+
24  denominator += exp_vi;
+
25  deriv += v[i].d_ * exp_vi;
+
26  }
+
27  return fvar<T>(log_sum_exp(vals), deriv / denominator);
+
28  }
+
29 
+
30  }
+
31 }
+
32 #endif
+ + +
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
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diff --git a/doc/api/html/fwd_2arr_2fun_2sum_8hpp.html b/doc/api/html/fwd_2arr_2fun_2sum_8hpp.html new file mode 100644 index 00000000000..c812ef5fee4 --- /dev/null +++ b/doc/api/html/fwd_2arr_2fun_2sum_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/arr/fun/sum.hpp File Reference + + + + + + + + + + +
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#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/arr/fun/sum.hpp>
+#include <vector>
+
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template<typename T >
fvar< T > stan::math::sum (const std::vector< fvar< T > > &m)
 Return the sum of the entries of the specified standard vector. More...
 
+
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diff --git a/doc/api/html/fwd_2arr_2fun_2sum_8hpp_source.html b/doc/api/html/fwd_2arr_2fun_2sum_8hpp_source.html new file mode 100644 index 00000000000..d55f0dc3313 --- /dev/null +++ b/doc/api/html/fwd_2arr_2fun_2sum_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/arr/fun/sum.hpp Source File + + + + + + + + + + +
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sum.hpp
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1 #ifndef STAN_MATH_FWD_ARR_FUN_SUM_HPP
+
2 #define STAN_MATH_FWD_ARR_FUN_SUM_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
19  template <typename T>
+
20  inline fvar<T> sum(const std::vector<fvar<T> >& m) {
+
21  using stan::math::sum;
+
22  if (m.size() == 0)
+
23  return 0.0;
+
24  std::vector<T> vals(m.size());
+
25  std::vector<T> tans(m.size());
+
26  for (size_t i = 0; i < m.size(); ++i) {
+
27  vals[i] = m[i].val();
+
28  tans[i] = m[i].tangent();
+
29  }
+
30  return fvar<T>(sum(vals), sum(tans));
+
31  }
+
32 
+
33  }
+
34 }
+
35 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + + + +
+
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diff --git a/doc/api/html/fwd_2arr_8hpp.html b/doc/api/html/fwd_2arr_8hpp.html new file mode 100644 index 00000000000..b0c52616625 --- /dev/null +++ b/doc/api/html/fwd_2arr_8hpp.html @@ -0,0 +1,119 @@ + + + + + + +Stan Math Library: stan/math/fwd/arr.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2arr_8hpp_source.html b/doc/api/html/fwd_2arr_8hpp_source.html new file mode 100644 index 00000000000..4688ea2ac31 --- /dev/null +++ b/doc/api/html/fwd_2arr_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/arr.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_ARR_HPP
+
2 #define STAN_MATH_FWD_ARR_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + +
7 
+
8 #include <stan/math/prim/arr.hpp>
+
9 #include <stan/math/fwd/scal.hpp>
+
10 
+ + + +
14 
+
15 #endif
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diff --git a/doc/api/html/fwd_2core_2operator__addition_8hpp.html b/doc/api/html/fwd_2core_2operator__addition_8hpp.html new file mode 100644 index 00000000000..4f73eb112ee --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__addition_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_addition.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::operator+ (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::operator+ (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::operator+ (const fvar< T > &x1, const double x2)
 
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diff --git a/doc/api/html/fwd_2core_2operator__addition_8hpp_source.html b/doc/api/html/fwd_2core_2operator__addition_8hpp_source.html new file mode 100644 index 00000000000..0f9653ad1f6 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__addition_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_addition.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_ADDITION_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_ADDITION_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline
+
12  fvar<T>
+
13  operator+(const fvar<T>& x1, const fvar<T>& x2) {
+
14  return fvar<T>(x1.val_ + x2.val_, x1.d_ + x2.d_);
+
15  }
+
16 
+
17  template <typename T>
+
18  inline
+
19  fvar<T>
+
20  operator+(const double x1, const fvar<T>& x2) {
+
21  return fvar<T>(x1 + x2.val_, x2.d_);
+
22  }
+
23 
+
24  template <typename T>
+
25  inline
+
26  fvar<T>
+
27  operator+(const fvar<T>& x1, const double x2) {
+
28  return fvar<T>(x1.val_ + x2, x1.d_);
+
29  }
+
30  }
+
31 }
+
32 #endif
+ + + + +
fvar< T > operator+(const fvar< T > &x1, const fvar< T > &x2)
+ +
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diff --git a/doc/api/html/fwd_2core_2operator__division_8hpp.html b/doc/api/html/fwd_2core_2operator__division_8hpp.html new file mode 100644 index 00000000000..a0e0fd0033f --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__division_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_division.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::operator/ (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::operator/ (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > stan::math::operator/ (const double x1, const fvar< T > &x2)
 
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diff --git a/doc/api/html/fwd_2core_2operator__division_8hpp_source.html b/doc/api/html/fwd_2core_2operator__division_8hpp_source.html new file mode 100644 index 00000000000..02476f29433 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__division_8hpp_source.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_division.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_DIVISION_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_DIVISION_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  operator/(const fvar<T>& x1, const fvar<T>& x2) {
+
15  return fvar<T>(x1.val_ / x2.val_,
+
16  (x1.d_ * x2.val_ - x1.val_ * x2.d_) / (x2.val_ * x2.val_));
+
17  }
+
18 
+
19  template <typename T>
+
20  inline
+
21  fvar<T>
+
22  operator/(const fvar<T>& x1, const double x2) {
+
23  return fvar<T>(x1.val_ / x2,
+
24  x1.d_ / x2);
+
25  }
+
26 
+
27  template <typename T>
+
28  inline
+
29  fvar<T>
+
30  operator/(const double x1, const fvar<T>& x2) {
+
31  return fvar<T>(x1 / x2.val_,
+
32  - x1 * x2.d_ / (x2.val_ * x2.val_));
+
33  }
+
34  }
+
35 }
+
36 #endif
+
fvar< T > operator/(const fvar< T > &x1, const fvar< T > &x2)
+ + + + + +
+
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diff --git a/doc/api/html/fwd_2core_2operator__equal_8hpp.html b/doc/api/html/fwd_2core_2operator__equal_8hpp.html new file mode 100644 index 00000000000..4624534b524 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_equal.hpp File Reference + + + + + + + + + + +
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template<typename T >
bool stan::math::operator== (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool stan::math::operator== (const fvar< T > &x, double y)
 
template<typename T >
bool stan::math::operator== (double x, const fvar< T > &y)
 
+
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diff --git a/doc/api/html/fwd_2core_2operator__equal_8hpp_source.html b/doc/api/html/fwd_2core_2operator__equal_8hpp_source.html new file mode 100644 index 00000000000..71f229c6496 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__equal_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_equal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_EQUAL_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_EQUAL_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  bool
+
14  operator==(const fvar<T>& x, const fvar<T>& y) {
+
15  return x.val_ == y.val_;
+
16  }
+
17 
+
18  template <typename T>
+
19  inline
+
20  bool
+
21  operator==(const fvar<T>& x, double y) {
+
22  return x.val_ == y;
+
23  }
+
24 
+
25  template <typename T>
+
26  inline
+
27  bool
+
28  operator==(double x, const fvar<T>& y) {
+
29  return x == y.val_;
+
30  }
+
31  }
+
32 }
+
33 #endif
+ + + +
bool operator==(const fvar< T > &x, const fvar< T > &y)
+ +
+
+
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diff --git a/doc/api/html/fwd_2core_2operator__greater__than_8hpp.html b/doc/api/html/fwd_2core_2operator__greater__than_8hpp.html new file mode 100644 index 00000000000..4b9e02ce4d7 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__greater__than_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_greater_than.hpp File Reference + + + + + + + + + + +
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template<typename T >
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template<typename T >
bool stan::math::operator> (const fvar< T > &x, double y)
 
template<typename T >
bool stan::math::operator> (double x, const fvar< T > &y)
 
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diff --git a/doc/api/html/fwd_2core_2operator__greater__than_8hpp_source.html b/doc/api/html/fwd_2core_2operator__greater__than_8hpp_source.html new file mode 100644 index 00000000000..54962182d7b --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__greater__than_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_greater_than.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_GREATER_THAN_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_GREATER_THAN_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  bool
+
14  operator>(const fvar<T>& x, const fvar<T>& y) {
+
15  return x.val_ > y.val_;
+
16  }
+
17 
+
18  template <typename T>
+
19  inline
+
20  bool
+
21  operator>(const fvar<T>& x, double y) {
+
22  return x.val_ > y;
+
23  }
+
24 
+
25  template <typename T>
+
26  inline
+
27  bool
+
28  operator>(double x, const fvar<T>& y) {
+
29  return x > y.val_;
+
30  }
+
31  }
+
32 }
+
33 #endif
+ + + +
bool operator>(const fvar< T > &x, const fvar< T > &y)
+ +
+
+
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diff --git a/doc/api/html/fwd_2core_2operator__greater__than__or__equal_8hpp.html b/doc/api/html/fwd_2core_2operator__greater__than__or__equal_8hpp.html new file mode 100644 index 00000000000..43727b54f19 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__greater__than__or__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_greater_than_or_equal.hpp File Reference + + + + + + + + + + +
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template<typename T >
bool stan::math::operator>= (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool stan::math::operator>= (const fvar< T > &x, double y)
 
template<typename T >
bool stan::math::operator>= (double x, const fvar< T > &y)
 
+
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diff --git a/doc/api/html/fwd_2core_2operator__greater__than__or__equal_8hpp_source.html b/doc/api/html/fwd_2core_2operator__greater__than__or__equal_8hpp_source.html new file mode 100644 index 00000000000..21dca805f55 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__greater__than__or__equal_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_greater_than_or_equal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_GREATER_THAN_OR_EQUAL_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_GREATER_THAN_OR_EQUAL_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  bool
+
14  operator>=(const fvar<T>& x, const fvar<T>& y) {
+
15  return x.val_ >= y.val_;
+
16  }
+
17 
+
18  template <typename T>
+
19  inline
+
20  bool
+
21  operator>=(const fvar<T>& x, double y) {
+
22  return x.val_ >= y;
+
23  }
+
24 
+
25  template <typename T>
+
26  inline
+
27  bool
+
28  operator>=(double x, const fvar<T>& y) {
+
29  return x >= y.val_;
+
30  }
+
31  }
+
32 }
+
33 #endif
+ + + +
bool operator>=(const fvar< T > &x, const fvar< T > &y)
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2core_2operator__less__than_8hpp.html b/doc/api/html/fwd_2core_2operator__less__than_8hpp.html new file mode 100644 index 00000000000..0fda26d2303 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__less__than_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_less_than.hpp File Reference + + + + + + + + + + +
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template<typename T >
bool stan::math::operator< (const fvar< T > &x, double y)
 
template<typename T >
bool stan::math::operator< (double x, const fvar< T > &y)
 
template<typename T >
bool stan::math::operator< (const fvar< T > &x, const fvar< T > &y)
 
+
+
+
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diff --git a/doc/api/html/fwd_2core_2operator__less__than_8hpp_source.html b/doc/api/html/fwd_2core_2operator__less__than_8hpp_source.html new file mode 100644 index 00000000000..c8f627a5433 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__less__than_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_less_than.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_LESS_THAN_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_LESS_THAN_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline bool operator<(const fvar<T>& x,
+
13  double y) {
+
14  return x.val_ < y;
+
15  }
+
16 
+
17  template <typename T>
+
18  inline bool operator<(double x,
+
19  const fvar<T>& y) {
+
20  return x < y.val_;
+
21  }
+
22 
+
23  template <typename T>
+
24  inline bool operator<(const fvar<T>& x,
+
25  const fvar<T>& y) {
+
26  return x.val_ < y.val_;
+
27  }
+
28  }
+
29 }
+
30 #endif
+ + + +
bool operator<(const fvar< T > &x, double y)
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2core_2operator__less__than__or__equal_8hpp.html b/doc/api/html/fwd_2core_2operator__less__than__or__equal_8hpp.html new file mode 100644 index 00000000000..cfe3fcf71e0 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__less__than__or__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_less_than_or_equal.hpp File Reference + + + + + + + + + + +
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template<typename T >
bool stan::math::operator<= (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool stan::math::operator<= (const fvar< T > &x, double y)
 
template<typename T >
bool stan::math::operator<= (double x, const fvar< T > &y)
 
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diff --git a/doc/api/html/fwd_2core_2operator__less__than__or__equal_8hpp_source.html b/doc/api/html/fwd_2core_2operator__less__than__or__equal_8hpp_source.html new file mode 100644 index 00000000000..b0f5ce38be2 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__less__than__or__equal_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_less_than_or_equal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_LESS_THAN_OR_EQUAL_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_LESS_THAN_OR_EQUAL_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  bool
+
14  operator<=(const fvar<T>& x, const fvar<T>& y) {
+
15  return x.val_ <= y.val_;
+
16  }
+
17 
+
18  template <typename T>
+
19  inline
+
20  bool
+
21  operator<=(const fvar<T>& x, double y) {
+
22  return x.val_ <= y;
+
23  }
+
24 
+
25  template <typename T>
+
26  inline
+
27  bool
+
28  operator<=(double x, const fvar<T>& y) {
+
29  return x <= y.val_;
+
30  }
+
31  }
+
32 }
+
33 #endif
+ + + + +
+
+
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diff --git a/doc/api/html/fwd_2core_2operator__multiplication_8hpp.html b/doc/api/html/fwd_2core_2operator__multiplication_8hpp.html new file mode 100644 index 00000000000..c76244a457b --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__multiplication_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_multiplication.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::operator* (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::operator* (double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::operator* (const fvar< T > &x1, double x2)
 
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diff --git a/doc/api/html/fwd_2core_2operator__multiplication_8hpp_source.html b/doc/api/html/fwd_2core_2operator__multiplication_8hpp_source.html new file mode 100644 index 00000000000..8ca57459429 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__multiplication_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_multiplication.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_MULTIPLICATION_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_MULTIPLICATION_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  operator*(const fvar<T>& x1, const fvar<T>& x2) {
+
15  return fvar<T>(x1.val_ * x2.val_,
+
16  x1.d_ * x2.val_ + x1.val_ * x2.d_);
+
17  }
+
18 
+
19  template <typename T>
+
20  inline
+
21  fvar<T>
+
22  operator*(double x1, const fvar<T>& x2) {
+
23  return fvar<T>(x1 * x2.val_, x1 * x2.d_);
+
24  }
+
25 
+
26  template <typename T>
+
27  inline
+
28  fvar<T>
+
29  operator*(const fvar<T>& x1, double x2) {
+
30  return fvar<T>(x1.val_ * x2, x1.d_ * x2);
+
31  }
+
32  }
+
33 }
+
34 #endif
+ + + + +
fvar< T > operator*(const fvar< T > &x1, const fvar< T > &x2)
+ +
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diff --git a/doc/api/html/fwd_2core_2operator__not__equal_8hpp.html b/doc/api/html/fwd_2core_2operator__not__equal_8hpp.html new file mode 100644 index 00000000000..05f80c66f32 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__not__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_not_equal.hpp File Reference + + + + + + + + + + +
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template<typename T >
bool stan::math::operator!= (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool stan::math::operator!= (const fvar< T > &x, double y)
 
template<typename T >
bool stan::math::operator!= (double x, const fvar< T > &y)
 
+
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diff --git a/doc/api/html/fwd_2core_2operator__not__equal_8hpp_source.html b/doc/api/html/fwd_2core_2operator__not__equal_8hpp_source.html new file mode 100644 index 00000000000..aece859942f --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__not__equal_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_not_equal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_NOT_EQUAL_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_NOT_EQUAL_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  bool
+
14  operator!=(const fvar<T>& x, const fvar<T>& y) {
+
15  return x.val_ != y.val_;
+
16  }
+
17 
+
18  template <typename T>
+
19  inline
+
20  bool
+
21  operator!=(const fvar<T>& x, double y) {
+
22  return x.val_ != y;
+
23  }
+
24 
+
25  template <typename T>
+
26  inline
+
27  bool
+
28  operator!=(double x, const fvar<T>& y) {
+
29  return x != y.val_;
+
30  }
+
31  }
+
32 }
+
33 #endif
+ +
bool operator!=(const fvar< T > &x, const fvar< T > &y)
+ + + +
+
+
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diff --git a/doc/api/html/fwd_2core_2operator__subtraction_8hpp.html b/doc/api/html/fwd_2core_2operator__subtraction_8hpp.html new file mode 100644 index 00000000000..69414cc6577 --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__subtraction_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_subtraction.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::operator- (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::operator- (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::operator- (const fvar< T > &x1, const double x2)
 
+
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diff --git a/doc/api/html/fwd_2core_2operator__subtraction_8hpp_source.html b/doc/api/html/fwd_2core_2operator__subtraction_8hpp_source.html new file mode 100644 index 00000000000..1b1592d5dff --- /dev/null +++ b/doc/api/html/fwd_2core_2operator__subtraction_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_subtraction.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_SUBTRACTION_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_SUBTRACTION_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  operator-(const fvar<T>& x1, const fvar<T>& x2) {
+
15  return fvar<T>(x1.val_ - x2.val_, x1.d_ - x2.d_);
+
16  }
+
17 
+
18  template <typename T>
+
19  inline
+
20  fvar<T>
+
21  operator-(const double x1, const fvar<T>& x2) {
+
22  return fvar<T>(x1 - x2.val_, -x2.d_);
+
23  }
+
24 
+
25  template <typename T>
+
26  inline
+
27  fvar<T>
+
28  operator-(const fvar<T>& x1, const double x2) {
+
29  return fvar<T>(x1.val_ - x2, x1.d_);
+
30  }
+
31  }
+
32 }
+
33 #endif
+
fvar< T > operator-(const fvar< T > &x1, const fvar< T > &x2)
+ + + + + +
+
+
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diff --git a/doc/api/html/fwd_2core_2std__numeric__limits_8hpp.html b/doc/api/html/fwd_2core_2std__numeric__limits_8hpp.html new file mode 100644 index 00000000000..b5a20882fb0 --- /dev/null +++ b/doc/api/html/fwd_2core_2std__numeric__limits_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/std_numeric_limits.hpp File Reference + + + + + + + + + + +
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#include <stan/math/fwd/core/fvar.hpp>
+#include <limits>
+
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struct  std::numeric_limits< stan::math::fvar< T > >
 
+ + + +

+Namespaces

 std
 
+
+
+
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diff --git a/doc/api/html/fwd_2core_2std__numeric__limits_8hpp_source.html b/doc/api/html/fwd_2core_2std__numeric__limits_8hpp_source.html new file mode 100644 index 00000000000..ab17410e87d --- /dev/null +++ b/doc/api/html/fwd_2core_2std__numeric__limits_8hpp_source.html @@ -0,0 +1,180 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/std_numeric_limits.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_STD_NUMERIC_LIMITS_HPP
+
2 #define STAN_MATH_FWD_CORE_STD_NUMERIC_LIMITS_HPP
+
3 
+ +
5 #include <limits>
+
6 
+
7 namespace std {
+
8 
+
9  template <typename T>
+
10 
+
11  struct numeric_limits<stan::math::fvar<T> > {
+
12  static const bool is_specialized = true;
+ + +
15  static const int digits = numeric_limits<double>::digits;
+
16  static const int digits10 = numeric_limits<double>::digits10;
+
17  static const bool is_signed = numeric_limits<double>::is_signed;
+
18  static const bool is_integer = numeric_limits<double>::is_integer;
+
19  static const bool is_exact = numeric_limits<double>::is_exact;
+
20  static const int radix = numeric_limits<double>::radix;
+ +
22  return numeric_limits<double>::epsilon(); }
+ +
24  return numeric_limits<double>::round_error(); }
+
25 
+
26  static const int min_exponent = numeric_limits<double>::min_exponent;
+
27  static const int min_exponent10 = numeric_limits<double>::min_exponent10;
+
28  static const int max_exponent = numeric_limits<double>::max_exponent;
+
29  static const int max_exponent10 = numeric_limits<double>::max_exponent10;
+
30 
+
31  static const bool has_infinity = numeric_limits<double>::has_infinity;
+
32  static const bool has_quiet_NaN = numeric_limits<double>::has_quiet_NaN;
+
33  static const bool has_signaling_NaN =
+
34  numeric_limits<double>::has_signaling_NaN;
+
35  static const float_denorm_style has_denorm =
+
36  numeric_limits<double>::has_denorm;
+
37  static const bool has_denorm_loss = numeric_limits<double>::has_denorm_loss;
+ +
39  return numeric_limits<double>::infinity(); }
+ +
41  return numeric_limits<double>::quiet_NaN(); }
+ +
43  return numeric_limits<double>::signaling_NaN(); }
+ +
45  return numeric_limits<double>::denorm_min(); }
+
46 
+
47  static const bool is_iec559 = numeric_limits<double>::is_iec559;
+
48  static const bool is_bounded = numeric_limits<double>::is_bounded;
+
49  static const bool is_modulo = numeric_limits<double>::is_modulo;
+
50 
+
51  static const bool traps = numeric_limits<double>::traps;
+
52  static const bool tinyness_before = numeric_limits<double>::tinyness_before;
+
53  static const float_round_style round_style =
+
54  numeric_limits<double>::round_style;
+
55  };
+
56 }
+
57 #endif
+ + + +
int min(const std::vector< int > &x)
Returns the minimum coefficient in the specified column vector.
Definition: min.hpp:20
+ + + + + +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+
static stan::math::fvar< T > signaling_NaN()
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2core_8hpp.html b/doc/api/html/fwd_2core_8hpp.html new file mode 100644 index 00000000000..8ad404bb03a --- /dev/null +++ b/doc/api/html/fwd_2core_8hpp.html @@ -0,0 +1,124 @@ + + + + + + +Stan Math Library: stan/math/fwd/core.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2core_8hpp_source.html b/doc/api/html/fwd_2core_8hpp_source.html new file mode 100644 index 00000000000..15db9f44fc7 --- /dev/null +++ b/doc/api/html/fwd_2core_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/core.hpp Source File + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2_eigen___num_traits_8hpp.html b/doc/api/html/fwd_2mat_2fun_2_eigen___num_traits_8hpp.html new file mode 100644 index 00000000000..4fc1477c3b9 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2_eigen___num_traits_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/Eigen_NumTraits.hpp File Reference + + + + + + + + + + +
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Eigen_NumTraits.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <limits>
+
+

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+ + + + + + + + +

+Classes

struct  Eigen::NumTraits< stan::math::fvar< T > >
 Numerical traits template override for Eigen for automatic gradient variables. More...
 
struct  Eigen::internal::significant_decimals_default_impl< stan::math::fvar< T >, false >
 Implemented this for printing to stream. More...
 
+ + + + + + + +

+Namespaces

 Eigen
 (Expert) Numerical traits for algorithmic differentiation variables.
 
 Eigen::internal
 (Expert) Product traits for algorithmic differentiation variables.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2mat_2fun_2_eigen___num_traits_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2_eigen___num_traits_8hpp_source.html new file mode 100644 index 00000000000..bc98e806edc --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2_eigen___num_traits_8hpp_source.html @@ -0,0 +1,187 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/Eigen_NumTraits.hpp Source File + + + + + + + + + + +
+
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Eigen_NumTraits.hpp
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1 #ifndef STAN_MATH_FWD_MAT_FUN_EIGEN_NUMTRAITS_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_EIGEN_NUMTRAITS_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <limits>
+
7 
+
8 namespace Eigen {
+
9 
+
14  template <typename T>
+
15  struct NumTraits<stan::math::fvar<T> > {
+ +
22 
+ +
29 
+ +
36 
+
43  inline static Real epsilon() {
+
44  return std::numeric_limits<double>::epsilon();
+
45  }
+
46 
+
50  inline static Real dummy_precision() {
+
51  return 1e-12; // copied from NumTraits.h values for double
+
52  }
+
53 
+
60  inline static Real highest() {
+ +
62  }
+
63 
+
70  inline static Real lowest() {
+ +
72  }
+
73 
+
78  enum {
+
79  IsInteger = 0,
+
80  IsSigned = 1,
+
81  IsComplex = 0,
+
82  RequireInitialization = 1,
+
83  ReadCost = 1,
+
84  AddCost = 1,
+
85  MulCost = 1,
+
86  HasFloatingPoint = 1
+
87  };
+
88  };
+
89 
+
90  namespace internal {
+
94  template<typename T>
+
95  struct significant_decimals_default_impl<stan::math::fvar<T>, false> {
+
96  static inline int run() {
+
97  using std::ceil;
+
98  using std::log;
+
99  return cast<double, int>
+
100  (ceil(-log(std::numeric_limits<double>::epsilon())
+
101  / log(10.0)));
+
102  }
+
103  };
+
104 
+
105  }
+
106 }
+
107 
+
108 #endif
+
stan::math::fvar< T > NonInteger
Non-integer valued variables.
+ + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
(Expert) Numerical traits for algorithmic differentiation variables.
+
static Real dummy_precision()
Return dummy precision.
+
static Real highest()
Return standard library's highest for double-precision floating point, std::numeric_limitsmax...
+
static Real lowest()
Return standard library's lowest for double-precision floating point, -std::numeric_limitsmax...
+
stan::math::fvar< T > Real
Real-valued variables.
+
stan::math::fvar< T > Nested
Nested variables.
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
static Real epsilon()
Return standard library's epsilon for double-precision floating point, std::numeric_limits::e...
+
fvar< T > ceil(const fvar< T > &x)
Definition: ceil.hpp:11
+ +
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2columns__dot__product_8hpp.html b/doc/api/html/fwd_2mat_2fun_2columns__dot__product_8hpp.html new file mode 100644 index 00000000000..6462d505ca3 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2columns__dot__product_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/columns_dot_product.hpp File Reference + + + + + + + + + + +
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template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, 1, C1 > stan::math::columns_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, 1, C1 > stan::math::columns_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, 1, C1 > stan::math::columns_dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2columns__dot__product_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2columns__dot__product_8hpp_source.html new file mode 100644 index 00000000000..52a91ce3f6b --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2columns__dot__product_8hpp_source.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/columns_dot_product.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_COLUMNS_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_COLUMNS_DOT_PRODUCT_HPP
+
3 
+ + + + + +
9 #include <stan/math/fwd/core.hpp>
+
10 #include <vector>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  template<typename T, int R1, int C1, int R2, int C2>
+
16  inline
+
17  Eigen::Matrix<fvar<T>, 1, C1>
+
18  columns_dot_product(const Eigen::Matrix<fvar<T>, R1, C1>& v1,
+
19  const Eigen::Matrix<fvar<T>, R2, C2>& v2) {
+
20  stan::math::check_matching_dims("columns_dot_product",
+
21  "v1", v1,
+
22  "v2", v2);
+
23  Eigen::Matrix<fvar<T>, 1, C1> ret(1, v1.cols());
+
24  for (size_type j = 0; j < v1.cols(); ++j) {
+
25  Eigen::Matrix<fvar<T>, R1, C1> ccol1 = v1.col(j);
+
26  Eigen::Matrix<fvar<T>, R2, C2> ccol2 = v2.col(j);
+
27  ret(0, j) = dot_product(ccol1, ccol2);
+
28  }
+
29  return ret;
+
30  }
+
31 
+
32  template<typename T, int R1, int C1, int R2, int C2>
+
33  inline
+
34  Eigen::Matrix<fvar<T>, 1, C1>
+
35  columns_dot_product(const Eigen::Matrix<fvar<T>, R1, C1>& v1,
+
36  const Eigen::Matrix<double, R2, C2>& v2) {
+
37  stan::math::check_matching_dims("columns_dot_product",
+
38  "v1", v1,
+
39  "v2", v2);
+
40  Eigen::Matrix<fvar<T>, 1, C1> ret(1, v1.cols());
+
41  for (size_type j = 0; j < v1.cols(); ++j) {
+
42  Eigen::Matrix<fvar<T>, R1, C1> ccol1 = v1.col(j);
+
43  Eigen::Matrix<double, R2, C2> ccol = v2.col(j);
+
44  ret(0, j) = dot_product(ccol1, ccol);
+
45  }
+
46  return ret;
+
47  }
+
48 
+
49  template<typename T, int R1, int C1, int R2, int C2>
+
50  inline
+
51  Eigen::Matrix<fvar<T>, 1, C1>
+
52  columns_dot_product(const Eigen::Matrix<double, R1, C1>& v1,
+
53  const Eigen::Matrix<fvar<T>, R2, C2>& v2) {
+
54  stan::math::check_matching_dims("columns_dot_product",
+
55  "v1", v1,
+
56  "v2", v2);
+
57  Eigen::Matrix<fvar<T>, 1, C1> ret(1, v1.cols());
+
58  for (size_type j = 0; j < v1.cols(); ++j) {
+
59  Eigen::Matrix<double, R1, C1> ccol = v1.col(j);
+
60  Eigen::Matrix<fvar<T>, R2, C2> ccol2 = v2.col(j);
+
61  ret(0, j) = dot_product(ccol, ccol2);
+
62  }
+
63  return ret;
+
64  }
+
65  }
+
66 }
+
67 #endif
+
Eigen::Matrix< fvar< T >, 1, C1 > columns_dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
+ + + + +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
+ +
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
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diff --git a/doc/api/html/fwd_2mat_2fun_2columns__dot__self_8hpp.html b/doc/api/html/fwd_2mat_2fun_2columns__dot__self_8hpp.html new file mode 100644 index 00000000000..9cb5ba012df --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2columns__dot__self_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/columns_dot_self.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, 1, C > stan::math::columns_dot_self (const Eigen::Matrix< fvar< T >, R, C > &x)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2columns__dot__self_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2columns__dot__self_8hpp_source.html new file mode 100644 index 00000000000..e7c7b84fa63 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2columns__dot__self_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/columns_dot_self.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_COLUMNS_DOT_SELF_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_COLUMNS_DOT_SELF_HPP
+
3 
+ + +
6 #include <stan/math/fwd/core.hpp>
+ +
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template<typename T, int R, int C>
+
14  inline Eigen::Matrix<fvar<T>, 1, C>
+
15  columns_dot_self(const Eigen::Matrix<fvar<T>, R, C>& x) {
+
16  Eigen::Matrix<fvar<T>, 1, C> ret(1, x.cols());
+
17  for (size_type i = 0; i < x.cols(); i++) {
+
18  Eigen::Matrix<fvar<T>, R, 1> ccol = x.col(i);
+
19  ret(0, i) = dot_self(ccol);
+
20  }
+
21  return ret;
+
22  }
+
23  }
+
24 }
+
25 #endif
+ + +
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ + +
Eigen::Matrix< fvar< T >, 1, C > columns_dot_self(const Eigen::Matrix< fvar< T >, R, C > &x)
+ + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2crossprod_8hpp.html b/doc/api/html/fwd_2mat_2fun_2crossprod_8hpp.html new file mode 100644 index 00000000000..7440ba5e018 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2crossprod_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/crossprod.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, C, C > stan::math::crossprod (const Eigen::Matrix< fvar< T >, R, C > &m)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2crossprod_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2crossprod_8hpp_source.html new file mode 100644 index 00000000000..edbabc9246d --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2crossprod_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/crossprod.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_CROSSPROD_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_CROSSPROD_HPP
+
3 
+ + + + + +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  template<typename T, int R, int C>
+
15  inline
+
16  Eigen::Matrix<fvar<T>, C, C>
+
17  crossprod(const Eigen::Matrix<fvar<T>, R, C>& m) {
+
18  if (m.rows() == 0)
+
19  return Eigen::Matrix<fvar<T>, C, C>(0, 0);
+ +
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ + +
Eigen::Matrix< fvar< T >, C, C > crossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: crossprod.hpp:17
+ +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
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diff --git a/doc/api/html/fwd_2mat_2fun_2determinant_8hpp.html b/doc/api/html/fwd_2mat_2fun_2determinant_8hpp.html new file mode 100644 index 00000000000..38010e31d4a --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2determinant_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/determinant.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
fvar< T > stan::math::determinant (const Eigen::Matrix< fvar< T >, R, C > &m)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2determinant_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2determinant_8hpp_source.html new file mode 100644 index 00000000000..b36a007efac --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2determinant_8hpp_source.html @@ -0,0 +1,174 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/determinant.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_DETERMINANT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_DETERMINANT_HPP
+
3 
+ +
5 #include <stan/math/fwd/core.hpp>
+ + + + + + +
12 #include <boost/math/tools/promotion.hpp>
+
13 #include <vector>
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  template<typename T, int R, int C>
+
19  inline
+
20  fvar<T>
+
21  determinant(const Eigen::Matrix<fvar<T>, R, C>& m) {
+ +
23  using stan::math::inverse;
+
24 
+
25  stan::math::check_square("determinant", "m", m);
+
26  Eigen::Matrix<T, R, C> m_deriv(m.rows(), m.cols());
+
27  Eigen::Matrix<T, R, C> m_val(m.rows(), m.cols());
+
28 
+
29  for (size_type i = 0; i < m.rows(); i++) {
+
30  for (size_type j = 0; j < m.cols(); j++) {
+
31  m_deriv(i, j) = m(i, j).d_;
+
32  m_val(i, j) = m(i, j).val_;
+
33  }
+
34  }
+
35 
+
36  Eigen::Matrix<T, R, C> m_inv = inverse<T>(m_val);
+
37  m_deriv = multiply(m_inv, m_deriv);
+
38 
+
39  fvar<T> result;
+
40  result.val_ = m_val.determinant();
+
41  result.d_ = result.val_ * m_deriv.trace();
+
42 
+
43  // FIXME: I think this will overcopy compared to retur fvar<T>(...);
+
44  return result;
+
45  }
+
46  }
+
47 }
+
48 #endif
+ + + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Eigen::Matrix< fvar< T >, R, C > inverse(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: inverse.hpp:20
+ +
fvar< T > determinant(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: determinant.hpp:21
+ + + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
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diff --git a/doc/api/html/fwd_2mat_2fun_2divide_8hpp.html b/doc/api/html/fwd_2mat_2fun_2divide_8hpp.html new file mode 100644 index 00000000000..614312cd797 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2divide_8hpp.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/divide.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::divide (const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::divide (const Eigen::Matrix< fvar< T >, R, C > &v, const double c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::divide (const Eigen::Matrix< double, R, C > &v, const fvar< T > &c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::operator/ (const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::operator/ (const Eigen::Matrix< fvar< T >, R, C > &v, const double c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::operator/ (const Eigen::Matrix< double, R, C > &v, const fvar< T > &c)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2divide_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2divide_8hpp_source.html new file mode 100644 index 00000000000..9d89f5b69f3 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2divide_8hpp_source.html @@ -0,0 +1,186 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/divide.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_DIVIDE_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_DIVIDE_HPP
+
3 
+ +
5 #include <stan/math/fwd/core.hpp>
+ + + +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  template <typename T, int R, int C>
+
15  inline Eigen::Matrix<fvar<T>, R, C>
+
16  divide(const Eigen::Matrix<fvar<T>, R, C>& v, const fvar<T>& c) {
+
17  Eigen::Matrix<fvar<T>, R, C> res(v.rows(), v.cols());
+
18  for (int i = 0; i < v.rows(); i++) {
+
19  for (int j = 0; j < v.cols(); j++)
+
20  res(i, j) = v(i, j) / c;
+
21  }
+
22  return res;
+
23  }
+
24 
+
25  template <typename T, int R, int C>
+
26  inline Eigen::Matrix<fvar<T>, R, C>
+
27  divide(const Eigen::Matrix<fvar<T>, R, C>& v, const double c) {
+
28  Eigen::Matrix<fvar<T>, R, C>
+
29  res(v.rows(), v.cols());
+
30  for (int i = 0; i < v.rows(); i++) {
+
31  for (int j = 0; j < v.cols(); j++)
+
32  res(i, j) = v(i, j) / c;
+
33  }
+
34  return res;
+
35  }
+
36 
+
37  template <typename T, int R, int C>
+
38  inline Eigen::Matrix<fvar<T>, R, C>
+
39  divide(const Eigen::Matrix<double, R, C>& v, const fvar<T>& c) {
+
40  Eigen::Matrix<fvar<T>, R, C>
+
41  res(v.rows(), v.cols());
+
42  for (int i = 0; i < v.rows(); i++) {
+
43  for (int j = 0; j < v.cols(); j++)
+
44  res(i, j) = v(i, j) / c;
+
45  }
+
46  return res;
+
47  }
+
48 
+
49  template <typename T, int R, int C>
+
50  inline Eigen::Matrix<fvar<T>, R, C>
+
51  operator/(const Eigen::Matrix<fvar<T>, R, C>& v, const fvar<T>& c) {
+
52  return divide(v, c);
+
53  }
+
54 
+
55  template <typename T, int R, int C>
+
56  inline Eigen::Matrix<fvar<T>, R, C>
+
57  operator/(const Eigen::Matrix<fvar<T>, R, C>& v, const double c) {
+
58  return divide(v, c);
+
59  }
+
60 
+
61  template <typename T, int R, int C>
+
62  inline Eigen::Matrix<fvar<T>, R, C>
+
63  operator/(const Eigen::Matrix<double, R, C>& v, const fvar<T>& c) {
+
64  return divide(v, c);
+
65  }
+
66  }
+
67 }
+
68 #endif
+ + +
fvar< T > operator/(const fvar< T > &x1, const fvar< T > &x2)
+ + +
Eigen::Matrix< fvar< T >, R, C > divide(const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
Definition: divide.hpp:16
+ + + +
+
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2dot__product_8hpp.html b/doc/api/html/fwd_2mat_2fun_2dot__product_8hpp.html new file mode 100644 index 00000000000..bde4e622213 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2dot__product_8hpp.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/dot_product.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
dot_product.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T , int R1, int C1, int R2, int C2>
fvar< T > stan::math::dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > stan::math::dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > stan::math::dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > stan::math::dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2, size_type &length)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > stan::math::dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2, size_type &length)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > stan::math::dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2, size_type &length)
 
template<typename T >
fvar< T > stan::math::dot_product (const std::vector< fvar< T > > &v1, const std::vector< fvar< T > > &v2)
 
template<typename T >
fvar< T > stan::math::dot_product (const std::vector< double > &v1, const std::vector< fvar< T > > &v2)
 
template<typename T >
fvar< T > stan::math::dot_product (const std::vector< fvar< T > > &v1, const std::vector< double > &v2)
 
template<typename T >
fvar< T > stan::math::dot_product (const std::vector< fvar< T > > &v1, const std::vector< fvar< T > > &v2, size_type &length)
 
template<typename T >
fvar< T > stan::math::dot_product (const std::vector< double > &v1, const std::vector< fvar< T > > &v2, size_type &length)
 
template<typename T >
fvar< T > stan::math::dot_product (const std::vector< fvar< T > > &v1, const std::vector< double > &v2, size_type &length)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2dot__product_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2dot__product_8hpp_source.html new file mode 100644 index 00000000000..6d90cfb5fe4 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2dot__product_8hpp_source.html @@ -0,0 +1,314 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/dot_product.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
dot_product.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_DOT_PRODUCT_HPP
+
3 
+ + + + + + +
10 #include <vector>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  // dot_product for vec (in matrix) * vec (in matrix);
+
16  // does all combos of row row, col col, row col, col row
+
17  template<typename T, int R1, int C1, int R2, int C2>
+
18  inline
+
19  fvar<T>
+
20  dot_product(const Eigen::Matrix<fvar<T>, R1, C1>& v1,
+
21  const Eigen::Matrix<fvar<T>, R2, C2>& v2) {
+
22  stan::math::check_vector("dot_product", "v1", v1);
+
23  stan::math::check_vector("dot_product", "v2", v2);
+ +
25  "v1", v1,
+
26  "v2", v2);
+
27 
+
28  fvar<T> ret(0, 0);
+
29  for (size_type i = 0; i < v1.size(); i++)
+
30  ret += v1(i) * v2(i);
+
31  return ret;
+
32  }
+
33 
+
34  template<typename T, int R1, int C1, int R2, int C2>
+
35  inline
+
36  fvar<T>
+
37  dot_product(const Eigen::Matrix<fvar<T>, R1, C1>& v1,
+
38  const Eigen::Matrix<double, R2, C2>& v2) {
+
39  stan::math::check_vector("dot_product", "v1", v1);
+
40  stan::math::check_vector("dot_product", "v2", v2);
+ +
42  "v1", v1,
+
43  "v2", v2);
+
44 
+
45  fvar<T> ret(0, 0);
+
46  for (size_type i = 0; i < v1.size(); i++)
+
47  ret += v1(i) * v2(i);
+
48  return ret;
+
49  }
+
50 
+
51  template<typename T, int R1, int C1, int R2, int C2>
+
52  inline
+
53  fvar<T>
+
54  dot_product(const Eigen::Matrix<double, R1, C1>& v1,
+
55  const Eigen::Matrix<fvar<T>, R2, C2>& v2) {
+
56  stan::math::check_vector("dot_product", "v1", v1);
+
57  stan::math::check_vector("dot_product", "v2", v2);
+ +
59  "v1", v1,
+
60  "v2", v2);
+
61 
+
62  fvar<T> ret(0, 0);
+
63  for (size_type i = 0; i < v1.size(); i++)
+
64  ret += v1(i) * v2(i);
+
65  return ret;
+
66  }
+
67 
+
68  template<typename T, int R1, int C1, int R2, int C2>
+
69  inline
+
70  fvar<T>
+
71  dot_product(const Eigen::Matrix<fvar<T>, R1, C1>& v1,
+
72  const Eigen::Matrix<fvar<T>, R2, C2>& v2,
+
73  size_type& length) {
+
74  stan::math::check_vector("dot_product", "v1", v1);
+
75  stan::math::check_vector("dot_product", "v2", v2);
+
76 
+
77  fvar<T> ret(0, 0);
+
78  for (size_type i = 0; i < length; i++)
+
79  ret += v1(i) * v2(i);
+
80  return ret;
+
81  }
+
82 
+
83  template<typename T, int R1, int C1, int R2, int C2>
+
84  inline
+
85  fvar<T>
+
86  dot_product(const Eigen::Matrix<fvar<T>, R1, C1>& v1,
+
87  const Eigen::Matrix<double, R2, C2>& v2,
+
88  size_type& length) {
+
89  stan::math::check_vector("dot_product", "v1", v1);
+
90  stan::math::check_vector("dot_product", "v2", v2);
+
91 
+
92  fvar<T> ret(0, 0);
+
93  for (size_type i = 0; i < length; i++)
+
94  ret += v1(i) * v2(i);
+
95  return ret;
+
96  }
+
97 
+
98  template<typename T, int R1, int C1, int R2, int C2>
+
99  inline
+
100  fvar<T>
+
101  dot_product(const Eigen::Matrix<double, R1, C1>& v1,
+
102  const Eigen::Matrix<fvar<T>, R2, C2>& v2,
+
103  size_type& length) {
+
104  stan::math::check_vector("dot_product", "v1", v1);
+
105  stan::math::check_vector("dot_product", "v2", v2);
+
106 
+
107  fvar<T> ret(0, 0);
+
108  for (size_type i = 0; i < length; i++)
+
109  ret += v1(i) * v2(i);
+
110  return ret;
+
111  }
+
112 
+
113  template<typename T>
+
114  inline
+
115  fvar<T>
+
116  dot_product(const std::vector<fvar<T> >& v1,
+
117  const std::vector<fvar<T> >& v2) {
+
118  stan::math::check_matching_sizes("dot_product",
+
119  "v1", v1,
+
120  "v2", v2);
+
121  fvar<T> ret(0, 0);
+
122  for (size_t i = 0; i < v1.size(); i++)
+
123  ret += v1.at(i) * v2.at(i);
+
124  return ret;
+
125  }
+
126 
+
127  template<typename T>
+
128  inline
+
129  fvar<T>
+
130  dot_product(const std::vector<double>& v1,
+
131  const std::vector<fvar<T> >& v2) {
+
132  stan::math::check_matching_sizes("dot_product",
+
133  "v1", v1,
+
134  "v2", v2);
+
135  fvar<T> ret(0, 0);
+
136  for (size_t i = 0; i < v1.size(); i++)
+
137  ret += v1.at(i) * v2.at(i);
+
138  return ret;
+
139  }
+
140 
+
141  template<typename T>
+
142  inline
+
143  fvar<T>
+
144  dot_product(const std::vector<fvar<T> >& v1,
+
145  const std::vector<double>& v2) {
+
146  stan::math::check_matching_sizes("dot_product",
+
147  "v1", v1,
+
148  "v2", v2);
+
149  fvar<T> ret(0, 0);
+
150  for (size_t i = 0; i < v1.size(); i++)
+
151  ret += v1.at(i) * v2.at(i);
+
152  return ret;
+
153  }
+
154 
+
155  template<typename T>
+
156  inline
+
157  fvar<T>
+
158  dot_product(const std::vector<fvar<T> >& v1,
+
159  const std::vector<fvar<T> >& v2,
+
160  size_type& length) {
+
161  fvar<T> ret(0, 0);
+
162  for (size_type i = 0; i < length; i++)
+
163  ret += v1.at(i) * v2.at(i);
+
164  return ret;
+
165  }
+
166 
+
167  template<typename T>
+
168  inline
+
169  fvar<T>
+
170  dot_product(const std::vector<double>& v1,
+
171  const std::vector<fvar<T> >& v2,
+
172  size_type& length) {
+
173  fvar<T> ret(0, 0);
+
174  for (size_type i = 0; i < length; i++)
+
175  ret += v1.at(i) * v2.at(i);
+
176  return ret;
+
177  }
+
178 
+
179  template<typename T>
+
180  inline
+
181  fvar<T>
+
182  dot_product(const std::vector<fvar<T> >& v1,
+
183  const std::vector<double>& v2,
+
184  size_type& length) {
+
185  fvar<T> ret(0, 0);
+
186  for (size_type i = 0; i < length; i++)
+
187  ret += v1.at(i) * v2.at(i);
+
188  return ret;
+
189  }
+
190  }
+
191 }
+
192 #endif
+ +
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ + + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2dot__self_8hpp.html b/doc/api/html/fwd_2mat_2fun_2dot__self_8hpp.html new file mode 100644 index 00000000000..cd8a2fd72bf --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2dot__self_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/dot_self.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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+ + +
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+ + +
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+ +
+
dot_self.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T , int R, int C>
fvar< T > stan::math::dot_self (const Eigen::Matrix< fvar< T >, R, C > &v)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2mat_2fun_2dot__self_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2dot__self_8hpp_source.html new file mode 100644 index 00000000000..07a8d0eaf60 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2dot__self_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/dot_self.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
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+ + +
+
+
+
dot_self.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_DOT_SELF_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_DOT_SELF_HPP
+
3 
+ + + +
7 #include <stan/math/fwd/core.hpp>
+ +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  template<typename T, int R, int C>
+
15  inline fvar<T>
+
16  dot_self(const Eigen::Matrix<fvar<T>, R, C>& v) {
+
17  stan::math::check_vector("dot_self",
+
18  "v", v);
+
19  return dot_product(v, v);
+
20  }
+
21  }
+
22 }
+
23 #endif
+ +
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ +
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+ +
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2inverse_8hpp.html b/doc/api/html/fwd_2mat_2fun_2inverse_8hpp.html new file mode 100644 index 00000000000..3cfeb3053c6 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2inverse_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/inverse.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+ + + + + + +
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+ + +
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+ +
+
inverse.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/multiply.hpp>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/fwd/mat/fun/to_fvar.hpp>
+#include <stan/math/fwd/mat/fun/multiply.hpp>
+#include <stan/math/prim/mat/fun/inverse.hpp>
+#include <stan/math/prim/mat/err/check_square.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::inverse (const Eigen::Matrix< fvar< T >, R, C > &m)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2mat_2fun_2inverse_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2inverse_8hpp_source.html new file mode 100644 index 00000000000..13ea497e4f9 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2inverse_8hpp_source.html @@ -0,0 +1,167 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/inverse.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+ + +
+
+
+
inverse.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_INVERSE_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_INVERSE_HPP
+
3 
+ + +
6 #include <stan/math/fwd/core.hpp>
+ + + + +
11 #include <boost/math/tools/promotion.hpp>
+
12 #include <vector>
+
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  template<typename T, int R, int C>
+
18  inline
+
19  Eigen::Matrix<fvar<T>, R, C>
+
20  inverse(const Eigen::Matrix<fvar<T>, R, C>& m) {
+ + +
23  using stan::math::inverse;
+
24  stan::math::check_square("inverse", "m", m);
+
25  Eigen::Matrix<T, R, C> m_deriv(m.rows(), m.cols());
+
26  Eigen::Matrix<T, R, C> m_inv(m.rows(), m.cols());
+
27 
+
28  for (size_type i = 0; i < m.rows(); i++) {
+
29  for (size_type j = 0; j < m.cols(); j++) {
+
30  m_inv(i, j) = m(i, j).val_;
+
31  m_deriv(i, j) = m(i, j).d_;
+
32  }
+
33  }
+
34 
+
35  m_inv = stan::math::inverse(m_inv);
+
36 
+
37  m_deriv = multiply(multiply(m_inv, m_deriv), m_inv);
+
38  m_deriv = -m_deriv;
+
39 
+
40  return to_fvar(m_inv, m_deriv);
+
41  }
+
42  }
+
43 }
+
44 #endif
+ + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Eigen::Matrix< fvar< T >, R, C > inverse(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: inverse.hpp:20
+ + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2log__determinant_8hpp.html b/doc/api/html/fwd_2mat_2fun_2log__determinant_8hpp.html new file mode 100644 index 00000000000..17351696d5b --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2log__determinant_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/log_determinant.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/fwd/mat/fun/typedefs.hpp>
+#include <stan/math/fwd/mat/fun/determinant.hpp>
+#include <stan/math/fwd/scal/fun/fabs.hpp>
+#include <stan/math/fwd/scal/fun/log.hpp>
+#include <stan/math/prim/mat/err/check_square.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <vector>
+
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template<typename T , int R, int C>
fvar< T > stan::math::log_determinant (const Eigen::Matrix< fvar< T >, R, C > &m)
 
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2log__determinant_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2log__determinant_8hpp_source.html new file mode 100644 index 00000000000..a3818cff63a --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2log__determinant_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/log_determinant.hpp Source File + + + + + + + + + + +
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log_determinant.hpp
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1 #ifndef STAN_MATH_FWD_MAT_FUN_LOG_DETERMINANT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_LOG_DETERMINANT_HPP
+
3 
+ +
5 #include <stan/math/fwd/core.hpp>
+ + + + + +
11 #include <boost/math/tools/promotion.hpp>
+
12 #include <vector>
+
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  template<typename T, int R, int C>
+
18  inline
+
19  fvar<T>
+
20  log_determinant(const Eigen::Matrix<fvar<T>, R, C>& m) {
+
21  stan::math::check_square("log_determinant", "m", m);
+
22 
+ +
24  }
+
25  }
+
26 }
+
27 #endif
+ + +
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
fvar< T > log_determinant(const Eigen::Matrix< fvar< T >, R, C > &m)
+ +
fvar< T > determinant(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: determinant.hpp:21
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2mat_2fun_2log__softmax_8hpp.html b/doc/api/html/fwd_2mat_2fun_2log__softmax_8hpp.html new file mode 100644 index 00000000000..29997ec8028 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2log__softmax_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/log_softmax.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > stan::math::log_softmax (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
 
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2log__softmax_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2log__softmax_8hpp_source.html new file mode 100644 index 00000000000..ed604b5b9ea --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2log__softmax_8hpp_source.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/log_softmax.hpp Source File + + + + + + + + + + +
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log_softmax.hpp
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1 #ifndef STAN_MATH_FWD_MAT_FUN_LOG_SOFTMAX_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_LOG_SOFTMAX_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + + +
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1>
+
16  log_softmax(const Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1>& alpha) {
+
17  using stan::math::softmax;
+ +
19  using Eigen::Matrix;
+
20  using Eigen::Dynamic;
+
21 
+
22  Matrix<T, Dynamic, 1> alpha_t(alpha.size());
+
23  for (int k = 0; k < alpha.size(); ++k)
+
24  alpha_t(k) = alpha(k).val_;
+
25 
+
26  Matrix<T, Dynamic, 1> softmax_alpha_t = softmax(alpha_t);
+
27  Matrix<T, Dynamic, 1> log_softmax_alpha_t = log_softmax(alpha_t);
+
28 
+
29  Matrix<fvar<T>, Dynamic, 1> log_softmax_alpha(alpha.size());
+
30  for (int k = 0; k < alpha.size(); ++k) {
+
31  log_softmax_alpha(k).val_ = log_softmax_alpha_t(k);
+
32  log_softmax_alpha(k).d_ = 0;
+
33  }
+
34 
+
35  // for each input position
+
36  for (int m = 0; m < alpha.size(); ++m) {
+
37  T negative_alpha_m_d_times_softmax_alpha_t_m
+
38  = - alpha(m).d_ * softmax_alpha_t(m);
+
39  // for each output position
+
40  for (int k = 0; k < alpha.size(); ++k) {
+
41  // chain from input to output
+
42  if (m == k)
+
43  log_softmax_alpha(k).d_
+
44  += alpha(m).d_
+
45  + negative_alpha_m_d_times_softmax_alpha_t_m;
+
46  else
+
47  log_softmax_alpha(k).d_
+
48  += negative_alpha_m_d_times_softmax_alpha_t_m;
+
49  }
+
50  }
+
51 
+
52  return log_softmax_alpha;
+
53  }
+
54 
+
55 
+
56  }
+
57 }
+
58 
+
59 #endif
+ +
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > softmax(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
Definition: softmax.hpp:14
+ + +
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > log_softmax(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
Definition: log_softmax.hpp:16
+ + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2log__sum__exp_8hpp.html b/doc/api/html/fwd_2mat_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..fa5d7aff5a8 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
fvar< T > stan::math::log_sum_exp (const Eigen::Matrix< fvar< T >, R, C > &v)
 
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..374b4a72ba2 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
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log_sum_exp.hpp
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1 #ifndef STAN_MATH_FWD_MAT_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_LOG_SUM_EXP_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + + +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15  // FIXME: cut-and-paste from fwd/log_sum_exp.hpp; should
+
16  // be able to generalize
+
17  template <typename T, int R, int C>
+
18  fvar<T>
+
19  log_sum_exp(const Eigen::Matrix<fvar<T>, R, C>& v) {
+ + +
22  using stan::math::exp;
+
23  using std::exp;
+
24  using stan::math::log;
+
25  using std::log;
+
26 
+
27  Eigen::Matrix<T, 1, Eigen::Dynamic> vals(v.size());
+
28  for (int i = 0; i < v.size(); ++i)
+
29  vals[i] = v(i).val_;
+
30  T deriv(0.0);
+
31  T denominator(0.0);
+
32  for (int i = 0; i < v.size(); ++i) {
+
33  T exp_vi = exp(vals[i]);
+
34  denominator += exp_vi;
+
35  deriv += v(i).d_ * exp_vi;
+
36  }
+
37  return fvar<T>(log_sum_exp(vals), deriv / denominator);
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+ + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__left_8hpp.html b/doc/api/html/fwd_2mat_2fun_2mdivide__left_8hpp.html new file mode 100644 index 00000000000..64a6dfed470 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__left_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_left.hpp File Reference + + + + + + + + + + +
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template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::mdivide_left (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::mdivide_left (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::mdivide_left (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__left_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2mdivide__left_8hpp_source.html new file mode 100644 index 00000000000..d2b570adff5 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__left_8hpp_source.html @@ -0,0 +1,254 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_left.hpp Source File + + + + + + + + + + +
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mdivide_left.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_MDIVIDE_LEFT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_MDIVIDE_LEFT_HPP
+
3 
+ + + +
7 #include <stan/math/fwd/core.hpp>
+ + + + + + + + +
16 #include <vector>
+
17 
+
18 namespace stan {
+
19  namespace math {
+
20 
+
21  template <typename T, int R1, int C1, int R2, int C2>
+
22  inline
+
23  Eigen::Matrix<fvar<T>, R1, C2>
+
24  mdivide_left(const Eigen::Matrix<fvar<T>, R1, C1> &A,
+
25  const Eigen::Matrix<fvar<T>, R2, C2> &b) {
+ + +
28  stan::math::check_square("mdivide_left", "A", A);
+
29  stan::math::check_multiplicable("mdivide_left",
+
30  "A", A,
+
31  "b", b);
+
32 
+
33  Eigen::Matrix<T, R1, C2> inv_A_mult_b(A.rows(), b.cols());
+
34  Eigen::Matrix<T, R1, C2> inv_A_mult_deriv_b(A.rows(), b.cols());
+
35  Eigen::Matrix<T, R1, C1> inv_A_mult_deriv_A(A.rows(), A.cols());
+
36  Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
+
37  Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
+
38  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
39  Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
+
40 
+
41  for (int j = 0; j < A.cols(); j++) {
+
42  for (int i = 0; i < A.rows(); i++) {
+
43  val_A(i, j) = A(i, j).val_;
+
44  deriv_A(i, j) = A(i, j).d_;
+
45  }
+
46  }
+
47 
+
48  for (int j = 0; j < b.cols(); j++) {
+
49  for (int i = 0; i < b.rows(); i++) {
+
50  val_b(i, j) = b(i, j).val_;
+
51  deriv_b(i, j) = b(i, j).d_;
+
52  }
+
53  }
+
54 
+
55  inv_A_mult_b = mdivide_left(val_A, val_b);
+
56  inv_A_mult_deriv_b = mdivide_left(val_A, deriv_b);
+
57  inv_A_mult_deriv_A = mdivide_left(val_A, deriv_A);
+
58 
+
59  Eigen::Matrix<T, R1, C2> deriv(A.rows(), b.cols());
+
60  deriv = inv_A_mult_deriv_b - multiply(inv_A_mult_deriv_A, inv_A_mult_b);
+
61 
+
62  return stan::math::to_fvar(inv_A_mult_b, deriv);
+
63  }
+
64 
+
65  template <typename T, int R1, int C1, int R2, int C2>
+
66  inline
+
67  Eigen::Matrix<fvar<T>, R1, C2>
+
68  mdivide_left(const Eigen::Matrix<double, R1, C1> &A,
+
69  const Eigen::Matrix<fvar<T>, R2, C2> &b) {
+ + +
72  stan::math::check_square("mdivide_left", "A", A);
+
73  stan::math::check_multiplicable("mdivide_left",
+
74  "A", A,
+
75  "b", b);
+
76 
+
77  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
78  Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
+
79 
+
80  for (int j = 0; j < b.cols(); j++) {
+
81  for (int i = 0; i < b.rows(); i++) {
+
82  val_b(i, j) = b(i, j).val_;
+
83  deriv_b(i, j) = b(i, j).d_;
+
84  }
+
85  }
+
86 
+
87  return stan::math::to_fvar(mdivide_left(A, val_b),
+
88  mdivide_left(A, deriv_b));
+
89  }
+
90 
+
91  template <typename T, int R1, int C1, int R2, int C2>
+
92  inline
+
93  Eigen::Matrix<fvar<T>, R1, C2>
+
94  mdivide_left(const Eigen::Matrix<fvar<T>, R1, C1> &A,
+
95  const Eigen::Matrix<double, R2, C2> &b) {
+ + +
98  stan::math::check_square("mdivide_left", "A", A);
+
99  stan::math::check_multiplicable("mdivide_left",
+
100  "A", A,
+
101  "b", b);
+
102 
+
103  Eigen::Matrix<T, R1, C2>
+
104  inv_A_mult_b(A.rows(), b.cols());
+
105  Eigen::Matrix<T, R1, C1> inv_A_mult_deriv_A(A.rows(), A.cols());
+
106  Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
+
107  Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
+
108 
+
109  for (int j = 0; j < A.cols(); j++) {
+
110  for (int i = 0; i < A.rows(); i++) {
+
111  val_A(i, j) = A(i, j).val_;
+
112  deriv_A(i, j) = A(i, j).d_;
+
113  }
+
114  }
+
115 
+
116  inv_A_mult_b = mdivide_left(val_A, b);
+
117  inv_A_mult_deriv_A = mdivide_left(val_A, deriv_A);
+
118 
+
119  Eigen::Matrix<T, R1, C2> deriv(A.rows(), b.cols());
+
120  deriv = -multiply(inv_A_mult_deriv_A, inv_A_mult_b);
+
121 
+
122  return stan::math::to_fvar(inv_A_mult_b, deriv);
+
123  }
+
124  }
+
125 }
+
126 #endif
+
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_left(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ + + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__left__ldlt_8hpp.html b/doc/api/html/fwd_2mat_2fun_2mdivide__left__ldlt_8hpp.html new file mode 100644 index 00000000000..b2d7406e43d --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__left__ldlt_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_left_ldlt.hpp File Reference + + + + + + + + + + +
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template<int R1, int C1, int R2, int C2, typename T2 >
Eigen::Matrix< fvar< T2 >, R1, C2 > stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html new file mode 100644 index 00000000000..bb0f5690385 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_left_ldlt.hpp Source File + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
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mdivide_left_ldlt.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_MDIVIDE_LEFT_LDLT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_MDIVIDE_LEFT_LDLT_HPP
+
3 
+ + + + + + +
10 #include <boost/math/tools/promotion.hpp>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
23  template <int R1, int C1, int R2, int C2, typename T2>
+
24  inline Eigen::Matrix<fvar<T2>, R1, C2>
+ +
26  const Eigen::Matrix<fvar<T2>, R2, C2> &b) {
+
27  stan::math::check_multiplicable("mdivide_left_ldlt",
+
28  "A", A,
+
29  "b", b);
+
30 
+
31  Eigen::Matrix<T2, R2, C2> b_val(b.rows(), b.cols());
+
32  Eigen::Matrix<T2, R2, C2> b_der(b.rows(), b.cols());
+
33  for (int i = 0; i < b.rows(); i++)
+
34  for (int j = 0; j < b.cols(); j++) {
+
35  b_val(i, j) = b(i, j).val_;
+
36  b_der(i, j) = b(i, j).d_;
+
37  }
+
38 
+
39  return to_fvar(mdivide_left_ldlt(A, b_val),
+
40  mdivide_left_ldlt(A, b_der));
+
41  }
+
42  }
+
43 }
+
44 #endif
+ + + +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+ + +
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt(const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
Returns the solution of the system Ax=b given an LDLT_factor of A.
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__left__tri__low_8hpp.html b/doc/api/html/fwd_2mat_2fun_2mdivide__left__tri__low_8hpp.html new file mode 100644 index 00000000000..5c0627c14cd --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__left__tri__low_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_left_tri_low.hpp File Reference + + + + + + + + + + +
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template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::mdivide_left_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::mdivide_left_tri_low (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::mdivide_left_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__left__tri__low_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2mdivide__left__tri__low_8hpp_source.html new file mode 100644 index 00000000000..be467816741 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__left__tri__low_8hpp_source.html @@ -0,0 +1,270 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_left_tri_low.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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mdivide_left_tri_low.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_MDIVIDE_LEFT_TRI_LOW_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_MDIVIDE_LEFT_TRI_LOW_HPP
+
3 
+ + + + + + + + +
12 #include <stan/math/fwd/core.hpp>
+ +
14 #include <vector>
+
15 
+
16 namespace stan {
+
17  namespace math {
+
18 
+
19  template<typename T, int R1, int C1, int R2, int C2>
+
20  inline
+
21  Eigen::Matrix<fvar<T>, R1, C1>
+
22  mdivide_left_tri_low(const Eigen::Matrix<fvar<T>, R1, C1>& A,
+
23  const Eigen::Matrix<fvar<T>, R2, C2>& b) {
+ + +
26  stan::math::check_square("mdivide_left_tri_low", "A", A);
+
27  stan::math::check_multiplicable("mdivide_left_tri_low",
+
28  "A", A,
+
29  "b", b);
+
30 
+
31  Eigen::Matrix<T, R1, C2> inv_A_mult_b(A.rows(), b.cols());
+
32  Eigen::Matrix<T, R1, C2> inv_A_mult_deriv_b(A.rows(), b.cols());
+
33  Eigen::Matrix<T, R1, C1> inv_A_mult_deriv_A(A.rows(), A.cols());
+
34  Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
+
35  Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
+
36  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
37  Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
+
38  val_A.setZero();
+
39  deriv_A.setZero();
+
40 
+
41  for (size_type j = 0; j < A.cols(); j++) {
+
42  for (size_type i = j; i < A.rows(); i++) {
+
43  val_A(i, j) = A(i, j).val_;
+
44  deriv_A(i, j) = A(i, j).d_;
+
45  }
+
46  }
+
47 
+
48  for (size_type j = 0; j < b.cols(); j++) {
+
49  for (size_type i = 0; i < b.rows(); i++) {
+
50  val_b(i, j) = b(i, j).val_;
+
51  deriv_b(i, j) = b(i, j).d_;
+
52  }
+
53  }
+
54 
+
55  inv_A_mult_b = mdivide_left(val_A, val_b);
+
56  inv_A_mult_deriv_b = mdivide_left(val_A, deriv_b);
+
57  inv_A_mult_deriv_A = mdivide_left(val_A, deriv_A);
+
58 
+
59  Eigen::Matrix<T, R1, C2> deriv(A.rows(), b.cols());
+
60  deriv = inv_A_mult_deriv_b - multiply(inv_A_mult_deriv_A, inv_A_mult_b);
+
61 
+
62  return stan::math::to_fvar(inv_A_mult_b, deriv);
+
63  }
+
64 
+
65  template<typename T, int R1, int C1, int R2, int C2>
+
66  inline
+
67  Eigen::Matrix<fvar<T>, R1, C1>
+
68  mdivide_left_tri_low(const Eigen::Matrix<double, R1, C1>& A,
+
69  const Eigen::Matrix<fvar<T>, R2, C2>& b) {
+ + +
72  stan::math::check_square("mdivide_left_tri_low", "A", A);
+
73  stan::math::check_multiplicable("mdivide_left_tri_low",
+
74  "A", A,
+
75  "b", b);
+
76 
+
77  Eigen::Matrix<T, R1, C2> inv_A_mult_b(A.rows(), b.cols());
+
78  Eigen::Matrix<T, R1, C2> inv_A_mult_deriv_b(A.rows(), b.cols());
+
79  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
80  Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
+
81  Eigen::Matrix<double, R1, C1> val_A(A.rows(), A.cols());
+
82  val_A.setZero();
+
83 
+
84  for (size_type j = 0; j < A.cols(); j++) {
+
85  for (size_type i = j; i < A.rows(); i++) {
+
86  val_A(i, j) = A(i, j);
+
87  }
+
88  }
+
89 
+
90  for (size_type j = 0; j < b.cols(); j++) {
+
91  for (size_type i = 0; i < b.rows(); i++) {
+
92  val_b(i, j) = b(i, j).val_;
+
93  deriv_b(i, j) = b(i, j).d_;
+
94  }
+
95  }
+
96 
+
97  inv_A_mult_b = mdivide_left(val_A, val_b);
+
98  inv_A_mult_deriv_b = mdivide_left(val_A, deriv_b);
+
99 
+
100  Eigen::Matrix<T, R1, C2> deriv(A.rows(), b.cols());
+
101  deriv = inv_A_mult_deriv_b;
+
102 
+
103  return stan::math::to_fvar(inv_A_mult_b, deriv);
+
104  }
+
105 
+
106  template<typename T, int R1, int C1, int R2, int C2>
+
107  inline
+
108  Eigen::Matrix<fvar<T>, R1, C1>
+
109  mdivide_left_tri_low(const Eigen::Matrix<fvar<T>, R1, C1>& A,
+
110  const Eigen::Matrix<double, R2, C2>& b) {
+
111  using stan::math::multiply;
+ +
113  stan::math::check_square("mdivide_left_tri_low", "A", A);
+
114  stan::math::check_multiplicable("mdivide_left_tri_low",
+
115  "A", A,
+
116  "b", b);
+
117 
+
118  Eigen::Matrix<T, R1, C2> inv_A_mult_b(A.rows(), b.cols());
+
119  Eigen::Matrix<T, R1, C1> inv_A_mult_deriv_A(A.rows(), A.cols());
+
120  Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
+
121  Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
+
122  val_A.setZero();
+
123  deriv_A.setZero();
+
124 
+
125  for (size_type j = 0; j < A.cols(); j++) {
+
126  for (size_type i = j; i < A.rows(); i++) {
+
127  val_A(i, j) = A(i, j).val_;
+
128  deriv_A(i, j) = A(i, j).d_;
+
129  }
+
130  }
+
131 
+
132  inv_A_mult_b = mdivide_left(val_A, b);
+
133  inv_A_mult_deriv_A = mdivide_left(val_A, deriv_A);
+
134 
+
135  Eigen::Matrix<T, R1, C2> deriv(A.rows(), b.cols());
+
136  deriv = -multiply(inv_A_mult_deriv_A, inv_A_mult_b);
+
137 
+
138  return stan::math::to_fvar(inv_A_mult_b, deriv);
+
139  }
+
140  }
+
141 }
+
142 #endif
+
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_left(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + +
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_left_tri_low(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + + + + +
+
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__right_8hpp.html b/doc/api/html/fwd_2mat_2fun_2mdivide__right_8hpp.html new file mode 100644 index 00000000000..aefe9b6a123 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__right_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_right.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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 Matrices and templated mathematical functions.
 
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template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::mdivide_right (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::mdivide_right (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::mdivide_right (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__right_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2mdivide__right_8hpp_source.html new file mode 100644 index 00000000000..c00b194e862 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__right_8hpp_source.html @@ -0,0 +1,255 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_right.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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mdivide_right.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_MDIVIDE_RIGHT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_MDIVIDE_RIGHT_HPP
+
3 
+ + + + + +
9 #include <stan/math/fwd/core.hpp>
+ + + + + + +
16 #include <vector>
+
17 
+
18 namespace stan {
+
19  namespace math {
+
20 
+
21  template <typename T, int R1, int C1, int R2, int C2>
+
22  inline
+
23  Eigen::Matrix<fvar<T>, R1, C2>
+
24  mdivide_right(const Eigen::Matrix<fvar<T>, R1, C1> &A,
+
25  const Eigen::Matrix<fvar<T>, R2, C2> &b) {
+ + +
28  stan::math::check_square("mdivide_right", "b", b);
+
29  stan::math::check_multiplicable("mdivide_right",
+
30  "A", A,
+
31  "b", b);
+
32 
+
33  Eigen::Matrix<T, R1, C2> A_mult_inv_b(A.rows(), b.cols());
+
34  Eigen::Matrix<T, R1, C2> deriv_A_mult_inv_b(A.rows(), b.cols());
+
35  Eigen::Matrix<T, R2, C2> deriv_b_mult_inv_b(b.rows(), b.cols());
+
36  Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
+
37  Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
+
38  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
39  Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
+
40 
+
41  for (int j = 0; j < A.cols(); j++) {
+
42  for (int i = 0; i < A.rows(); i++) {
+
43  val_A(i, j) = A(i, j).val_;
+
44  deriv_A(i, j) = A(i, j).d_;
+
45  }
+
46  }
+
47 
+
48  for (int j = 0; j < b.cols(); j++) {
+
49  for (int i = 0; i < b.rows(); i++) {
+
50  val_b(i, j) = b(i, j).val_;
+
51  deriv_b(i, j) = b(i, j).d_;
+
52  }
+
53  }
+
54 
+
55  A_mult_inv_b = mdivide_right(val_A, val_b);
+
56  deriv_A_mult_inv_b = mdivide_right(deriv_A, val_b);
+
57  deriv_b_mult_inv_b = mdivide_right(deriv_b, val_b);
+
58 
+
59  Eigen::Matrix<T, R1, C2> deriv(A.rows(), b.cols());
+
60  deriv = deriv_A_mult_inv_b - multiply(A_mult_inv_b, deriv_b_mult_inv_b);
+
61 
+
62  return stan::math::to_fvar(A_mult_inv_b, deriv);
+
63  }
+
64 
+
65  template <typename T, int R1, int C1, int R2, int C2>
+
66  inline
+
67  Eigen::Matrix<fvar<T>, R1, C2>
+
68  mdivide_right(const Eigen::Matrix<fvar<T>, R1, C1> &A,
+
69  const Eigen::Matrix<double, R2, C2> &b) {
+ + +
72  stan::math::check_square("mdivide_right", "b", b);
+
73  stan::math::check_multiplicable("mdivide_right",
+
74  "A", A,
+
75  "b", b);
+
76 
+
77  Eigen::Matrix<T, R2, C2> deriv_b_mult_inv_b(b.rows(), b.cols());
+
78  Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
+
79  Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
+
80 
+
81  for (int j = 0; j < A.cols(); j++) {
+
82  for (int i = 0; i < A.rows(); i++) {
+
83  val_A(i, j) = A(i, j).val_;
+
84  deriv_A(i, j) = A(i, j).d_;
+
85  }
+
86  }
+
87 
+
88  return stan::math::to_fvar(mdivide_right(val_A, b),
+
89  mdivide_right(deriv_A, b));
+
90  }
+
91 
+
92  template <typename T, int R1, int C1, int R2, int C2>
+
93  inline
+
94  Eigen::Matrix<fvar<T>, R1, C2>
+
95  mdivide_right(const Eigen::Matrix<double, R1, C1> &A,
+
96  const Eigen::Matrix<fvar<T>, R2, C2> &b) {
+ + +
99  stan::math::check_square("mdivide_right", "b", b);
+
100  stan::math::check_multiplicable("mdivide_right",
+
101  "A", A,
+
102  "b", b);
+
103  Eigen::Matrix<T, R1, C2>
+
104  A_mult_inv_b(A.rows(), b.cols());
+
105  Eigen::Matrix<T, R2, C2> deriv_b_mult_inv_b(b.rows(), b.cols());
+
106  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
107  Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
+
108 
+
109  for (int j = 0; j < b.cols(); j++) {
+
110  for (int i = 0; i < b.rows(); i++) {
+
111  val_b(i, j) = b(i, j).val_;
+
112  deriv_b(i, j) = b(i, j).d_;
+
113  }
+
114  }
+
115 
+
116  A_mult_inv_b = mdivide_right(A, val_b);
+
117  deriv_b_mult_inv_b = mdivide_right(deriv_b, val_b);
+
118 
+
119  Eigen::Matrix<T, R1, C2>
+
120  deriv(A.rows(), b.cols());
+
121  deriv = -multiply(A_mult_inv_b, deriv_b_mult_inv_b);
+
122 
+
123  return stan::math::to_fvar(A_mult_inv_b, deriv);
+
124  }
+
125  }
+
126 }
+
127 #endif
+ + + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + + + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_right(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ + + + +
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__right__tri__low_8hpp.html b/doc/api/html/fwd_2mat_2fun_2mdivide__right__tri__low_8hpp.html new file mode 100644 index 00000000000..73211347634 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__right__tri__low_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_right_tri_low.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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mdivide_right_tri_low.hpp File Reference
+
+
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Go to the source code of this file.

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+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::mdivide_right_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::mdivide_right_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::mdivide_right_tri_low (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2mdivide__right__tri__low_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2mdivide__right__tri__low_8hpp_source.html new file mode 100644 index 00000000000..15586276bd4 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2mdivide__right__tri__low_8hpp_source.html @@ -0,0 +1,266 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/mdivide_right_tri_low.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
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+
+
+
mdivide_right_tri_low.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_MDIVIDE_RIGHT_TRI_LOW_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_MDIVIDE_RIGHT_TRI_LOW_HPP
+
3 
+ + + + + + + + + +
13 #include <stan/math/fwd/core.hpp>
+
14 #include <vector>
+
15 
+
16 namespace stan {
+
17  namespace math {
+
18 
+
19  template<typename T, int R1, int C1, int R2, int C2>
+
20  inline
+
21  Eigen::Matrix<fvar<T>, R1, C1>
+
22  mdivide_right_tri_low(const Eigen::Matrix<fvar<T>, R1, C1>& A,
+
23  const Eigen::Matrix<fvar<T>, R2, C2>& b) {
+ + +
26  stan::math::check_square("mdivide_right_tri_low", "b", b);
+
27  stan::math::check_multiplicable("mdivide_right_tri_low",
+
28  "A", A,
+
29  "b", b);
+
30 
+
31  Eigen::Matrix<T, R1, C2> A_mult_inv_b(A.rows(), b.cols());
+
32  Eigen::Matrix<T, R1, C2> deriv_A_mult_inv_b(A.rows(), b.cols());
+
33  Eigen::Matrix<T, R2, C2> deriv_b_mult_inv_b(b.rows(), b.cols());
+
34  Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
+
35  Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
+
36  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
37  Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
+
38  val_b.setZero();
+
39  deriv_b.setZero();
+
40 
+
41  for (size_type j = 0; j < A.cols(); j++) {
+
42  for (size_type i = 0; i < A.rows(); i++) {
+
43  val_A(i, j) = A(i, j).val_;
+
44  deriv_A(i, j) = A(i, j).d_;
+
45  }
+
46  }
+
47 
+
48  for (size_type j = 0; j < b.cols(); j++) {
+
49  for (size_type i = j; i < b.rows(); i++) {
+
50  val_b(i, j) = b(i, j).val_;
+
51  deriv_b(i, j) = b(i, j).d_;
+
52  }
+
53  }
+
54 
+
55  A_mult_inv_b = mdivide_right(val_A, val_b);
+
56  deriv_A_mult_inv_b = mdivide_right(deriv_A, val_b);
+
57  deriv_b_mult_inv_b = mdivide_right(deriv_b, val_b);
+
58 
+
59  Eigen::Matrix<T, R1, C2> deriv(A.rows(), b.cols());
+
60  deriv = deriv_A_mult_inv_b - multiply(A_mult_inv_b, deriv_b_mult_inv_b);
+
61 
+
62  return stan::math::to_fvar(A_mult_inv_b, deriv);
+
63  }
+
64 
+
65  template <typename T, int R1, int C1, int R2, int C2>
+
66  inline
+
67  Eigen::Matrix<fvar<T>, R1, C2>
+
68  mdivide_right_tri_low(const Eigen::Matrix<fvar<T>, R1, C1> &A,
+
69  const Eigen::Matrix<double, R2, C2> &b) {
+ + +
72  stan::math::check_square("mdivide_right_tri_low", "b", b);
+
73  stan::math::check_multiplicable("mdivide_right_tri_low",
+
74  "A", A,
+
75  "b", b);
+
76 
+
77  Eigen::Matrix<T, R2, C2> deriv_b_mult_inv_b(b.rows(), b.cols());
+
78  Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
+
79  Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
+
80  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
81  val_b.setZero();
+
82 
+
83  for (int j = 0; j < A.cols(); j++) {
+
84  for (int i = 0; i < A.rows(); i++) {
+
85  val_A(i, j) = A(i, j).val_;
+
86  deriv_A(i, j) = A(i, j).d_;
+
87  }
+
88  }
+
89 
+
90  for (size_type j = 0; j < b.cols(); j++) {
+
91  for (size_type i = j; i < b.rows(); i++) {
+
92  val_b(i, j) = b(i, j);
+
93  }
+
94  }
+
95 
+
96  return stan::math::to_fvar(mdivide_right(val_A, val_b),
+
97  mdivide_right(deriv_A, val_b));
+
98  }
+
99 
+
100  template <typename T, int R1, int C1, int R2, int C2>
+
101  inline
+
102  Eigen::Matrix<fvar<T>, R1, C2>
+
103  mdivide_right_tri_low(const Eigen::Matrix<double, R1, C1> &A,
+
104  const Eigen::Matrix<fvar<T>, R2, C2> &b) {
+
105  using stan::math::multiply;
+ +
107  stan::math::check_square("mdivide_right_tri_low", "b", b);
+
108  stan::math::check_multiplicable("mdivide_right_tri_low",
+
109  "A", A,
+
110  "b", b);
+
111 
+
112  Eigen::Matrix<T, R1, C2>
+
113  A_mult_inv_b(A.rows(), b.cols());
+
114  Eigen::Matrix<T, R2, C2> deriv_b_mult_inv_b(b.rows(), b.cols());
+
115  Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
+
116  Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
+
117  val_b.setZero();
+
118  deriv_b.setZero();
+
119 
+
120  for (int j = 0; j < b.cols(); j++) {
+
121  for (int i = j; i < b.rows(); i++) {
+
122  val_b(i, j) = b(i, j).val_;
+
123  deriv_b(i, j) = b(i, j).d_;
+
124  }
+
125  }
+
126 
+
127  A_mult_inv_b = mdivide_right(A, val_b);
+
128  deriv_b_mult_inv_b = mdivide_right(deriv_b, val_b);
+
129 
+
130  Eigen::Matrix<T, R1, C2>
+
131  deriv(A.rows(), b.cols());
+
132  deriv = -multiply(A_mult_inv_b, deriv_b_mult_inv_b);
+
133 
+
134  return stan::math::to_fvar(A_mult_inv_b, deriv);
+
135  }
+
136  }
+
137 }
+
138 #endif
+ + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_right(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ + + +
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_right_tri_low(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2mat_2fun_2multiply_8hpp.html b/doc/api/html/fwd_2mat_2fun_2multiply_8hpp.html new file mode 100644 index 00000000000..5cd5efae08b --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2multiply_8hpp.html @@ -0,0 +1,172 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/multiply.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
multiply.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/typedefs.hpp>
+#include <stan/math/prim/mat/err/check_multiplicable.hpp>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/fwd/mat/fun/typedefs.hpp>
+#include <stan/math/fwd/mat/fun/to_fvar.hpp>
+#include <stan/math/fwd/mat/fun/dot_product.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <stdexcept>
+#include <vector>
+
+

Go to the source code of this file.

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 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::multiply (const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
 
template<typename T , int R2, int C2>
Eigen::Matrix< fvar< T >, R2, C2 > stan::math::multiply (const Eigen::Matrix< fvar< T >, R2, C2 > &m, const double c)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::multiply (const Eigen::Matrix< double, R1, C1 > &m, const fvar< T > &c)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::multiply (const fvar< T > &c, const Eigen::Matrix< fvar< T >, R1, C1 > &m)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::multiply (const double c, const Eigen::Matrix< fvar< T >, R1, C1 > &m)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > stan::math::multiply (const fvar< T > &c, const Eigen::Matrix< double, R1, C1 > &m)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::multiply (const Eigen::Matrix< fvar< T >, R1, C1 > &m1, const Eigen::Matrix< fvar< T >, R2, C2 > &m2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::multiply (const Eigen::Matrix< fvar< T >, R1, C1 > &m1, const Eigen::Matrix< double, R2, C2 > &m2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > stan::math::multiply (const Eigen::Matrix< double, R1, C1 > &m1, const Eigen::Matrix< fvar< T >, R2, C2 > &m2)
 
template<typename T , int C1, int R2>
fvar< T > stan::math::multiply (const Eigen::Matrix< fvar< T >, 1, C1 > &rv, const Eigen::Matrix< fvar< T >, R2, 1 > &v)
 
template<typename T , int C1, int R2>
fvar< T > stan::math::multiply (const Eigen::Matrix< fvar< T >, 1, C1 > &rv, const Eigen::Matrix< double, R2, 1 > &v)
 
template<typename T , int C1, int R2>
fvar< T > stan::math::multiply (const Eigen::Matrix< double, 1, C1 > &rv, const Eigen::Matrix< fvar< T >, R2, 1 > &v)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2multiply_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2multiply_8hpp_source.html new file mode 100644 index 00000000000..f5405357f67 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2multiply_8hpp_source.html @@ -0,0 +1,289 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/multiply.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
multiply.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_MULTIPLY_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_MULTIPLY_HPP
+
3 
+ + + +
7 #include <stan/math/fwd/core.hpp>
+ + + +
11 #include <boost/math/tools/promotion.hpp>
+
12 #include <stdexcept>
+
13 #include <vector>
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  template<typename T, int R1, int C1>
+
19  inline
+
20  Eigen::Matrix<fvar<T>, R1, C1>
+
21  multiply(const Eigen::Matrix<fvar<T>, R1, C1>& m, const fvar<T>& c) {
+
22  Eigen::Matrix<fvar<T>, R1, C1> res(m.rows(), m.cols());
+
23  for (int i = 0; i < m.rows(); i++) {
+
24  for (int j = 0; j < m.cols(); j++)
+
25  res(i, j) = c * m(i, j);
+
26  }
+
27  return res;
+
28  }
+
29 
+
30  template<typename T, int R2, int C2>
+
31  inline
+
32  Eigen::Matrix<fvar<T>, R2, C2>
+
33  multiply(const Eigen::Matrix<fvar<T>, R2, C2>& m, const double c) {
+
34  Eigen::Matrix<fvar<T>, R2, C2> res(m.rows(), m.cols());
+
35  for (int i = 0; i < m.rows(); i++) {
+
36  for (int j = 0; j < m.cols(); j++)
+
37  res(i, j) = c * m(i, j);
+
38  }
+
39  return res;
+
40  }
+
41 
+
42  template<typename T, int R1, int C1>
+
43  inline
+
44  Eigen::Matrix<fvar<T>, R1, C1>
+
45  multiply(const Eigen::Matrix<double, R1, C1>& m, const fvar<T>& c) {
+
46  Eigen::Matrix<fvar<T>, R1, C1> res(m.rows(), m.cols());
+
47  for (int i = 0; i < m.rows(); i++) {
+
48  for (int j = 0; j < m.cols(); j++)
+
49  res(i, j) = c * m(i, j);
+
50  }
+
51  return res;
+
52  }
+
53 
+
54  template<typename T, int R1, int C1>
+
55  inline
+
56  Eigen::Matrix<fvar<T>, R1, C1>
+
57  multiply(const fvar<T>& c, const Eigen::Matrix<fvar<T>, R1, C1>& m) {
+
58  return multiply(m, c);
+
59  }
+
60 
+
61  template<typename T, int R1, int C1>
+
62  inline
+
63  Eigen::Matrix<fvar<T>, R1, C1>
+
64  multiply(const double c, const Eigen::Matrix<fvar<T>, R1, C1>& m) {
+
65  return multiply(m, c);
+
66  }
+
67 
+
68  template<typename T, int R1, int C1>
+
69  inline
+
70  Eigen::Matrix<fvar<T>, R1, C1>
+
71  multiply(const fvar<T>& c, const Eigen::Matrix<double, R1, C1>& m) {
+
72  return multiply(m, c);
+
73  }
+
74 
+
75  template<typename T, int R1, int C1, int R2, int C2>
+
76  inline
+
77  Eigen::Matrix<fvar<T>, R1, C2>
+
78  multiply(const Eigen::Matrix<fvar<T>, R1, C1>& m1,
+
79  const Eigen::Matrix<fvar<T>, R2, C2>& m2) {
+ +
81  "m1", m1,
+
82  "m2", m2);
+
83  Eigen::Matrix<fvar<T>, R1, C2> result(m1.rows(), m2.cols());
+
84  for (size_type i = 0; i < m1.rows(); i++) {
+
85  Eigen::Matrix<fvar<T>, 1, C1> crow = m1.row(i);
+
86  for (size_type j = 0; j < m2.cols(); j++) {
+
87  Eigen::Matrix<fvar<T>, R2, 1> ccol = m2.col(j);
+
88  result(i, j) = stan::math::dot_product(crow, ccol);
+
89  }
+
90  }
+
91  return result;
+
92  }
+
93 
+
94  template<typename T, int R1, int C1, int R2, int C2>
+
95  inline
+
96  Eigen::Matrix<fvar<T>, R1, C2>
+
97  multiply(const Eigen::Matrix<fvar<T>, R1, C1>& m1,
+
98  const Eigen::Matrix<double, R2, C2>& m2) {
+ +
100  "m1", m1,
+
101  "m2", m2);
+
102  Eigen::Matrix<fvar<T>, R1, C2> result(m1.rows(), m2.cols());
+
103  for (size_type i = 0; i < m1.rows(); i++) {
+
104  Eigen::Matrix<fvar<T>, 1, C1> crow = m1.row(i);
+
105  for (size_type j = 0; j < m2.cols(); j++) {
+
106  Eigen::Matrix<double, R2, 1> ccol = m2.col(j);
+
107  result(i, j) = stan::math::dot_product(crow, ccol);
+
108  }
+
109  }
+
110  return result;
+
111  }
+
112 
+
113  template<typename T, int R1, int C1, int R2, int C2>
+
114  inline
+
115  Eigen::Matrix<fvar<T>, R1, C2>
+
116  multiply(const Eigen::Matrix<double, R1, C1>& m1,
+
117  const Eigen::Matrix<fvar<T>, R2, C2>& m2) {
+ +
119  "m1", m1,
+
120  "m2", m2);
+
121  Eigen::Matrix<fvar<T>, R1, C2> result(m1.rows(), m2.cols());
+
122  for (size_type i = 0; i < m1.rows(); i++) {
+
123  Eigen::Matrix<double, 1, C1> crow = m1.row(i);
+
124  for (size_type j = 0; j < m2.cols(); j++) {
+
125  Eigen::Matrix<fvar<T>, R2, 1> ccol = m2.col(j);
+
126  result(i, j) = stan::math::dot_product(crow, ccol);
+
127  }
+
128  }
+
129  return result;
+
130  }
+
131 
+
132  template <typename T, int C1, int R2>
+
133  inline
+
134  fvar<T>
+
135  multiply(const Eigen::Matrix<fvar<T>, 1, C1>& rv,
+
136  const Eigen::Matrix<fvar<T>, R2, 1>& v) {
+
137  if (rv.size() != v.size())
+
138  throw std::domain_error("row vector and vector must be same length "
+
139  "in multiply");
+
140  return dot_product(rv, v);
+
141  }
+
142 
+
143  template <typename T, int C1, int R2>
+
144  inline
+
145  fvar<T>
+
146  multiply(const Eigen::Matrix<fvar<T>, 1, C1>& rv,
+
147  const Eigen::Matrix<double, R2, 1>& v) {
+
148  if (rv.size() != v.size())
+
149  throw std::domain_error("row vector and vector must be same length "
+
150  "in multiply");
+
151  return dot_product(rv, v);
+
152  }
+
153 
+
154  template <typename T, int C1, int R2>
+
155  inline
+
156  fvar<T>
+
157  multiply(const Eigen::Matrix<double, 1, C1>& rv,
+
158  const Eigen::Matrix<fvar<T>, R2, 1>& v) {
+
159  if (rv.size() != v.size())
+
160  throw std::domain_error("row vector and vector must be same length "
+
161  "in multiply");
+
162  return dot_product(rv, v);
+
163  }
+
164  }
+
165 }
+
166 #endif
+ + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html b/doc/api/html/fwd_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html new file mode 100644 index 00000000000..ae0cb33f867 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/multiply_lower_tri_self_transpose.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
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diff --git a/doc/api/html/fwd_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html new file mode 100644 index 00000000000..ce5e330ed45 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/multiply_lower_tri_self_transpose.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_MULTIPLY_LOWER_TRI_SELF_TRANSPOSE_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_MULTIPLY_LOWER_TRI_SELF_TRANSPOSE_HPP
+
3 
+ + + + + +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  template<typename T, int R, int C>
+
15  inline
+
16  Eigen::Matrix<fvar<T>, R, R>
+
17  multiply_lower_tri_self_transpose(const Eigen::Matrix<fvar<T>, R, C>& m) {
+
18  if (m.rows() == 0)
+
19  return Eigen::Matrix<fvar<T>, R, R>(0, 0);
+
20  Eigen::Matrix<fvar<T>, R, C> L(m.rows(), m.cols());
+
21  L.setZero();
+
22 
+
23  for (size_type i = 0; i < m.rows(); i++) {
+
24  for (size_type j = 0; (j < i + 1) && (j < m.cols()); j++)
+
25  L(i, j) = m(i, j);
+
26  }
+
27 
+ +
29  }
+
30 
+
31  }
+
32 }
+
33 #endif
+ + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ + +
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose(const Eigen::Matrix< fvar< T >, R, C > &m)
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+ + +
+
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2qr___q_8hpp.html b/doc/api/html/fwd_2mat_2fun_2qr___q_8hpp.html new file mode 100644 index 00000000000..f84a6babb05 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2qr___q_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/qr_Q.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > stan::math::qr_Q (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > &m)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2qr___q_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2qr___q_8hpp_source.html new file mode 100644 index 00000000000..12ca2f17297 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2qr___q_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/qr_Q.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_QR_Q_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_QR_Q_HPP
+
3 
+ + + +
7 #include <stan/math/fwd/core.hpp>
+
8 #include <Eigen/QR>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  Eigen::Matrix<fvar<T>, Eigen::Dynamic, Eigen::Dynamic>
+
15  qr_Q(const Eigen::Matrix<fvar<T>, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
16  typedef Eigen::Matrix<fvar<T>, Eigen::Dynamic, Eigen::Dynamic>
+
17  matrix_fwd_t;
+
18  stan::math::check_nonzero_size("qr_Q", "m", m);
+
19  stan::math::check_greater_or_equal("qr_Q", "m.rows()", m.rows(),
+
20  m.cols());
+
21  Eigen::HouseholderQR< matrix_fwd_t > qr(m.rows(), m.cols());
+
22  qr.compute(m);
+
23  matrix_fwd_t Q = qr.householderQ();
+
24  for (int i = 0; i < m.cols(); i++)
+
25  if (qr.matrixQR()(i, i) < 0.0)
+
26  Q.col(i) *= -1.0;
+
27  return Q;
+
28  }
+
29  }
+
30 }
+
31 #endif
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+ + +
Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > qr_Q(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > &m)
Definition: qr_Q.hpp:15
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
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diff --git a/doc/api/html/fwd_2mat_2fun_2qr___r_8hpp.html b/doc/api/html/fwd_2mat_2fun_2qr___r_8hpp.html new file mode 100644 index 00000000000..d096ada197d --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2qr___r_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/qr_R.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > stan::math::qr_R (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > &m)
 
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2qr___r_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2qr___r_8hpp_source.html new file mode 100644 index 00000000000..c90b8872537 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2qr___r_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/qr_R.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_QR_R_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_QR_R_HPP
+
3 
+ + + +
7 #include <stan/math/fwd/core.hpp>
+
8 #include <Eigen/QR>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  Eigen::Matrix<fvar<T>, Eigen::Dynamic, Eigen::Dynamic>
+
15  qr_R(const Eigen::Matrix<fvar<T>, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
16  typedef Eigen::Matrix<fvar<T>, Eigen::Dynamic, Eigen::Dynamic>
+
17  matrix_fwd_t;
+
18  stan::math::check_nonzero_size("qr_R", "m", m);
+
19  stan::math::check_greater_or_equal("qr_R", "m.rows()", m.rows(),
+
20  m.cols());
+
21  Eigen::HouseholderQR< matrix_fwd_t > qr(m.rows(), m.cols());
+
22  qr.compute(m);
+
23  matrix_fwd_t R = qr.matrixQR().topLeftCorner(m.rows(), m.cols());
+
24  for (int i = 0; i < R.rows(); i++) {
+
25  for (int j = 0; j < i; j++)
+
26  R(i, j) = 0.0;
+
27  if (i < R.cols() && R(i, i) < 0.0)
+
28  R.row(i) *= -1.0;
+
29  }
+
30  return R;
+
31  }
+
32  }
+
33 }
+
34 #endif
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+ +
Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > qr_R(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > &m)
Definition: qr_R.hpp:15
+ +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
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diff --git a/doc/api/html/fwd_2mat_2fun_2quad__form__sym_8hpp.html b/doc/api/html/fwd_2mat_2fun_2quad__form__sym_8hpp.html new file mode 100644 index 00000000000..73d5b67d0ae --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2quad__form__sym_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/quad_form_sym.hpp File Reference + + + + + + + + + + +
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template<int RA, int CA, int RB, int CB, typename T >
Eigen::Matrix< fvar< T >, CB, CB > stan::math::quad_form_sym (const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
 
template<int RA, int CA, int RB, typename T >
fvar< T > stan::math::quad_form_sym (const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, 1 > &B)
 
template<int RA, int CA, int RB, int CB, typename T >
Eigen::Matrix< fvar< T >, CB, CB > stan::math::quad_form_sym (const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
 
template<int RA, int CA, int RB, typename T >
fvar< T > stan::math::quad_form_sym (const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, 1 > &B)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2quad__form__sym_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2quad__form__sym_8hpp_source.html new file mode 100644 index 00000000000..4f266dff275 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2quad__form__sym_8hpp_source.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/quad_form_sym.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_QUAD_FORM_SYM_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_QUAD_FORM_SYM_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template<int RA, int CA, int RB, int CB, typename T>
+
13  inline Eigen::Matrix<fvar<T>, CB, CB>
+
14  quad_form_sym(const Eigen::Matrix<fvar<T>, RA, CA>& A,
+
15  const Eigen::Matrix<double, RB, CB>& B) {
+
16  check_square("quad_form_sym", "A", A);
+
17  check_multiplicable("quad_form_sym",
+
18  "A", A,
+
19  "B", B);
+
20  check_symmetric("quad_form_sym", "A", A);
+
21  Eigen::Matrix<fvar<T>, CB, CB>
+
22  ret(multiply(transpose(B), multiply(A, B)));
+
23  return T(0.5) * (ret + transpose(ret));
+
24  }
+
25 
+
26  template<int RA, int CA, int RB, typename T>
+
27  inline fvar<T>
+
28  quad_form_sym(const Eigen::Matrix<fvar<T>, RA, CA>& A,
+
29  const Eigen::Matrix<double, RB, 1>& B) {
+
30  check_square("quad_form_sym", "A", A);
+
31  check_multiplicable("quad_form_sym",
+
32  "A", A,
+
33  "B", B);
+
34  check_symmetric("quad_form_sym", "A", A);
+
35  return dot_product(B, multiply(A, B));
+
36  }
+
37  template<int RA, int CA, int RB, int CB, typename T>
+
38  inline Eigen::Matrix<fvar<T>, CB, CB>
+
39  quad_form_sym(const Eigen::Matrix<double, RA, CA>& A,
+
40  const Eigen::Matrix<fvar<T>, RB, CB>& B) {
+
41  check_square("quad_form_sym", "A", A);
+
42  check_multiplicable("quad_form_sym",
+
43  "A", A,
+
44  "B", B);
+
45  check_symmetric("quad_form_sym", "A", A);
+
46  Eigen::Matrix<fvar<T>, CB, CB>
+
47  ret(multiply(transpose(B), multiply(A, B)));
+
48  return T(0.5) * (ret + transpose(ret));
+
49  }
+
50 
+
51  template<int RA, int CA, int RB, typename T>
+
52  inline fvar<T>
+
53  quad_form_sym(const Eigen::Matrix<double, RA, CA>& A,
+
54  const Eigen::Matrix<fvar<T>, RB, 1>& B) {
+
55  check_square("quad_form_sym", "A", A);
+
56  check_multiplicable("quad_form_sym",
+
57  "A", A,
+
58  "B", B);
+
59  check_symmetric("quad_form_sym", "A", A);
+
60  return dot_product(B, multiply(A, B));
+
61  }
+
62  }
+
63 }
+
64 
+
65 #endif
+
66 
+ + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+
Eigen::Matrix< fvar< T >, CB, CB > quad_form_sym(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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diff --git a/doc/api/html/fwd_2mat_2fun_2rows__dot__product_8hpp.html b/doc/api/html/fwd_2mat_2fun_2rows__dot__product_8hpp.html new file mode 100644 index 00000000000..dd3b2b0de9f --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2rows__dot__product_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/rows_dot_product.hpp File Reference + + + + + + + + + + +
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template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, 1 > stan::math::rows_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, 1 > stan::math::rows_dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, 1 > stan::math::rows_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2rows__dot__product_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2rows__dot__product_8hpp_source.html new file mode 100644 index 00000000000..d596e3fc42c --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2rows__dot__product_8hpp_source.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/rows_dot_product.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_ROWS_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_ROWS_DOT_PRODUCT_HPP
+
3 
+ + + + + +
9 #include <stan/math/fwd/core.hpp>
+
10 #include <vector>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  template<typename T, int R1, int C1, int R2, int C2>
+
16  inline
+
17  Eigen::Matrix<fvar<T>, R1, 1>
+
18  rows_dot_product(const Eigen::Matrix<fvar<T>, R1, C1>& v1,
+
19  const Eigen::Matrix<fvar<T>, R2, C2>& v2) {
+
20  stan::math::check_matching_dims("rows_dot_product",
+
21  "v1", v1,
+
22  "v2", v2);
+
23  Eigen::Matrix<fvar<T>, R1, 1> ret(v1.rows(), 1);
+
24  for (size_type j = 0; j < v1.rows(); ++j) {
+
25  Eigen::Matrix<fvar<T>, R1, C1> crow1 = v1.row(j);
+
26  Eigen::Matrix<fvar<T>, R2, C2> crow2 = v2.row(j);
+
27  ret(j, 0) = dot_product(crow1, crow2);
+
28  }
+
29  return ret;
+
30  }
+
31 
+
32  template<typename T, int R1, int C1, int R2, int C2>
+
33  inline
+
34  Eigen::Matrix<fvar<T>, R1, 1>
+
35  rows_dot_product(const Eigen::Matrix<double, R1, C1>& v1,
+
36  const Eigen::Matrix<fvar<T>, R2, C2>& v2) {
+
37  stan::math::check_matching_dims("rows_dot_product",
+
38  "v1", v1,
+
39  "v2", v2);
+
40  Eigen::Matrix<fvar<T>, R1, 1> ret(v1.rows(), 1);
+
41  for (size_type j = 0; j < v1.rows(); ++j) {
+
42  Eigen::Matrix<double, R1, C1> crow = v1.row(j);
+
43  Eigen::Matrix<fvar<T>, R2, C2> crow2 = v2.row(j);
+
44  ret(j, 0) = dot_product(crow, crow2);
+
45  }
+
46  return ret;
+
47  }
+
48 
+
49  template<typename T, int R1, int C1, int R2, int C2>
+
50  inline
+
51  Eigen::Matrix<fvar<T>, R1, 1>
+
52  rows_dot_product(const Eigen::Matrix<fvar<T>, R1, C1>& v1,
+
53  const Eigen::Matrix<double, R2, C2>& v2) {
+
54  stan::math::check_matching_dims("rows_dot_product",
+
55  "v1", v1,
+
56  "v2", v2);
+
57  Eigen::Matrix<fvar<T>, R1, 1> ret(v1.rows(), 1);
+
58  for (size_type j = 0; j < v1.rows(); ++j) {
+
59  Eigen::Matrix<fvar<T>, R1, C1> crow1 = v1.row(j);
+
60  Eigen::Matrix<double, R2, C2> crow = v2.row(j);
+
61  ret(j, 0) = dot_product(crow1, crow);
+
62  }
+
63  return ret;
+
64  }
+
65  }
+
66 }
+
67 #endif
+ + + + +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
+ +
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ +
Eigen::Matrix< fvar< T >, R1, 1 > rows_dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
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diff --git a/doc/api/html/fwd_2mat_2fun_2rows__dot__self_8hpp.html b/doc/api/html/fwd_2mat_2fun_2rows__dot__self_8hpp.html new file mode 100644 index 00000000000..633ad4082e9 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2rows__dot__self_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/rows_dot_self.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, 1 > stan::math::rows_dot_self (const Eigen::Matrix< fvar< T >, R, C > &x)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2rows__dot__self_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2rows__dot__self_8hpp_source.html new file mode 100644 index 00000000000..2cf0395387f --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2rows__dot__self_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/rows_dot_self.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_ROWS_DOT_SELF_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_ROWS_DOT_SELF_HPP
+
3 
+ + +
6 #include <stan/math/fwd/core.hpp>
+ +
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template<typename T, int R, int C>
+
14  inline Eigen::Matrix<fvar<T>, R, 1>
+
15  rows_dot_self(const Eigen::Matrix<fvar<T>, R, C>& x) {
+
16  Eigen::Matrix<fvar<T>, R, 1> ret(x.rows(), 1);
+
17  for (size_type i = 0; i < x.rows(); i++) {
+
18  Eigen::Matrix<fvar<T>, 1, C> crow = x.row(i);
+
19  ret(i, 0) = dot_self(crow);
+
20  }
+
21  return ret;
+
22  }
+
23  }
+
24 }
+
25 #endif
+ + +
Eigen::Matrix< fvar< T >, R, 1 > rows_dot_self(const Eigen::Matrix< fvar< T >, R, C > &x)
+
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
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diff --git a/doc/api/html/fwd_2mat_2fun_2softmax_8hpp.html b/doc/api/html/fwd_2mat_2fun_2softmax_8hpp.html new file mode 100644 index 00000000000..a3085cfbae4 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2softmax_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/softmax.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > stan::math::softmax (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2softmax_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2softmax_8hpp_source.html new file mode 100644 index 00000000000..509b5a4d2b3 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2softmax_8hpp_source.html @@ -0,0 +1,173 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/softmax.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_SOFTMAX_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_SOFTMAX_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1>
+
14  softmax(const Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1>& alpha) {
+
15  using stan::math::softmax;
+
16  using Eigen::Matrix;
+
17  using Eigen::Dynamic;
+
18 
+
19  Matrix<T, Dynamic, 1> alpha_t(alpha.size());
+
20  for (int k = 0; k < alpha.size(); ++k)
+
21  alpha_t(k) = alpha(k).val_;
+
22 
+
23  Matrix<T, Dynamic, 1> softmax_alpha_t = softmax(alpha_t);
+
24 
+
25  Matrix<fvar<T>, Dynamic, 1> softmax_alpha(alpha.size());
+
26  for (int k = 0; k < alpha.size(); ++k) {
+
27  softmax_alpha(k).val_ = softmax_alpha_t(k);
+
28  softmax_alpha(k).d_ = 0;
+
29  }
+
30 
+
31  // for each input position
+
32  for (int m = 0; m < alpha.size(); ++m) {
+
33  // for each output position
+
34  T negative_alpha_m_d_times_softmax_alpha_t_m
+
35  = - alpha(m).d_ * softmax_alpha_t(m);
+
36  for (int k = 0; k < alpha.size(); ++k) {
+
37  // chain from input to output
+
38  if (m == k) {
+
39  softmax_alpha(k).d_
+
40  += softmax_alpha_t(k)
+
41  * (alpha(m).d_
+
42  + negative_alpha_m_d_times_softmax_alpha_t_m);
+
43  } else {
+
44  softmax_alpha(k).d_
+
45  += negative_alpha_m_d_times_softmax_alpha_t_m
+
46  * softmax_alpha_t(k);
+
47  }
+
48  }
+
49  }
+
50 
+
51  return softmax_alpha;
+
52  }
+
53 
+
54 
+
55  }
+
56 }
+
57 
+
58 #endif
+ +
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > softmax(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
Definition: softmax.hpp:14
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diff --git a/doc/api/html/fwd_2mat_2fun_2sort__asc_8hpp.html b/doc/api/html/fwd_2mat_2fun_2sort__asc_8hpp.html new file mode 100644 index 00000000000..920e0e27f15 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2sort__asc_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/sort_asc.hpp File Reference + + + + + + + + + + +
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#include <stan/math/fwd/core.hpp>
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+#include <algorithm>
+#include <functional>
+#include <vector>
+
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template<typename T >
std::vector< fvar< T > > stan::math::sort_asc (std::vector< fvar< T > > xs)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::sort_asc (Eigen::Matrix< fvar< T >, R, C > xs)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2sort__asc_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2sort__asc_8hpp_source.html new file mode 100644 index 00000000000..d70c8406ceb --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2sort__asc_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/sort_asc.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_SORT_ASC_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_SORT_ASC_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <algorithm> // std::sort
+
7 #include <functional> // std::greater
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  template <typename T>
+
15  inline
+
16  std::vector< fvar<T> >
+
17  sort_asc(std::vector< fvar<T> > xs) {
+
18  std::sort(xs.begin(), xs.end());
+
19  return xs;
+
20  }
+
21 
+
22  template <typename T, int R, int C>
+
23  inline
+
24  typename Eigen::Matrix<fvar<T>, R, C>
+
25  sort_asc(Eigen::Matrix<fvar<T>, R, C> xs) {
+
26  std::sort(xs.data(), xs.data()+xs.size());
+
27  return xs;
+
28  }
+
29 
+
30  }
+
31 }
+
32 #endif
+ + + +
std::vector< fvar< T > > sort_asc(std::vector< fvar< T > > xs)
Definition: sort_asc.hpp:17
+ +
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diff --git a/doc/api/html/fwd_2mat_2fun_2sort__desc_8hpp.html b/doc/api/html/fwd_2mat_2fun_2sort__desc_8hpp.html new file mode 100644 index 00000000000..ece9ec5adcb --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2sort__desc_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/sort_desc.hpp File Reference + + + + + + + + + + +
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#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <algorithm>
+#include <functional>
+#include <vector>
+
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template<typename T >
std::vector< fvar< T > > stan::math::sort_desc (std::vector< fvar< T > > xs)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::sort_desc (Eigen::Matrix< fvar< T >, R, C > xs)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2sort__desc_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2sort__desc_8hpp_source.html new file mode 100644 index 00000000000..4e8a7cb0909 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2sort__desc_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/sort_desc.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_SORT_DESC_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_SORT_DESC_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <algorithm> // std::sort
+
7 #include <functional> // std::greater
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  template <typename T>
+
15  inline
+
16  std::vector< fvar<T> >
+
17  sort_desc(std::vector< fvar<T> > xs) {
+
18  std::sort(xs.begin(), xs.end(), std::greater< fvar<T> >());
+
19  return xs;
+
20  }
+
21 
+
22  template <typename T, int R, int C>
+
23  inline
+
24  typename Eigen::Matrix<fvar<T>, R, C>
+
25  sort_desc(Eigen::Matrix<fvar<T>, R, C> xs) {
+
26  std::sort(xs.data(), xs.data()+xs.size(), std::greater< fvar<T> >());
+
27  return xs;
+
28  }
+
29 
+
30  }
+
31 }
+
32 #endif
+ +
std::vector< fvar< T > > sort_desc(std::vector< fvar< T > > xs)
Definition: sort_desc.hpp:17
+ + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2sum_8hpp.html b/doc/api/html/fwd_2mat_2fun_2sum_8hpp.html new file mode 100644 index 00000000000..b17b94824f6 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2sum_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/sum.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
fvar< T > stan::math::sum (const Eigen::Matrix< fvar< T >, R, C > &m)
 Return the sum of the entries of the specified matrix. More...
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2sum_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2sum_8hpp_source.html new file mode 100644 index 00000000000..dc98b4d116a --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2sum_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/sum.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_SUM_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_SUM_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
20  template <typename T, int R, int C>
+
21  inline fvar<T> sum(const Eigen::Matrix<fvar<T>, R, C>& m) {
+
22  using stan::math::sum;
+
23  if (m.size() == 0)
+
24  return 0.0;
+
25  Eigen::Matrix<T, Eigen::Dynamic, 1> vals(m.size());
+
26  Eigen::Matrix<T, Eigen::Dynamic, 1> tans(m.size());
+
27  for (int i = 0; i < m.size(); ++i) {
+
28  vals(i) = m(i).val();
+
29  tans(i) = m(i).tangent();
+
30  }
+
31  return fvar<T>(sum(vals), sum(tans));
+
32  }
+
33 
+
34  }
+
35 }
+
36 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + + + + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2tcrossprod_8hpp.html b/doc/api/html/fwd_2mat_2fun_2tcrossprod_8hpp.html new file mode 100644 index 00000000000..93373c8ec03 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2tcrossprod_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/tcrossprod.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, R > stan::math::tcrossprod (const Eigen::Matrix< fvar< T >, R, C > &m)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2tcrossprod_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2tcrossprod_8hpp_source.html new file mode 100644 index 00000000000..148ff8beca2 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2tcrossprod_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/tcrossprod.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_TCROSSPROD_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_TCROSSPROD_HPP
+
3 
+ + + + + +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  template<typename T, int R, int C>
+
15  inline
+
16  Eigen::Matrix<fvar<T>, R, R>
+
17  tcrossprod(const Eigen::Matrix<fvar<T>, R, C>& m) {
+
18  if (m.rows() == 0)
+
19  return Eigen::Matrix<fvar<T>, R, R>(0, 0);
+ +
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
Eigen::Matrix< fvar< T >, R, R > tcrossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: tcrossprod.hpp:17
+ + +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+ + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2trace__gen__quad__form_8hpp.html b/doc/api/html/fwd_2mat_2fun_2trace__gen__quad__form_8hpp.html new file mode 100644 index 00000000000..2aaf53fa24f --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2trace__gen__quad__form_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/trace_gen_quad_form.hpp File Reference + + + + + + + + + + +
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template<int RD, int CD, int RA, int CA, int RB, int CB, typename T >
fvar< T > stan::math::trace_gen_quad_form (const Eigen::Matrix< fvar< T >, RD, CD > &D, const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2trace__gen__quad__form_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2trace__gen__quad__form_8hpp_source.html new file mode 100644 index 00000000000..ee4d9df6e3d --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2trace__gen__quad__form_8hpp_source.html @@ -0,0 +1,159 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/trace_gen_quad_form.hpp Source File + + + + + + + + + + +
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trace_gen_quad_form.hpp
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1 #ifndef STAN_MATH_FWD_MAT_FUN_TRACE_GEN_QUAD_FORM_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_TRACE_GEN_QUAD_FORM_HPP
+
3 
+ + + + + + +
10 
+
11 namespace stan {
+
12  namespace math {
+
13  template<int RD, int CD, int RA, int CA, int RB, int CB, typename T>
+
14  inline fvar<T>
+
15  trace_gen_quad_form(const Eigen::Matrix<fvar<T>, RD, CD> &D,
+
16  const Eigen::Matrix<fvar<T>, RA, CA> &A,
+
17  const Eigen::Matrix<fvar<T>, RB, CB> &B) {
+ + +
20 
+
21  stan::math::check_square("trace_gen_quad_form", "A", A);
+
22  stan::math::check_square("trace_gen_quad_form", "D", D);
+
23  stan::math::check_multiplicable("trace_gen_quad_form",
+
24  "A", A,
+
25  "B", B);
+
26  stan::math::check_multiplicable("trace_gen_quad_form",
+
27  "B", B,
+
28  "D", D);
+ +
30  multiply(A, B)));
+
31  }
+
32  }
+
33 }
+
34 
+
35 #endif
+
36 
+ + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ + +
fvar< T > trace_gen_quad_form(const Eigen::Matrix< fvar< T >, RD, CD > &D, const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2trace__quad__form_8hpp.html b/doc/api/html/fwd_2mat_2fun_2trace__quad__form_8hpp.html new file mode 100644 index 00000000000..152d2a3803a --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2trace__quad__form_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/trace_quad_form.hpp File Reference + + + + + + + + + + +
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template<int RA, int CA, int RB, int CB, typename T >
fvar< T > stan::math::trace_quad_form (const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
 
template<int RA, int CA, int RB, int CB, typename T >
fvar< T > stan::math::trace_quad_form (const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
 
template<int RA, int CA, int RB, int CB, typename T >
fvar< T > stan::math::trace_quad_form (const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2trace__quad__form_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2trace__quad__form_8hpp_source.html new file mode 100644 index 00000000000..0c9afbb2730 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2trace__quad__form_8hpp_source.html @@ -0,0 +1,179 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/trace_quad_form.hpp Source File + + + + + + + + + + +
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trace_quad_form.hpp
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1 #ifndef STAN_MATH_FWD_MAT_FUN_TRACE_QUAD_FORM_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_TRACE_QUAD_FORM_HPP
+
3 
+
4 #include <boost/type_traits.hpp>
+ + + + + + +
11 #include <stan/math/fwd/core.hpp>
+
12 
+
13 namespace stan {
+
14  namespace math {
+
15 
+
16  template<int RA, int CA, int RB, int CB, typename T>
+
17  inline fvar<T>
+
18  trace_quad_form(const Eigen::Matrix<fvar<T>, RA, CA> &A,
+
19  const Eigen::Matrix<fvar<T>, RB, CB> &B) {
+
20  check_square("trace_quad_form", "A", A);
+
21  check_multiplicable("trace_quad_form",
+
22  "A", A,
+
23  "B", B);
+
24  return trace(multiply(transpose(B),
+
25  multiply(A, B)));
+
26  }
+
27 
+
28  template<int RA, int CA, int RB, int CB, typename T>
+
29  inline fvar<T>
+
30  trace_quad_form(const Eigen::Matrix<fvar<T>, RA, CA> &A,
+
31  const Eigen::Matrix<double, RB, CB> &B) {
+
32  check_square("trace_quad_form", "A", A);
+
33  check_multiplicable("trace_quad_form",
+
34  "A", A,
+
35  "B", B);
+
36  return trace(multiply(transpose(B),
+
37  multiply(A, B)));
+
38  }
+
39 
+
40  template<int RA, int CA, int RB, int CB, typename T>
+
41  inline fvar<T>
+
42  trace_quad_form(const Eigen::Matrix<double, RA, CA> &A,
+
43  const Eigen::Matrix<fvar<T>, RB, CB> &B) {
+
44  check_square("trace_quad_form", "A", A);
+
45  check_multiplicable("trace_quad_form",
+
46  "A", A,
+
47  "B", B);
+
48  return trace(multiply(transpose(B),
+
49  multiply(A, B)));
+
50  }
+
51  }
+
52 }
+
53 
+
54 #endif
+
55 
+ + + +
fvar< T > trace_quad_form(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+ +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ + + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
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diff --git a/doc/api/html/fwd_2mat_2fun_2typedefs_8hpp.html b/doc/api/html/fwd_2mat_2fun_2typedefs_8hpp.html new file mode 100644 index 00000000000..57bdb2e3041 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2typedefs_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/typedefs.hpp File Reference + + + + + + + + + + +
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+Typedefs

typedef Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index stan::math::size_type
 Type for sizes and indexes in an Eigen matrix with double e. More...
 
typedef Eigen::Matrix< fvar< double >, Eigen::Dynamic, Eigen::Dynamic > stan::math::matrix_fd
 
typedef Eigen::Matrix< fvar< fvar< double > >, Eigen::Dynamic, Eigen::Dynamic > stan::math::matrix_ffd
 
typedef Eigen::Matrix< fvar< double >, Eigen::Dynamic, 1 > stan::math::vector_fd
 
typedef Eigen::Matrix< fvar< fvar< double > >, Eigen::Dynamic, 1 > stan::math::vector_ffd
 
typedef Eigen::Matrix< fvar< double >, 1, Eigen::Dynamic > stan::math::row_vector_fd
 
typedef Eigen::Matrix< fvar< fvar< double > >, 1, Eigen::Dynamic > stan::math::row_vector_ffd
 
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diff --git a/doc/api/html/fwd_2mat_2fun_2typedefs_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2typedefs_8hpp_source.html new file mode 100644 index 00000000000..cffc7e5ae7c --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2typedefs_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/typedefs.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_TYPEDEFS_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_TYPEDEFS_HPP
+
3 
+ +
5 #include <stan/math/fwd/core.hpp>
+ +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  typedef
+
12  Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>::Index
+ +
14 
+
15  typedef
+
16  Eigen::Matrix<fvar<double>, Eigen::Dynamic, Eigen::Dynamic>
+ +
18 
+
19  typedef
+
20  Eigen::Matrix<fvar<fvar<double> >, Eigen::Dynamic, Eigen::Dynamic>
+ +
22 
+
23  typedef
+
24  Eigen::Matrix<fvar<double>, Eigen::Dynamic, 1>
+ +
26 
+
27  typedef
+
28  Eigen::Matrix<fvar<fvar<double> >, Eigen::Dynamic, 1>
+ +
30 
+
31  typedef
+
32  Eigen::Matrix<fvar<double>, 1, Eigen::Dynamic>
+ +
34 
+
35  typedef
+
36  Eigen::Matrix<fvar<fvar<double> >, 1, Eigen::Dynamic>
+ +
38 
+
39  }
+
40 }
+
41 #endif
+ +
Eigen::Matrix< fvar< double >, Eigen::Dynamic, 1 > vector_fd
Definition: typedefs.hpp:25
+ +
Eigen::Matrix< fvar< double >, Eigen::Dynamic, Eigen::Dynamic > matrix_fd
Definition: typedefs.hpp:17
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Eigen::Matrix< fvar< fvar< double > >, Eigen::Dynamic, Eigen::Dynamic > matrix_ffd
Definition: typedefs.hpp:21
+
Eigen::Matrix< fvar< double >, 1, Eigen::Dynamic > row_vector_fd
Definition: typedefs.hpp:33
+ +
Eigen::Matrix< fvar< fvar< double > >, 1, Eigen::Dynamic > row_vector_ffd
Definition: typedefs.hpp:37
+
Eigen::Matrix< fvar< fvar< double > >, Eigen::Dynamic, 1 > vector_ffd
Definition: typedefs.hpp:29
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2unit__vector__constrain_8hpp.html b/doc/api/html/fwd_2mat_2fun_2unit__vector__constrain_8hpp.html new file mode 100644 index 00000000000..15f3359e0d6 --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2unit__vector__constrain_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/unit_vector_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::unit_vector_constrain (const Eigen::Matrix< fvar< T >, R, C > &y)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::unit_vector_constrain (const Eigen::Matrix< fvar< T >, R, C > &y, fvar< T > &lp)
 
+
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diff --git a/doc/api/html/fwd_2mat_2fun_2unit__vector__constrain_8hpp_source.html b/doc/api/html/fwd_2mat_2fun_2unit__vector__constrain_8hpp_source.html new file mode 100644 index 00000000000..a8b583cc99f --- /dev/null +++ b/doc/api/html/fwd_2mat_2fun_2unit__vector__constrain_8hpp_source.html @@ -0,0 +1,189 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/unit_vector_constrain.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUN_UNIT_VECTOR_CONSTRAIN_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_UNIT_VECTOR_CONSTRAIN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + + + + + + + +
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  template <typename T, int R, int C>
+
19  inline Eigen::Matrix<fvar<T>, R, C>
+
20  unit_vector_constrain(const Eigen::Matrix<fvar<T>, R, C>& y) {
+
21  using std::sqrt;
+
22  using Eigen::Matrix;
+
23 
+
24  Matrix<T, R, C> y_t(y.size());
+
25  for (int k = 0; k < y.size(); ++k)
+
26  y_t.coeffRef(k) = y.coeff(k).val_;
+
27 
+
28  Matrix<T, R, C> unit_vector_y_t
+
29  = unit_vector_constrain(y_t);
+
30  Matrix<fvar<T>, R, C> unit_vector_y(y.size());
+
31  for (int k = 0; k < y.size(); ++k)
+
32  unit_vector_y.coeffRef(k).val_ = unit_vector_y_t.coeff(k);
+
33 
+
34  const T squared_norm = dot_self(y_t);
+
35  const T norm = sqrt(squared_norm);
+
36  const T inv_norm = inv(norm);
+
37  Matrix<T, Eigen::Dynamic, Eigen::Dynamic> J
+
38  = divide(tcrossprod(y_t), -norm * squared_norm);
+
39 
+
40  // for each input position
+
41  for (int m = 0; m < y.size(); ++m) {
+
42  J.coeffRef(m, m) += inv_norm;
+
43  // for each output position
+
44  for (int k = 0; k < y.size(); ++k) {
+
45  // chain from input to output
+
46  unit_vector_y.coeffRef(k).d_ = J.coeff(k, m);
+
47  }
+
48  }
+
49  return unit_vector_y;
+
50  }
+
51 
+
52  template <typename T, int R, int C>
+
53  inline Eigen::Matrix<fvar<T>, R, C>
+
54  unit_vector_constrain(const Eigen::Matrix<fvar<T>, R, C>& y, fvar<T>& lp) {
+
55  const fvar<T> squared_norm = dot_self(y);
+
56  lp -= 0.5 * squared_norm;
+
57  return unit_vector_constrain(y);
+
58  }
+
59 
+
60  }
+
61 }
+
62 #endif
+ + + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
Eigen::Matrix< fvar< T >, R, R > tcrossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: tcrossprod.hpp:17
+
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
Eigen::Matrix< fvar< T >, R, C > unit_vector_constrain(const Eigen::Matrix< fvar< T >, R, C > &y)
+ + +
Eigen::Matrix< fvar< T >, R, C > divide(const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
Definition: divide.hpp:16
+ + + + + +
fvar< T > inv(const fvar< T > &x)
Definition: inv.hpp:15
+
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diff --git a/doc/api/html/fwd_2mat_2functor_2gradient_8hpp.html b/doc/api/html/fwd_2mat_2functor_2gradient_8hpp.html new file mode 100644 index 00000000000..553449764c2 --- /dev/null +++ b/doc/api/html/fwd_2mat_2functor_2gradient_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/functor/gradient.hpp File Reference + + + + + + + + + + +
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template<typename T , typename F >
void stan::math::gradient (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &fx, Eigen::Matrix< T, Eigen::Dynamic, 1 > &grad_fx)
 Calculate the value and the gradient of the specified function at the specified argument. More...
 
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diff --git a/doc/api/html/fwd_2mat_2functor_2gradient_8hpp_source.html b/doc/api/html/fwd_2mat_2functor_2gradient_8hpp_source.html new file mode 100644 index 00000000000..5def7a6a241 --- /dev/null +++ b/doc/api/html/fwd_2mat_2functor_2gradient_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/functor/gradient.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_FUNCTOR_GRADIENT_HPP
+
2 #define STAN_MATH_FWD_MAT_FUNCTOR_GRADIENT_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
39  template <typename T, typename F>
+
40  void
+
41  gradient(const F& f,
+
42  const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
43  T& fx,
+
44  Eigen::Matrix<T, Eigen::Dynamic, 1>& grad_fx) {
+
45  Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1> x_fvar(x.size());
+
46  grad_fx.resize(x.size());
+
47  for (int i = 0; i < x.size(); ++i) {
+
48  for (int k = 0; k < x.size(); ++k)
+
49  x_fvar(k) = fvar<T>(x(k), k == i);
+
50  fvar<T> fx_fvar = f(x_fvar);
+
51  if (i == 0) fx = fx_fvar.val_;
+
52  grad_fx(i) = fx_fvar.d_;
+
53  }
+
54  }
+
55 
+
56  } // namespace math
+
57 } // namespace stan
+
58 #endif
+ + + + + +
void gradient(const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &fx, Eigen::Matrix< T, Eigen::Dynamic, 1 > &grad_fx)
Calculate the value and the gradient of the specified function at the specified argument.
Definition: gradient.hpp:41
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diff --git a/doc/api/html/fwd_2mat_2functor_2jacobian_8hpp.html b/doc/api/html/fwd_2mat_2functor_2jacobian_8hpp.html new file mode 100644 index 00000000000..b288db0f9ee --- /dev/null +++ b/doc/api/html/fwd_2mat_2functor_2jacobian_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/functor/jacobian.hpp File Reference + + + + + + + + + + +
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#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
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template<typename T , typename F >
void stan::math::jacobian (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, Eigen::Matrix< T, Eigen::Dynamic, 1 > &fx, Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &J)
 
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diff --git a/doc/api/html/fwd_2mat_2functor_2jacobian_8hpp_source.html b/doc/api/html/fwd_2mat_2functor_2jacobian_8hpp_source.html new file mode 100644 index 00000000000..00d241b3561 --- /dev/null +++ b/doc/api/html/fwd_2mat_2functor_2jacobian_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/functor/jacobian.hpp Source File + + + + + + + + + + +
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jacobian.hpp
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1 #ifndef STAN_MATH_FWD_MAT_FUNCTOR_JACOBIAN_HPP
+
2 #define STAN_MATH_FWD_MAT_FUNCTOR_JACOBIAN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T, typename F>
+
13  void
+
14  jacobian(const F& f,
+
15  const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
16  Eigen::Matrix<T, Eigen::Dynamic, 1>& fx,
+
17  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& J) {
+
18  using Eigen::Matrix;
+
19  using Eigen::Dynamic;
+
20  using stan::math::fvar;
+
21  Matrix<fvar<T>, Dynamic, 1> x_fvar(x.size());
+
22  for (int i = 0; i < x.size(); ++i) {
+
23  for (int k = 0; k < x.size(); ++k)
+
24  x_fvar(k) = fvar<T>(x(k), i == k);
+
25  Matrix<fvar<T>, Dynamic, 1> fx_fvar
+
26  = f(x_fvar);
+
27  if (i == 0) {
+
28  J.resize(fx_fvar.size(), x.size());
+
29  fx.resize(fx_fvar.size());
+
30  for (int k = 0; k < fx_fvar.size(); ++k)
+
31  fx(k) = fx_fvar(k).val_;
+
32  }
+
33  for (int k = 0; k < fx_fvar.size(); ++k) {
+
34  J(k, i) = fx_fvar(k).d_;
+
35  }
+
36  }
+
37  }
+
38 
+
39  } // namespace math
+
40 } // namespace stan
+
41 #endif
+ + + +
void jacobian(const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, Eigen::Matrix< T, Eigen::Dynamic, 1 > &fx, Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &J)
Definition: jacobian.hpp:14
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diff --git a/doc/api/html/fwd_2mat_2vectorize_2apply__scalar__unary_8hpp.html b/doc/api/html/fwd_2mat_2vectorize_2apply__scalar__unary_8hpp.html new file mode 100644 index 00000000000..4190897e8b0 --- /dev/null +++ b/doc/api/html/fwd_2mat_2vectorize_2apply__scalar__unary_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/vectorize/apply_scalar_unary.hpp File Reference + + + + + + + + + + +
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struct  stan::math::apply_scalar_unary< F, stan::math::fvar< T > >
 Template specialization to fvar for vectorizing a unary scalar function. More...
 
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diff --git a/doc/api/html/fwd_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html b/doc/api/html/fwd_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html new file mode 100644 index 00000000000..d920299db90 --- /dev/null +++ b/doc/api/html/fwd_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/vectorize/apply_scalar_unary.hpp Source File + + + + + + + + + + +
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apply_scalar_unary.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_VECTORIZE_APPLY_UNARY_SCALAR_HPP
+
2 #define STAN_MATH_FWD_MAT_VECTORIZE_APPLY_UNARY_SCALAR_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
21  template <typename F, typename T>
+ + +
28 
+
35  static inline return_t apply(const stan::math::fvar<T>& x) {
+
36  return F::fun(x);
+
37  }
+
38  };
+
39 
+
40  }
+
41 }
+
42 #endif
+ +
stan::math::fvar< T > return_t
Function return type, which is same as the argument type for the function, fvar.
+
static return_t apply(const stan::math::fvar< T > &x)
Apply the function specified by F to the specified argument.
+ +
Base template class for vectorization of unary scalar functions defined by a template class F to a sc...
+ + +
+
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diff --git a/doc/api/html/fwd_2mat_8hpp.html b/doc/api/html/fwd_2mat_8hpp.html new file mode 100644 index 00000000000..69bb3413817 --- /dev/null +++ b/doc/api/html/fwd_2mat_8hpp.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat.hpp File Reference + + + + + + + + + + +
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mat.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/fwd/scal/meta/is_fvar.hpp>
+#include <stan/math/fwd/scal/meta/partials_type.hpp>
+#include <stan/math/prim/mat.hpp>
+#include <stan/math/fwd/arr.hpp>
+#include <stan/math/fwd/mat/fun/Eigen_NumTraits.hpp>
+#include <stan/math/fwd/mat/fun/columns_dot_product.hpp>
+#include <stan/math/fwd/mat/fun/columns_dot_self.hpp>
+#include <stan/math/fwd/mat/fun/crossprod.hpp>
+#include <stan/math/fwd/mat/fun/determinant.hpp>
+#include <stan/math/fwd/mat/fun/divide.hpp>
+#include <stan/math/fwd/mat/fun/dot_product.hpp>
+#include <stan/math/fwd/mat/fun/dot_self.hpp>
+#include <stan/math/fwd/mat/fun/inverse.hpp>
+#include <stan/math/fwd/mat/fun/log_determinant.hpp>
+#include <stan/math/fwd/mat/fun/log_softmax.hpp>
+#include <stan/math/fwd/mat/fun/log_sum_exp.hpp>
+#include <stan/math/fwd/mat/fun/mdivide_left.hpp>
+#include <stan/math/fwd/mat/fun/mdivide_left_ldlt.hpp>
+#include <stan/math/fwd/mat/fun/mdivide_left_tri_low.hpp>
+#include <stan/math/fwd/mat/fun/mdivide_right.hpp>
+#include <stan/math/fwd/mat/fun/mdivide_right_tri_low.hpp>
+#include <stan/math/fwd/mat/fun/multiply.hpp>
+#include <stan/math/fwd/mat/fun/multiply_lower_tri_self_transpose.hpp>
+#include <stan/math/fwd/mat/fun/qr_Q.hpp>
+#include <stan/math/fwd/mat/fun/qr_R.hpp>
+#include <stan/math/fwd/mat/fun/quad_form_sym.hpp>
+#include <stan/math/fwd/mat/fun/rows_dot_product.hpp>
+#include <stan/math/fwd/mat/fun/rows_dot_self.hpp>
+#include <stan/math/fwd/mat/fun/softmax.hpp>
+#include <stan/math/fwd/mat/fun/sort_asc.hpp>
+#include <stan/math/fwd/mat/fun/sort_desc.hpp>
+#include <stan/math/fwd/mat/fun/sum.hpp>
+#include <stan/math/fwd/mat/fun/tcrossprod.hpp>
+#include <stan/math/fwd/mat/fun/to_fvar.hpp>
+#include <stan/math/fwd/mat/fun/trace_gen_quad_form.hpp>
+#include <stan/math/fwd/mat/fun/trace_quad_form.hpp>
+#include <stan/math/fwd/mat/fun/typedefs.hpp>
+#include <stan/math/fwd/mat/fun/unit_vector_constrain.hpp>
+#include <stan/math/fwd/mat/functor/gradient.hpp>
+#include <stan/math/fwd/mat/functor/jacobian.hpp>
+
+

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diff --git a/doc/api/html/fwd_2mat_8hpp_source.html b/doc/api/html/fwd_2mat_8hpp_source.html new file mode 100644 index 00000000000..6d1ee6bb231 --- /dev/null +++ b/doc/api/html/fwd_2mat_8hpp_source.html @@ -0,0 +1,199 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_MAT_HPP
+
2 #define STAN_MATH_FWD_MAT_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + +
7 
+
8 #include <stan/math/prim/mat.hpp>
+
9 #include <stan/math/fwd/arr.hpp>
+
10 
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48 
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49 #endif
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diff --git a/doc/api/html/fwd_2scal_2fun_2_phi_8hpp.html b/doc/api/html/fwd_2scal_2fun_2_phi_8hpp.html new file mode 100644 index 00000000000..df3f1adf94f --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2_phi_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/Phi.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::Phi (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2_phi_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2_phi_8hpp_source.html new file mode 100644 index 00000000000..a7d908c7e46 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2_phi_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/Phi.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_PHI_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_PHI_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline fvar<T> Phi(const fvar<T>& x) {
+
15  using stan::math::Phi;
+
16  using std::exp;
+
17  using std::sqrt;
+
18  T xv = x.val_;
+
19  return fvar<T>(Phi(xv),
+
20  x.d_ * exp(xv * xv / -2.0) / sqrt(2.0 * stan::math::pi()));
+
21  }
+
22  }
+
23 }
+
24 #endif
+ + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > Phi(const fvar< T > &x)
Definition: Phi.hpp:14
+ +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2abs_8hpp.html b/doc/api/html/fwd_2scal_2fun_2abs_8hpp.html new file mode 100644 index 00000000000..0af0ef342fc --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2abs_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/abs.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::abs (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2abs_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2abs_8hpp_source.html new file mode 100644 index 00000000000..0db8ae9500b --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2abs_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/abs.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ABS_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ABS_HPP
+
3 
+ +
5 #include <stan/math/fwd/core.hpp>
+ + + + +
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  template<typename T>
+
15  inline fvar<T> abs(const fvar<T>& x) {
+
16  using stan::math::abs;
+ +
18  if (x.val_ > 0.0)
+
19  return x;
+
20  else if (x.val_ < 0.0)
+
21  return fvar<T>(-x.val_, -x.d_);
+
22  else if (x.val_ == 0.0)
+
23  return fvar<T>(0, 0);
+
24  else
+ +
26  }
+
27 
+
28  }
+
29 }
+
30 #endif
+
fvar< T > abs(const fvar< T > &x)
Definition: abs.hpp:15
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ + + + + + + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2acos_8hpp.html b/doc/api/html/fwd_2scal_2fun_2acos_8hpp.html new file mode 100644 index 00000000000..fa2ba0397d2 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2acos_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/acos.hpp File Reference + + + + + + + + + + +
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+
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+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
+

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template<typename T >
fvar< T > stan::math::acos (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2acos_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2acos_8hpp_source.html new file mode 100644 index 00000000000..906e152b288 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2acos_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/acos.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ACOS_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ACOS_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  acos(const fvar<T>& x) {
+
15  using std::acos;
+
16  using std::sqrt;
+
17  using stan::math::square;
+
18  return fvar<T>(acos(x.val_), x.d_ / -sqrt(1 - square(x.val_)));
+
19  }
+
20 
+
21  }
+
22 }
+
23 #endif
+ + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
var acos(const var &a)
Return the principal value of the arc cosine of a variable, in radians (cmath).
Definition: acos.hpp:59
+ +
fvar< T > acos(const fvar< T > &x)
Definition: acos.hpp:14
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2acosh_8hpp.html b/doc/api/html/fwd_2scal_2fun_2acosh_8hpp.html new file mode 100644 index 00000000000..470f3413d0f --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2acosh_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/acosh.hpp File Reference + + + + + + + + + + +
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+
+
+
#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
+

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+Functions

template<typename T >
fvar< T > stan::math::acosh (const fvar< T > &x)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2acosh_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2acosh_8hpp_source.html new file mode 100644 index 00000000000..6fd2e167d5c --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2acosh_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/acosh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ACOSH_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ACOSH_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline fvar<T> acosh(const fvar<T>& x) {
+ +
16  using stan::math::square;
+
17  using std::sqrt;
+ +
19  return fvar<T>(acosh(x.val_),
+
20  x.d_ / sqrt(square(x.val_) - 1));
+
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
var acosh(const var &a)
The inverse hyperbolic cosine function for variables (C99).
Definition: acosh.hpp:68
+ +
fvar< T > acosh(const fvar< T > &x)
Definition: acosh.hpp:14
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2fun_2asin_8hpp.html b/doc/api/html/fwd_2scal_2fun_2asin_8hpp.html new file mode 100644 index 00000000000..893041bb0da --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2asin_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/asin.hpp File Reference + + + + + + + + + + +
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+
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+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::asin (const fvar< T > &x)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2asin_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2asin_8hpp_source.html new file mode 100644 index 00000000000..70743a341d3 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2asin_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/asin.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ASIN_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ASIN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline fvar<T> asin(const fvar<T>& x) {
+
13  using std::asin;
+
14  using std::sqrt;
+
15  using stan::math::square;
+
16  return fvar<T>(asin(x.val_), x.d_ / sqrt(1 - square(x.val_)));
+
17  }
+
18 
+
19  }
+
20 }
+
21 #endif
+ + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
var asin(const var &a)
Return the principal value of the arc sine, in radians, of the specified variable (cmath)...
Definition: asin.hpp:58
+ +
fvar< T > asin(const fvar< T > &x)
Definition: asin.hpp:12
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2fun_2asinh_8hpp.html b/doc/api/html/fwd_2scal_2fun_2asinh_8hpp.html new file mode 100644 index 00000000000..428e12681a4 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2asinh_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/asinh.hpp File Reference + + + + + + + + + + +
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+
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+
#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::asinh (const fvar< T > &x)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2asinh_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2asinh_8hpp_source.html new file mode 100644 index 00000000000..48ccdfc600b --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2asinh_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/asinh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ASINH_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ASINH_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ +
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline fvar<T> asinh(const fvar<T>& x) {
+ +
15  using std::sqrt;
+
16  using stan::math::square;
+
17  return fvar<T>(asinh(x.val_), x.d_ / sqrt(square(x.val_) + 1));
+
18  }
+
19 
+
20  }
+
21 }
+
22 #endif
+ + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
fvar< T > asinh(const fvar< T > &x)
Definition: asinh.hpp:13
+
var asinh(const var &a)
The inverse hyperbolic sine function for variables (C99).
Definition: asinh.hpp:67
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2atan2_8hpp.html b/doc/api/html/fwd_2scal_2fun_2atan2_8hpp.html new file mode 100644 index 00000000000..fc6db7ebe11 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2atan2_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/atan2.hpp File Reference + + + + + + + + + + +
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+
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+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
+

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template<typename T >
fvar< T > stan::math::atan2 (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::atan2 (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::atan2 (const fvar< T > &x1, const double x2)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2fun_2atan2_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2atan2_8hpp_source.html new file mode 100644 index 00000000000..7f5aea957c2 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2atan2_8hpp_source.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/atan2.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ATAN2_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ATAN2_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline fvar<T> atan2(const fvar<T>& x1, const fvar<T>& x2) {
+
13  using std::atan2;
+
14  using stan::math::square;
+
15  return fvar<T>(atan2(x1.val_, x2.val_),
+
16  (x1.d_ * x2.val_ - x1.val_ * x2.d_) /
+
17  (square(x2.val_) + square(x1.val_)));
+
18  }
+
19 
+
20  template <typename T>
+
21  inline fvar<T> atan2(const double x1, const fvar<T>& x2) {
+
22  using std::atan2;
+
23  using stan::math::square;
+
24  return fvar<T>(atan2(x1, x2.val_),
+
25  (-x1 * x2.d_) / (square(x1) + square(x2.val_)));
+
26  }
+
27 
+
28  template <typename T>
+
29  inline fvar<T> atan2(const fvar<T>& x1, const double x2) {
+
30  using std::atan2;
+
31  using stan::math::square;
+
32  return fvar<T>(atan2(x1.val_, x2),
+
33  (x1.d_ * x2) / (square(x2) + square(x1.val_)));
+
34  }
+
35 
+
36  }
+
37 }
+
38 #endif
+ + + +
fvar< T > atan2(const fvar< T > &x1, const fvar< T > &x2)
Definition: atan2.hpp:12
+ +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
var atan2(const double a, const var &b)
Return the principal value of the arc tangent, in radians, of the first scalar divided by the second ...
Definition: atan2.hpp:119
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2fun_2atan_8hpp.html b/doc/api/html/fwd_2scal_2fun_2atan_8hpp.html new file mode 100644 index 00000000000..f03c2019db0 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2atan_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/atan.hpp File Reference + + + + + + + + + + +
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+
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+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
+

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template<typename T >
fvar< T > stan::math::atan (const fvar< T > &x)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2atan_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2atan_8hpp_source.html new file mode 100644 index 00000000000..dcfb58b84b0 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2atan_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/atan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ATAN_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ATAN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline fvar<T> atan(const fvar<T>& x) {
+
13  using std::atan;
+
14  using stan::math::square;
+
15  return fvar<T>(atan(x.val_), x.d_ / (1 + square(x.val_)));
+
16  }
+
17 
+
18  }
+
19 }
+
20 #endif
+ + + + +
fvar< T > atan(const fvar< T > &x)
Definition: atan.hpp:12
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
var atan(const var &a)
Return the principal value of the arc tangent, in radians, of the specified variable (cmath)...
Definition: atan.hpp:55
+ +
+
+
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#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::atanh (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2atanh_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2atanh_8hpp_source.html new file mode 100644 index 00000000000..d6cf8ebe9f9 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2atanh_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/atanh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ATANH_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ATANH_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ +
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline fvar<T> atanh(const fvar<T>& x) {
+ +
15  using stan::math::square;
+
16  return fvar<T>(atanh(x.val_), x.d_ / (1 - square(x.val_)));
+
17  }
+
18 
+
19  }
+
20 }
+
21 #endif
+ + +
fvar< T > atanh(const fvar< T > &x)
Definition: atanh.hpp:13
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
var atanh(const var &a)
The inverse hyperbolic tangent function for variables (C99).
Definition: atanh.hpp:70
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2bessel__first__kind_8hpp.html b/doc/api/html/fwd_2scal_2fun_2bessel__first__kind_8hpp.html new file mode 100644 index 00000000000..596c5dfd89a --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2bessel__first__kind_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/bessel_first_kind.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2bessel__first__kind_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2bessel__first__kind_8hpp_source.html new file mode 100644 index 00000000000..1684cfa4718 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2bessel__first__kind_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/bessel_first_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_BESSEL_FIRST_KIND_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_BESSEL_FIRST_KIND_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  bessel_first_kind(int v, const fvar<T>& z) {
+ +
17 
+
18  T bessel_first_kind_z(bessel_first_kind(v, z.val_));
+
19  return fvar<T>(bessel_first_kind_z,
+
20  v * z.d_ * bessel_first_kind_z / z.val_
+
21  - z.d_ * bessel_first_kind(v + 1, z.val_));
+
22  }
+
23  }
+
24 }
+
25 #endif
+ + +
fvar< T > bessel_first_kind(int v, const fvar< T > &z)
+ + + + +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2bessel__second__kind_8hpp.html b/doc/api/html/fwd_2scal_2fun_2bessel__second__kind_8hpp.html new file mode 100644 index 00000000000..5af685e645c --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2bessel__second__kind_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/bessel_second_kind.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::bessel_second_kind (int v, const fvar< T > &z)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2bessel__second__kind_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2bessel__second__kind_8hpp_source.html new file mode 100644 index 00000000000..cc8df65cb88 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2bessel__second__kind_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/bessel_second_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_BESSEL_SECOND_KIND_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_BESSEL_SECOND_KIND_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  bessel_second_kind(int v, const fvar<T>& z) {
+ +
17 
+
18  T bessel_second_kind_z(bessel_second_kind(v, z.val_));
+
19  return fvar<T>(bessel_second_kind_z,
+
20  v * z.d_ * bessel_second_kind_z / z.val_
+
21  - z.d_ * bessel_second_kind(v + 1, z.val_));
+
22  }
+
23  }
+
24 }
+
25 #endif
+ + + +
fvar< T > bessel_second_kind(int v, const fvar< T > &z)
+ + + +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2binary__log__loss_8hpp.html b/doc/api/html/fwd_2scal_2fun_2binary__log__loss_8hpp.html new file mode 100644 index 00000000000..aab76bec519 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2binary__log__loss_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/binary_log_loss.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::binary_log_loss (const int y, const fvar< T > &y_hat)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2binary__log__loss_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2binary__log__loss_8hpp_source.html new file mode 100644 index 00000000000..3c171498339 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2binary__log__loss_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/binary_log_loss.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_BINARY_LOG_LOSS_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_BINARY_LOG_LOSS_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  binary_log_loss(const int y, const fvar<T>& y_hat) {
+ +
17 
+
18  if (y)
+
19  return fvar<T>(binary_log_loss(y, y_hat.val_),
+
20  -y_hat.d_ / y_hat.val_);
+
21  else
+
22  return fvar<T>(binary_log_loss(y, y_hat.val_),
+
23  y_hat.d_ / (1.0 - y_hat.val_));
+
24  }
+
25  }
+
26 }
+
27 #endif
+ + + +
fvar< T > binary_log_loss(const int y, const fvar< T > &y_hat)
+ + + +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2binomial__coefficient__log_8hpp.html b/doc/api/html/fwd_2scal_2fun_2binomial__coefficient__log_8hpp.html new file mode 100644 index 00000000000..53a4ce94581 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2binomial__coefficient__log_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/binomial_coefficient_log.hpp File Reference + + + + + + + + + + +
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binomial_coefficient_log.hpp File Reference
+
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+
#include <stan/math/fwd/core.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+#include <stan/math/prim/scal/fun/binomial_coefficient_log.hpp>
+
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template<typename T >
fvar< T > stan::math::binomial_coefficient_log (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::binomial_coefficient_log (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > stan::math::binomial_coefficient_log (const double x1, const fvar< T > &x2)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2binomial__coefficient__log_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2binomial__coefficient__log_8hpp_source.html new file mode 100644 index 00000000000..d086afba217 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2binomial__coefficient__log_8hpp_source.html @@ -0,0 +1,209 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/binomial_coefficient_log.hpp Source File + + + + + + + + + + +
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binomial_coefficient_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_BINOMIAL_COEFFICIENT_LOG_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_BINOMIAL_COEFFICIENT_LOG_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 #include <boost/math/special_functions/digamma.hpp>
+ +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  fvar<T>
+
16  binomial_coefficient_log(const fvar<T>& x1, const fvar<T>& x2) {
+ +
18  using std::log;
+ +
20  const double cutoff = 1000;
+
21  if ((x1.val_ < cutoff) || (x1.val_ - x2.val_ < cutoff)) {
+ +
23  x1.d_ * digamma(x1.val_ + 1)
+
24  - x2.d_ * digamma(x2.val_ + 1)
+
25  - (x1.d_ - x2.d_) * digamma(x1.val_ - x2.val_ + 1));
+
26  } else {
+ +
28  x2.d_ * log(x1.val_ - x2.val_)
+
29  + x2.val_ * (x1.d_ - x2.d_) / (x1.val_ - x2.val_)
+
30  + x1.d_ * log(x1.val_ / (x1.val_ - x2.val_))
+
31  + (x1.val_ + 0.5) / (x1.val_ / (x1.val_ - x2.val_))
+
32  * (x1.d_ * (x1.val_ - x2.val_)
+
33  - (x1.d_ - x2.d_) * x1.val_)
+
34  / ((x1.val_ - x2.val_) * (x1.val_ - x2.val_))
+
35  - x1.d_ / (12.0 * x1.val_ * x1.val_)
+
36  - x2.d_
+
37  + (x1.d_ - x2.d_) / (12.0 * (x1.val_ - x2.val_)
+
38  * (x1.val_ - x2.val_))
+
39  - digamma(x2.val_ + 1) * x2.d_);
+
40  }
+
41  }
+
42 
+
43  template <typename T>
+
44  inline
+
45  fvar<T>
+
46  binomial_coefficient_log(const fvar<T>& x1, const double x2) {
+ +
48  using std::log;
+ +
50  const double cutoff = 1000;
+
51  if ((x1.val_ < cutoff) || (x1.val_ - x2 < cutoff)) {
+
52  return fvar<T>(binomial_coefficient_log(x1.val_, x2),
+
53  x1.d_ * digamma(x1.val_ + 1)
+
54  - x1.d_ * digamma(x1.val_ - x2 + 1));
+
55  } else {
+
56  return fvar<T>(binomial_coefficient_log(x1.val_, x2),
+
57  x2 * x1.d_ / (x1.val_ - x2)
+
58  + x1.d_ * log(x1.val_ / (x1.val_ - x2))
+
59  + (x1.val_ + 0.5) / (x1.val_ / (x1.val_ - x2))
+
60  * (x1.d_ * (x1.val_ - x2) - x1.d_ * x1.val_)
+
61  / ((x1.val_ - x2) * (x1.val_ - x2))
+
62  - x1.d_ / (12.0 * x1.val_ * x1.val_)
+
63  + x1.d_ / (12.0 * (x1.val_ - x2) * (x1.val_ - x2)));
+
64  }
+
65  }
+
66 
+
67  template <typename T>
+
68  inline
+
69  fvar<T>
+
70  binomial_coefficient_log(const double x1, const fvar<T>& x2) {
+ +
72  using std::log;
+ +
74  const double cutoff = 1000;
+
75  if ((x1 < cutoff) || (x1 - x2.val_ < cutoff)) {
+
76  return fvar<T>(binomial_coefficient_log(x1, x2.val_),
+
77  -x2.d_ * digamma(x2.val_ + 1)
+
78  - x2.d_ * digamma(x1 - x2.val_ + 1));
+
79  } else {
+
80  return fvar<T>(binomial_coefficient_log(x1, x2.val_),
+
81  x2.d_ * log(x1 - x2.val_)
+
82  + x2.val_ * -x2.d_ / (x1 - x2.val_)
+
83  - x2.d_
+
84  - x2.d_ / (12.0 * (x1 - x2.val_) * (x1 - x2.val_))
+
85  + x2.d_ * (x1 + 0.5) / (x1 - x2.val_)
+
86  - digamma(x2.val_ + 1) * x2.d_);
+
87  }
+
88  }
+
89  }
+
90 }
+
91 #endif
+ + +
fvar< T > binomial_coefficient_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ + + +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2fun_2cbrt_8hpp.html b/doc/api/html/fwd_2scal_2fun_2cbrt_8hpp.html new file mode 100644 index 00000000000..de58c22e63c --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2cbrt_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/cbrt.hpp File Reference + + + + + + + + + + +
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+
#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+
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template<typename T >
fvar< T > stan::math::cbrt (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2cbrt_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2cbrt_8hpp_source.html new file mode 100644 index 00000000000..9a54aa0c564 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2cbrt_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/cbrt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_CBRT_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_CBRT_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  cbrt(const fvar<T>& x) {
+ +
16  using stan::math::square;
+
17  return fvar<T>(cbrt(x.val_),
+
18  x.d_ / (square(cbrt(x.val_)) * 3.0));
+
19  }
+
20 
+
21  }
+
22 }
+
23 #endif
+ + + +
fvar< T > cbrt(const fvar< T > &x)
Definition: cbrt.hpp:14
+ +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
var cbrt(const var &a)
Returns the cube root of the specified variable (C99).
Definition: cbrt.hpp:56
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2ceil_8hpp.html b/doc/api/html/fwd_2scal_2fun_2ceil_8hpp.html new file mode 100644 index 00000000000..aa247c6c7f9 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2ceil_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/ceil.hpp File Reference + + + + + + + + + + +
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+
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diff --git a/doc/api/html/fwd_2scal_2fun_2ceil_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2ceil_8hpp_source.html new file mode 100644 index 00000000000..77a7165f917 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2ceil_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/ceil.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_CEIL_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_CEIL_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline fvar<T> ceil(const fvar<T>& x) {
+
12  using std::ceil;
+
13  return fvar<T>(ceil(x.val_), 0);
+
14  }
+
15 
+
16  }
+
17 }
+
18 #endif
+ + + +
var ceil(const var &a)
Return the ceiling of the specified variable (cmath).
Definition: ceil.hpp:60
+
fvar< T > ceil(const fvar< T > &x)
Definition: ceil.hpp:11
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2cos_8hpp.html b/doc/api/html/fwd_2scal_2fun_2cos_8hpp.html new file mode 100644 index 00000000000..1ca84383472 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2cos_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/cos.hpp File Reference + + + + + + + + + + +
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+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::cos (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2cos_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2cos_8hpp_source.html new file mode 100644 index 00000000000..9590e867db4 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2cos_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/cos.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_COS_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_COS_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline
+
12  fvar<T>
+
13  cos(const fvar<T>& x) {
+
14  using std::sin;
+
15  using std::cos;
+
16  return fvar<T>(cos(x.val_), x.d_ * -sin(x.val_));
+
17  }
+
18 
+
19  }
+
20 }
+
21 #endif
+
fvar< T > cos(const fvar< T > &x)
Definition: cos.hpp:13
+ + +
var cos(const var &a)
Return the cosine of a radian-scaled variable (cmath).
Definition: cos.hpp:49
+ +
fvar< T > sin(const fvar< T > &x)
Definition: sin.hpp:14
+ + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2cosh_8hpp.html b/doc/api/html/fwd_2scal_2fun_2cosh_8hpp.html new file mode 100644 index 00000000000..0225f245f37 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2cosh_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/cosh.hpp File Reference + + + + + + + + + + +
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#include <stan/math/fwd/core.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::cosh (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2cosh_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2cosh_8hpp_source.html new file mode 100644 index 00000000000..9bae52a09cc --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2cosh_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/cosh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_COSH_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_COSH_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline
+
12  fvar<T>
+
13  cosh(const fvar<T>& x) {
+
14  using std::sinh;
+
15  using std::cosh;
+
16  return fvar<T>(cosh(x.val_), x.d_ * sinh(x.val_));
+
17  }
+
18 
+
19  }
+
20 }
+
21 #endif
+ + +
fvar< T > cosh(const fvar< T > &x)
Definition: cosh.hpp:13
+ + +
var cosh(const var &a)
Return the hyperbolic cosine of the specified variable (cmath).
Definition: cosh.hpp:50
+
fvar< T > sinh(const fvar< T > &x)
Definition: sinh.hpp:14
+ +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2digamma_8hpp.html b/doc/api/html/fwd_2scal_2fun_2digamma_8hpp.html new file mode 100644 index 00000000000..e54f1904fad --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2digamma_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/digamma.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::digamma (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2digamma_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2digamma_8hpp_source.html new file mode 100644 index 00000000000..3486a97d878 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2digamma_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/digamma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_DIGAMMA_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_DIGAMMA_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  fvar<T>
+
16  digamma(const fvar<T>& x) {
+
17  using stan::math::digamma;
+ +
19  return fvar<T>(digamma(x.val_), x.d_ * trigamma(x.val_));
+
20  }
+
21  }
+
22 }
+
23 #endif
+
T trigamma(T x)
Definition: trigamma.hpp:50
+ + + + + + + +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2erf_8hpp.html b/doc/api/html/fwd_2scal_2fun_2erf_8hpp.html new file mode 100644 index 00000000000..c993993e0d2 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2erf_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/erf.hpp File Reference + + + + + + + + + + +
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#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::erf (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2erf_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2erf_8hpp_source.html new file mode 100644 index 00000000000..e3f00744a2c --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2erf_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/erf.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ERF_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ERF_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline fvar<T> erf(const fvar<T>& x) {
+ +
16  using std::sqrt;
+
17  using std::exp;
+
18  using stan::math::square;
+
19  return fvar<T>(erf(x.val_), x.d_ * exp(-square(x.val_))
+ +
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+
var erf(const var &a)
The error function for variables (C99).
Definition: erf.hpp:68
+ + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
const double TWO_OVER_SQRT_PI
Definition: constants.hpp:161
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2erfc_8hpp.html b/doc/api/html/fwd_2scal_2fun_2erfc_8hpp.html new file mode 100644 index 00000000000..9f2195047b7 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2erfc_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/erfc.hpp File Reference + + + + + + + + + + +
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#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::erfc (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2erfc_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2erfc_8hpp_source.html new file mode 100644 index 00000000000..a09866f7fdf --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2erfc_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/erfc.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ERFC_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ERFC_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline fvar<T> erfc(const fvar<T>& x) {
+ +
16  using std::sqrt;
+
17  using std::exp;
+
18  using stan::math::square;
+
19  return fvar<T>(erfc(x.val_), -x.d_ * exp(-square(x.val_))
+ +
21  }
+
22  }
+
23 }
+
24 #endif
+ + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
var erfc(const var &a)
The complementary error function for variables (C99).
Definition: erfc.hpp:68
+ +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
const double TWO_OVER_SQRT_PI
Definition: constants.hpp:161
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2exp2_8hpp.html b/doc/api/html/fwd_2scal_2fun_2exp2_8hpp.html new file mode 100644 index 00000000000..071a0b9429b --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2exp2_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/exp2.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::exp2 (const fvar< T > &x)
 
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2exp2_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2exp2_8hpp_source.html new file mode 100644 index 00000000000..649e80e65aa --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2exp2_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/exp2.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_EXP2_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_EXP2_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + +
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline fvar<T>
+
14  exp2(const fvar<T>& x) {
+
15  using stan::math::exp2;
+
16  using std::log;
+
17  return fvar<T>(exp2(x.val_), x.d_ * exp2(x.val_) * stan::math::LOG_2);
+
18  }
+
19 
+
20  }
+
21 }
+
22 #endif
+
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:33
+ + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
fvar< T > exp2(const fvar< T > &x)
Definition: exp2.hpp:14
+ + + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2exp_8hpp.html b/doc/api/html/fwd_2scal_2fun_2exp_8hpp.html new file mode 100644 index 00000000000..ecddd5d09fd --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2exp_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/exp.hpp File Reference + + + + + + + + + + +
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+
+
+
#include <stan/math/fwd/core.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::exp (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2exp_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2exp_8hpp_source.html new file mode 100644 index 00000000000..e5bf631a918 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2exp_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_EXP_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_EXP_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9  template <typename T>
+
10  inline fvar<T> exp(const fvar<T>& x) {
+
11  using std::exp;
+
12  return fvar<T>(exp(x.val_), x.d_ * exp(x.val_));
+
13  }
+
14 
+
15  }
+
16 }
+
17 #endif
+ + + +
var exp(const var &a)
Return the exponentiation of the specified variable (cmath).
Definition: exp.hpp:44
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2expm1_8hpp.html b/doc/api/html/fwd_2scal_2fun_2expm1_8hpp.html new file mode 100644 index 00000000000..029f1432c17 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2expm1_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/expm1.hpp File Reference + + + + + + + + + + +
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#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::expm1 (const fvar< T > &x)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2expm1_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2expm1_8hpp_source.html new file mode 100644 index 00000000000..9fa643028df --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2expm1_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/expm1.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_EXPM1_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_EXPM1_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline fvar<T> expm1(const fvar<T>& x) {
+
13  using std::exp;
+ +
15  return fvar<T>(expm1(x.val_), x.d_ * exp(x.val_));
+
16  }
+
17 
+
18  }
+
19 }
+
20 #endif
+ + + +
var expm1(const stan::math::var &a)
The exponentiation of the specified variable minus 1 (C99).
Definition: expm1.hpp:57
+
fvar< T > expm1(const fvar< T > &x)
Definition: expm1.hpp:12
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2fabs_8hpp.html b/doc/api/html/fwd_2scal_2fun_2fabs_8hpp.html new file mode 100644 index 00000000000..69ca7c0e5bf --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fabs_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fabs.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::fabs (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2fabs_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2fabs_8hpp_source.html new file mode 100644 index 00000000000..7447e72fe65 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fabs_8hpp_source.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fabs.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_FABS_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_FABS_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template<typename T>
+
14  inline fvar<T> fabs(const fvar<T>& x) {
+
15  using std::fabs;
+ + +
18 
+ + +
21  else if (x.val_ > 0.0)
+
22  return x;
+
23  else if (x.val_ < 0.0)
+
24  return fvar<T>(-x.val_, -x.d_);
+
25  else
+
26  return fvar<T>(0, 0);
+
27  }
+
28 
+
29  }
+
30 }
+
31 #endif
+ + +
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+ +
var fabs(const var &a)
Return the absolute value of the variable (cmath).
Definition: fabs.hpp:50
+ + + + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2falling__factorial_8hpp.html b/doc/api/html/fwd_2scal_2fun_2falling__factorial_8hpp.html new file mode 100644 index 00000000000..2ae740f35db --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2falling__factorial_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/falling_factorial.hpp File Reference + + + + + + + + + + +
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+
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+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/falling_factorial.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+
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template<typename T >
fvar< T > stan::math::falling_factorial (const fvar< T > &x, const fvar< T > &n)
 
template<typename T >
fvar< T > stan::math::falling_factorial (const fvar< T > &x, const double n)
 
template<typename T >
fvar< T > stan::math::falling_factorial (const double x, const fvar< T > &n)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2falling__factorial_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2falling__factorial_8hpp_source.html new file mode 100644 index 00000000000..3cf3dcdd7e4 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2falling__factorial_8hpp_source.html @@ -0,0 +1,171 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/falling_factorial.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_FALLING_FACTORIAL_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_FALLING_FACTORIAL_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 #include <boost/math/special_functions/digamma.hpp>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template<typename T>
+
14  inline fvar<T>
+
15  falling_factorial(const fvar<T>& x, const fvar<T>& n) {
+ + +
18 
+
19  T falling_fact(falling_factorial(x.val_, n.val_));
+
20  return fvar<T>(falling_fact,
+
21  falling_fact
+
22  * (digamma(x.val_ + 1) - digamma(x.val_ - n.val_ + 1))
+
23  * x.d_
+
24  + falling_fact
+
25  * digamma(x.val_ - n.val_ + 1) * n.d_);
+
26  }
+
27 
+
28  template<typename T>
+
29  inline fvar<T>
+
30  falling_factorial(const fvar<T>& x, const double n) {
+ + +
33 
+
34  T falling_fact(falling_factorial(x.val_, n));
+
35  return fvar<T>(falling_fact,
+
36  falling_fact
+
37  * (digamma(x.val_ + 1) - digamma(x.val_ - n + 1))
+
38  * x.d_);
+
39  }
+
40 
+
41  template<typename T>
+
42  inline fvar<T>
+
43  falling_factorial(const double x, const fvar<T>& n) {
+ + +
46 
+
47  T falling_fact(falling_factorial(x, n.val_));
+
48  return fvar<T>(falling_fact,
+
49  falling_fact
+
50  * digamma(x - n.val_ + 1) * n.d_);
+
51  }
+
52  }
+
53 }
+
54 #endif
+ + + + + +
fvar< T > falling_factorial(const fvar< T > &x, const fvar< T > &n)
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2fdim_8hpp.html b/doc/api/html/fwd_2scal_2fun_2fdim_8hpp.html new file mode 100644 index 00000000000..e8b2cc7d771 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fdim_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fdim.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::fdim (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::fdim (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > stan::math::fdim (const double x1, const fvar< T > &x2)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2fdim_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2fdim_8hpp_source.html new file mode 100644 index 00000000000..95ee8809e3f --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fdim_8hpp_source.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fdim.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_FDIM_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_FDIM_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline fvar<T> fdim(const fvar<T>& x1, const fvar<T>& x2) {
+
12  using stan::math::fdim;
+
13  using std::floor;
+
14  if (x1.val_ < x2.val_)
+
15  return fvar<T>(fdim(x1.val_, x2.val_), 0);
+
16  else
+
17  return fvar<T>(fdim(x1.val_, x2.val_),
+
18  x1.d_ - x2.d_ * floor(x1.val_ / x2.val_));
+
19  }
+
20 
+
21  template <typename T>
+
22  inline fvar<T> fdim(const fvar<T>& x1, const double x2) {
+
23  using stan::math::fdim;
+
24  using std::floor;
+
25  if (x1.val_ < x2)
+
26  return fvar<T>(fdim(x1.val_, x2), 0);
+
27  else
+
28  return fvar<T>(fdim(x1.val_, x2), x1.d_);
+
29  }
+
30 
+
31  template <typename T>
+
32  inline fvar<T> fdim(const double x1, const fvar<T>& x2) {
+
33  using stan::math::fdim;
+
34  using std::floor;
+
35  if (x1 < x2.val_)
+
36  return fvar<T>(fdim(x1, x2.val_), 0);
+
37  else
+
38  return fvar<T>(fdim(x1, x2.val_), x2.d_ * -floor(x1 / x2.val_));
+
39  }
+
40 
+
41  }
+
42 }
+
43 #endif
+ + + + +
fvar< T > fdim(const fvar< T > &x1, const fvar< T > &x2)
Definition: fdim.hpp:11
+
fvar< T > floor(const fvar< T > &x)
Definition: floor.hpp:11
+ + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2floor_8hpp.html b/doc/api/html/fwd_2scal_2fun_2floor_8hpp.html new file mode 100644 index 00000000000..0141728fb0c --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2floor_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/floor.hpp File Reference + + + + + + + + + + +
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template<typename T >
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diff --git a/doc/api/html/fwd_2scal_2fun_2floor_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2floor_8hpp_source.html new file mode 100644 index 00000000000..c6b1d715e49 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2floor_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/floor.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_FLOOR_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_FLOOR_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline fvar<T> floor(const fvar<T>& x) {
+
12  using std::floor;
+
13  return fvar<T>(floor(x.val_), 0);
+
14  }
+
15 
+
16  }
+
17 }
+
18 #endif
+ + +
var floor(const var &a)
Return the floor of the specified variable (cmath).
Definition: floor.hpp:60
+ +
fvar< T > floor(const fvar< T > &x)
Definition: floor.hpp:11
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2fma_8hpp.html b/doc/api/html/fwd_2scal_2fun_2fma_8hpp.html new file mode 100644 index 00000000000..2901ba4dbff --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fma_8hpp.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fma.hpp File Reference + + + + + + + + + + +
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#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/meta/return_type.hpp>
+
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template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > stan::math::fma (const fvar< T1 > &x1, const fvar< T2 > &x2, const fvar< T3 > &x3)
 The fused multiply-add operation (C99). More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > stan::math::fma (const T1 &x1, const fvar< T2 > &x2, const fvar< T3 > &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > stan::math::fma (const fvar< T1 > &x1, const T2 &x2, const fvar< T3 > &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > stan::math::fma (const fvar< T1 > &x1, const fvar< T2 > &x2, const T3 &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > stan::math::fma (const T1 &x1, const T2 &x2, const fvar< T3 > &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > stan::math::fma (const fvar< T1 > &x1, const T2 &x2, const T3 &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > stan::math::fma (const T1 &x1, const fvar< T2 > &x2, const T3 &x3)
 See all-var input signature for details on the function and derivatives. More...
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2fma_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2fma_8hpp_source.html new file mode 100644 index 00000000000..4ff654b7509 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fma_8hpp_source.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_FMA_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_FMA_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
58  template <typename T1, typename T2, typename T3>
+
59  inline
+
60  fvar<typename stan::return_type<T1, T2, T3>::type>
+
61  fma(const fvar<T1>& x1, const fvar<T2>& x2, const fvar<T3>& x3) {
+ + +
64  (fma(x1.val_, x2.val_, x3.val_),
+
65  x1.d_ * x2.val_ + x2.d_ * x1.val_ + x3.d_);
+
66  }
+
67 
+
71  template <typename T1, typename T2, typename T3>
+
72  inline
+
73  fvar<typename stan::return_type<T1, T2, T3>::type>
+
74  fma(const T1& x1, const fvar<T2>& x2, const fvar<T3>& x3) {
+ + +
77  (fma(x1, x2.val_, x3.val_), x2.d_ * x1 + x3.d_);
+
78  }
+
79 
+
83  template <typename T1, typename T2, typename T3>
+
84  inline
+
85  fvar<typename stan::return_type<T1, T2, T3>::type>
+
86  fma(const fvar<T1>& x1, const T2& x2, const fvar<T3>& x3) {
+ + +
89  (fma(x1.val_, x2, x3.val_), x1.d_ * x2 + x3.d_);
+
90  }
+
91 
+
95  template <typename T1, typename T2, typename T3>
+
96  inline
+
97  fvar<typename stan::return_type<T1, T2, T3>::type>
+
98  fma(const fvar<T1>& x1, const fvar<T2>& x2, const T3& x3) {
+ + +
101  (fma(x1.val_, x2.val_, x3), x1.d_ * x2.val_ + x2.d_ * x1.val_);
+
102  }
+
103 
+
107  template <typename T1, typename T2, typename T3>
+
108  inline
+
109  fvar<typename stan::return_type<T1, T2, T3>::type>
+
110  fma(const T1& x1, const T2& x2, const fvar<T3>& x3) {
+
111  using ::fma;
+ +
113  (fma(x1, x2, x3.val_), x3.d_);
+
114  }
+
115 
+
119  template <typename T1, typename T2, typename T3>
+
120  inline
+
121  fvar<typename stan::return_type<T1, T2, T3>::type>
+
122  fma(const fvar<T1>& x1, const T2& x2, const T3& x3) {
+
123  using ::fma;
+ +
125  (fma(x1.val_, x2, x3), x1.d_ * x2);
+
126  }
+
127 
+
131  template <typename T1, typename T2, typename T3>
+
132  inline
+
133  fvar<typename stan::return_type<T1, T2, T3>::type>
+
134  fma(const T1& x1, const fvar<T2>& x2, const T3& x3) {
+
135  using ::fma;
+ +
137  (fma(x1, x2.val_, x3), x2.d_ * x1);
+
138  }
+
139 
+
140  }
+
141 }
+
142 #endif
+ + + + + +
fvar< typename stan::return_type< T1, T2, T3 >::type > fma(const fvar< T1 > &x1, const fvar< T2 > &x2, const fvar< T3 > &x3)
The fused multiply-add operation (C99).
Definition: fma.hpp:61
+
var fma(const double &a, const stan::math::var &b, const stan::math::var &c)
The fused multiply-add function for a value and two variables (C99).
Definition: fma.hpp:280
+ +
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diff --git a/doc/api/html/fwd_2scal_2fun_2fmax_8hpp.html b/doc/api/html/fwd_2scal_2fun_2fmax_8hpp.html new file mode 100644 index 00000000000..3ce737e675c --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fmax_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fmax.hpp File Reference + + + + + + + + + + +
+
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+
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template<typename T >
fvar< T > stan::math::fmax (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::fmax (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::fmax (const fvar< T > &x1, const double x2)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2fmax_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2fmax_8hpp_source.html new file mode 100644 index 00000000000..0f0c71b4c7f --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fmax_8hpp_source.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fmax.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
+
fmax.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_FMAX_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_FMAX_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline fvar<T> fmax(const fvar<T>& x1, const fvar<T>& x2) {
+ + +
16  if (unlikely(boost::math::isnan(x1.val_))) {
+
17  if (boost::math::isnan(x2.val_))
+
18  return fvar<T>(fmax(x1.val_, x2.val_), NOT_A_NUMBER);
+
19  else
+
20  return fvar<T>(x2.val_, x2.d_);
+
21  } else if (unlikely(boost::math::isnan(x2.val_))) {
+
22  return fvar<T>(x1.val_, x1.d_);
+
23  } else if (x1.val_ > x2.val_) {
+
24  return fvar<T>(x1.val_, x1.d_);
+
25  } else if (x1.val_ == x2.val_) {
+
26  return fvar<T>(x1.val_, NOT_A_NUMBER);
+
27  } else {
+
28  return fvar<T>(x2.val_, x2.d_);
+
29  }
+
30  }
+
31 
+
32  template <typename T>
+
33  inline fvar<T> fmax(const double x1, const fvar<T>& x2) {
+ + +
36  if (unlikely(boost::math::isnan(x1))) {
+
37  if (boost::math::isnan(x2.val_))
+
38  return fvar<T>(fmax(x1, x2.val_), NOT_A_NUMBER);
+
39  else
+
40  return fvar<T>(x2.val_, x2.d_);
+
41  } else if (unlikely(boost::math::isnan(x2.val_))) {
+
42  return fvar<T>(x1, 0.0);
+
43  } else if (x1 > x2.val_) {
+
44  return fvar<T>(x1, 0.0);
+
45  } else if (x1 == x2.val_) {
+
46  return fvar<T>(x2.val_, NOT_A_NUMBER);
+
47  } else {
+
48  return fvar<T>(x2.val_, x2.d_);
+
49  }
+
50  }
+
51 
+
52  template <typename T>
+
53  inline fvar<T> fmax(const fvar<T>& x1, const double x2) {
+ + +
56  if (unlikely(boost::math::isnan(x1.val_))) {
+
57  if (boost::math::isnan(x2))
+
58  return fvar<T>(fmax(x1.val_, x2), NOT_A_NUMBER);
+
59  else
+
60  return fvar<T>(x2, 0.0);
+
61  } else if (unlikely(boost::math::isnan(x2))) {
+
62  return fvar<T>(x1.val_, x1.d_);
+
63  } else if (x1.val_ > x2) {
+
64  return fvar<T>(x1.val_, x1.d_);
+
65  } else if (x1.val_ == x2) {
+
66  return fvar<T>(x1.val_, NOT_A_NUMBER);
+
67  } else {
+
68  return fvar<T>(x2, 0.0);
+
69  }
+
70  }
+
71  }
+
72 }
+
73 #endif
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
var fmax(const double &a, const stan::math::var &b)
Returns the maximum of a scalar and variable, promoting the scalar to a variable if it is larger (C99...
Definition: fmax.hpp:127
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+ + + +
fvar< T > fmax(const fvar< T > &x1, const fvar< T > &x2)
Definition: fmax.hpp:13
+ +
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+
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diff --git a/doc/api/html/fwd_2scal_2fun_2fmin_8hpp.html b/doc/api/html/fwd_2scal_2fun_2fmin_8hpp.html new file mode 100644 index 00000000000..81e810ef251 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fmin_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fmin.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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+Functions

template<typename T >
fvar< T > stan::math::fmin (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::fmin (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::fmin (const fvar< T > &x1, const double x2)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2fmin_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2fmin_8hpp_source.html new file mode 100644 index 00000000000..ef908f44c98 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fmin_8hpp_source.html @@ -0,0 +1,195 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fmin.hpp Source File + + + + + + + + + + +
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fmin.hpp
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_FMIN_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_FMIN_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline fvar<T> fmin(const fvar<T>& x1, const fvar<T>& x2) {
+ + +
16  if (unlikely(boost::math::isnan(x1.val_))) {
+
17  if (boost::math::isnan(x2.val_))
+
18  return fvar<T>(fmin(x1.val_, x2.val_), NOT_A_NUMBER);
+
19  else
+
20  return fvar<T>(x2.val_, x2.d_);
+
21  } else if (unlikely(boost::math::isnan(x2.val_))) {
+
22  return fvar<T>(x1.val_, x1.d_);
+
23  } else if (x1.val_ < x2.val_) {
+
24  return fvar<T>(x1.val_, x1.d_);
+
25  } else if (x1.val_ == x2.val_) {
+
26  return fvar<T>(x1.val_, NOT_A_NUMBER);
+
27  } else {
+
28  return fvar<T>(x2.val_, x2.d_);
+
29  }
+
30  }
+
31 
+
32  template <typename T>
+
33  inline fvar<T> fmin(const double x1, const fvar<T>& x2) {
+ + +
36  if (unlikely(boost::math::isnan(x1))) {
+
37  if (boost::math::isnan(x2.val_))
+
38  return fvar<T>(fmin(x1, x2.val_), NOT_A_NUMBER);
+
39  else
+
40  return fvar<T>(x2.val_, x2.d_);
+
41  } else if (unlikely(boost::math::isnan(x2.val_))) {
+
42  return fvar<T>(x1, 0.0);
+
43  } else if (x1 < x2.val_) {
+
44  return fvar<T>(x1, 0.0);
+
45  } else if (x1 == x2.val_) {
+
46  return fvar<T>(x2.val_, NOT_A_NUMBER);
+
47  } else {
+
48  return fvar<T>(x2.val_, x2.d_);
+
49  }
+
50  }
+
51 
+
52  template <typename T>
+
53  inline fvar<T> fmin(const fvar<T>& x1, const double x2) {
+ + +
56  if (unlikely(boost::math::isnan(x1.val_))) {
+
57  if (boost::math::isnan(x2))
+
58  return fvar<T>(fmin(x1.val_, x2), NOT_A_NUMBER);
+
59  else
+
60  return fvar<T>(x2, 0.0);
+
61  } else if (unlikely(boost::math::isnan(x2))) {
+
62  return fvar<T>(x1.val_, x1.d_);
+
63  } else if (x1.val_ < x2) {
+
64  return fvar<T>(x1.val_, x1.d_);
+
65  } else if (x1.val_ == x2) {
+
66  return fvar<T>(x1.val_, NOT_A_NUMBER);
+
67  } else {
+
68  return fvar<T>(x2, 0.0);
+
69  }
+
70  }
+
71 
+
72  }
+
73 }
+
74 #endif
+
fvar< T > fmin(const fvar< T > &x1, const fvar< T > &x2)
Definition: fmin.hpp:13
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
var fmin(double a, const stan::math::var &b)
Returns the minimum of a scalar and variable, promoting the scalar to a variable if it is larger (C99...
Definition: fmin.hpp:120
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+ + + + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2fmod_8hpp.html b/doc/api/html/fwd_2scal_2fun_2fmod_8hpp.html new file mode 100644 index 00000000000..190ecc43497 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fmod_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fmod.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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+Functions

template<typename T >
fvar< T > stan::math::fmod (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::fmod (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > stan::math::fmod (const double x1, const fvar< T > &x2)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2fmod_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2fmod_8hpp_source.html new file mode 100644 index 00000000000..2149bd3f5b2 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2fmod_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/fmod.hpp Source File + + + + + + + + + + +
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fmod.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_FMOD_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_FMOD_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  fvar<T>
+
16  fmod(const fvar<T>& x1, const fvar<T>& x2) {
+
17  using std::fmod;
+
18  using std::floor;
+
19  return fvar<T>(fmod(x1.val_, x2.val_),
+
20  x1.d_ - x2.d_ * floor(x1.val_ / x2.val_));
+
21  }
+
22 
+
23  template <typename T>
+
24  inline
+
25  fvar<T>
+
26  fmod(const fvar<T>& x1, const double x2) {
+
27  using std::fmod;
+ + +
30  || boost::math::isnan(x2)))
+
31  return fvar<T>(fmod(x1.val_, x2), stan::math::NOT_A_NUMBER);
+
32  else
+
33  return fvar<T>(fmod(x1.val_, x2), x1.d_ / x2);
+
34  }
+
35 
+
36  template <typename T>
+
37  inline
+
38  fvar<T>
+
39  fmod(const double x1, const fvar<T>& x2) {
+
40  using std::fmod;
+
41  using std::floor;
+
42  return fvar<T>(fmod(x1, x2.val_), -x2.d_ * floor(x1 / x2.val_));
+
43  }
+
44  }
+
45 }
+
46 #endif
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > fmod(const fvar< T > &x1, const fvar< T > &x2)
Definition: fmod.hpp:16
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+ +
var fmod(const double a, const var &b)
Return the floating point remainder after dividing the first scalar by the second variable (cmath)...
Definition: fmod.hpp:137
+ +
fvar< T > floor(const fvar< T > &x)
Definition: floor.hpp:11
+ + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2gamma__p_8hpp.html b/doc/api/html/fwd_2scal_2fun_2gamma__p_8hpp.html new file mode 100644 index 00000000000..4e1f279b8df --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2gamma__p_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/gamma_p.hpp File Reference + + + + + + + + + + +
+
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template<typename T >
fvar< T > stan::math::gamma_p (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::gamma_p (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > stan::math::gamma_p (const double x1, const fvar< T > &x2)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2gamma__p_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2gamma__p_8hpp_source.html new file mode 100644 index 00000000000..47e71add686 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2gamma__p_8hpp_source.html @@ -0,0 +1,224 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/gamma_p.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_GAMMA_P_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_GAMMA_P_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  gamma_p(const fvar<T>& x1, const fvar<T>& x2) {
+
16  using stan::math::gamma_p;
+
17  using std::log;
+
18  using std::exp;
+
19  using std::pow;
+
20  using std::fabs;
+
21  using boost::math::tgamma;
+ +
23 
+
24  T u = gamma_p(x1.val_, x2.val_);
+
25 
+
26  T S = 0;
+
27  T s = 1;
+
28  T l = log(x2.val_);
+
29  T g = tgamma(x1.val_);
+
30  T dig = digamma(x1.val_);
+
31 
+
32  int k = 0;
+
33  T delta = s / (x1.val_ * x1.val_);
+
34 
+
35  while (fabs(delta) > 1e-6) {
+
36  S += delta;
+
37  ++k;
+
38  s *= -x2.val_ / k;
+
39  delta = s / ((k + x1.val_) * (k + x1.val_));
+
40  }
+
41 
+
42  T der1 = u * (dig - l) + exp(x1.val_ * l) * S / g;
+
43  T der2 = exp(-x2.val_) * pow(x2.val_, x1.val_ - 1.0) / g;
+
44 
+
45  return fvar<T>(u, x1.d_ * -der1 + x2.d_ * der2);
+
46  }
+
47 
+
48  template <typename T>
+
49  inline
+
50  fvar<T>
+
51  gamma_p(const fvar<T>& x1, const double x2) {
+
52  using stan::math::gamma_p;
+
53  using std::log;
+
54  using std::exp;
+
55  using std::pow;
+
56  using std::fabs;
+
57  using boost::math::tgamma;
+ +
59 
+
60  T u = gamma_p(x1.val_, x2);
+
61 
+
62  T S = 0.0;
+
63  double s = 1.0;
+
64  double l = log(x2);
+
65  T g = tgamma(x1.val_);
+
66  T dig = digamma(x1.val_);
+
67 
+
68  int k = 0;
+
69  T delta = s / (x1.val_ * x1.val_);
+
70 
+
71  while (fabs(delta) > 1e-6) {
+
72  S += delta;
+
73  ++k;
+
74  s *= -x2 / k;
+
75  delta = s / ((k + x1.val_) * (k + x1.val_));
+
76  }
+
77 
+
78  T der1 = u * (dig - l) + exp(x1.val_ * l) * S / g;
+
79 
+
80  return fvar<T>(u, x1.d_ * -der1);
+
81  }
+
82 
+
83  template <typename T>
+
84  inline
+
85  fvar<T>
+
86  gamma_p(const double x1, const fvar<T>& x2) {
+
87  using stan::math::gamma_p;
+
88  using std::exp;
+
89  using std::pow;
+
90 
+
91  T u = gamma_p(x1, x2.val_);
+
92 
+
93  double g = boost::math::tgamma(x1);
+
94 
+
95  T der2 = exp(-x2.val_) * pow(x2.val_, x1 - 1.0) / g;
+
96 
+
97  return fvar<T>(u, x2.d_ * der2);
+
98  }
+
99  }
+
100 }
+
101 #endif
+ + +
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2gamma__q_8hpp.html b/doc/api/html/fwd_2scal_2fun_2gamma__q_8hpp.html new file mode 100644 index 00000000000..92b6dca5895 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2gamma__q_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/gamma_q.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::gamma_q (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::gamma_q (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > stan::math::gamma_q (const double x1, const fvar< T > &x2)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2gamma__q_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2gamma__q_8hpp_source.html new file mode 100644 index 00000000000..5a2f3e5207b --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2gamma__q_8hpp_source.html @@ -0,0 +1,224 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/gamma_q.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_GAMMA_Q_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_GAMMA_Q_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  gamma_q(const fvar<T>& x1, const fvar<T>& x2) {
+
16  using stan::math::gamma_q;
+
17  using std::log;
+
18  using std::exp;
+
19  using std::pow;
+
20  using std::fabs;
+
21  using boost::math::tgamma;
+ +
23 
+
24  T u = gamma_q(x1.val_, x2.val_);
+
25 
+
26  T S = 0;
+
27  T s = 1;
+
28  T l = log(x2.val_);
+
29  T g = tgamma(x1.val_);
+
30  T dig = digamma(x1.val_);
+
31 
+
32  int k = 0;
+
33  T delta = s / (x1.val_ * x1.val_);
+
34 
+
35  while (fabs(delta) > 1e-6) {
+
36  S += delta;
+
37  ++k;
+
38  s *= -x2.val_ / k;
+
39  delta = s / ((k + x1.val_) * (k + x1.val_));
+
40  }
+
41 
+
42  T der1 = (1.0 - u) * (dig - l) + exp(x1.val_ * l) * S / g;
+
43  T der2 = -exp(-x2.val_) * pow(x2.val_, x1.val_ - 1.0) / g;
+
44 
+
45  return fvar<T>(u, x1.d_ * der1 + x2.d_ * der2);
+
46  }
+
47 
+
48  template <typename T>
+
49  inline
+
50  fvar<T>
+
51  gamma_q(const fvar<T>& x1, const double x2) {
+
52  using stan::math::gamma_q;
+
53  using std::log;
+
54  using std::exp;
+
55  using std::pow;
+
56  using std::fabs;
+
57  using boost::math::tgamma;
+ +
59 
+
60  T u = gamma_q(x1.val_, x2);
+
61 
+
62  T S = 0;
+
63  double s = 1;
+
64  double l = log(x2);
+
65  T g = tgamma(x1.val_);
+
66  T dig = digamma(x1.val_);
+
67 
+
68  int k = 0;
+
69  T delta = s / (x1.val_ * x1.val_);
+
70 
+
71  while (fabs(delta) > 1e-6) {
+
72  S += delta;
+
73  ++k;
+
74  s *= -x2 / k;
+
75  delta = s / ((k + x1.val_) * (k + x1.val_));
+
76  }
+
77 
+
78  T der1 = (1.0 - u) * (dig - l) + exp(x1.val_ * l) * S / g;
+
79 
+
80  return fvar<T>(u, x1.d_ * der1);
+
81  }
+
82 
+
83  template <typename T>
+
84  inline
+
85  fvar<T>
+
86  gamma_q(const double x1, const fvar<T>& x2) {
+
87  using stan::math::gamma_q;
+
88  using std::exp;
+
89  using std::pow;
+
90 
+
91  T u = gamma_q(x1, x2.val_);
+
92 
+
93  double g = boost::math::tgamma(x1);
+
94 
+
95  T der2 = -exp(-x2.val_) * pow(x2.val_, x1 - 1.0) / g;
+
96 
+
97  return fvar<T>(u, x2.d_ * der2);
+
98  }
+
99  }
+
100 }
+
101 #endif
+ + +
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2grad__inc__beta_8hpp.html b/doc/api/html/fwd_2scal_2fun_2grad__inc__beta_8hpp.html new file mode 100644 index 00000000000..024e8f01a5d --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2grad__inc__beta_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/grad_inc_beta.hpp File Reference + + + + + + + + + + +
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template<typename T >
void stan::math::grad_inc_beta (stan::math::fvar< T > &g1, stan::math::fvar< T > &g2, stan::math::fvar< T > a, stan::math::fvar< T > b, stan::math::fvar< T > z)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2grad__inc__beta_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2grad__inc__beta_8hpp_source.html new file mode 100644 index 00000000000..fad30f44bf9 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2grad__inc__beta_8hpp_source.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/grad_inc_beta.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_GRAD_INC_BETA_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_GRAD_INC_BETA_HPP
+
3 
+ + + + + + + +
11 #include <stan/math/fwd/core.hpp>
+ + +
14 #include <cmath>
+
15 
+
16 namespace stan {
+
17  namespace math {
+
18 
+
19  // Gradient of the incomplete beta function beta(a, b, z)
+
20  // with respect to the first two arguments, using the
+
21  // equivalence to a hypergeometric function.
+
22  // See http://dlmf.nist.gov/8.17#ii
+
23  template<typename T>
+ + + + + + + +
31  using stan::math::log1m;
+
32 
+
33  stan::math::fvar<T> c1 = log(z);
+
34  stan::math::fvar<T> c2 = log1m(z);
+
35  stan::math::fvar<T> c3 = exp(lbeta(a, b)) * inc_beta(a, b, z);
+
36 
+
37  stan::math::fvar<T> C = exp(a * c1 + b * c2) / a;
+
38 
+
39  stan::math::fvar<T> dF1 = 0;
+
40  stan::math::fvar<T> dF2 = 0;
+
41 
+
42  if (value_of(value_of(C)))
+
43  stan::math::grad_2F1(dF1, dF2, a + b,
+ +
45  a + 1, z);
+
46 
+
47  g1 = (c1 - 1.0 / a) * c3 + C * (dF1 + dF2);
+
48  g2 = c2 * c3 + C * dF1;
+
49  }
+
50 
+
51  }
+
52 }
+
53 #endif
+ + + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
void grad_inc_beta(stan::math::fvar< T > &g1, stan::math::fvar< T > &g2, stan::math::fvar< T > a, stan::math::fvar< T > b, stan::math::fvar< T > z)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + + + + +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+ +
void grad_2F1(T &gradA, T &gradC, T a, T b, T c, T z, T precision=1e-6)
Definition: grad_2F1.hpp:13
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2hypot_8hpp.html b/doc/api/html/fwd_2scal_2fun_2hypot_8hpp.html new file mode 100644 index 00000000000..fb9589517f5 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2hypot_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/hypot.hpp File Reference + + + + + + + + + + +
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+
#include <math.h>
+#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/inv.hpp>
+#include <cmath>
+
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template<typename T >
fvar< T > stan::math::hypot (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::hypot (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > stan::math::hypot (const double x1, const fvar< T > &x2)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2hypot_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2hypot_8hpp_source.html new file mode 100644 index 00000000000..16c266d4625 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2hypot_8hpp_source.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/hypot.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_HYPOT_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_HYPOT_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+ +
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline fvar<T> hypot(const fvar<T>& x1, const fvar<T>& x2) {
+ +
15  using std::sqrt;
+
16  using stan::math::inv;
+
17  T u = hypot(x1.val_, x2.val_);
+
18  return fvar<T>(u, (x1.d_ * x1.val_ + x2.d_ * x2.val_) * inv(u));
+
19  }
+
20 
+
21  template <typename T>
+
22  inline fvar<T> hypot(const fvar<T>& x1, const double x2) {
+ +
24  using std::sqrt;
+
25  using stan::math::inv;
+
26  T u = hypot(x1.val_, x2);
+
27  return fvar<T>(u, (x1.d_ * x1.val_) * inv(u));
+
28  }
+
29 
+
30  template <typename T>
+
31  inline fvar<T> hypot(const double x1, const fvar<T>& x2) {
+ +
33  using std::sqrt;
+
34  using stan::math::inv;
+
35  T u = hypot(x1, x2.val_);
+
36  return fvar<T>(u, (x2.d_ * x2.val_) * inv(u));
+
37  }
+
38 
+
39  }
+
40 }
+
41 #endif
+ + +
fvar< T > hypot(const fvar< T > &x1, const fvar< T > &x2)
Definition: hypot.hpp:13
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + + + +
fvar< T > inv(const fvar< T > &x)
Definition: inv.hpp:15
+
var hypot(double a, const var &b)
Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99)...
Definition: hypot.hpp:116
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2inc__beta_8hpp.html b/doc/api/html/fwd_2scal_2fun_2inc__beta_8hpp.html new file mode 100644 index 00000000000..6f91786b5e5 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inc__beta_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inc_beta.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::inc_beta (const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2inc__beta_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2inc__beta_8hpp_source.html new file mode 100644 index 00000000000..460b517dec1 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inc__beta_8hpp_source.html @@ -0,0 +1,175 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inc_beta.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_INC_BETA_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_INC_BETA_HPP
+
3 
+
4 #include <boost/math/special_functions/beta.hpp>
+ + + + + + +
11 #include <stan/math/fwd/core.hpp>
+ + +
14 
+
15 namespace stan {
+
16 
+
17  namespace math {
+
18 
+
19  template<typename T>
+
20  inline fvar<T> inc_beta(const fvar<T>& a,
+
21  const fvar<T>& b,
+
22  const fvar<T>& x) {
+
23  using stan::math::digamma;
+ + +
26  using stan::math::lbeta;
+
27  using stan::math::digamma;
+
28  using stan::math::lbeta;
+
29  using stan::math::pow;
+
30  using std::exp;
+
31  using std::pow;
+
32 
+
33  T d_a; T d_b; T d_x;
+
34 
+
35  grad_reg_inc_beta(d_a, d_b, a.val_, b.val_, x.val_,
+
36  digamma(a.val_), digamma(b.val_),
+
37  digamma(a.val_+b.val_),
+
38  exp(lbeta(a.val_, b.val_)));
+
39  d_x = pow((1-x.val_), b.val_-1)*pow(x.val_, a.val_-1)
+
40  / exp(lbeta(a.val_, b.val_));
+
41  return fvar<T>(inc_beta(a.val_, b.val_, x.val_),
+
42  a.d_ * d_a + b.d_ * d_b + x.d_ * d_x);
+
43  }
+
44  }
+
45 }
+
46 
+
47 #endif
+ + + +
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ + + + +
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+ + +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv_8hpp.html b/doc/api/html/fwd_2scal_2fun_2inv_8hpp.html new file mode 100644 index 00000000000..2800e659ea6 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::inv (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2inv_8hpp_source.html new file mode 100644 index 00000000000..2b56d1e4a00 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_INV_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_INV_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  inv(const fvar<T>& x) {
+
16  using stan::math::square;
+
17  return fvar<T>(1 / x.val_, -x.d_ / square(x.val_));
+
18  }
+
19  }
+
20 }
+
21 #endif
+ + + + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
fvar< T > inv(const fvar< T > &x)
Definition: inv.hpp:15
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv___phi_8hpp.html b/doc/api/html/fwd_2scal_2fun_2inv___phi_8hpp.html new file mode 100644 index 00000000000..348defc25ac --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv___phi_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_Phi.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::inv_Phi (const fvar< T > &p)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv___phi_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2inv___phi_8hpp_source.html new file mode 100644 index 00000000000..67d871ae393 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv___phi_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_Phi.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_INV_PHI_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_INV_PHI_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + + +
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  template <typename T>
+
15  inline fvar<T> inv_Phi(const fvar<T>& p) {
+
16  using stan::math::inv_Phi;
+
17  using std::exp;
+
18  T xv = inv_Phi(p.val_);
+
19  return fvar<T>(xv,
+
20  p.d_ / exp(-0.5 * square(xv)) * SQRT_2_TIMES_SQRT_PI);
+
21  }
+
22  }
+
23 }
+
24 #endif
+ + +
fvar< T > inv_Phi(const fvar< T > &p)
Definition: inv_Phi.hpp:15
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
const double SQRT_2_TIMES_SQRT_PI
Definition: constants.hpp:158
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv__cloglog_8hpp.html b/doc/api/html/fwd_2scal_2fun_2inv__cloglog_8hpp.html new file mode 100644 index 00000000000..0f82f5ab0c6 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv__cloglog_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_cloglog.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::inv_cloglog (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv__cloglog_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2inv__cloglog_8hpp_source.html new file mode 100644 index 00000000000..9e25f521983 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv__cloglog_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_cloglog.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_INV_CLOGLOG_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_INV_CLOGLOG_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  inv_cloglog(const fvar<T>& x) {
+
16  using std::exp;
+ +
18  return fvar<T>(inv_cloglog(x.val_), x.d_ * exp(x.val_ - exp(x.val_)));
+
19  }
+
20  }
+
21 }
+
22 #endif
+ + + + + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > inv_cloglog(const fvar< T > &x)
Definition: inv_cloglog.hpp:15
+ +
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv__logit_8hpp.html b/doc/api/html/fwd_2scal_2fun_2inv__logit_8hpp.html new file mode 100644 index 00000000000..09a73952a8c --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv__logit_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_logit.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::inv_logit (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv__logit_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2inv__logit_8hpp_source.html new file mode 100644 index 00000000000..bc1de7330f5 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv__logit_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_logit.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_INV_LOGIT_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_INV_LOGIT_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  inv_logit(const fvar<T>& x) {
+
16  using std::exp;
+
17  using std::pow;
+ +
19  return fvar<T>(inv_logit(x.val_),
+
20  x.d_ * inv_logit(x.val_) * (1 - inv_logit(x.val_)));
+
21  }
+
22  }
+
23 }
+
24 #endif
+ + + +
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv__sqrt_8hpp.html b/doc/api/html/fwd_2scal_2fun_2inv__sqrt_8hpp.html new file mode 100644 index 00000000000..a071f631afa --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv__sqrt_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_sqrt.hpp File Reference + + + + + + + + + + +
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template<typename T >
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv__sqrt_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2inv__sqrt_8hpp_source.html new file mode 100644 index 00000000000..a3092093fbe --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv__sqrt_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_sqrt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_INV_SQRT_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_INV_SQRT_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 #include <boost/math/tools/promotion.hpp>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  inv_sqrt(const fvar<T>& x) {
+
16  using std::sqrt;
+
17  T sqrt_x(sqrt(x.val_));
+
18  return fvar<T>(1 / sqrt_x, -0.5 * x.d_ / (x.val_ * sqrt_x));
+
19  }
+
20  }
+
21 }
+
22 #endif
+ +
fvar< T > inv_sqrt(const fvar< T > &x)
Definition: inv_sqrt.hpp:15
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + + +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv__square_8hpp.html b/doc/api/html/fwd_2scal_2fun_2inv__square_8hpp.html new file mode 100644 index 00000000000..5c6eefd89b6 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv__square_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_square.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::inv_square (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2inv__square_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2inv__square_8hpp_source.html new file mode 100644 index 00000000000..a3aab5ab135 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2inv__square_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/inv_square.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_INV_SQUARE_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_INV_SQUARE_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  inv_square(const fvar<T>& x) {
+
16  using stan::math::square;
+
17  T square_x(square(x.val_));
+
18  return fvar<T>(1 / square_x, -2 * x.d_ / (square_x * x.val_));
+
19  }
+
20  }
+
21 }
+
22 #endif
+ + + + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
fvar< T > inv_square(const fvar< T > &x)
Definition: inv_square.hpp:15
+ +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2is__inf_8hpp.html b/doc/api/html/fwd_2scal_2fun_2is__inf_8hpp.html new file mode 100644 index 00000000000..a7343449ac7 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2is__inf_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/is_inf.hpp File Reference + + + + + + + + + + +
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int stan::math::is_inf (const fvar< T > &x)
 Returns 1 if the input's value is infinite and 0 otherwise. More...
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2is__inf_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2is__inf_8hpp_source.html new file mode 100644 index 00000000000..a8f4c099693 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2is__inf_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/is_inf.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_IS_INF_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_IS_INF_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
19  template <typename T>
+
20  inline
+
21  int
+
22  is_inf(const fvar<T>& x) {
+
23  using stan::math::is_inf;
+
24  return is_inf(x.val());
+
25  }
+
26 
+
27  }
+
28 }
+
29 
+
30 #endif
+ + + +
int is_inf(const fvar< T > &x)
Returns 1 if the input's value is infinite and 0 otherwise.
Definition: is_inf.hpp:22
+
T val() const
Definition: fvar.hpp:17
+ +
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diff --git a/doc/api/html/fwd_2scal_2fun_2is__nan_8hpp.html b/doc/api/html/fwd_2scal_2fun_2is__nan_8hpp.html new file mode 100644 index 00000000000..fd0fefd1319 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2is__nan_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/is_nan.hpp File Reference + + + + + + + + + + +
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int stan::math::is_nan (const fvar< T > &x)
 Returns 1 if the input's value is NaN and 0 otherwise. More...
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2is__nan_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2is__nan_8hpp_source.html new file mode 100644 index 00000000000..9b084c3a9da --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2is__nan_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/is_nan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_IS_NAN_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_IS_NAN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
19  template <typename T>
+
20  inline
+
21  int
+
22  is_nan(const fvar<T>& x) {
+
23  using stan::math::is_nan;
+
24  return is_nan(x.val());
+
25  }
+
26 
+
27  }
+
28 }
+
29 
+
30 #endif
+ + + +
T val() const
Definition: fvar.hpp:17
+
int is_nan(const fvar< T > &x)
Returns 1 if the input's value is NaN and 0 otherwise.
Definition: is_nan.hpp:22
+ +
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diff --git a/doc/api/html/fwd_2scal_2fun_2lbeta_8hpp.html b/doc/api/html/fwd_2scal_2fun_2lbeta_8hpp.html new file mode 100644 index 00000000000..e9c5f2c14c5 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2lbeta_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/lbeta.hpp File Reference + + + + + + + + + + +
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#include <stan/math/fwd/core.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+#include <stan/math/prim/scal/fun/lbeta.hpp>
+
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template<typename T >
fvar< T > stan::math::lbeta (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::lbeta (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::lbeta (const fvar< T > &x1, const double x2)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2lbeta_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2lbeta_8hpp_source.html new file mode 100644 index 00000000000..187d7e8933a --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2lbeta_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/lbeta.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LBETA_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LBETA_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 #include <boost/math/special_functions/digamma.hpp>
+ +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  fvar<T>
+
16  lbeta(const fvar<T>& x1, const fvar<T>& x2) {
+
17  using stan::math::lbeta;
+ +
19  return fvar<T>(lbeta(x1.val_, x2.val_),
+
20  x1.d_ * digamma(x1.val_)
+
21  + x2.d_ * digamma(x2.val_)
+
22  - (x1.d_ + x2.d_) * digamma(x1.val_ + x2.val_));
+
23  }
+
24 
+
25  template <typename T>
+
26  inline
+
27  fvar<T>
+
28  lbeta(const double x1, const fvar<T>& x2) {
+
29  using stan::math::lbeta;
+ +
31  return fvar<T>(lbeta(x1, x2.val_),
+
32  x2.d_ * digamma(x2.val_) - x2.d_ * digamma(x1 + x2.val_));
+
33  }
+
34 
+
35  template <typename T>
+
36  inline
+
37  fvar<T>
+
38  lbeta(const fvar<T>& x1, const double x2) {
+
39  using stan::math::lbeta;
+ +
41  return fvar<T>(lbeta(x1.val_, x2),
+
42  x1.d_ * digamma(x1.val_) - x1.d_ * digamma(x1.val_ + x2));
+
43  }
+
44  }
+
45 }
+
46 #endif
+ + + +
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ + + +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2lgamma_8hpp.html b/doc/api/html/fwd_2scal_2fun_2lgamma_8hpp.html new file mode 100644 index 00000000000..2e5f753b173 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2lgamma_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/lgamma.hpp File Reference + + + + + + + + + + +
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+
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#include <stan/math/fwd/core.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+
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template<typename T >
fvar< T > stan::math::lgamma (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2lgamma_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2lgamma_8hpp_source.html new file mode 100644 index 00000000000..d9aa9b29bb2 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2lgamma_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/lgamma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LGAMMA_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LGAMMA_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 #include <boost/math/special_functions/digamma.hpp>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  lgamma(const fvar<T>& x) {
+ +
17  using boost::math::lgamma;
+
18  return fvar<T>(lgamma(x.val_), x.d_ * digamma(x.val_));
+
19  }
+
20  }
+
21 }
+
22 #endif
+ + +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
var lgamma(const stan::math::var &a)
The log gamma function for variables (C99).
Definition: lgamma.hpp:35
+ + +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2lmgamma_8hpp.html b/doc/api/html/fwd_2scal_2fun_2lmgamma_8hpp.html new file mode 100644 index 00000000000..86fa90f00dd --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2lmgamma_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/lmgamma.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< typename stan::return_type< T, int >::type > stan::math::lmgamma (int x1, const fvar< T > &x2)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2lmgamma_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2lmgamma_8hpp_source.html new file mode 100644 index 00000000000..49c7585cad7 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2lmgamma_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/lmgamma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LMGAMMA_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LMGAMMA_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  fvar<typename stan::return_type<T, int>::type>
+
16  lmgamma(int x1, const fvar<T>& x2) {
+
17  using stan::math::lmgamma;
+
18  using stan::math::digamma;
+
19  using std::log;
+
20  T deriv = 0;
+
21  for (int count = 1; count < x1 + 1; count++)
+
22  deriv += x2.d_ * digamma(x2.val_ + (1.0 - count) / 2.0);
+
23  return fvar<typename
+ +
25  }
+
26  }
+
27 }
+
28 #endif
+ + + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
fvar< typename stan::return_type< T, int >::type > lmgamma(int x1, const fvar< T > &x2)
Definition: lmgamma.hpp:16
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log10_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log10_8hpp.html new file mode 100644 index 00000000000..21d36f1b20a --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log10_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log10.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::log10 (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log10_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log10_8hpp_source.html new file mode 100644 index 00000000000..cda21fba0cd --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log10_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log10.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG10_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG10_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  log10(const fvar<T>& x) {
+
16  using std::log;
+
17  using std::log10;
+ +
19  if (x.val_ < 0.0)
+ +
21  else
+
22  return fvar<T>(log10(x.val_), x.d_ / (x.val_ * stan::math::LOG_10));
+
23  }
+
24  }
+
25 }
+
26 #endif
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
var log10(const var &a)
Return the base 10 log of the specified variable (cmath).
Definition: log10.hpp:54
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
const double LOG_10
The natural logarithm of 10, .
Definition: constants.hpp:39
+
fvar< T > log10(const fvar< T > &x)
Definition: log10.hpp:15
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2fun_2log1m_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log1m_8hpp.html new file mode 100644 index 00000000000..5b40406edc8 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1m_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1m.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::log1m (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1m_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log1m_8hpp_source.html new file mode 100644 index 00000000000..94e9ead0e97 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1m_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1m.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG1M_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG1M_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  fvar<T>
+
16  log1m(const fvar<T>& x) {
+
17  using stan::math::log1m;
+ +
19  if (x.val_ > 1.0)
+ +
21  else
+
22  return fvar<T>(log1m(x.val_), -x.d_ / (1 - x.val_));
+
23  }
+
24  }
+
25 }
+
26 #endif
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ + + + +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1m__exp_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log1m__exp_8hpp.html new file mode 100644 index 00000000000..eaf92566cfa --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1m__exp_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1m_exp.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1m__exp_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log1m__exp_8hpp_source.html new file mode 100644 index 00000000000..dca46b38f17 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1m__exp_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1m_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG1M_EXP_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG1M_EXP_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  fvar<T>
+
16  log1m_exp(const fvar<T>& x) {
+ + + +
20  if (x.val_ >= 0)
+
21  return fvar<T>(NOT_A_NUMBER);
+
22  return fvar<T>(log1m_exp(x.val_), x.d_ / -expm1(-x.val_));
+
23  }
+
24 
+
25  }
+
26 }
+
27 #endif
+ + + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
fvar< T > expm1(const fvar< T > &x)
Definition: expm1.hpp:12
+ +
fvar< T > log1m_exp(const fvar< T > &x)
Definition: log1m_exp.hpp:16
+ + + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1m__inv__logit_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log1m__inv__logit_8hpp.html new file mode 100644 index 00000000000..a22205577c1 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1m__inv__logit_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1m_inv_logit.hpp File Reference + + + + + + + + + + +
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fvar< T > stan::math::log1m_inv_logit (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1m__inv__logit_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log1m__inv__logit_8hpp_source.html new file mode 100644 index 00000000000..a0c6a011fbf --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1m__inv__logit_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1m_inv_logit.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG1M_INV_LOGIT_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG1M_INV_LOGIT_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+ +
16  using std::exp;
+ +
18  return fvar<T>(log1m_inv_logit(x.val_),
+
19  -x.d_ / (1 + exp(-x.val_)));
+
20  }
+
21  }
+
22 }
+
23 #endif
+
fvar< T > log1m_inv_logit(const fvar< T > &x)
+ + + + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1p_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log1p_8hpp.html new file mode 100644 index 00000000000..31b53dd7ae9 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1p_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1p.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::log1p (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1p_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log1p_8hpp_source.html new file mode 100644 index 00000000000..3ff9855ccbe --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1p_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1p.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG1P_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG1P_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline
+
15  fvar<T>
+
16  log1p(const fvar<T>& x) {
+
17  using stan::math::log1p;
+ +
19  if (x.val_ < -1.0)
+ +
21  else
+
22  return fvar<T>(log1p(x.val_), x.d_ / (1 + x.val_));
+
23  }
+
24  }
+
25 }
+
26 #endif
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ + + +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1p__exp_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log1p__exp_8hpp.html new file mode 100644 index 00000000000..0c6c858b7ea --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1p__exp_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1p_exp.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::log1p_exp (const fvar< T > &x)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log1p__exp_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log1p__exp_8hpp_source.html new file mode 100644 index 00000000000..bf758c41c50 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log1p__exp_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log1p_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG1P_EXP_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG1P_EXP_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline
+
12  fvar<T>
+
13  log1p_exp(const fvar<T>& x) {
+ +
15  using std::exp;
+
16  return fvar<T>(log1p_exp(x.val_), x.d_ / (1 + exp(-x.val_)));
+
17  }
+
18 
+
19  }
+
20 }
+
21 #endif
+ + + + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
fvar< T > log1p_exp(const fvar< T > &x)
Definition: log1p_exp.hpp:13
+ +
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diff --git a/doc/api/html/fwd_2scal_2fun_2log2_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log2_8hpp.html new file mode 100644 index 00000000000..a9e799343ac --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log2_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log2.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::log2 (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2log2_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log2_8hpp_source.html new file mode 100644 index 00000000000..ae93de59d7d --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log2_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log2.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG2_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG2_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + +
8 
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  template <typename T>
+
15  inline
+
16  fvar<T>
+
17  log2(const fvar<T>& x) {
+
18  using std::log;
+
19  using stan::math::log2;
+ +
21  if (x.val_ < 0.0)
+ +
23  else
+
24  return fvar<T>(log2(x.val_), x.d_ / (x.val_ * stan::math::LOG_2));
+
25  }
+
26  }
+
27 }
+
28 #endif
+
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:33
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ + + +
fvar< T > log2(const fvar< T > &x)
Definition: log2.hpp:17
+ +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log_8hpp.html new file mode 100644 index 00000000000..a399b346422 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::log (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2log_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log_8hpp_source.html new file mode 100644 index 00000000000..8153992ce92 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  log(const fvar<T>& x) {
+
16  using std::log;
+ +
18  if (x.val_ < 0.0)
+ +
20  else
+
21  return fvar<T>(log(x.val_), x.d_ / x.val_);
+
22  }
+
23  }
+
24 }
+
25 #endif
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
var log(const var &a)
Return the natural log of the specified variable (cmath).
Definition: log.hpp:50
+ + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__diff__exp_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log__diff__exp_8hpp.html new file mode 100644 index 00000000000..87c03b00804 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__diff__exp_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_diff_exp.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::log_diff_exp (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T1 , typename T2 >
fvar< T2 > stan::math::log_diff_exp (const T1 &x1, const fvar< T2 > &x2)
 
template<typename T1 , typename T2 >
fvar< T1 > stan::math::log_diff_exp (const fvar< T1 > &x1, const T2 &x2)
 
+
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+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__diff__exp_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log__diff__exp_8hpp_source.html new file mode 100644 index 00000000000..c577cce20dd --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__diff__exp_8hpp_source.html @@ -0,0 +1,167 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_diff_exp.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_DIFF_EXP_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_DIFF_EXP_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename T> inline fvar<T>
+
14  log_diff_exp(const fvar<T>& x1, const fvar<T>& x2) {
+ + +
17  using std::exp;
+
18  if (x1.val_ <= x2.val_)
+ +
20  return fvar<T>(log_diff_exp(x1.val_, x2.val_),
+
21  x1.d_ / (1 - exp(x2.val_ - x1.val_))
+
22  + x2.d_ / (1 - exp(x1.val_ - x2.val_)));
+
23  }
+
24 
+
25  template <typename T1, typename T2> inline fvar<T2>
+
26  log_diff_exp(const T1& x1, const fvar<T2>& x2) {
+ + +
29  using std::exp;
+
30  if (x1 <= x2.val_)
+ +
32  return fvar<T2>(log_diff_exp(x1, x2.val_),
+
33  x2.d_ / (1 - exp(x1 - x2.val_)));
+
34  }
+
35 
+
36  template <typename T1, typename T2> inline fvar<T1>
+
37  log_diff_exp(const fvar<T1>& x1, const T2& x2) {
+ + +
40  using std::exp;
+
41  if (x1.val_ <= x2)
+ +
43  return fvar<T1>(log_diff_exp(x1.val_, x2),
+
44  x1.d_ / (1 - exp(x2 - x1.val_)));
+
45  }
+
46  }
+
47 }
+
48 #endif
+ + + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
fvar< T > log_diff_exp(const fvar< T > &x1, const fvar< T > &x2)
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__falling__factorial_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log__falling__factorial_8hpp.html new file mode 100644 index 00000000000..1a3ce73eacb --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__falling__factorial_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_falling_factorial.hpp File Reference + + + + + + + + + + +
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log_falling_factorial.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/log_falling_factorial.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+
+

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template<typename T >
fvar< T > stan::math::log_falling_factorial (const fvar< T > &x, const fvar< T > &n)
 
template<typename T >
fvar< T > stan::math::log_falling_factorial (const double x, const fvar< T > &n)
 
template<typename T >
fvar< T > stan::math::log_falling_factorial (const fvar< T > &x, const double n)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__falling__factorial_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log__falling__factorial_8hpp_source.html new file mode 100644 index 00000000000..f0fa9f601df --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__falling__factorial_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_falling_factorial.hpp Source File + + + + + + + + + + +
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log_falling_factorial.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_FALLING_FACTORIAL_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_FALLING_FACTORIAL_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 #include <boost/math/special_functions/digamma.hpp>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template<typename T>
+
14  inline fvar<T>
+
15  log_falling_factorial(const fvar<T>& x, const fvar<T>& n) {
+ + +
18 
+ +
20  (digamma(x.val_ + 1)
+
21  - digamma(x.val_ - n.val_ + 1)) * x.d_
+
22  + digamma(x.val_ - n.val_ + 1) * n.d_);
+
23  }
+
24 
+
25  template<typename T>
+
26  inline fvar<T>
+
27  log_falling_factorial(const double x, const fvar<T>& n) {
+ + +
30 
+
31  return fvar<T>(log_falling_factorial(x, n.val_),
+
32  digamma(x - n.val_ + 1) * n.d_);
+
33  }
+
34 
+
35  template<typename T>
+
36  inline fvar<T>
+
37  log_falling_factorial(const fvar<T>& x, const double n) {
+ + +
40 
+
41  return fvar<T>(log_falling_factorial(x.val_, n),
+
42  (digamma(x.val_ + 1)
+
43  - digamma(x.val_ - n + 1)) * x.d_);
+
44  }
+
45  }
+
46 }
+
47 #endif
+ +
fvar< T > log_falling_factorial(const fvar< T > &x, const fvar< T > &n)
+ + + + + +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__inv__logit_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log__inv__logit_8hpp.html new file mode 100644 index 00000000000..30c24fa1426 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__inv__logit_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_inv_logit.hpp File Reference + + + + + + + + + + +
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log_inv_logit.hpp File Reference
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+ + + + +

+Functions

template<typename T >
fvar< T > stan::math::log_inv_logit (const fvar< T > &x)
 
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__inv__logit_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log__inv__logit_8hpp_source.html new file mode 100644 index 00000000000..d82b748ee58 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__inv__logit_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_inv_logit.hpp Source File + + + + + + + + + + +
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log_inv_logit.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_INV_LOGIT_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_INV_LOGIT_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  log_inv_logit(const fvar<T>& x) {
+
16  using std::exp;
+ +
18  return fvar<T>(log_inv_logit(x.val_),
+
19  x.d_ / (1 + exp(x.val_)));
+
20  }
+
21  }
+
22 }
+
23 #endif
+ + + + + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > log_inv_logit(const fvar< T > &x)
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__mix_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log__mix_8hpp.html new file mode 100644 index 00000000000..749a7b81b0e --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__mix_8hpp.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_mix.hpp File Reference + + + + + + + + + + +
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log_mix.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <stan/math/prim/scal/fun/log_mix.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <cmath>
+
+

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+Functions

template<typename T_theta , typename T_lambda1 , typename T_lambda2 , int N>
void stan::math::log_mix_partial_helper (const T_theta &theta, const T_lambda1 &lambda1, const T_lambda2 &lambda2, typename boost::math::tools::promote_args< T_theta, T_lambda1, T_lambda2 >::type(&partials_array)[N])
 
template<typename T >
fvar< T > stan::math::log_mix (const fvar< T > &theta, const fvar< T > &lambda1, const fvar< T > &lambda2)
 Return the log mixture density with specified mixing proportion and log densities and its derivative at each. More...
 
template<typename T >
fvar< T > stan::math::log_mix (const fvar< T > &theta, const fvar< T > &lambda1, const double lambda2)
 
template<typename T >
fvar< T > stan::math::log_mix (const fvar< T > &theta, const double lambda1, const fvar< T > &lambda2)
 
template<typename T >
fvar< T > stan::math::log_mix (const double theta, const fvar< T > &lambda1, const fvar< T > &lambda2)
 
template<typename T >
fvar< T > stan::math::log_mix (const fvar< T > &theta, const double lambda1, const double lambda2)
 
template<typename T >
fvar< T > stan::math::log_mix (const double theta, const fvar< T > &lambda1, const double lambda2)
 
template<typename T >
fvar< T > stan::math::log_mix (const double theta, const double lambda1, const fvar< T > &lambda2)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__mix_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log__mix_8hpp_source.html new file mode 100644 index 00000000000..f0722489555 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__mix_8hpp_source.html @@ -0,0 +1,359 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_mix.hpp Source File + + + + + + + + + + +
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log_mix.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_MIX_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_MIX_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + +
7 #include <boost/math/tools/promotion.hpp>
+
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  /* Returns an array of size N with partials of log_mix wrt to its
+
15  * parameters instantiated as fvar<T>
+
16  *
+
17  * @tparam T_theta theta scalar type
+
18  * @tparam T_lambda1 lambda_1 scalar type
+
19  * @tparam T_lambda2 lambda_2 scalar type
+
20  *
+
21  * @param[in] N output array size
+
22  * @param[in] theta_d mixing proportion theta
+
23  * @param[in] lambda1_d log_density with mixing proportion theta
+
24  * @param[in] lambda2_d log_density with mixing proportion 1.0 - theta
+
25  * @param[out] partials_array array of partials derivatives
+
26  */
+
27  template <typename T_theta, typename T_lambda1, typename T_lambda2, int N>
+
28  inline void
+
29  log_mix_partial_helper(const T_theta& theta,
+
30  const T_lambda1& lambda1,
+
31  const T_lambda2& lambda2,
+
32  typename
+
33  boost::math::tools::promote_args<
+
34  T_theta, T_lambda1, T_lambda2>::type
+
35  (&partials_array)[N]) {
+
36  using std::exp;
+
37  using boost::is_same;
+
38  using boost::math::tools::promote_args;
+
39  typedef typename promote_args<T_theta, T_lambda1, T_lambda2>::type
+
40  partial_return_type;
+
41 
+
42  typename promote_args<T_lambda1, T_lambda2>::type lam2_m_lam1
+
43  = lambda2 - lambda1;
+
44  typename promote_args<T_lambda1, T_lambda2>::type exp_lam2_m_lam1
+
45  = exp(lam2_m_lam1);
+
46  typename promote_args<T_lambda1, T_lambda2>::type one_m_exp_lam2_m_lam1
+
47  = 1.0 - exp_lam2_m_lam1;
+
48  typename promote_args<double, T_theta>::type one_m_t = 1.0 - theta;
+
49  partial_return_type one_m_t_prod_exp_lam2_m_lam1
+
50  = one_m_t * exp_lam2_m_lam1;
+
51  partial_return_type t_plus_one_m_t_prod_exp_lam2_m_lam1
+
52  = theta + one_m_t_prod_exp_lam2_m_lam1;
+
53  partial_return_type one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1
+
54  = 1.0 / t_plus_one_m_t_prod_exp_lam2_m_lam1;
+
55 
+
56  unsigned int offset = 0;
+
57  if (is_same<T_theta, partial_return_type>::value) {
+
58  partials_array[offset]
+
59  = one_m_exp_lam2_m_lam1
+
60  * one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1;
+
61  ++offset;
+
62  }
+
63  if (is_same<T_lambda1, partial_return_type>::value) {
+
64  partials_array[offset]
+
65  = theta * one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1;
+
66  ++offset;
+
67  }
+
68  if (is_same<T_lambda2, partial_return_type>::value) {
+
69  partials_array[offset]
+
70  = one_m_t_prod_exp_lam2_m_lam1
+
71  * one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1;
+
72  }
+
73  }
+
74 
+
114  template <typename T>
+
115  inline
+
116  fvar<T>
+
117  log_mix(const fvar<T>& theta, const fvar<T>& lambda1,
+
118  const fvar<T>& lambda2) {
+
119  using stan::math::log_mix;
+
120  using stan::math::value_of;
+
121 
+
122  if (lambda1.val_ > lambda2.val_) {
+
123  fvar<T> partial_deriv_array[3];
+
124  log_mix_partial_helper(theta, lambda1, lambda2, partial_deriv_array);
+
125  return fvar<T>(log_mix(theta.val_, lambda1.val_, lambda2.val_),
+
126  theta.d_ * value_of(partial_deriv_array[0])
+
127  + lambda1.d_ * value_of(partial_deriv_array[1])
+
128  + lambda2.d_ * value_of(partial_deriv_array[2]));
+
129  } else {
+
130  fvar<T> partial_deriv_array[3];
+
131  log_mix_partial_helper(1.0 - theta, lambda2, lambda1,
+
132  partial_deriv_array);
+
133  return fvar<T>(log_mix(theta.val_, lambda1.val_, lambda2.val_),
+
134  -theta.d_ * value_of(partial_deriv_array[0])
+
135  + lambda1.d_ * value_of(partial_deriv_array[2])
+
136  + lambda2.d_ * value_of(partial_deriv_array[1]));
+
137  }
+
138  }
+
139 
+
140  template <typename T>
+
141  inline
+
142  fvar<T>
+
143  log_mix(const fvar<T>& theta, const fvar<T>& lambda1,
+
144  const double lambda2) {
+
145  using stan::math::log_mix;
+
146  using stan::math::value_of;
+
147 
+
148  if (lambda1.val_ > lambda2) {
+
149  fvar<T> partial_deriv_array[2];
+
150  log_mix_partial_helper(theta, lambda1, lambda2,
+
151  partial_deriv_array);
+
152  return fvar<T>(log_mix(theta.val_, lambda1.val_, lambda2),
+
153  theta.d_ * value_of(partial_deriv_array[0])
+
154  + lambda1.d_ * value_of(partial_deriv_array[1]));
+
155  } else {
+
156  fvar<T> partial_deriv_array[2];
+
157  log_mix_partial_helper(1.0 - theta, lambda2, lambda1,
+
158  partial_deriv_array);
+
159  return fvar<T>(log_mix(theta.val_, lambda1.val_, lambda2),
+
160  -theta.d_ * value_of(partial_deriv_array[0])
+
161  + lambda1.d_ * value_of(partial_deriv_array[1]));
+
162  }
+
163  }
+
164 
+
165  template<typename T>
+
166  inline
+
167  fvar<T>
+
168  log_mix(const fvar<T>& theta, const double lambda1,
+
169  const fvar<T>& lambda2) {
+
170  using stan::math::log_mix;
+
171  using stan::math::value_of;
+
172 
+
173  if (lambda1 > lambda2.val_) {
+
174  fvar<T> partial_deriv_array[2];
+
175  log_mix_partial_helper(theta, lambda1, lambda2,
+
176  partial_deriv_array);
+
177  return fvar<T>(log_mix(theta.val_, lambda1, lambda2.val_),
+
178  theta.d_ * value_of(partial_deriv_array[0])
+
179  + lambda2.d_ * value_of(partial_deriv_array[1]));
+
180  } else {
+
181  fvar<T> partial_deriv_array[2];
+
182  log_mix_partial_helper(1.0 - theta, lambda2, lambda1,
+
183  partial_deriv_array);
+
184  return fvar<T>(log_mix(theta.val_, lambda1, lambda2.val_),
+
185  -theta.d_ * value_of(partial_deriv_array[0])
+
186  + lambda2.d_ * value_of(partial_deriv_array[1]));
+
187  }
+
188  }
+
189 
+
190  template<typename T>
+
191  inline
+
192  fvar<T>
+
193  log_mix(const double theta, const fvar<T>& lambda1,
+
194  const fvar<T>& lambda2) {
+
195  using stan::math::log_mix;
+
196  using stan::math::value_of;
+
197 
+
198  if (lambda1.val_ > lambda2.val_) {
+
199  fvar<T> partial_deriv_array[2];
+
200  log_mix_partial_helper(theta, lambda1, lambda2, partial_deriv_array);
+
201  return fvar<T>(log_mix(theta, lambda1.val_, lambda2.val_),
+
202  lambda1.d_ * value_of(partial_deriv_array[0])
+
203  + lambda2.d_ * value_of(partial_deriv_array[1]));
+
204  } else {
+
205  fvar<T> partial_deriv_array[2];
+
206  log_mix_partial_helper(1.0 - theta, lambda2, lambda1,
+
207  partial_deriv_array);
+
208  return fvar<T>(log_mix(theta, lambda1.val_, lambda2.val_),
+
209  lambda1.d_ * value_of(partial_deriv_array[1])
+
210  + lambda2.d_ * value_of(partial_deriv_array[0]));
+
211  }
+
212  }
+
213 
+
214  template<typename T>
+
215  inline
+
216  fvar<T>
+
217  log_mix(const fvar<T>& theta, const double lambda1, const double lambda2) {
+
218  using stan::math::log_mix;
+
219  using stan::math::value_of;
+
220 
+
221  if (lambda1 > lambda2) {
+
222  fvar<T> partial_deriv_array[1];
+
223  log_mix_partial_helper(theta, lambda1, lambda2, partial_deriv_array);
+
224  return fvar<T>(log_mix(theta.val_, lambda1, lambda2),
+
225  theta.d_ * value_of(partial_deriv_array[0]));
+
226  } else {
+
227  fvar<T> partial_deriv_array[1];
+
228  log_mix_partial_helper(1.0 - theta, lambda2, lambda1,
+
229  partial_deriv_array);
+
230  return fvar<T>(log_mix(theta.val_, lambda1, lambda2),
+
231  -theta.d_ * value_of(partial_deriv_array[0]));
+
232  }
+
233  }
+
234 
+
235  template<typename T>
+
236  inline
+
237  fvar<T>
+
238  log_mix(const double theta, const fvar<T>& lambda1, const double lambda2) {
+
239  using stan::math::log_mix;
+
240  using stan::math::value_of;
+
241 
+
242  if (lambda1.val_ > lambda2) {
+
243  fvar<T> partial_deriv_array[1];
+
244  log_mix_partial_helper(theta, lambda1, lambda2, partial_deriv_array);
+
245  return fvar<T>(log_mix(theta, lambda1.val_, lambda2),
+
246  lambda1.d_ * value_of(partial_deriv_array[0]));
+
247  } else {
+
248  fvar<T> partial_deriv_array[1];
+
249  log_mix_partial_helper(1.0 - theta, lambda2, lambda1,
+
250  partial_deriv_array);
+
251  return fvar<T>(log_mix(theta, lambda1.val_, lambda2),
+
252  lambda1.d_ * value_of(partial_deriv_array[0]));
+
253  }
+
254  }
+
255 
+
256  template<typename T>
+
257  inline
+
258  fvar<T>
+
259  log_mix(const double theta, const double lambda1, const fvar<T>& lambda2) {
+
260  using stan::math::log_mix;
+
261  using stan::math::value_of;
+
262 
+
263  if (lambda1 > lambda2.val_) {
+
264  fvar<T> partial_deriv_array[1];
+
265  log_mix_partial_helper(theta, lambda1, lambda2, partial_deriv_array);
+
266  return fvar<T>(log_mix(theta, lambda1, lambda2.val_),
+
267  lambda2.d_ * value_of(partial_deriv_array[0]));
+
268  } else {
+
269  fvar<T> partial_deriv_array[1];
+
270  log_mix_partial_helper(1.0 - theta, lambda2, lambda1,
+
271  partial_deriv_array);
+
272  return fvar<T>(log_mix(theta, lambda1, lambda2.val_),
+
273  lambda2.d_ * value_of(partial_deriv_array[0]));
+
274  }
+
275  }
+
276  }
+
277 }
+
278 #endif
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
void log_mix_partial_helper(const T_theta &theta, const T_lambda1 &lambda1, const T_lambda2 &lambda2, typename boost::math::tools::promote_args< T_theta, T_lambda1, T_lambda2 >::type(&partials_array)[N])
Definition: log_mix.hpp:29
+ +
fvar< T > log_mix(const fvar< T > &theta, const fvar< T > &lambda1, const fvar< T > &lambda2)
Return the log mixture density with specified mixing proportion and log densities and its derivative ...
Definition: log_mix.hpp:117
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__rising__factorial_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log__rising__factorial_8hpp.html new file mode 100644 index 00000000000..6e23168ad85 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__rising__factorial_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_rising_factorial.hpp File Reference + + + + + + + + + + +
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#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/scal/fun/log_rising_factorial.hpp>
+#include <boost/math/special_functions/digamma.hpp>
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template<typename T >
fvar< T > stan::math::log_rising_factorial (const fvar< T > &x, const fvar< T > &n)
 
template<typename T >
fvar< T > stan::math::log_rising_factorial (const fvar< T > &x, const double n)
 
template<typename T >
fvar< T > stan::math::log_rising_factorial (const double x, const fvar< T > &n)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__rising__factorial_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log__rising__factorial_8hpp_source.html new file mode 100644 index 00000000000..26d1ecfbb88 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__rising__factorial_8hpp_source.html @@ -0,0 +1,165 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_rising_factorial.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_RISING_FACTORIAL_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_RISING_FACTORIAL_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 #include <boost/math/special_functions/digamma.hpp>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template<typename T>
+
14  inline
+
15  fvar<T>
+
16  log_rising_factorial(const fvar<T>& x, const fvar<T>& n) {
+ + +
19 
+ +
21  (digamma(x.val_ + n.val_) * (x.d_ + n.d_)
+
22  - digamma(x.val_) * x.d_));
+
23  }
+
24 
+
25  template<typename T>
+
26  inline
+
27  fvar<T>
+
28  log_rising_factorial(const fvar<T>& x, const double n) {
+ + +
31 
+
32  return fvar<T>(log_rising_factorial(x.val_, n),
+
33  (digamma(x.val_ + n) - digamma(x.val_)) * x.d_);
+
34  }
+
35 
+
36  template<typename T>
+
37  inline
+
38  fvar<T>
+
39  log_rising_factorial(const double x, const fvar<T>& n) {
+ + +
42 
+
43  return fvar<T>(log_rising_factorial(x, n.val_),
+
44  (digamma(x + n.val_) * n.d_));
+
45  }
+
46  }
+
47 }
+
48 #endif
+ + + + + +
fvar< T > log_rising_factorial(const fvar< T > &x, const fvar< T > &n)
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__sum__exp_8hpp.html b/doc/api/html/fwd_2scal_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..9a9f12e5aec --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::log_sum_exp (const fvar< T > &x1, const fvar< T > &x2)
 
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fvar< T > stan::math::log_sum_exp (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::log_sum_exp (const fvar< T > &x1, const double x2)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..11575ce74f9 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_SUM_EXP_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  log_sum_exp(const fvar<T>& x1, const fvar<T>& x2) {
+ +
17  using std::exp;
+
18  return fvar<T>(log_sum_exp(x1.val_, x2.val_),
+
19  x1.d_ / (1 + exp(x2.val_ - x1.val_))
+
20  + x2.d_ / (exp(x1.val_ - x2.val_) + 1));
+
21  }
+
22 
+
23  template <typename T>
+
24  inline
+
25  fvar<T>
+
26  log_sum_exp(const double x1, const fvar<T>& x2) {
+ +
28  using std::exp;
+
29  return fvar<T>(log_sum_exp(x1, x2.val_),
+
30  x2.d_ / (exp(x1 - x2.val_) + 1));
+
31  }
+
32 
+
33  template <typename T>
+
34  inline
+
35  fvar<T>
+
36  log_sum_exp(const fvar<T>& x1, const double x2) {
+ +
38  using std::exp;
+
39  return fvar<T>(log_sum_exp(x1.val_, x2),
+
40  x1.d_ / (1 + exp(x2 - x1.val_)));
+
41  }
+
42 
+
43  }
+
44 }
+
45 #endif
+ + + +
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
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diff --git a/doc/api/html/fwd_2scal_2fun_2logit_8hpp.html b/doc/api/html/fwd_2scal_2fun_2logit_8hpp.html new file mode 100644 index 00000000000..1fd1e47badc --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2logit_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/logit.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::logit (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2logit_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2logit_8hpp_source.html new file mode 100644 index 00000000000..dbbf03d8fbf --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2logit_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/logit.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOGIT_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_LOGIT_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + + +
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  template <typename T>
+
15  inline
+
16  fvar<T>
+
17  logit(const fvar<T>& x) {
+
18  using stan::math::logit;
+
19  using stan::math::square;
+ +
21  if (x.val_ > 1 || x.val_ < 0)
+ +
23  else
+
24  return fvar<T>(logit(x.val_), x.d_ / (x.val_ - square(x.val_)));
+
25  }
+
26  }
+
27 }
+
28 #endif
+ + +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
fvar< T > logit(const fvar< T > &x)
Definition: logit.hpp:17
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diff --git a/doc/api/html/fwd_2scal_2fun_2modified__bessel__first__kind_8hpp.html b/doc/api/html/fwd_2scal_2fun_2modified__bessel__first__kind_8hpp.html new file mode 100644 index 00000000000..942eb15d0e9 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2modified__bessel__first__kind_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/modified_bessel_first_kind.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::modified_bessel_first_kind (int v, const fvar< T > &z)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html new file mode 100644 index 00000000000..8498709be43 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/modified_bessel_first_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_MODIFIED_BESSEL_FIRST_KIND_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_MODIFIED_BESSEL_FIRST_KIND_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+ + +
17 
+
18  T modified_bessel_first_kind_z(modified_bessel_first_kind(v, z.val_));
+
19  return fvar<T>(modified_bessel_first_kind_z,
+
20  -v * z.d_ * modified_bessel_first_kind_z / z.val_
+
21  + z.d_ * modified_bessel_first_kind(v - 1, z.val_));
+
22  }
+
23  }
+
24 }
+
25 #endif
+ + + + +
fvar< T > modified_bessel_first_kind(int v, const fvar< T > &z)
+ + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2modified__bessel__second__kind_8hpp.html b/doc/api/html/fwd_2scal_2fun_2modified__bessel__second__kind_8hpp.html new file mode 100644 index 00000000000..44c21fd5034 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2modified__bessel__second__kind_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/modified_bessel_second_kind.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::modified_bessel_second_kind (int v, const fvar< T > &z)
 
+
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html new file mode 100644 index 00000000000..8458796ce0b --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/modified_bessel_second_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_MODIFIED_BESSEL_SECOND_KIND_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_MODIFIED_BESSEL_SECOND_KIND_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+ + +
17 
+
18  T modified_bessel_second_kind_z(modified_bessel_second_kind(v, z.val_));
+
19  return fvar<T>(modified_bessel_second_kind_z,
+
20  -v * z.d_ * modified_bessel_second_kind_z / z.val_
+
21  - z.d_ * modified_bessel_second_kind(v - 1, z.val_));
+
22  }
+
23  }
+
24 }
+
25 #endif
+
fvar< T > modified_bessel_second_kind(int v, const fvar< T > &z)
+ + + + + + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2multiply__log_8hpp.html b/doc/api/html/fwd_2scal_2fun_2multiply__log_8hpp.html new file mode 100644 index 00000000000..a13f3730041 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2multiply__log_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/multiply_log.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::multiply_log (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::multiply_log (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::multiply_log (const fvar< T > &x1, const double x2)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2multiply__log_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2multiply__log_8hpp_source.html new file mode 100644 index 00000000000..b37c60798da --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2multiply__log_8hpp_source.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/multiply_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_MULTIPLY_LOG_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_MULTIPLY_LOG_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  multiply_log(const fvar<T>& x1, const fvar<T>& x2) {
+ +
17  using std::log;
+
18  return fvar<T>(multiply_log(x1.val_, x2.val_),
+
19  x1.d_ * log(x2.val_) + x1.val_ * x2.d_ / x2.val_);
+
20  }
+
21 
+
22  template <typename T>
+
23  inline
+
24  fvar<T>
+
25  multiply_log(const double x1, const fvar<T>& x2) {
+ +
27  using std::log;
+
28  return fvar<T>(multiply_log(x1, x2.val_),
+
29  x1 * x2.d_ / x2.val_);
+
30  }
+
31 
+
32  template <typename T>
+
33  inline
+
34  fvar<T>
+
35  multiply_log(const fvar<T>& x1, const double x2) {
+ +
37  using std::log;
+
38  return fvar<T>(multiply_log(x1.val_, x2),
+
39  x1.d_ * log(x2));
+
40  }
+
41  }
+
42 }
+
43 #endif
+ + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
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diff --git a/doc/api/html/fwd_2scal_2fun_2owens__t_8hpp.html b/doc/api/html/fwd_2scal_2fun_2owens__t_8hpp.html new file mode 100644 index 00000000000..31b8c97efb3 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2owens__t_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/owens_t.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::owens_t (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::owens_t (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::owens_t (const fvar< T > &x1, const double x2)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2owens__t_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2owens__t_8hpp_source.html new file mode 100644 index 00000000000..d75f04ee1d4 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2owens__t_8hpp_source.html @@ -0,0 +1,190 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/owens_t.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_OWENS_T_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_OWENS_T_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T>
+
14  inline fvar<T> owens_t(const fvar<T>& x1, const fvar<T>& x2) {
+
15  using stan::math::owens_t;
+
16  using stan::math::pi;
+ + +
19  using stan::math::square;
+
20  using std::exp;
+ +
22 
+
23  T neg_x1_sq_div_2 = -square(x1.val_) * 0.5;
+
24  T one_p_x2_sq = 1.0 + square(x2.val_);
+
25  return fvar<T>(owens_t(x1.val_, x2.val_),
+
26  - x1.d_
+
27  * (erf(x2.val_ * x1.val_ * INV_SQRT_2)
+
28  * exp(neg_x1_sq_div_2) * INV_SQRT_TWO_PI * 0.5)
+
29  + x2.d_ * exp(neg_x1_sq_div_2 * one_p_x2_sq)
+
30  / (one_p_x2_sq * 2.0 * pi()));
+
31  }
+
32 
+
33  template <typename T>
+
34  inline fvar<T> owens_t(const double x1, const fvar<T>& x2) {
+
35  using stan::math::owens_t;
+
36  using stan::math::pi;
+
37  using stan::math::square;
+
38  using std::exp;
+
39 
+
40  T neg_x1_sq_div_2 = -square(x1) * 0.5;
+
41  T one_p_x2_sq = 1.0 + square(x2.val_);
+
42  return fvar<T>(owens_t(x1, x2.val_),
+
43  x2.d_ * exp(neg_x1_sq_div_2 * one_p_x2_sq)
+
44  / (one_p_x2_sq * 2.0 * pi()));
+
45  }
+
46 
+
47  template <typename T>
+
48  inline fvar<T> owens_t(const fvar<T>& x1, const double x2) {
+
49  using stan::math::owens_t;
+
50  using stan::math::pi;
+
51  using stan::math::square;
+ + +
54  using std::exp;
+ +
56 
+
57  T neg_x1_sq_div_2 = -square(x1.val_) * 0.5;
+
58  return fvar<T>(owens_t(x1.val_, x2),
+
59  -x1.d_ * (erf(x2 * x1.val_ * INV_SQRT_2)
+
60  * exp(neg_x1_sq_div_2)
+
61  * INV_SQRT_TWO_PI * 0.5));
+
62  }
+
63 
+
64  }
+
65 }
+
66 #endif
+
const double INV_SQRT_TWO_PI
Definition: constants.hpp:166
+ + + + +
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
fvar< T > owens_t(const fvar< T > &x1, const fvar< T > &x2)
Definition: owens_t.hpp:14
+ +
const double INV_SQRT_2
The value of 1 over the square root of 2, .
Definition: constants.hpp:27
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2fun_2pow_8hpp.html b/doc/api/html/fwd_2scal_2fun_2pow_8hpp.html new file mode 100644 index 00000000000..2bddec31114 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2pow_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/pow.hpp File Reference + + + + + + + + + + +
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template<typename T >
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template<typename T >
fvar< T > stan::math::pow (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > stan::math::pow (const fvar< T > &x1, const double x2)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2pow_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2pow_8hpp_source.html new file mode 100644 index 00000000000..979033769de --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2pow_8hpp_source.html @@ -0,0 +1,193 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/pow.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_POW_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_POW_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ + + + +
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15  template <typename T>
+
16  inline
+
17  fvar<T>
+
18  pow(const fvar<T>& x1, const fvar<T>& x2) {
+
19  using std::pow;
+
20  using std::log;
+
21  T pow_x1_x2(pow(x1.val_, x2.val_));
+
22  return fvar<T>(pow_x1_x2,
+
23  (x2.d_ * log(x1.val_)
+
24  + x2.val_ * x1.d_ / x1.val_) * pow_x1_x2);
+
25  }
+
26 
+
27  template <typename T>
+
28  inline
+
29  fvar<T>
+
30  pow(const double x1, const fvar<T>& x2) {
+
31  using std::pow;
+
32  using std::log;
+
33  T u = pow(x1, x2.val_);
+
34  return fvar<T>(u, x2.d_ * log(x1) * u);
+
35  }
+
36 
+
37  template <typename T>
+
38  inline
+
39  fvar<T>
+
40  pow(const fvar<T>& x1, const double x2) {
+
41  using std::pow;
+
42  using stan::math::sqrt;
+
43  using stan::math::inv;
+ + +
46  using std::sqrt;
+
47  using stan::math::square;
+
48 
+
49  if (x2 == -2)
+
50  return inv_square(x1);
+
51  if (x2 == -1)
+
52  return inv(x1);
+
53  if (x2 == -0.5)
+
54  return inv_sqrt(x1);
+
55  if (x2 == 0.5)
+
56  return sqrt(x1);
+
57  if (x2 == 1.0)
+
58  return x1;
+
59  if (x2 == 2.0)
+
60  return square(x1);
+
61 
+
62  return fvar<T>(pow(x1.val_, x2),
+
63  x1.d_ * x2 * pow(x1.val_, x2 - 1));
+
64  }
+
65  }
+
66 }
+
67 #endif
+ +
fvar< T > inv_sqrt(const fvar< T > &x)
Definition: inv_sqrt.hpp:15
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
var pow(const double base, const var &exponent)
Return the base scalar raised to the power of the exponent variable (cmath).
Definition: pow.hpp:141
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + + +
fvar< T > inv_square(const fvar< T > &x)
Definition: inv_square.hpp:15
+ +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
fvar< T > inv(const fvar< T > &x)
Definition: inv.hpp:15
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2primitive__value_8hpp.html b/doc/api/html/fwd_2scal_2fun_2primitive__value_8hpp.html new file mode 100644 index 00000000000..74ed958f963 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2primitive__value_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/primitive_value.hpp File Reference + + + + + + + + + + +
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template<typename T >
double stan::math::primitive_value (const fvar< T > &v)
 Return the primitive value of the specified forward-mode autodiff variable. More...
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2primitive__value_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2primitive__value_8hpp_source.html new file mode 100644 index 00000000000..6cde9ce16d1 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2primitive__value_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/primitive_value.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_PRIMITIVE_VALUE_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_PRIMITIVE_VALUE_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11 
+
21  template <typename T>
+
22  inline double primitive_value(const fvar<T>& v) {
+ +
24  return primitive_value(v.val_);
+
25  }
+
26 
+
27 
+
28  }
+
29 
+
30 }
+
31 
+
32 #endif
+ + + +
double primitive_value(const fvar< T > &v)
Return the primitive value of the specified forward-mode autodiff variable.
+ + +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2rising__factorial_8hpp.html b/doc/api/html/fwd_2scal_2fun_2rising__factorial_8hpp.html new file mode 100644 index 00000000000..51b195dc319 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2rising__factorial_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/rising_factorial.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::rising_factorial (const fvar< T > &x, const fvar< T > &n)
 
template<typename T >
fvar< T > stan::math::rising_factorial (const fvar< T > &x, const double n)
 
template<typename T >
fvar< T > stan::math::rising_factorial (const double x, const fvar< T > &n)
 
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2rising__factorial_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2rising__factorial_8hpp_source.html new file mode 100644 index 00000000000..ae8d61943c7 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2rising__factorial_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/rising_factorial.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_RISING_FACTORIAL_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_RISING_FACTORIAL_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + +
7 #include <iostream>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template<typename T>
+
14  inline
+
15  fvar<T>
+
16  rising_factorial(const fvar<T>& x, const fvar<T>& n) {
+ +
18 
+
19  T rising_fact(rising_factorial(x.val_, n.val_));
+
20  return fvar<T>(rising_fact,
+
21  rising_fact * (digamma(x.val_ + n.val_)
+
22  * (x.d_ + n.d_) - digamma(x.val_) * x.d_));
+
23  }
+
24 
+
25  template<typename T>
+
26  inline
+
27  fvar<T>
+
28  rising_factorial(const fvar<T>& x, const double n) {
+ + +
31 
+
32  T rising_fact(rising_factorial(x.val_, n));
+
33  return fvar<T>(rising_fact,
+
34  rising_fact * x.d_
+
35  * (digamma(x.val_ + n) - digamma(x.val_)));
+
36  }
+
37 
+
38  template<typename T>
+
39  inline
+
40  fvar<T>
+
41  rising_factorial(const double x, const fvar<T>& n) {
+ + +
44 
+
45  T rising_fact(rising_factorial(x, n.val_));
+
46  return fvar<T>(rising_fact,
+
47  rising_fact * (digamma(x + n.val_) * n.d_));
+
48  }
+
49  }
+
50 }
+
51 #endif
+ + + + + + +
fvar< T > rising_factorial(const fvar< T > &x, const fvar< T > &n)
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2round_8hpp.html b/doc/api/html/fwd_2scal_2fun_2round_8hpp.html new file mode 100644 index 00000000000..3abdcd5eb59 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2round_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/round.hpp File Reference + + + + + + + + + + +
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template<typename T >
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diff --git a/doc/api/html/fwd_2scal_2fun_2round_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2round_8hpp_source.html new file mode 100644 index 00000000000..1df43724c58 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2round_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/round.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_ROUND_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_ROUND_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  template <typename T>
+
11  inline fvar<T> round(const fvar<T>& x) {
+ +
13  return fvar<T>(round(x.val_), 0);
+
14  }
+
15 
+
16  }
+
17 }
+
18 #endif
+ + +
fvar< T > round(const fvar< T > &x)
Definition: round.hpp:11
+
var round(const var &a)
Returns the rounded form of the specified variable (C99).
Definition: round.hpp:57
+ + +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2sin_8hpp.html b/doc/api/html/fwd_2scal_2fun_2sin_8hpp.html new file mode 100644 index 00000000000..64799a46a53 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2sin_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/sin.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::sin (const fvar< T > &x)
 
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diff --git a/doc/api/html/fwd_2scal_2fun_2sin_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2sin_8hpp_source.html new file mode 100644 index 00000000000..5fdf24caef1 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2sin_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/sin.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_SIN_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_SIN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  sin(const fvar<T>& x) {
+
15  using std::sin;
+
16  using std::cos;
+
17  return fvar<T>(sin(x.val_),
+
18  x.d_ * cos(x.val_));
+
19  }
+
20  }
+
21 }
+
22 #endif
+
fvar< T > cos(const fvar< T > &x)
Definition: cos.hpp:13
+
var sin(const var &a)
Return the sine of a radian-scaled variable (cmath).
Definition: sin.hpp:49
+ + + +
fvar< T > sin(const fvar< T > &x)
Definition: sin.hpp:14
+ + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2sinh_8hpp.html b/doc/api/html/fwd_2scal_2fun_2sinh_8hpp.html new file mode 100644 index 00000000000..7978698c24f --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2sinh_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/sinh.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2sinh_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2sinh_8hpp_source.html new file mode 100644 index 00000000000..ab4773af950 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2sinh_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/sinh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_SINH_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_SINH_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  sinh(const fvar<T>& x) {
+
15  using std::sinh;
+
16  using std::cosh;
+
17  return fvar<T>(sinh(x.val_),
+
18  x.d_ * cosh(x.val_));
+
19  }
+
20  }
+
21 }
+
22 #endif
+ + +
fvar< T > cosh(const fvar< T > &x)
Definition: cosh.hpp:13
+ + +
fvar< T > sinh(const fvar< T > &x)
Definition: sinh.hpp:14
+
var sinh(const var &a)
Return the hyperbolic sine of the specified variable (cmath).
Definition: sinh.hpp:49
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2sqrt_8hpp.html b/doc/api/html/fwd_2scal_2fun_2sqrt_8hpp.html new file mode 100644 index 00000000000..c1fa33f1df3 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2sqrt_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/sqrt.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2sqrt_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2sqrt_8hpp_source.html new file mode 100644 index 00000000000..f3803b63d19 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2sqrt_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/sqrt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_SQRT_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_SQRT_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  sqrt(const fvar<T>& x) {
+
16  using std::sqrt;
+ +
18  return fvar<T>(sqrt(x.val_), 0.5 * x.d_ * inv_sqrt(x.val_));
+
19  }
+
20  }
+
21 }
+
22 #endif
+ +
fvar< T > inv_sqrt(const fvar< T > &x)
Definition: inv_sqrt.hpp:15
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
var sqrt(const var &a)
Return the square root of the specified variable (cmath).
Definition: sqrt.hpp:50
+ + + +
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2square_8hpp.html b/doc/api/html/fwd_2scal_2fun_2square_8hpp.html new file mode 100644 index 00000000000..710562b31d0 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2square_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/square.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2square_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2square_8hpp_source.html new file mode 100644 index 00000000000..c29d54d8a56 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2square_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/square.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_SQUARE_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_SQUARE_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  square(const fvar<T>& x) {
+
16  using stan::math::square;
+
17  return fvar<T>(square(x.val_),
+
18  x.d_ * 2 * x.val_);
+
19  }
+
20  }
+
21 }
+
22 #endif
+ + + + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2tan_8hpp.html b/doc/api/html/fwd_2scal_2fun_2tan_8hpp.html new file mode 100644 index 00000000000..fd18446920e --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2tan_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/tan.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2tan_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2tan_8hpp_source.html new file mode 100644 index 00000000000..b05a8ab0157 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2tan_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/tan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_TAN_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_TAN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  tan(const fvar<T>& x) {
+
15  using std::cos;
+
16  using std::tan;
+
17  return fvar<T>(tan(x.val_), x.d_ / (cos(x.val_) * cos(x.val_)));
+
18  }
+
19  }
+
20 }
+
21 #endif
+
fvar< T > cos(const fvar< T > &x)
Definition: cos.hpp:13
+ + + + +
fvar< T > tan(const fvar< T > &x)
Definition: tan.hpp:14
+
var tan(const var &a)
Return the tangent of a radian-scaled variable (cmath).
Definition: tan.hpp:49
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2tanh_8hpp.html b/doc/api/html/fwd_2scal_2fun_2tanh_8hpp.html new file mode 100644 index 00000000000..f75d09e1e09 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2tanh_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/tanh.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2tanh_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2tanh_8hpp_source.html new file mode 100644 index 00000000000..284de90a8b9 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2tanh_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/tanh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_TANH_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_TANH_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  tanh(const fvar<T>& x) {
+
15  using std::tanh;
+
16  T u = tanh(x.val_);
+
17  return fvar<T>(u, x.d_ * (1 - u * u));
+
18  }
+
19  }
+
20 }
+
21 #endif
+ + + + +
fvar< T > tanh(const fvar< T > &x)
Definition: tanh.hpp:14
+
var tanh(const var &a)
Return the hyperbolic tangent of the specified variable (cmath).
Definition: tanh.hpp:50
+ +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2tgamma_8hpp.html b/doc/api/html/fwd_2scal_2fun_2tgamma_8hpp.html new file mode 100644 index 00000000000..b12a8d84d3e --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2tgamma_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/tgamma.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2tgamma_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2tgamma_8hpp_source.html new file mode 100644 index 00000000000..ec9acb3e651 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2tgamma_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/tgamma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_TGAMMA_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_TGAMMA_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 #include <boost/math/special_functions/digamma.hpp>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  fvar<T>
+
15  tgamma(const fvar<T>& x) {
+ +
17  using boost::math::tgamma;
+
18  T u = tgamma(x.val_);
+
19  return fvar<T>(u, x.d_ * u * digamma(x.val_));
+
20  }
+
21  }
+
22 }
+
23 #endif
+
var tgamma(const stan::math::var &a)
Return the Gamma function applied to the specified variable (C99).
Definition: tgamma.hpp:65
+ + + + +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2trunc_8hpp.html b/doc/api/html/fwd_2scal_2fun_2trunc_8hpp.html new file mode 100644 index 00000000000..0a0ff221f0a --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2trunc_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/trunc.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2trunc_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2trunc_8hpp_source.html new file mode 100644 index 00000000000..3f18ccee7c4 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2trunc_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/trunc.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_TRUNC_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_TRUNC_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/fwd/core.hpp>
+
6 
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline fvar<T> trunc(const fvar<T>& x) {
+ +
14  return fvar<T>(trunc(x.val_), 0);
+
15  }
+
16 
+
17  }
+
18 }
+
19 #endif
+
var trunc(const var &a)
Returns the truncatation of the specified variable (C99).
Definition: trunc.hpp:60
+ + +
fvar< T > trunc(const fvar< T > &x)
Definition: trunc.hpp:12
+ + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2value__of_8hpp.html b/doc/api/html/fwd_2scal_2fun_2value__of_8hpp.html new file mode 100644 index 00000000000..842a4910047 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2value__of_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/value_of.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/fwd_2scal_2fun_2value__of_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2value__of_8hpp_source.html new file mode 100644 index 00000000000..9d68a479c59 --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2value__of_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/value_of.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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value_of.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_VALUE_OF_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_VALUE_OF_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
15  template<typename T>
+
16  inline T value_of(const fvar<T>& v) {
+
17  return v.val_;
+
18  }
+
19 
+
20  }
+
21 }
+
22 #endif
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ + +
+
+
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diff --git a/doc/api/html/fwd_2scal_2fun_2value__of__rec_8hpp.html b/doc/api/html/fwd_2scal_2fun_2value__of__rec_8hpp.html new file mode 100644 index 00000000000..ced14a0196c --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2value__of__rec_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/value_of_rec.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
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+
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value_of_rec.hpp File Reference
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+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T >
double stan::math::value_of_rec (const fvar< T > &v)
 Return the value of the specified variable. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2fun_2value__of__rec_8hpp_source.html b/doc/api/html/fwd_2scal_2fun_2value__of__rec_8hpp_source.html new file mode 100644 index 00000000000..b876e1c197b --- /dev/null +++ b/doc/api/html/fwd_2scal_2fun_2value__of__rec_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/value_of_rec.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
value_of_rec.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_VALUE_OF_REC_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_VALUE_OF_REC_HPP
+
3 
+ +
5 #include <stan/math/fwd/core.hpp>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
20  template <typename T>
+
21  inline double value_of_rec(const fvar<T>& v) {
+ +
23  return value_of_rec(v.val_);
+
24  }
+
25 
+
26 
+
27  }
+
28 }
+
29 #endif
+ + +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2meta_2_operands_and_partials_8hpp.html b/doc/api/html/fwd_2scal_2meta_2_operands_and_partials_8hpp.html new file mode 100644 index 00000000000..0862dbe1255 --- /dev/null +++ b/doc/api/html/fwd_2scal_2meta_2_operands_and_partials_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/meta/OperandsAndPartials.hpp File Reference + + + + + + + + + + +
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+
OperandsAndPartials.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
 This class builds partial derivatives with respect to a set of operands. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2meta_2_operands_and_partials_8hpp_source.html b/doc/api/html/fwd_2scal_2meta_2_operands_and_partials_8hpp_source.html new file mode 100644 index 00000000000..f21db243f78 --- /dev/null +++ b/doc/api/html/fwd_2scal_2meta_2_operands_and_partials_8hpp_source.html @@ -0,0 +1,307 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/meta/OperandsAndPartials.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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+
OperandsAndPartials.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_META_OPERANDSANDPARTIALS_HPP
+
2 #define STAN_MATH_FWD_SCAL_META_OPERANDSANDPARTIALS_HPP
+
3 
+ + + +
7 #include <stan/math/fwd/core.hpp>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  // These are helpers to the OperandsAndPartials specialization for
+
13  // stan::math::fvar
+
14  namespace {
+
15  template <typename T_derivative,
+
16  typename T,
+
17  typename T_partials,
+
18  bool is_vec = is_vector<T>::value,
+
19  bool is_const = is_constant_struct<T>::value>
+
20  struct increment_derivative {
+
21  inline T_derivative operator()(const T& x,
+
22  const T_partials& d_dx) {
+
23  return 0;
+
24  }
+
25  };
+
26 
+
27  template <typename T_derivative,
+
28  typename T,
+
29  typename T_partials>
+
30  struct increment_derivative<T_derivative, T, T_partials, false, false> {
+
31  inline T_derivative operator()(const T& x,
+
32  const T_partials& d_dx) {
+
33  return d_dx[0] * x.d_;
+
34  }
+
35  };
+
36 
+
37  template <typename T_derivative,
+
38  typename T,
+
39  typename T_partials>
+
40  struct increment_derivative<T_derivative, T, T_partials, true, false> {
+
41  inline T_derivative operator()(const T& x,
+
42  const T_partials& d_dx) {
+
43  T_derivative derivative(0);
+
44  for (size_t n = 0; n < length(x); n++)
+
45  derivative += d_dx[n] * x[n].d_;
+
46  return derivative;
+
47  }
+
48  };
+
49 
+
50  template <typename T,
+
51  typename T1, typename D1, typename T2, typename D2,
+
52  typename T3, typename D3, typename T4, typename D4,
+
53  typename T5, typename D5, typename T6, typename D6>
+
54  fvar<T> partials_to_fvar(T& logp,
+
55  const T1& x1, D1& d_x1,
+
56  const T2& x2, D2& d_x2,
+
57  const T3& x3, D3& d_x3,
+
58  const T4& x4, D4& d_x4,
+
59  const T5& x5, D5& d_x5,
+
60  const T6& x6, D6& d_x6) {
+
61  T deriv = 0;
+
62  if (!is_constant_struct<T1>::value)
+
63  deriv += increment_derivative<T, T1, D1>()(x1, d_x1);
+
64  if (!is_constant_struct<T2>::value)
+
65  deriv += increment_derivative<T, T2, D2>()(x2, d_x2);
+
66  if (!is_constant_struct<T3>::value)
+
67  deriv += increment_derivative<T, T3, D3>()(x3, d_x3);
+
68  if (!is_constant_struct<T4>::value)
+
69  deriv += increment_derivative<T, T4, D4>()(x4, d_x4);
+
70  if (!is_constant_struct<T5>::value)
+
71  deriv += increment_derivative<T, T5, D5>()(x5, d_x5);
+
72  if (!is_constant_struct<T6>::value)
+
73  deriv += increment_derivative<T, T6, D6>()(x6, d_x6);
+
74  return stan::math::fvar<T>(logp, deriv);
+
75  }
+
76  }
+
77 
+
78 
+
101  template<typename T1, typename T2, typename T3,
+
102  typename T4, typename T5, typename T6,
+
103  typename T_partials_return>
+
104  struct OperandsAndPartials<T1, T2, T3, T4, T5, T6,
+
105  typename stan::math::fvar<T_partials_return> > {
+ +
107 
+
108  const T1& x1_;
+
109  const T2& x2_;
+
110  const T3& x3_;
+
111  const T4& x4_;
+
112  const T5& x5_;
+
113  const T6& x6_;
+
114 
+
115  size_t n_partials;
+
116  T_partials_return* all_partials;
+
117 
+
118 
+
119  VectorView<T_partials_return,
+ + +
122  VectorView<T_partials_return,
+ + +
125  VectorView<T_partials_return,
+ + +
128  VectorView<T_partials_return,
+ + +
131  VectorView<T_partials_return,
+ + +
134  VectorView<T_partials_return,
+ + +
137 
+
138  OperandsAndPartials(const T1& x1 = 0, const T2& x2 = 0, const T3& x3 = 0,
+
139  const T4& x4 = 0, const T5& x5 = 0, const T6& x6 = 0)
+
140  : x1_(x1), x2_(x2), x3_(x3), x4_(x4), x5_(x5), x6_(x6),
+
141  n_partials(!is_constant_struct<T1>::value * length(x1) +
+
142  !is_constant_struct<T2>::value * length(x2) +
+
143  !is_constant_struct<T3>::value * length(x3) +
+
144  !is_constant_struct<T4>::value * length(x4) +
+
145  !is_constant_struct<T5>::value * length(x5) +
+
146  !is_constant_struct<T6>::value * length(x6)),
+
147  all_partials(new T_partials_return[n_partials]),
+
148  d_x1(all_partials),
+
149  d_x2(all_partials
+
150  + (!is_constant_struct<T1>::value) * length(x1)),
+
151  d_x3(all_partials
+
152  + (!is_constant_struct<T1>::value) * length(x1)
+
153  + (!is_constant_struct<T2>::value) * length(x2)),
+
154  d_x4(all_partials
+
155  + (!is_constant_struct<T1>::value) * length(x1)
+
156  + (!is_constant_struct<T2>::value) * length(x2)
+
157  + (!is_constant_struct<T3>::value) * length(x3)),
+
158  d_x5(all_partials
+
159  + (!is_constant_struct<T1>::value) * length(x1)
+
160  + (!is_constant_struct<T2>::value) * length(x2)
+
161  + (!is_constant_struct<T3>::value) * length(x3)
+
162  + (!is_constant_struct<T4>::value) * length(x4)),
+
163  d_x6(all_partials
+
164  + (!is_constant_struct<T1>::value) * length(x1)
+
165  + (!is_constant_struct<T2>::value) * length(x2)
+
166  + (!is_constant_struct<T3>::value) * length(x3)
+
167  + (!is_constant_struct<T4>::value) * length(x4)
+
168  + (!is_constant_struct<T5>::value) * length(x5)) {
+
169  std::fill(all_partials, all_partials + n_partials, 0);
+
170  }
+
171 
+
172  T_return_type
+
173  value(T_partials_return value) {
+
174  return partials_to_fvar(value,
+
175  x1_, d_x1, x2_, d_x2,
+
176  x3_, d_x3, x4_, d_x4,
+
177  x5_, d_x4, x6_, d_x5);
+
178  }
+
179 
+ +
181  delete[] all_partials;
+
182  }
+
183  };
+
184 
+
185 
+
186  }
+
187 }
+
188 #endif
+ + + +
VectorView< T_partials_return, is_vector< T2 >::value, is_constant_struct< T2 >::value > d_x2
+
VectorView< T_partials_return, is_vector< T1 >::value, is_constant_struct< T1 >::value > d_x1
+ + +
VectorView< T_partials_return, is_vector< T5 >::value, is_constant_struct< T5 >::value > d_x5
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
VectorView< T_partials_return, is_vector< T4 >::value, is_constant_struct< T4 >::value > d_x4
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
This class builds partial derivatives with respect to a set of operands.
+
void derivative(const F &f, const T &x, T &fx, T &dfx_dx)
Return the derivative of the specified univariate function at the specified argument.
Definition: derivative.hpp:26
+ + +
VectorView< T_partials_return, is_vector< T3 >::value, is_constant_struct< T3 >::value > d_x3
+ +
void fill(std::vector< T > &x, const S &y)
Fill the specified container with the specified value.
Definition: fill.hpp:22
+ + +
VectorView< T_partials_return, is_vector< T6 >::value, is_constant_struct< T6 >::value > d_x6
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
OperandsAndPartials(const T1 &x1=0, const T2 &x2=0, const T3 &x3=0, const T4 &x4=0, const T5 &x5=0, const T6 &x6=0)
+ +
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diff --git a/doc/api/html/fwd_2scal_2meta_2is__fvar_8hpp.html b/doc/api/html/fwd_2scal_2meta_2is__fvar_8hpp.html new file mode 100644 index 00000000000..11971d70144 --- /dev/null +++ b/doc/api/html/fwd_2scal_2meta_2is__fvar_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/meta/is_fvar.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
is_fvar.hpp File Reference
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diff --git a/doc/api/html/fwd_2scal_2meta_2is__fvar_8hpp_source.html b/doc/api/html/fwd_2scal_2meta_2is__fvar_8hpp_source.html new file mode 100644 index 00000000000..d2fa9f7173a --- /dev/null +++ b/doc/api/html/fwd_2scal_2meta_2is__fvar_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/meta/is_fvar.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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is_fvar.hpp
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1 #ifndef STAN_MATH_FWD_SCAL_META_IS_FVAR_HPP
+
2 #define STAN_MATH_FWD_SCAL_META_IS_FVAR_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  template <typename T>
+
10  struct is_fvar<stan::math::fvar<T> > {
+
11  enum { value = true };
+
12  };
+
13 
+
14 }
+
15 #endif
+ + + + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/fwd_2scal_2meta_2partials__type_8hpp.html b/doc/api/html/fwd_2scal_2meta_2partials__type_8hpp.html new file mode 100644 index 00000000000..c02e192a8a3 --- /dev/null +++ b/doc/api/html/fwd_2scal_2meta_2partials__type_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/meta/partials_type.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+
partials_type.hpp File Reference
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+
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diff --git a/doc/api/html/fwd_2scal_2meta_2partials__type_8hpp_source.html b/doc/api/html/fwd_2scal_2meta_2partials__type_8hpp_source.html new file mode 100644 index 00000000000..c10f663acbe --- /dev/null +++ b/doc/api/html/fwd_2scal_2meta_2partials__type_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/meta/partials_type.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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partials_type.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_META_PARTIALS_TYPE_HPP
+
2 #define STAN_MATH_FWD_SCAL_META_PARTIALS_TYPE_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  template <typename T>
+
10  struct partials_type<stan::math::fvar<T> > {
+
11  typedef T type;
+
12  };
+
13 
+
14 }
+
15 #endif
+
16 
+ + + + + + +
+
+
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diff --git a/doc/api/html/fwd_2scal_8hpp.html b/doc/api/html/fwd_2scal_8hpp.html new file mode 100644 index 00000000000..fe65c4f9a52 --- /dev/null +++ b/doc/api/html/fwd_2scal_8hpp.html @@ -0,0 +1,197 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
scal.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/fwd/scal/meta/is_fvar.hpp>
+#include <stan/math/fwd/scal/meta/partials_type.hpp>
+#include <stan/math/fwd/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal.hpp>
+#include <stan/math/fwd/scal/fun/Phi.hpp>
+#include <stan/math/fwd/scal/fun/abs.hpp>
+#include <stan/math/fwd/scal/fun/acos.hpp>
+#include <stan/math/fwd/scal/fun/acosh.hpp>
+#include <stan/math/fwd/scal/fun/asin.hpp>
+#include <stan/math/fwd/scal/fun/asinh.hpp>
+#include <stan/math/fwd/scal/fun/atan.hpp>
+#include <stan/math/fwd/scal/fun/atan2.hpp>
+#include <stan/math/fwd/scal/fun/atanh.hpp>
+#include <stan/math/fwd/scal/fun/bessel_first_kind.hpp>
+#include <stan/math/fwd/scal/fun/bessel_second_kind.hpp>
+#include <stan/math/fwd/scal/fun/binary_log_loss.hpp>
+#include <stan/math/fwd/scal/fun/binomial_coefficient_log.hpp>
+#include <stan/math/fwd/scal/fun/cbrt.hpp>
+#include <stan/math/fwd/scal/fun/ceil.hpp>
+#include <stan/math/fwd/scal/fun/cos.hpp>
+#include <stan/math/fwd/scal/fun/cosh.hpp>
+#include <stan/math/fwd/scal/fun/digamma.hpp>
+#include <stan/math/fwd/scal/fun/erf.hpp>
+#include <stan/math/fwd/scal/fun/erfc.hpp>
+#include <stan/math/fwd/scal/fun/exp.hpp>
+#include <stan/math/fwd/scal/fun/exp2.hpp>
+#include <stan/math/fwd/scal/fun/expm1.hpp>
+#include <stan/math/fwd/scal/fun/fabs.hpp>
+#include <stan/math/fwd/scal/fun/falling_factorial.hpp>
+#include <stan/math/fwd/scal/fun/fdim.hpp>
+#include <stan/math/fwd/scal/fun/floor.hpp>
+#include <stan/math/fwd/scal/fun/fma.hpp>
+#include <stan/math/fwd/scal/fun/fmax.hpp>
+#include <stan/math/fwd/scal/fun/fmin.hpp>
+#include <stan/math/fwd/scal/fun/fmod.hpp>
+#include <stan/math/fwd/scal/fun/gamma_p.hpp>
+#include <stan/math/fwd/scal/fun/gamma_q.hpp>
+#include <stan/math/fwd/scal/fun/grad_inc_beta.hpp>
+#include <stan/math/fwd/scal/fun/hypot.hpp>
+#include <stan/math/fwd/scal/fun/inc_beta.hpp>
+#include <stan/math/fwd/scal/fun/inv.hpp>
+#include <stan/math/fwd/scal/fun/inv_Phi.hpp>
+#include <stan/math/fwd/scal/fun/inv_cloglog.hpp>
+#include <stan/math/fwd/scal/fun/inv_logit.hpp>
+#include <stan/math/fwd/scal/fun/inv_sqrt.hpp>
+#include <stan/math/fwd/scal/fun/inv_square.hpp>
+#include <stan/math/fwd/scal/fun/is_inf.hpp>
+#include <stan/math/fwd/scal/fun/is_nan.hpp>
+#include <stan/math/fwd/scal/fun/lbeta.hpp>
+#include <stan/math/fwd/scal/fun/lgamma.hpp>
+#include <stan/math/fwd/scal/fun/lmgamma.hpp>
+#include <stan/math/fwd/scal/fun/log.hpp>
+#include <stan/math/fwd/scal/fun/log10.hpp>
+#include <stan/math/fwd/scal/fun/log1m.hpp>
+#include <stan/math/fwd/scal/fun/log1m_exp.hpp>
+#include <stan/math/fwd/scal/fun/log1m_inv_logit.hpp>
+#include <stan/math/fwd/scal/fun/log1p.hpp>
+#include <stan/math/fwd/scal/fun/log1p_exp.hpp>
+#include <stan/math/fwd/scal/fun/log2.hpp>
+#include <stan/math/fwd/scal/fun/log_diff_exp.hpp>
+#include <stan/math/fwd/scal/fun/log_falling_factorial.hpp>
+#include <stan/math/fwd/scal/fun/log_inv_logit.hpp>
+#include <stan/math/fwd/scal/fun/log_mix.hpp>
+#include <stan/math/fwd/scal/fun/log_rising_factorial.hpp>
+#include <stan/math/fwd/scal/fun/log_sum_exp.hpp>
+#include <stan/math/fwd/scal/fun/logit.hpp>
+#include <stan/math/fwd/scal/fun/modified_bessel_first_kind.hpp>
+#include <stan/math/fwd/scal/fun/modified_bessel_second_kind.hpp>
+#include <stan/math/fwd/scal/fun/multiply_log.hpp>
+#include <stan/math/fwd/scal/fun/owens_t.hpp>
+#include <stan/math/fwd/scal/fun/pow.hpp>
+#include <stan/math/fwd/scal/fun/primitive_value.hpp>
+#include <stan/math/fwd/scal/fun/rising_factorial.hpp>
+#include <stan/math/fwd/scal/fun/round.hpp>
+#include <stan/math/fwd/scal/fun/sin.hpp>
+#include <stan/math/fwd/scal/fun/sinh.hpp>
+#include <stan/math/fwd/scal/fun/sqrt.hpp>
+#include <stan/math/fwd/scal/fun/square.hpp>
+#include <stan/math/fwd/scal/fun/tan.hpp>
+#include <stan/math/fwd/scal/fun/tanh.hpp>
+#include <stan/math/fwd/scal/fun/tgamma.hpp>
+#include <stan/math/fwd/scal/fun/to_fvar.hpp>
+#include <stan/math/fwd/scal/fun/trunc.hpp>
+#include <stan/math/fwd/scal/fun/value_of.hpp>
+#include <stan/math/fwd/scal/fun/value_of_rec.hpp>
+
+

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diff --git a/doc/api/html/fwd_2scal_8hpp_source.html b/doc/api/html/fwd_2scal_8hpp_source.html new file mode 100644 index 00000000000..7ae6539abdd --- /dev/null +++ b/doc/api/html/fwd_2scal_8hpp_source.html @@ -0,0 +1,288 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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scal.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_HPP
+
2 #define STAN_MATH_FWD_SCAL_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + + +
8 
+ +
10 
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92 
+
93 #endif
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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diff --git a/doc/api/html/gamma__ccdf__log_8hpp.html b/doc/api/html/gamma__ccdf__log_8hpp.html new file mode 100644 index 00000000000..c51df8bb8fc --- /dev/null +++ b/doc/api/html/gamma__ccdf__log_8hpp.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_ccdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
gamma_ccdf_log.hpp File Reference
+
+
+ +

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+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type stan::math::gamma_ccdf_log (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gamma__ccdf__log_8hpp_source.html b/doc/api/html/gamma__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..eafc8b15bc0 --- /dev/null +++ b/doc/api/html/gamma__ccdf__log_8hpp_source.html @@ -0,0 +1,301 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_ccdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
gamma_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GAMMA_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GAMMA_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + +
24 #include <boost/random/gamma_distribution.hpp>
+
25 #include <boost/random/variate_generator.hpp>
+
26 #include <cmath>
+
27 #include <limits>
+
28 
+
29 namespace stan {
+
30 
+
31  namespace math {
+
32 
+
33  template <typename T_y, typename T_shape, typename T_inv_scale>
+
34  typename return_type<T_y, T_shape, T_inv_scale>::type
+
35  gamma_ccdf_log(const T_y& y, const T_shape& alpha,
+
36  const T_inv_scale& beta) {
+
37  // Size checks
+
38  if (!(stan::length(y) && stan::length(alpha) && stan::length(beta)))
+
39  return 0.0;
+
40 
+
41  typedef typename stan::partials_return_type<T_y, T_shape,
+
42  T_inv_scale>::type
+
43  T_partials_return;
+
44 
+
45  // Error checks
+
46  static const char* function("stan::math::gamma_ccdf_log");
+
47 
+ + + + + + + +
55  using boost::math::tools::promote_args;
+
56  using std::exp;
+
57 
+
58  T_partials_return P(0.0);
+
59 
+
60  check_positive_finite(function, "Shape parameter", alpha);
+
61  check_positive_finite(function, "Scale parameter", beta);
+
62  check_not_nan(function, "Random variable", y);
+
63  check_nonnegative(function, "Random variable", y);
+
64  check_consistent_sizes(function,
+
65  "Random variable", y,
+
66  "Shape parameter", alpha,
+
67  "Scale Parameter", beta);
+
68 
+
69  // Wrap arguments in vectors
+
70  VectorView<const T_y> y_vec(y);
+
71  VectorView<const T_shape> alpha_vec(alpha);
+
72  VectorView<const T_inv_scale> beta_vec(beta);
+
73  size_t N = max_size(y, alpha, beta);
+
74 
+ +
76  operands_and_partials(y, alpha, beta);
+
77 
+
78  // Explicit return for extreme values
+
79  // The gradients are technically ill-defined, but treated as zero
+
80 
+
81  for (size_t i = 0; i < stan::length(y); i++) {
+
82  if (value_of(y_vec[i]) == 0)
+
83  return operands_and_partials.value(0.0);
+
84  }
+
85 
+
86  // Compute ccdf_log and its gradients
+
87  using stan::math::gamma_p;
+
88  using stan::math::digamma;
+
89  using boost::math::tgamma;
+
90  using std::exp;
+
91  using std::pow;
+
92  using std::log;
+
93 
+
94  // Cache a few expensive function calls if nu is a parameter
+ +
96  T_partials_return, T_shape> gamma_vec(stan::length(alpha));
+ +
98  T_partials_return, T_shape>
+
99  digamma_vec(stan::length(alpha));
+
100 
+ +
102  for (size_t i = 0; i < stan::length(alpha); i++) {
+
103  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
104  gamma_vec[i] = tgamma(alpha_dbl);
+
105  digamma_vec[i] = digamma(alpha_dbl);
+
106  }
+
107  }
+
108 
+
109  // Compute vectorized ccdf_log and gradient
+
110  for (size_t n = 0; n < N; n++) {
+
111  // Explicit results for extreme values
+
112  // The gradients are technically ill-defined, but treated as zero
+
113  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
114  return operands_and_partials.value(stan::math::negative_infinity());
+
115 
+
116  // Pull out values
+
117  const T_partials_return y_dbl = value_of(y_vec[n]);
+
118  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
119  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
120 
+
121  // Compute
+
122  const T_partials_return Pn = 1.0 - gamma_p(alpha_dbl, beta_dbl * y_dbl);
+
123 
+
124  P += log(Pn);
+
125 
+ +
127  operands_and_partials.d_x1[n] -= beta_dbl * exp(-beta_dbl * y_dbl)
+
128  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+ +
130  operands_and_partials.d_x2[n]
+
131  += stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
132  * y_dbl, gamma_vec[n],
+
133  digamma_vec[n]) / Pn;
+ +
135  operands_and_partials.d_x3[n] -= y_dbl * exp(-beta_dbl * y_dbl)
+
136  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+
137  }
+
138 
+
139  return operands_and_partials.value(P);
+
140  }
+
141  }
+
142 }
+
143 
+
144 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
return_type< T_y, T_shape, T_inv_scale >::type gamma_ccdf_log(const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ +
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gamma__cdf_8hpp.html b/doc/api/html/gamma__cdf_8hpp.html new file mode 100644 index 00000000000..861ada6093a --- /dev/null +++ b/doc/api/html/gamma__cdf_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+
+ +
+
gamma_cdf.hpp File Reference
+
+
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+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type stan::math::gamma_cdf (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 The cumulative density function for a gamma distribution for y with the specified shape and inverse scale parameters. More...
 
+
+
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diff --git a/doc/api/html/gamma__cdf_8hpp_source.html b/doc/api/html/gamma__cdf_8hpp_source.html new file mode 100644 index 00000000000..66cd58df22b --- /dev/null +++ b/doc/api/html/gamma__cdf_8hpp_source.html @@ -0,0 +1,309 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+
+
+
gamma_cdf.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GAMMA_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GAMMA_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + +
24 #include <boost/random/gamma_distribution.hpp>
+
25 #include <boost/random/variate_generator.hpp>
+
26 #include <cmath>
+
27 #include <limits>
+
28 
+
29 namespace stan {
+
30 
+
31  namespace math {
+
32 
+
47  template <typename T_y, typename T_shape, typename T_inv_scale>
+
48  typename return_type<T_y, T_shape, T_inv_scale>::type
+
49  gamma_cdf(const T_y& y, const T_shape& alpha, const T_inv_scale& beta) {
+
50  // Size checks
+
51  if (!(stan::length(y) && stan::length(alpha) && stan::length(beta)))
+
52  return 1.0;
+
53  typedef typename stan::partials_return_type<T_y, T_shape,
+
54  T_inv_scale>::type
+
55  T_partials_return;
+
56 
+
57  // Error checks
+
58  static const char* function("stan::math::gamma_cdf");
+
59 
+ + + + + + + +
67  using boost::math::tools::promote_args;
+
68  using std::exp;
+
69 
+
70  T_partials_return P(1.0);
+
71 
+
72  check_positive_finite(function, "Shape parameter", alpha);
+
73  check_positive_finite(function, "Scale parameter", beta);
+
74  check_not_nan(function, "Random variable", y);
+
75  check_nonnegative(function, "Random variable", y);
+
76  check_consistent_sizes(function,
+
77  "Random variable", y,
+
78  "Shape parameter", alpha,
+
79  "Scale Parameter", beta);
+
80 
+
81  // Wrap arguments in vectors
+
82  VectorView<const T_y> y_vec(y);
+
83  VectorView<const T_shape> alpha_vec(alpha);
+
84  VectorView<const T_inv_scale> beta_vec(beta);
+
85  size_t N = max_size(y, alpha, beta);
+
86 
+ +
88  operands_and_partials(y, alpha, beta);
+
89 
+
90  // Explicit return for extreme values
+
91  // The gradients are technically ill-defined, but treated as zero
+
92 
+
93  for (size_t i = 0; i < stan::length(y); i++) {
+
94  if (value_of(y_vec[i]) == 0)
+
95  return operands_and_partials.value(0.0);
+
96  }
+
97 
+
98  // Compute CDF and its gradients
+
99  using stan::math::gamma_p;
+
100  using stan::math::digamma;
+
101  using boost::math::tgamma;
+
102  using std::exp;
+
103  using std::pow;
+
104 
+
105  // Cache a few expensive function calls if nu is a parameter
+ +
107  T_partials_return, T_shape> gamma_vec(stan::length(alpha));
+ +
109  T_partials_return, T_shape>
+
110  digamma_vec(stan::length(alpha));
+
111 
+ +
113  for (size_t i = 0; i < stan::length(alpha); i++) {
+
114  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
115  gamma_vec[i] = tgamma(alpha_dbl);
+
116  digamma_vec[i] = digamma(alpha_dbl);
+
117  }
+
118  }
+
119 
+
120  // Compute vectorized CDF and gradient
+
121  for (size_t n = 0; n < N; n++) {
+
122  // Explicit results for extreme values
+
123  // The gradients are technically ill-defined, but treated as zero
+
124  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
125  continue;
+
126 
+
127  // Pull out values
+
128  const T_partials_return y_dbl = value_of(y_vec[n]);
+
129  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
130  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
131 
+
132  // Compute
+
133  const T_partials_return Pn = gamma_p(alpha_dbl, beta_dbl * y_dbl);
+
134 
+
135  P *= Pn;
+
136 
+ +
138  operands_and_partials.d_x1[n] += beta_dbl * exp(-beta_dbl * y_dbl)
+
139  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+ +
141  operands_and_partials.d_x2[n]
+
142  -= stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
143  * y_dbl, gamma_vec[n],
+
144  digamma_vec[n]) / Pn;
+ +
146  operands_and_partials.d_x3[n] += y_dbl * exp(-beta_dbl * y_dbl)
+
147  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+
148  }
+
149 
+ +
151  for (size_t n = 0; n < stan::length(y); ++n)
+
152  operands_and_partials.d_x1[n] *= P;
+
153  }
+ +
155  for (size_t n = 0; n < stan::length(alpha); ++n)
+
156  operands_and_partials.d_x2[n] *= P;
+
157  }
+ +
159  for (size_t n = 0; n < stan::length(beta); ++n)
+
160  operands_and_partials.d_x3[n] *= P;
+
161  }
+
162 
+
163  return operands_and_partials.value(P);
+
164  }
+
165  }
+
166 }
+
167 
+
168 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+
return_type< T_y, T_shape, T_inv_scale >::type gamma_cdf(const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
The cumulative density function for a gamma distribution for y with the specified shape and inverse s...
Definition: gamma_cdf.hpp:49
+ +
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gamma__cdf__log_8hpp.html b/doc/api/html/gamma__cdf__log_8hpp.html new file mode 100644 index 00000000000..d14d08963e2 --- /dev/null +++ b/doc/api/html/gamma__cdf__log_8hpp.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
gamma_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type stan::math::gamma_cdf_log (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gamma__cdf__log_8hpp_source.html b/doc/api/html/gamma__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..53d9b79ee6c --- /dev/null +++ b/doc/api/html/gamma__cdf__log_8hpp_source.html @@ -0,0 +1,299 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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gamma_cdf_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GAMMA_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GAMMA_CDF_LOG_HPP
+
3 
+
4 #include <boost/random/gamma_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + + + +
26 #include <cmath>
+
27 #include <limits>
+
28 
+
29 namespace stan {
+
30 
+
31  namespace math {
+
32 
+
33  template <typename T_y, typename T_shape, typename T_inv_scale>
+
34  typename return_type<T_y, T_shape, T_inv_scale>::type
+
35  gamma_cdf_log(const T_y& y, const T_shape& alpha, const T_inv_scale& beta) {
+
36  // Size checks
+
37  if (!(stan::length(y) && stan::length(alpha) && stan::length(beta)))
+
38  return 0.0;
+
39  typedef typename stan::partials_return_type<T_y, T_shape,
+
40  T_inv_scale>::type
+
41  T_partials_return;
+
42 
+
43  // Error checks
+
44  static const char* function("stan::math::gamma_cdf_log");
+
45 
+ + + + + + + +
53  using boost::math::tools::promote_args;
+
54  using std::exp;
+
55 
+
56  T_partials_return P(0.0);
+
57 
+
58  check_positive_finite(function, "Shape parameter", alpha);
+
59  check_positive_finite(function, "Scale parameter", beta);
+
60  check_not_nan(function, "Random variable", y);
+
61  check_nonnegative(function, "Random variable", y);
+
62  check_consistent_sizes(function,
+
63  "Random variable", y,
+
64  "Shape parameter", alpha,
+
65  "Scale Parameter", beta);
+
66 
+
67  // Wrap arguments in vectors
+
68  VectorView<const T_y> y_vec(y);
+
69  VectorView<const T_shape> alpha_vec(alpha);
+
70  VectorView<const T_inv_scale> beta_vec(beta);
+
71  size_t N = max_size(y, alpha, beta);
+
72 
+ +
74  operands_and_partials(y, alpha, beta);
+
75 
+
76  // Explicit return for extreme values
+
77  // The gradients are technically ill-defined, but treated as zero
+
78 
+
79  for (size_t i = 0; i < stan::length(y); i++) {
+
80  if (value_of(y_vec[i]) == 0)
+
81  return operands_and_partials.value(stan::math::negative_infinity());
+
82  }
+
83 
+
84  // Compute cdf_log and its gradients
+
85  using stan::math::gamma_p;
+
86  using stan::math::digamma;
+
87  using boost::math::tgamma;
+
88  using std::exp;
+
89  using std::pow;
+
90  using std::log;
+
91 
+
92  // Cache a few expensive function calls if nu is a parameter
+ +
94  T_partials_return, T_shape> gamma_vec(stan::length(alpha));
+ +
96  T_partials_return, T_shape>
+
97  digamma_vec(stan::length(alpha));
+
98 
+ +
100  for (size_t i = 0; i < stan::length(alpha); i++) {
+
101  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
102  gamma_vec[i] = tgamma(alpha_dbl);
+
103  digamma_vec[i] = digamma(alpha_dbl);
+
104  }
+
105  }
+
106 
+
107  // Compute vectorized cdf_log and gradient
+
108  for (size_t n = 0; n < N; n++) {
+
109  // Explicit results for extreme values
+
110  // The gradients are technically ill-defined, but treated as zero
+
111  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
112  return operands_and_partials.value(0.0);
+
113 
+
114  // Pull out values
+
115  const T_partials_return y_dbl = value_of(y_vec[n]);
+
116  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
117  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
118 
+
119  // Compute
+
120  const T_partials_return Pn = gamma_p(alpha_dbl, beta_dbl * y_dbl);
+
121 
+
122  P += log(Pn);
+
123 
+ +
125  operands_and_partials.d_x1[n] += beta_dbl * exp(-beta_dbl * y_dbl)
+
126  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+ +
128  operands_and_partials.d_x2[n]
+
129  -= stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
130  * y_dbl, gamma_vec[n],
+
131  digamma_vec[n]) / Pn;
+ +
133  operands_and_partials.d_x3[n] += y_dbl * exp(-beta_dbl * y_dbl)
+
134  * pow(beta_dbl * y_dbl, alpha_dbl-1) / tgamma(alpha_dbl) / Pn;
+
135  }
+
136 
+
137  return operands_and_partials.value(P);
+
138  }
+
139  }
+
140 }
+
141 
+
142 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
return_type< T_y, T_shape, T_inv_scale >::type gamma_cdf_log(const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ +
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gamma__log_8hpp.html b/doc/api/html/gamma__log_8hpp.html new file mode 100644 index 00000000000..009d8029308 --- /dev/null +++ b/doc/api/html/gamma__log_8hpp.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
gamma_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type stan::math::gamma_log (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 The log of a gamma density for y with the specified shape and inverse scale parameters. More...
 
template<typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type stan::math::gamma_log (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gamma__log_8hpp_source.html b/doc/api/html/gamma__log_8hpp_source.html new file mode 100644 index 00000000000..a5d64629552 --- /dev/null +++ b/doc/api/html/gamma__log_8hpp_source.html @@ -0,0 +1,301 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
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+
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+
gamma_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GAMMA_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GAMMA_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + +
21 #include <boost/random/gamma_distribution.hpp>
+
22 #include <boost/random/variate_generator.hpp>
+
23 #include <cmath>
+
24 
+
25 namespace stan {
+
26 
+
27  namespace math {
+
28 
+
51  template <bool propto,
+
52  typename T_y, typename T_shape, typename T_inv_scale>
+
53  typename return_type<T_y, T_shape, T_inv_scale>::type
+
54  gamma_log(const T_y& y, const T_shape& alpha, const T_inv_scale& beta) {
+
55  static const char* function("stan::math::gamma_log");
+
56  typedef typename stan::partials_return_type<T_y, T_shape,
+
57  T_inv_scale>::type
+
58  T_partials_return;
+
59 
+ + + + + + +
66 
+
67  // check if any vectors are zero length
+
68  if (!(stan::length(y)
+
69  && stan::length(alpha)
+
70  && stan::length(beta)))
+
71  return 0.0;
+
72 
+
73  // set up return value accumulator
+
74  T_partials_return logp(0.0);
+
75 
+
76  // validate args (here done over var, which should be OK)
+
77  check_not_nan(function, "Random variable", y);
+
78  check_positive_finite(function, "Shape parameter", alpha);
+
79  check_positive_finite(function, "Inverse scale parameter", beta);
+
80  check_consistent_sizes(function,
+
81  "Random variable", y,
+
82  "Shape parameter", alpha,
+
83  "Inverse scale parameter", beta);
+
84 
+
85  // check if no variables are involved and prop-to
+ +
87  return 0.0;
+
88 
+
89  // set up template expressions wrapping scalars into vector views
+
90  VectorView<const T_y> y_vec(y);
+
91  VectorView<const T_shape> alpha_vec(alpha);
+
92  VectorView<const T_inv_scale> beta_vec(beta);
+
93 
+
94  for (size_t n = 0; n < length(y); n++) {
+
95  const T_partials_return y_dbl = value_of(y_vec[n]);
+
96  if (y_dbl < 0)
+
97  return LOG_ZERO;
+
98  }
+
99 
+
100  size_t N = max_size(y, alpha, beta);
+ +
102  operands_and_partials(y, alpha, beta);
+
103 
+
104  using boost::math::lgamma;
+ +
106  using boost::math::digamma;
+
107  using std::log;
+
108 
+ +
110  T_partials_return, T_y> log_y(length(y));
+ +
112  for (size_t n = 0; n < length(y); n++) {
+
113  if (value_of(y_vec[n]) > 0)
+
114  log_y[n] = log(value_of(y_vec[n]));
+
115  }
+
116  }
+
117 
+ +
119  T_partials_return, T_shape> lgamma_alpha(length(alpha));
+ +
121  T_partials_return, T_shape> digamma_alpha(length(alpha));
+
122  for (size_t n = 0; n < length(alpha); n++) {
+ +
124  lgamma_alpha[n] = lgamma(value_of(alpha_vec[n]));
+ +
126  digamma_alpha[n] = digamma(value_of(alpha_vec[n]));
+
127  }
+
128 
+ +
130  T_partials_return, T_inv_scale> log_beta(length(beta));
+ +
132  for (size_t n = 0; n < length(beta); n++)
+
133  log_beta[n] = log(value_of(beta_vec[n]));
+
134  }
+
135 
+
136  for (size_t n = 0; n < N; n++) {
+
137  // pull out values of arguments
+
138  const T_partials_return y_dbl = value_of(y_vec[n]);
+
139  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
140  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
141 
+ +
143  logp -= lgamma_alpha[n];
+ +
145  logp += alpha_dbl * log_beta[n];
+ +
147  logp += (alpha_dbl-1.0) * log_y[n];
+ +
149  logp -= beta_dbl * y_dbl;
+
150 
+
151  // gradients
+ +
153  operands_and_partials.d_x1[n] += (alpha_dbl-1)/y_dbl - beta_dbl;
+ +
155  operands_and_partials.d_x2[n] += -digamma_alpha[n] + log_beta[n]
+
156  + log_y[n];
+ +
158  operands_and_partials.d_x3[n] += alpha_dbl / beta_dbl - y_dbl;
+
159  }
+
160  return operands_and_partials.value(logp);
+
161  }
+
162 
+
163  template <typename T_y, typename T_shape, typename T_inv_scale>
+
164  inline
+ +
166  gamma_log(const T_y& y, const T_shape& alpha, const T_inv_scale& beta) {
+
167  return gamma_log<false>(y, alpha, beta);
+
168  }
+
169  }
+
170 }
+
171 
+
172 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
return_type< T_y, T_shape, T_inv_scale >::type gamma_log(const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
The log of a gamma density for y with the specified shape and inverse scale parameters.
Definition: gamma_log.hpp:54
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gamma__rng_8hpp.html b/doc/api/html/gamma__rng_8hpp.html new file mode 100644 index 00000000000..0598dc68394 --- /dev/null +++ b/doc/api/html/gamma__rng_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
gamma_rng.hpp File Reference
+
+ +
+
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diff --git a/doc/api/html/gamma__rng_8hpp_source.html b/doc/api/html/gamma__rng_8hpp_source.html new file mode 100644 index 00000000000..20ff65982b0 --- /dev/null +++ b/doc/api/html/gamma__rng_8hpp_source.html @@ -0,0 +1,185 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gamma_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
gamma_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GAMMA_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GAMMA_RNG_HPP
+
3 
+
4 #include <boost/random/gamma_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + +
23 
+
24 namespace stan {
+
25 
+
26  namespace math {
+
27 
+
28  template <class RNG>
+
29  inline double
+
30  gamma_rng(const double alpha,
+
31  const double beta,
+
32  RNG& rng) {
+
33  using boost::variate_generator;
+
34  using boost::gamma_distribution;
+
35 
+
36  static const char* function("stan::math::gamma_rng");
+
37 
+ +
39 
+
40  check_positive_finite(function, "Shape parameter", alpha);
+
41  check_positive_finite(function, "Inverse scale parameter", beta);
+
42 
+
43  /*
+
44  the boost gamma distribution is defined by
+
45  shape and scale, whereas the stan one is defined
+
46  by shape and rate
+
47  */
+
48  variate_generator<RNG&, gamma_distribution<> >
+
49  gamma_rng(rng, gamma_distribution<>(alpha, 1.0 / beta));
+
50  return gamma_rng();
+
51  }
+
52 
+
53  }
+
54 }
+
55 
+
56 #endif
+ +
double gamma_rng(const double alpha, const double beta, RNG &rng)
Definition: gamma_rng.hpp:30
+ + + + + + + + + + + + + + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
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diff --git a/doc/api/html/gaussian__dlm__obs__log_8hpp.html b/doc/api/html/gaussian__dlm__obs__log_8hpp.html new file mode 100644 index 00000000000..8cd7c4ca6ca --- /dev/null +++ b/doc/api/html/gaussian__dlm__obs__log_8hpp.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/gaussian_dlm_obs_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
gaussian_dlm_obs_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type stan::math::gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, Eigen::Dynamic > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
 The log of a Gaussian dynamic linear model (GDLM). More...
 
template<typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type stan::math::gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, Eigen::Dynamic > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
 
template<bool propto, typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type stan::math::gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, 1 > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
 The log of a Gaussian dynamic linear model (GDLM) with uncorrelated observation disturbances. More...
 
template<typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type stan::math::gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, 1 > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
 
+
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diff --git a/doc/api/html/gaussian__dlm__obs__log_8hpp_source.html b/doc/api/html/gaussian__dlm__obs__log_8hpp_source.html new file mode 100644 index 00000000000..b00fe2e66d7 --- /dev/null +++ b/doc/api/html/gaussian__dlm__obs__log_8hpp_source.html @@ -0,0 +1,543 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/gaussian_dlm_obs_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
gaussian_dlm_obs_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_GAUSSIAN_DLM_OBS_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_GAUSSIAN_DLM_OBS_LOG_HPP
+
3 
+
4 #include <boost/random/normal_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + +
24 
+ + +
27 
+
28 /*
+
29  TODO: time-varying system matrices
+
30  TODO: use sequential processing even for non-diagonal obs
+
31  covariance.
+
32  TODO: add constant terms in observation.
+
33 */
+
34 
+
35 namespace stan {
+
36  namespace math {
+
70  template <bool propto,
+
71  typename T_y,
+
72  typename T_F, typename T_G,
+
73  typename T_V, typename T_W,
+
74  typename T_m0, typename T_C0
+
75  >
+
76  typename return_type<
+
77  T_y,
+
78  typename return_type<T_F, T_G, T_V, T_W, T_m0, T_C0>::type >::type
+
79  gaussian_dlm_obs_log(const Eigen::Matrix
+
80  <T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
81  const Eigen::Matrix
+
82  <T_F, Eigen::Dynamic, Eigen::Dynamic>& F,
+
83  const Eigen::Matrix
+
84  <T_G, Eigen::Dynamic, Eigen::Dynamic>& G,
+
85  const Eigen::Matrix
+
86  <T_V, Eigen::Dynamic, Eigen::Dynamic>& V,
+
87  const Eigen::Matrix
+
88  <T_W, Eigen::Dynamic, Eigen::Dynamic>& W,
+
89  const Eigen::Matrix<T_m0, Eigen::Dynamic, 1>& m0,
+
90  const Eigen::Matrix
+
91  <T_C0, Eigen::Dynamic, Eigen::Dynamic>& C0) {
+
92  static const char* function("stan::math::gaussian_dlm_obs_log");
+
93  typedef typename return_type<
+
94  T_y,
+ +
96  T_lp lp(0.0);
+
97 
+
98  using stan::math::add;
+ + + + + + + + +
107  using stan::math::multiply;
+ +
109  using stan::math::subtract;
+ +
111  using stan::math::transpose;
+
112 
+
113  int r = y.rows(); // number of variables
+
114  int T = y.cols(); // number of observations
+
115  int n = G.rows(); // number of states
+
116 
+
117  // check y
+
118  check_finite(function, "y", y);
+
119  check_not_nan(function, "y", y);
+
120  // check F
+
121  check_size_match(function,
+
122  "columns of F", F.cols(),
+
123  "rows of y", y.rows());
+
124  check_size_match(function,
+
125  "rows of F", F.rows(),
+
126  "rows of G", G.rows());
+
127  check_finite(function, "F", F);
+
128  // check G
+
129  check_square(function, "G", G);
+
130  check_finite(function, "G", G);
+
131  // check V
+
132  check_size_match(function,
+
133  "rows of V", V.rows(),
+
134  "rows of y", y.rows());
+
135  // TODO(anyone): incorporate support for infinite V
+
136  check_finite(function, "V", V);
+
137  check_spsd_matrix(function, "V", V);
+
138  // check W
+
139  check_size_match(function,
+
140  "rows of W", W.rows(),
+
141  "rows of G", G.rows());
+
142  // TODO(anyone): incorporate support for infinite W
+
143  check_finite(function, "W", W);
+
144  check_spsd_matrix(function, "W", W);
+
145  // check m0
+
146  check_size_match(function,
+
147  "size of m0", m0.size(),
+
148  "rows of G", G.rows());
+
149  check_finite(function, "m0", m0);
+
150  // check C0
+
151  check_size_match(function,
+
152  "rows of C0", C0.rows(),
+
153  "rows of G", G.rows());
+
154  check_cov_matrix(function, "C0", C0);
+
155  check_finite(function, "C0", C0);
+
156 
+
157  if (y.cols() == 0 || y.rows() == 0)
+
158  return lp;
+
159 
+ +
161  lp -= 0.5 * LOG_TWO_PI * r * T;
+
162  }
+
163 
+ +
165  Eigen::Matrix<T_lp, Eigen::Dynamic, 1> m(n);
+
166  Eigen::Matrix<T_lp, Eigen::Dynamic, Eigen::Dynamic> C(n, n);
+
167 
+
168  // TODO(anyone): how to recast matrices
+
169  for (int i = 0; i < m0.size(); i++) {
+
170  m(i) = m0(i);
+
171  }
+
172  for (int i = 0; i < C0.rows(); i++) {
+
173  for (int j = 0; j < C0.cols(); j++) {
+
174  C(i, j) = C0(i, j);
+
175  }
+
176  }
+
177 
+
178  Eigen::Matrix<typename return_type<T_y>::type,
+
179  Eigen::Dynamic, 1> yi(r);
+
180  Eigen::Matrix<T_lp, Eigen::Dynamic, 1> a(n);
+
181  Eigen::Matrix<T_lp, Eigen::Dynamic, Eigen::Dynamic> R(n, n);
+
182  Eigen::Matrix<T_lp, Eigen::Dynamic, 1> f(r);
+
183  Eigen::Matrix<T_lp, Eigen::Dynamic, Eigen::Dynamic> Q(r, r);
+
184  Eigen::Matrix<T_lp, Eigen::Dynamic, Eigen::Dynamic> Q_inv(r, r);
+
185  Eigen::Matrix<T_lp, Eigen::Dynamic, 1> e(r);
+
186  Eigen::Matrix<T_lp, Eigen::Dynamic, Eigen::Dynamic> A(n, r);
+
187 
+
188  for (int i = 0; i < y.cols(); i++) {
+
189  yi = y.col(i);
+
190  // // Predict state
+
191  // a_t = G_t m_{t-1}
+
192  a = multiply(G, m);
+
193  // R_t = G_t C_{t-1} G_t' + W_t
+
194  R = add(quad_form_sym(C, transpose(G)), W);
+
195  // // predict observation
+
196  // f_t = F_t' a_t
+
197  f = multiply(transpose(F), a);
+
198  // Q_t = F'_t R_t F_t + V_t
+
199  Q = add(quad_form_sym(R, F), V);
+
200  Q_inv = inverse_spd(Q);
+
201  // // filtered state
+
202  // e_t = y_t - f_t
+
203  e = subtract(yi, f);
+
204  // A_t = R_t F_t Q^{-1}_t
+
205  A = multiply(multiply(R, F), Q_inv);
+
206  // m_t = a_t + A_t e_t
+
207  m = add(a, multiply(A, e));
+
208  // C = R_t - A_t Q_t A_t'
+
209  C = subtract(R, quad_form_sym(Q, transpose(A)));
+
210  lp -= 0.5 * (log_determinant_spd(Q) + trace_quad_form(Q_inv, e));
+
211  }
+
212  }
+
213  return lp;
+
214  }
+
215 
+
216  template <typename T_y,
+
217  typename T_F, typename T_G,
+
218  typename T_V, typename T_W,
+
219  typename T_m0, typename T_C0
+
220  >
+
221  inline
+
222  typename return_type<
+
223  T_y,
+ +
225  gaussian_dlm_obs_log(const Eigen::Matrix
+
226  <T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
227  const Eigen::Matrix
+
228  <T_F, Eigen::Dynamic, Eigen::Dynamic>& F,
+
229  const Eigen::Matrix
+
230  <T_G, Eigen::Dynamic, Eigen::Dynamic>& G,
+
231  const Eigen::Matrix
+
232  <T_V, Eigen::Dynamic, Eigen::Dynamic>& V,
+
233  const Eigen::Matrix
+
234  <T_W, Eigen::Dynamic, Eigen::Dynamic>& W,
+
235  const Eigen::Matrix<T_m0, Eigen::Dynamic, 1>& m0,
+
236  const Eigen::Matrix
+
237  <T_C0, Eigen::Dynamic, Eigen::Dynamic>& C0) {
+
238  return gaussian_dlm_obs_log<false>(y, F, G, V, W, m0, C0);
+
239  }
+
240 
+
276  template <bool propto,
+
277  typename T_y,
+
278  typename T_F, typename T_G,
+
279  typename T_V, typename T_W,
+
280  typename T_m0, typename T_C0
+
281  >
+
282  typename return_type<
+
283  T_y,
+ +
285  gaussian_dlm_obs_log(const Eigen::Matrix
+
286  <T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
287  const Eigen::Matrix
+
288  <T_F, Eigen::Dynamic, Eigen::Dynamic>& F,
+
289  const Eigen::Matrix
+
290  <T_G, Eigen::Dynamic, Eigen::Dynamic>& G,
+
291  const Eigen::Matrix<T_V, Eigen::Dynamic, 1>& V,
+
292  const Eigen::Matrix
+
293  <T_W, Eigen::Dynamic, Eigen::Dynamic>& W,
+
294  const Eigen::Matrix<T_m0, Eigen::Dynamic, 1>& m0,
+
295  const Eigen::Matrix
+
296  <T_C0, Eigen::Dynamic, Eigen::Dynamic>& C0) {
+
297  static const char* function("stan::math::gaussian_dlm_obs_log");
+
298  typedef
+
299  typename return_type
+ +
301  T_lp;
+
302  T_lp lp(0.0);
+
303 
+
304  using stan::math::add;
+ + + + + + + +
312  using stan::math::multiply;
+ +
314  using stan::math::subtract;
+ + +
317  using stan::math::transpose;
+
318  using std::log;
+
319 
+
320  int r = y.rows(); // number of variables
+
321  int T = y.cols(); // number of observations
+
322  int n = G.rows(); // number of states
+
323 
+
324  // check y
+
325  check_finite(function, "y", y);
+
326  check_not_nan(function, "y", y);
+
327  // check F
+
328  check_size_match(function,
+
329  "columns of F", F.cols(),
+
330  "rows of y", y.rows());
+
331  check_size_match(function,
+
332  "rows of F", F.rows(),
+
333  "rows of G", G.rows());
+
334  check_finite(function, "F", F);
+
335  check_not_nan(function, "F", F);
+
336  // check G
+
337  check_size_match(function,
+
338  "rows of G", G.rows(),
+
339  "columns of G", G.cols());
+
340  check_finite(function, "G", G);
+
341  check_not_nan(function, "G", G);
+
342  // check V
+
343  check_nonnegative(function, "V", V);
+
344  check_size_match(function,
+
345  "size of V", V.size(),
+
346  "rows of y", y.rows());
+
347  // TODO(anyone): support infinite V
+
348  check_finite(function, "V", V);
+
349  check_not_nan(function, "V", V);
+
350  // check W
+
351  check_spsd_matrix(function, "W", W);
+
352  check_size_match(function,
+
353  "rows of W", W.rows(),
+
354  "rows of G", G.rows());
+
355  // TODO(anyone): support infinite W
+
356  check_finite(function, "W", W);
+
357  check_not_nan(function, "W", W);
+
358  // check m0
+
359  check_size_match(function,
+
360  "size of m0", m0.size(),
+
361  "rows of G", G.rows());
+
362  check_finite(function, "m0", m0);
+
363  check_not_nan(function, "m0", m0);
+
364  // check C0
+
365  check_cov_matrix(function, "C0", C0);
+
366  check_size_match(function,
+
367  "rows of C0", C0.rows(),
+
368  "rows of G", G.rows());
+
369  check_finite(function, "C0", C0);
+
370  check_not_nan(function, "C0", C0);
+
371 
+
372  if (y.cols() == 0 || y.rows() == 0)
+
373  return lp;
+
374 
+ +
376  lp += 0.5 * NEG_LOG_TWO_PI * r * T;
+
377  }
+
378 
+ +
380  T_lp f;
+
381  T_lp Q;
+
382  T_lp Q_inv;
+
383  T_lp e;
+
384  Eigen::Matrix<T_lp, Eigen::Dynamic, 1> A(n);
+
385  Eigen::Matrix<T_lp, Eigen::Dynamic, 1> Fj(n);
+
386  Eigen::Matrix<T_lp, Eigen::Dynamic, 1> m(n);
+
387  Eigen::Matrix<T_lp, Eigen::Dynamic, Eigen::Dynamic> C(n, n);
+
388 
+
389  // TODO(anyone): how to recast matrices
+
390  for (int i = 0; i < m0.size(); i++) {
+
391  m(i) = m0(i);
+
392  }
+
393  for (int i = 0; i < C0.rows(); i++) {
+
394  for (int j = 0; j < C0.cols(); j++) {
+
395  C(i, j) = C0(i, j);
+
396  }
+
397  }
+
398 
+
399  for (int i = 0; i < y.cols(); i++) {
+
400  // Predict state
+
401  // reuse m and C instead of using a and R
+
402  m = multiply(G, m);
+
403  C = add(quad_form_sym(C, transpose(G)), W);
+
404  for (int j = 0; j < y.rows(); ++j) {
+
405  // predict observation
+
406  T_lp yij(y(j, i));
+
407  // dim Fj = (n, 1)
+
408  for (int k = 0; k < F.rows(); ++k) {
+
409  Fj(k) = F(k, j);
+
410  }
+
411  // // f_{t, i} = F_{t, i}' m_{t, i-1}
+
412  f = dot_product(Fj, m);
+
413  Q = trace_quad_form(C, Fj) + V(j);
+
414  Q_inv = 1.0 / Q;
+
415  // // filtered observation
+
416  // // e_{t, i} = y_{t, i} - f_{t, i}
+
417  e = yij - f;
+
418  // // A_{t, i} = C_{t, i-1} F_{t, i} Q_{t, i}^{-1}
+
419  A = multiply(multiply(C, Fj), Q_inv);
+
420  // // m_{t, i} = m_{t, i-1} + A_{t, i} e_{t, i}
+
421  m += multiply(A, e);
+
422  // // c_{t, i} = C_{t, i-1} - Q_{t, i} A_{t, i} A_{t, i}'
+
423  // // // tcrossprod throws an error (ambiguous)
+
424  // C = subtract(C, multiply(Q, tcrossprod(A)));
+
425  C -= multiply(Q, multiply(A, transpose(A)));
+
426  C = 0.5 * add(C, transpose(C));
+
427  lp -= 0.5 * (log(Q) + pow(e, 2) * Q_inv);
+
428  }
+
429  }
+
430  }
+
431  return lp;
+
432  }
+
433 
+
434  template <typename T_y,
+
435  typename T_F, typename T_G,
+
436  typename T_V, typename T_W,
+
437  typename T_m0, typename T_C0>
+
438  inline
+
439  typename return_type
+ + +
442  (const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
443  const Eigen::Matrix<T_F, Eigen::Dynamic, Eigen::Dynamic>& F,
+
444  const Eigen::Matrix<T_G, Eigen::Dynamic, Eigen::Dynamic>& G,
+
445  const Eigen::Matrix<T_V, Eigen::Dynamic, 1>& V,
+
446  const Eigen::Matrix<T_W, Eigen::Dynamic, Eigen::Dynamic>& W,
+
447  const Eigen::Matrix<T_m0, Eigen::Dynamic, 1>& m0,
+
448  const Eigen::Matrix<T_C0, Eigen::Dynamic, Eigen::Dynamic>& C0) {
+
449  return gaussian_dlm_obs_log<false>(y, F, G, V, W, m0, C0);
+
450  }
+
451  }
+
452 
+
453 }
+
454 
+
455 #endif
+ + + + +
fvar< T > trace_quad_form(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the result of subtracting the second specified matrix from the first specified matrix...
Definition: subtract.hpp:27
+
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type gaussian_dlm_obs_log(const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, Eigen::Dynamic > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
The log of a Gaussian dynamic linear model (GDLM).
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of...
Definition: return_type.hpp:19
+
Eigen::Matrix< fvar< T >, R, R > tcrossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: tcrossprod.hpp:17
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
bool check_spsd_matrix(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a square, symmetric, and positive semi-definite.
+ + + +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
const double LOG_TWO_PI
Definition: constants.hpp:193
+ + + +
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ +
bool check_cov_matrix(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a valid covariance matrix.
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
Eigen::Matrix< fvar< T >, CB, CB > quad_form_sym(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
+ + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > inverse_spd(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the inverse of the specified symmetric, pos/neg-definite matrix.
Definition: inverse_spd.hpp:20
+
const double NEG_LOG_TWO_PI
Definition: constants.hpp:195
+
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > add(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the sum of the specified matrices.
Definition: add.hpp:27
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+ + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
T log_determinant_spd(const Eigen::Matrix< T, R, C > &m)
Returns the log absolute determinant of the specified square matrix.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/get__base1_8hpp.html b/doc/api/html/get__base1_8hpp.html new file mode 100644 index 00000000000..7ed7eebfadf --- /dev/null +++ b/doc/api/html/get__base1_8hpp.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/get_base1.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
get_base1.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
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+Functions

template<typename T >
const T & stan::math::get_base1 (const std::vector< T > &x, size_t i, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one index. More...
 
template<typename T >
const T & stan::math::get_base1 (const std::vector< std::vector< T > > &x, size_t i1, size_t i2, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & stan::math::get_base1 (const std::vector< std::vector< std::vector< T > > > &x, size_t i1, size_t i2, size_t i3, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< T > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, size_t i7, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, size_t i7, size_t i8, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x, size_t m, const char *error_msg, size_t idx)
 Return a copy of the row of the specified vector at the specified base-one row index. More...
 
template<typename T >
const T & stan::math::get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x, size_t m, size_t n, const char *error_msg, size_t idx)
 Return a reference to the value of the specified matrix at the specified base-one row and column indexes. More...
 
template<typename T >
const T & stan::math::get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t m, const char *error_msg, size_t idx)
 Return a reference to the value of the specified column vector at the specified base-one index. More...
 
template<typename T >
const T & stan::math::get_base1 (const Eigen::Matrix< T, 1, Eigen::Dynamic > &x, size_t n, const char *error_msg, size_t idx)
 Return a reference to the value of the specified row vector at the specified base-one index. More...
 
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diff --git a/doc/api/html/get__base1_8hpp_source.html b/doc/api/html/get__base1_8hpp_source.html new file mode 100644 index 00000000000..1256f97b71d --- /dev/null +++ b/doc/api/html/get__base1_8hpp_source.html @@ -0,0 +1,298 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/get_base1.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
get_base1.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_GET_BASE1_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_GET_BASE1_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
25  template <typename T>
+
26  inline const T&
+
27  get_base1(const std::vector<T>& x,
+
28  size_t i,
+
29  const char* error_msg,
+
30  size_t idx) {
+ +
32  check_range("[]", "x", x.size(), i, idx, error_msg);
+
33  return x[i - 1];
+
34  }
+
35 
+
51  template <typename T>
+
52  inline const T&
+
53  get_base1(const std::vector<std::vector<T> >& x,
+
54  size_t i1,
+
55  size_t i2,
+
56  const char* error_msg,
+
57  size_t idx) {
+ +
59  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
60  return get_base1(x[i1 - 1], i2, error_msg, idx+1);
+
61  }
+
62 
+
79  template <typename T>
+
80  inline const T&
+
81  get_base1(const std::vector<std::vector<std::vector<T> > >& x,
+
82  size_t i1,
+
83  size_t i2,
+
84  size_t i3,
+
85  const char* error_msg,
+
86  size_t idx) {
+ +
88  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
89  return get_base1(x[i1 - 1], i2, i3, error_msg, idx+1);
+
90  }
+
91 
+
109  template <typename T>
+
110  inline const T&
+
111  get_base1(const std::vector<std::vector<std::vector<std::vector<T> > > >& x,
+
112  size_t i1,
+
113  size_t i2,
+
114  size_t i3,
+
115  size_t i4,
+
116  const char* error_msg,
+
117  size_t idx) {
+ +
119  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
120  return get_base1(x[i1 - 1], i2, i3, i4, error_msg, idx+1);
+
121  }
+
122 
+
141  template <typename T>
+
142  inline const T&
+
143  get_base1(const std::vector<std::vector<std::vector<std::vector
+
144  <std::vector<T> > > > >& x,
+
145  size_t i1,
+
146  size_t i2,
+
147  size_t i3,
+
148  size_t i4,
+
149  size_t i5,
+
150  const char* error_msg,
+
151  size_t idx) {
+ +
153  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
154  return get_base1(x[i1 - 1], i2, i3, i4, i5, error_msg, idx+1);
+
155  }
+
156 
+
176  template <typename T>
+
177  inline const T&
+
178  get_base1(const std::vector<std::vector<std::vector<std::vector
+
179  <std::vector<std::vector<T> > > > > >& x,
+
180  size_t i1,
+
181  size_t i2,
+
182  size_t i3,
+
183  size_t i4,
+
184  size_t i5,
+
185  size_t i6,
+
186  const char* error_msg,
+
187  size_t idx) {
+ +
189  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
190  return get_base1(x[i1 - 1], i2, i3, i4, i5, i6, error_msg, idx+1);
+
191  }
+
192 
+
193 
+
214  template <typename T>
+
215  inline const T&
+
216  get_base1(const std::vector<std::vector<std::vector<std::vector
+
217  <std::vector<std::vector<std::vector<T> > > > > > >& x,
+
218  size_t i1,
+
219  size_t i2,
+
220  size_t i3,
+
221  size_t i4,
+
222  size_t i5,
+
223  size_t i6,
+
224  size_t i7,
+
225  const char* error_msg,
+
226  size_t idx) {
+ +
228  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
229  return get_base1(x[i1 - 1], i2, i3, i4, i5, i6, i7, error_msg, idx+1);
+
230  }
+
231 
+
232 
+
254  template <typename T>
+
255  inline const T&
+
256  get_base1(const std::vector<std::vector<std::vector
+
257  <std::vector<std::vector<std::vector
+
258  <std::vector<std::vector<T> > > > > > > >& x,
+
259  size_t i1,
+
260  size_t i2,
+
261  size_t i3,
+
262  size_t i4,
+
263  size_t i5,
+
264  size_t i6,
+
265  size_t i7,
+
266  size_t i8,
+
267  const char* error_msg,
+
268  size_t idx) {
+ +
270  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
271  return get_base1(x[i1 - 1], i2, i3, i4, i5, i6, i7, i8, error_msg, idx+1);
+
272  }
+
273 
+
274 
+
275 
+
295  template <typename T>
+
296  inline Eigen::Matrix<T, 1, Eigen::Dynamic>
+
297  get_base1(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& x,
+
298  size_t m,
+
299  const char* error_msg,
+
300  size_t idx) {
+ +
302  check_range("[]", "rows of x", x.rows(), m, idx, error_msg);
+
303  return x.block(m-1, 0, 1, x.cols());
+
304  }
+
305 
+
322  template <typename T>
+
323  inline const T&
+
324  get_base1(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& x,
+
325  size_t m,
+
326  size_t n,
+
327  const char* error_msg,
+
328  size_t idx) {
+ +
330  check_range("[]", "rows of x", x.rows(), m, idx, error_msg);
+
331  check_range("[]", "cols of x", x.cols(), n, idx + 1, error_msg);
+
332  return x(m - 1, n - 1);
+
333  }
+
334 
+
349  template <typename T>
+
350  inline
+
351  const T& get_base1(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
352  size_t m,
+
353  const char* error_msg,
+
354  size_t idx) {
+ +
356  check_range("[]", "x", x.size(), m, idx, error_msg);
+
357  return x(m - 1);
+
358  }
+
359 
+
374  template <typename T>
+
375  inline const T&
+
376  get_base1(const Eigen::Matrix<T, 1, Eigen::Dynamic>& x,
+
377  size_t n,
+
378  const char* error_msg,
+
379  size_t idx) {
+ +
381  check_range("[]", "x", x.size(), n, idx, error_msg);
+
382  return x(n - 1);
+
383  }
+
384 
+
385  }
+
386 }
+
387 #endif
+ +
bool check_range(const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
Return true if specified index is within range.
Definition: check_range.hpp:29
+
const T & get_base1(const std::vector< T > &x, size_t i, const char *error_msg, size_t idx)
Return a reference to the value of the specified vector at the specified base-one index...
Definition: get_base1.hpp:27
+ + +
+
+
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diff --git a/doc/api/html/get__base1__lhs_8hpp.html b/doc/api/html/get__base1__lhs_8hpp.html new file mode 100644 index 00000000000..1c74e856240 --- /dev/null +++ b/doc/api/html/get__base1__lhs_8hpp.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/get_base1_lhs.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
get_base1_lhs.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T >
T & stan::math::get_base1_lhs (std::vector< T > &x, size_t i, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one index. More...
 
template<typename T >
T & stan::math::get_base1_lhs (std::vector< std::vector< T > > &x, size_t i1, size_t i2, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & stan::math::get_base1_lhs (std::vector< std::vector< std::vector< T > > > &x, size_t i1, size_t i2, size_t i3, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< T > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, size_t i7, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, size_t i7, size_t i8, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
Eigen::Block< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > > stan::math::get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x, size_t m, const char *error_msg, size_t idx)
 Return a copy of the row of the specified vector at the specified base-one row index. More...
 
template<typename T >
T & stan::math::get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x, size_t m, size_t n, const char *error_msg, size_t idx)
 Return a reference to the value of the specified matrix at the specified base-one row and column indexes. More...
 
template<typename T >
T & stan::math::get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t m, const char *error_msg, size_t idx)
 Return a reference to the value of the specified column vector at the specified base-one index. More...
 
template<typename T >
T & stan::math::get_base1_lhs (Eigen::Matrix< T, 1, Eigen::Dynamic > &x, size_t n, const char *error_msg, size_t idx)
 Return a reference to the value of the specified row vector at the specified base-one index. More...
 
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diff --git a/doc/api/html/get__base1__lhs_8hpp_source.html b/doc/api/html/get__base1__lhs_8hpp_source.html new file mode 100644 index 00000000000..761d42d070f --- /dev/null +++ b/doc/api/html/get__base1__lhs_8hpp_source.html @@ -0,0 +1,302 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/get_base1_lhs.hpp Source File + + + + + + + + + + +
+
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+
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get_base1_lhs.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_GET_BASE1_LHS_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_GET_BASE1_LHS_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
25  template <typename T>
+
26  inline
+
27  T& get_base1_lhs(std::vector<T>& x,
+
28  size_t i,
+
29  const char* error_msg,
+
30  size_t idx) {
+ +
32  check_range("[]", "x", x.size(), i, idx, error_msg);
+
33  return x[i - 1];
+
34  }
+
35 
+
51  template <typename T>
+
52  inline
+
53  T& get_base1_lhs(std::vector<std::vector<T> >& x,
+
54  size_t i1,
+
55  size_t i2,
+
56  const char* error_msg,
+
57  size_t idx) {
+ +
59  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
60  return get_base1_lhs(x[i1 - 1], i2, error_msg, idx+1);
+
61  }
+
62 
+
79  template <typename T>
+
80  inline
+
81  T& get_base1_lhs(std::vector<std::vector<std::vector<T> > >& x,
+
82  size_t i1,
+
83  size_t i2,
+
84  size_t i3,
+
85  const char* error_msg,
+
86  size_t idx) {
+ +
88  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
89  return get_base1_lhs(x[i1 - 1], i2, i3, error_msg, idx+1);
+
90  }
+
91 
+
109  template <typename T>
+
110  inline
+
111  T& get_base1_lhs(std::vector<std::vector<std::vector
+
112  <std::vector<T> > > >& x,
+
113  size_t i1,
+
114  size_t i2,
+
115  size_t i3,
+
116  size_t i4,
+
117  const char* error_msg,
+
118  size_t idx) {
+ +
120  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
121  return get_base1_lhs(x[i1 - 1], i2, i3, i4, error_msg, idx+1);
+
122  }
+
123 
+
142  template <typename T>
+
143  inline
+
144  T& get_base1_lhs(std::vector<std::vector<std::vector<std::vector
+
145  <std::vector<T> > > > >& x,
+
146  size_t i1,
+
147  size_t i2,
+
148  size_t i3,
+
149  size_t i4,
+
150  size_t i5,
+
151  const char* error_msg,
+
152  size_t idx) {
+ +
154  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
155  return get_base1_lhs(x[i1 - 1], i2, i3, i4, i5, error_msg, idx+1);
+
156  }
+
157 
+
177  template <typename T>
+
178  inline
+
179  T& get_base1_lhs(std::vector<std::vector<std::vector<std::vector
+
180  <std::vector<std::vector<T> > > > > >& x,
+
181  size_t i1,
+
182  size_t i2,
+
183  size_t i3,
+
184  size_t i4,
+
185  size_t i5,
+
186  size_t i6,
+
187  const char* error_msg,
+
188  size_t idx) {
+ +
190  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
191  return get_base1_lhs(x[i1 - 1], i2, i3, i4, i5, i6, error_msg, idx+1);
+
192  }
+
193 
+
194 
+
215  template <typename T>
+
216  inline
+
217  T& get_base1_lhs(std::vector<std::vector<std::vector<std::vector
+
218  <std::vector<std::vector
+
219  <std::vector<T> > > > > > >& x,
+
220  size_t i1,
+
221  size_t i2,
+
222  size_t i3,
+
223  size_t i4,
+
224  size_t i5,
+
225  size_t i6,
+
226  size_t i7,
+
227  const char* error_msg,
+
228  size_t idx) {
+ +
230  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
231  return get_base1_lhs(x[i1 - 1], i2, i3, i4, i5, i6, i7, error_msg, idx+1);
+
232  }
+
233 
+
234 
+
256  template <typename T>
+
257  inline
+
258  T& get_base1_lhs(std::vector<std::vector<std::vector<std::vector
+
259  <std::vector<std::vector<std::vector
+
260  <std::vector<T> > > > > > > >& x,
+
261  size_t i1,
+
262  size_t i2,
+
263  size_t i3,
+
264  size_t i4,
+
265  size_t i5,
+
266  size_t i6,
+
267  size_t i7,
+
268  size_t i8,
+
269  const char* error_msg,
+
270  size_t idx) {
+ +
272  check_range("[]", "x", x.size(), i1, idx, error_msg);
+
273  return get_base1_lhs(x[i1 - 1], i2, i3, i4, i5, i6, i7, i8,
+
274  error_msg, idx+1);
+
275  }
+
276 
+
277 
+
278 
+
298  template <typename T>
+
299  inline
+
300  Eigen::Block<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
+
301  get_base1_lhs(Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& x,
+
302  size_t m,
+
303  const char* error_msg,
+
304  size_t idx) {
+ +
306  check_range("[]", "rows of x", x.rows(), m, idx, error_msg);
+
307  return x.block(m-1, 0, 1, x.cols());
+
308  }
+
309 
+
326  template <typename T>
+
327  inline
+
328  T& get_base1_lhs(Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& x,
+
329  size_t m,
+
330  size_t n,
+
331  const char* error_msg,
+
332  size_t idx) {
+ +
334  check_range("[]", "rows of x", x.rows(), m, idx, error_msg);
+
335  check_range("[]", "cols of x", x.cols(), n, idx + 1, error_msg);
+
336  return x(m - 1, n - 1);
+
337  }
+
338 
+
353  template <typename T>
+
354  inline
+
355  T& get_base1_lhs(Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
356  size_t m,
+
357  const char* error_msg,
+
358  size_t idx) {
+ +
360  check_range("[]", "x", x.size(), m, idx, error_msg);
+
361  return x(m - 1);
+
362  }
+
363 
+
378  template <typename T>
+
379  inline
+
380  T& get_base1_lhs(Eigen::Matrix<T, 1, Eigen::Dynamic>& x,
+
381  size_t n,
+
382  const char* error_msg,
+
383  size_t idx) {
+ +
385  check_range("[]", "x", x.size(), n, idx, error_msg);
+
386  return x(n - 1);
+
387  }
+
388 
+
389  }
+
390 }
+
391 #endif
+ +
bool check_range(const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
Return true if specified index is within range.
Definition: check_range.hpp:29
+ +
T & get_base1_lhs(std::vector< T > &x, size_t i, const char *error_msg, size_t idx)
Return a reference to the value of the specified vector at the specified base-one index...
+ +
+
+
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diff --git a/doc/api/html/get__lp_8hpp.html b/doc/api/html/get__lp_8hpp.html new file mode 100644 index 00000000000..3ee5e1a3217 --- /dev/null +++ b/doc/api/html/get__lp_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/get_lp.hpp File Reference + + + + + + + + + + +
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#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/mat/fun/accumulator.hpp>
+
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template<typename T_lp , typename T_lp_accum >
boost::math::tools::promote_args< T_lp, T_lp_accum >::type stan::math::get_lp (const T_lp &lp, const stan::math::accumulator< T_lp_accum > &lp_accum)
 
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diff --git a/doc/api/html/get__lp_8hpp_source.html b/doc/api/html/get__lp_8hpp_source.html new file mode 100644 index 00000000000..25cf665e3d4 --- /dev/null +++ b/doc/api/html/get__lp_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/get_lp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_GET_LP_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_GET_LP_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T_lp, typename T_lp_accum>
+
12  inline
+
13  typename boost::math::tools::promote_args<T_lp, T_lp_accum>::type
+
14  get_lp(const T_lp& lp,
+
15  const stan::math::accumulator<T_lp_accum>& lp_accum) {
+
16  return lp + lp_accum.sum();
+
17  }
+
18 
+
19  }
+
20 
+
21 }
+
22 
+
23 #endif
+
T sum() const
Return the sum of the accumulated values.
+ + +
boost::math::tools::promote_args< T_lp, T_lp_accum >::type get_lp(const T_lp &lp, const stan::math::accumulator< T_lp_accum > &lp_accum)
Definition: get_lp.hpp:14
+
Class to accumulate values and eventually return their sum.
Definition: accumulator.hpp:25
+
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diff --git a/doc/api/html/gevv__vvv__vari_8hpp.html b/doc/api/html/gevv__vvv__vari_8hpp.html new file mode 100644 index 00000000000..23ff6c664c2 --- /dev/null +++ b/doc/api/html/gevv__vvv__vari_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/core/gevv_vvv_vari.hpp File Reference + + + + + + + + + + +
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class  stan::math::gevv_vvv_vari
 
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diff --git a/doc/api/html/gevv__vvv__vari_8hpp_source.html b/doc/api/html/gevv__vvv__vari_8hpp_source.html new file mode 100644 index 00000000000..661d188e814 --- /dev/null +++ b/doc/api/html/gevv__vvv__vari_8hpp_source.html @@ -0,0 +1,191 @@ + + + + + + +Stan Math Library: stan/math/rev/core/gevv_vvv_vari.hpp Source File + + + + + + + + + + +
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gevv_vvv_vari.hpp
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1 #ifndef STAN_MATH_REV_CORE_GEVV_VVV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_GEVV_VVV_VARI_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+ +
12  protected:
+ + + +
16  double dotval_;
+
17  size_t length_;
+
18  inline static double eval_gevv(const stan::math::var* alpha,
+
19  const stan::math::var* v1, int stride1,
+
20  const stan::math::var* v2, int stride2,
+
21  size_t length, double *dotprod) {
+
22  double result = 0;
+
23  for (size_t i = 0; i < length; i++)
+
24  result += v1[i*stride1].vi_->val_ * v2[i*stride2].vi_->val_;
+
25  *dotprod = result;
+
26  return alpha->vi_->val_ * result;
+
27  }
+
28 
+
29  public:
+ +
31  const stan::math::var* v1, int stride1,
+
32  const stan::math::var* v2, int stride2, size_t length) :
+
33  vari(eval_gevv(alpha, v1, stride1, v2, stride2, length, &dotval_)),
+
34  length_(length) {
+
35  alpha_ = alpha->vi_;
+
36  // TODO(carpenter): replace this with array alloc fun call
+
37  v1_ = reinterpret_cast<stan::math::vari**>
+ +
39  .alloc(2 * length_ * sizeof(stan::math::vari*)));
+
40  v2_ = v1_ + length_;
+
41  for (size_t i = 0; i < length_; i++)
+
42  v1_[i] = v1[i*stride1].vi_;
+
43  for (size_t i = 0; i < length_; i++)
+
44  v2_[i] = v2[i*stride2].vi_;
+
45  }
+
46  virtual ~gevv_vvv_vari() {}
+
47  void chain() {
+
48  const double adj_alpha = adj_ * alpha_->val_;
+
49  for (size_t i = 0; i < length_; i++) {
+
50  v1_[i]->adj_ += adj_alpha * v2_[i]->val_;
+
51  v2_[i]->adj_ += adj_alpha * v1_[i]->val_;
+
52  }
+
53  alpha_->adj_ += adj_ * dotval_;
+
54  }
+
55  };
+
56 
+
57  }
+
58 }
+
59 
+
60 #endif
+ + + + +
The variable implementation base class.
Definition: vari.hpp:30
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
static double eval_gevv(const stan::math::var *alpha, const stan::math::var *v1, int stride1, const stan::math::var *v2, int stride2, size_t length, double *dotprod)
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+ +
stan::math::vari * alpha_
+ +
stan::math::vari ** v1_
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
gevv_vvv_vari(const stan::math::var *alpha, const stan::math::var *v1, int stride1, const stan::math::var *v2, int stride2, size_t length)
+
stan::math::vari ** v2_
+ +
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+ +
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
+
+
+
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template<typename T >
void stan::math::grad_2F1 (T &gradA, T &gradC, T a, T b, T c, T z, T precision=1e-6)
 
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diff --git a/doc/api/html/grad__2_f1_8hpp_source.html b/doc/api/html/grad__2_f1_8hpp_source.html new file mode 100644 index 00000000000..248e844fcc2 --- /dev/null +++ b/doc/api/html/grad__2_f1_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_2F1.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_GRAD_2F1_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_GRAD_2F1_HPP
+
3 
+
4 #include <cmath>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
10  // Gradient of the hypergeometric function 2F1(a, b | c | z)
+
11  // with respect to a and c
+
12  template<typename T>
+
13  void grad_2F1(T& gradA, T& gradC, T a, T b, T c, T z, T precision = 1e-6) {
+
14  using std::fabs;
+
15 
+
16  gradA = 0;
+
17  gradC = 0;
+
18 
+
19  T gradAold = 0;
+
20  T gradCold = 0;
+
21 
+
22  int k = 0;
+
23  T tDak = 1.0 / (a - 1);
+
24 
+
25  while (fabs(tDak * (a + (k - 1)) ) > precision || k == 0) {
+
26  const T r = ( (a + k) / (c + k) ) * ( (b + k) / (T)(k + 1) ) * z;
+
27  tDak = r * tDak * (a + (k - 1)) / (a + k);
+
28 
+
29  if (r == 0) break;
+
30 
+
31  gradAold = r * gradAold + tDak;
+
32  gradCold = r * gradCold - tDak * ((a + k) / (c + k));
+
33 
+
34  gradA += gradAold;
+
35  gradC += gradCold;
+
36 
+
37  ++k;
+
38 
+
39  if (k > 200) break;
+
40  }
+
41  }
+
42 
+
43 
+
44  }
+
45 
+
46 }
+
47 
+
48 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
void grad_2F1(T &gradA, T &gradC, T a, T b, T c, T z, T precision=1e-6)
Definition: grad_2F1.hpp:13
+
+
+
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diff --git a/doc/api/html/grad___f32_8hpp.html b/doc/api/html/grad___f32_8hpp.html new file mode 100644 index 00000000000..6f8f1439e2d --- /dev/null +++ b/doc/api/html/grad___f32_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_F32.hpp File Reference + + + + + + + + + + +
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#include <cmath>
+
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template<typename T >
void stan::math::grad_F32 (T *g, T a, T b, T c, T d, T e, T z, T precision=1e-6)
 
+
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diff --git a/doc/api/html/grad___f32_8hpp_source.html b/doc/api/html/grad___f32_8hpp_source.html new file mode 100644 index 00000000000..12760a83239 --- /dev/null +++ b/doc/api/html/grad___f32_8hpp_source.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_F32.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_GRAD_F32_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_GRAD_F32_HPP
+
3 
+
4 #include <cmath>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
10  template<typename T>
+
11  void grad_F32(T* g, T a, T b, T c, T d, T e, T z, T precision = 1e-6) {
+
12  using std::log;
+
13  using std::fabs;
+
14  using std::exp;
+
15 
+
16  T gOld[6];
+
17 
+
18  for (T *p = g; p != g + 6; ++p) *p = 0;
+
19  for (T *p = gOld; p != gOld + 6; ++p) *p = 0;
+
20 
+
21  T tOld = 1;
+
22  T tNew = 0;
+
23 
+
24  T logT = 0;
+
25 
+
26  T logZ = log(z);
+
27 
+
28  int k = 0;
+
29 
+
30  while (fabs(tNew) > precision || k == 0) {
+
31  T C = (a + k) / (d + k);
+
32  C *= (b + k) / (e + k);
+
33  C *= (c + k) / (1 + k);
+
34 
+
35  // If a, b, or c is a negative integer then the series terminates
+
36  // after a finite number of interations
+
37  if (C == 0) break;
+
38 
+
39  logT += (C > 0 ? 1 : -1) * log(fabs(C)) + logZ;
+
40 
+
41  tNew = exp(logT);
+
42 
+
43  gOld[0] = tNew * (gOld[0] / tOld + 1.0 / (a + k));
+
44  gOld[1] = tNew * (gOld[1] / tOld + 1.0 / (b + k));
+
45  gOld[2] = tNew * (gOld[2] / tOld + 1.0 / (c + k));
+
46 
+
47  gOld[3] = tNew * (gOld[3] / tOld - 1.0 / (d + k));
+
48  gOld[4] = tNew * (gOld[4] / tOld - 1.0 / (e + k));
+
49 
+
50  gOld[5] = tNew * (gOld[5] / tOld + 1.0 / z);
+
51 
+
52  for (int i = 0; i < 6; ++i) g[i] += gOld[i];
+
53 
+
54  tOld = tNew;
+
55 
+
56  ++k;
+
57  }
+
58  }
+
59 
+
60  }
+
61 }
+
62 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
void grad_F32(T *g, T a, T b, T c, T d, T e, T z, T precision=1e-6)
Definition: grad_F32.hpp:11
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/grad__hessian_8hpp.html b/doc/api/html/grad__hessian_8hpp.html new file mode 100644 index 00000000000..b470c3d65e8 --- /dev/null +++ b/doc/api/html/grad__hessian_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/grad_hessian.hpp File Reference + + + + + + + + + + +
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grad_hessian.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stdexcept>
+#include <vector>
+
+

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+ + + + + +

+Functions

template<typename F >
void stan::math::grad_hessian (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &H, std::vector< Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > > &grad_H)
 Calculate the value, the Hessian, and the gradient of the Hessian of the specified function at the specified argument. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/grad__hessian_8hpp_source.html b/doc/api/html/grad__hessian_8hpp_source.html new file mode 100644 index 00000000000..a3bdfa742f1 --- /dev/null +++ b/doc/api/html/grad__hessian_8hpp_source.html @@ -0,0 +1,176 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/grad_hessian.hpp Source File + + + + + + + + + + +
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grad_hessian.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_GRAD_HESSIAN_HPP
+
2 #define STAN_MATH_MIX_MAT_FUNCTOR_GRAD_HESSIAN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <stan/math/rev/core.hpp>
+
7 #include <stdexcept>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
43  template <typename F>
+
44  void
+
45  grad_hessian(const F& f,
+
46  const Eigen::Matrix<double, Eigen::Dynamic, 1>& x,
+
47  double& fx,
+
48  Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& H,
+
49  std::vector<Eigen::Matrix<double,
+
50  Eigen::Dynamic, Eigen::Dynamic> >&
+
51  grad_H) {
+
52  using Eigen::Matrix;
+
53  using Eigen::Dynamic;
+
54  fx = f(x);
+
55  int d = x.size();
+
56  H.resize(d, d);
+
57  grad_H.resize(d, Matrix<double, Dynamic, Dynamic>(d, d));
+
58  try {
+
59  for (int i = 0; i < d; ++i) {
+
60  for (int j = i; j < d; ++j) {
+
61  start_nested();
+
62  Matrix<fvar<fvar<var> >, Dynamic, 1> x_ffvar(d);
+
63  for (int k = 0; k < d; ++k)
+
64  x_ffvar(k) = fvar<fvar<var> >(fvar<var>(x(k), i == k),
+
65  fvar<var>(j == k, 0));
+
66  fvar<fvar<var> > fx_ffvar = f(x_ffvar);
+
67  H(i, j) = fx_ffvar.d_.d_.val();
+
68  H(j, i) = H(i, j);
+
69  stan::math::grad(fx_ffvar.d_.d_.vi_);
+
70  for (int k = 0; k < d; ++k) {
+
71  grad_H[i](j, k) = x_ffvar(k).val_.val_.adj();
+
72  grad_H[j](i, k) = grad_H[i](j, k);
+
73  }
+ +
75  }
+
76  }
+
77  } catch (const std::exception& e) {
+ +
79  throw;
+
80  }
+
81  }
+
82 
+
83  } // namespace math
+
84 } // namespace stan
+
85 #endif
+ + + + +
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+
void grad_hessian(const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &H, std::vector< Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > > &grad_H)
Calculate the value, the Hessian, and the gradient of the Hessian of the specified function at the sp...
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/grad__reg__inc__beta_8hpp.html b/doc/api/html/grad__reg__inc__beta_8hpp.html new file mode 100644 index 00000000000..712ac6d4a80 --- /dev/null +++ b/doc/api/html/grad__reg__inc__beta_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_reg_inc_beta.hpp File Reference + + + + + + + + + + +
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+Functions

template<typename T >
void stan::math::grad_reg_inc_beta (T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
 
+
+
+
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diff --git a/doc/api/html/grad__reg__inc__beta_8hpp_source.html b/doc/api/html/grad__reg__inc__beta_8hpp_source.html new file mode 100644 index 00000000000..6076c0585e7 --- /dev/null +++ b/doc/api/html/grad__reg__inc__beta_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_reg_inc_beta.hpp Source File + + + + + + + + + + +
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grad_reg_inc_beta.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_GRAD_REG_INC_BETA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_GRAD_REG_INC_BETA_HPP
+
3 
+ + + +
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  // Gradient of the regularized incomplete beta function ibeta(a, b, z)
+
13  template<typename T>
+
14  void grad_reg_inc_beta(T& g1, T& g2, T a, T b, T z,
+
15  T digammaA, T digammaB, T digammaSum, T betaAB) {
+ + +
18  using std::exp;
+
19  using stan::math::lbeta;
+
20 
+
21  T dBda = 0;
+
22  T dBdb = 0;
+
23  grad_inc_beta(dBda, dBdb, a, b, z);
+
24  T b1 = exp(lbeta(a, b)) * inc_beta(a, b, z);
+
25  g1 = (dBda - b1 * (digammaA - digammaSum)) / betaAB;
+
26  g2 = (dBdb - b1 * (digammaB - digammaSum)) / betaAB;
+
27  }
+
28 
+
29  }
+
30 }
+
31 #endif
+ +
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
void grad_inc_beta(stan::math::fvar< T > &g1, stan::math::fvar< T > &g2, stan::math::fvar< T > a, stan::math::fvar< T > b, stan::math::fvar< T > z)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + + +
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/grad__reg__inc__gamma_8hpp.html b/doc/api/html/grad__reg__inc__gamma_8hpp.html new file mode 100644 index 00000000000..8a21afcbdce --- /dev/null +++ b/doc/api/html/grad__reg__inc__gamma_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_reg_inc_gamma.hpp File Reference + + + + + + + + + + +
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grad_reg_inc_gamma.hpp File Reference
+
+
+
#include <stan/math/prim/scal/fun/gamma_p.hpp>
+#include <cmath>
+#include <stdexcept>
+
+

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 Matrices and templated mathematical functions.
 
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template<typename T >
stan::math::grad_reg_inc_gamma (T a, T z, T g, T dig, T precision=1e-6)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/grad__reg__inc__gamma_8hpp_source.html b/doc/api/html/grad__reg__inc__gamma_8hpp_source.html new file mode 100644 index 00000000000..598622fb249 --- /dev/null +++ b/doc/api/html/grad__reg__inc__gamma_8hpp_source.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_reg_inc_gamma.hpp Source File + + + + + + + + + + +
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grad_reg_inc_gamma.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_GRAD_REG_INC_GAMMA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_GRAD_REG_INC_GAMMA_HPP
+
3 
+ +
5 #include <cmath>
+
6 #include <stdexcept>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  // Gradient of the regularized incomplete gamma functions igamma(a, g)
+
12  // Precomputed values
+
13  // g = boost::math::tgamma(a)
+
14  // dig = boost::math::digamma(a)
+
15  template<typename T>
+
16  T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision = 1e-6) {
+
17  using boost::math::isinf;
+
18  using stan::math::gamma_p;
+
19  using std::domain_error;
+
20  using std::exp;
+
21  using std::fabs;
+
22  using std::log;
+
23 
+
24  T S = 0;
+
25  T s = 1;
+
26  T l = log(z);
+
27  int k = 0;
+
28  T delta = s / (a * a);
+
29  while (fabs(delta) > precision) {
+
30  S += delta;
+
31  ++k;
+
32  s *= - z / k;
+
33  delta = s / ((k + a) * (k + a));
+
34  if (isinf(delta))
+
35  throw domain_error("stan::math::gradRegIncGamma not converging");
+
36  }
+
37  return gamma_p(a, z) * ( dig - l ) + exp( a * l ) * S / g;
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+
int isinf(const stan::math::var &a)
Checks if the given number is infinite.
Definition: std_isinf.hpp:18
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/grad__tr__mat__times__hessian_8hpp.html b/doc/api/html/grad__tr__mat__times__hessian_8hpp.html new file mode 100644 index 00000000000..257755b83da --- /dev/null +++ b/doc/api/html/grad__tr__mat__times__hessian_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/grad_tr_mat_times_hessian.hpp File Reference + + + + + + + + + + +
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grad_tr_mat_times_hessian.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/mix/mat/functor/gradient_dot_vector.hpp>
+#include <stdexcept>
+#include <vector>
+
+

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template<typename F >
void stan::math::grad_tr_mat_times_hessian (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &M, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad_tr_MH)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/grad__tr__mat__times__hessian_8hpp_source.html b/doc/api/html/grad__tr__mat__times__hessian_8hpp_source.html new file mode 100644 index 00000000000..6dd7b434b71 --- /dev/null +++ b/doc/api/html/grad__tr__mat__times__hessian_8hpp_source.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/grad_tr_mat_times_hessian.hpp Source File + + + + + + + + + + +
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grad_tr_mat_times_hessian.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_GRAD_TR_MAT_TIMES_HESSIAN_HPP
+
2 #define STAN_MATH_MIX_MAT_FUNCTOR_GRAD_TR_MAT_TIMES_HESSIAN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <stan/math/rev/core.hpp>
+ +
8 #include <stdexcept>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15 
+
16  // FIXME: add other results that are easy to extract
+
17  // // N * (fwd(2) + bk)
+
18  template <typename F>
+
19  void
+ +
21  const F& f,
+
22  const Eigen::Matrix<double, Eigen::Dynamic, 1>& x,
+
23  const Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& M,
+
24  Eigen::Matrix<double, Eigen::Dynamic, 1>& grad_tr_MH
+
25  ) {
+
26  using Eigen::Matrix;
+
27  using Eigen::Dynamic;
+
28  start_nested();
+
29  try {
+
30  grad_tr_MH.resize(x.size());
+
31 
+
32  Matrix<var, Dynamic, 1> x_var(x.size());
+
33  for (int i = 0; i < x.size(); ++i)
+
34  x_var(i) = x(i);
+
35 
+
36  Matrix<fvar<var>, Dynamic, 1> x_fvar(x.size());
+
37 
+
38  var sum(0.0);
+
39  Matrix<double, Dynamic, 1> M_n(x.size());
+
40  for (int n = 0; n < x.size(); ++n) {
+
41  for (int k = 0; k < x.size(); ++k)
+
42  M_n(k) = M(n, k);
+
43  for (int k = 0; k < x.size(); ++k)
+
44  x_fvar(k) = fvar<var>(x_var(k), k == n);
+
45  fvar<var> fx;
+
46  fvar<var> grad_fx_dot_v;
+
47  gradient_dot_vector<fvar<var>, double>(f, x_fvar, M_n, fx,
+
48  grad_fx_dot_v);
+
49  sum += grad_fx_dot_v.d_;
+
50  }
+
51 
+
52  stan::math::grad(sum.vi_);
+
53  for (int i = 0; i < x.size(); ++i)
+
54  grad_tr_MH(i) = x_var(i).adj();
+
55  } catch (const std::exception& e) {
+ +
57  throw;
+
58  }
+ +
60  }
+
61 
+
62 
+
63  } // namespace math
+
64 } // namespace stan
+
65 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + + + +
void grad_tr_mat_times_hessian(const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &M, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad_tr_MH)
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+ + +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gradient__dot__vector_8hpp.html b/doc/api/html/gradient__dot__vector_8hpp.html new file mode 100644 index 00000000000..cfdfde56d04 --- /dev/null +++ b/doc/api/html/gradient__dot__vector_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/gradient_dot_vector.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
gradient_dot_vector.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T1 , typename T2 , typename F >
void stan::math::gradient_dot_vector (const F &f, const Eigen::Matrix< T1, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< T2, Eigen::Dynamic, 1 > &v, T1 &fx, T1 &grad_fx_dot_v)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gradient__dot__vector_8hpp_source.html b/doc/api/html/gradient__dot__vector_8hpp_source.html new file mode 100644 index 00000000000..e27b504e175 --- /dev/null +++ b/doc/api/html/gradient__dot__vector_8hpp_source.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/gradient_dot_vector.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
gradient_dot_vector.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_GRADIENT_DOT_VECTOR_HPP
+
2 #define STAN_MATH_MIX_MAT_FUNCTOR_GRADIENT_DOT_VECTOR_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <stan/math/rev/core.hpp>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  // aka directional derivative (not length normalized)
+
14  // T2 must be assignable to T1
+
15  template <typename T1, typename T2, typename F>
+
16  void
+
17  gradient_dot_vector(const F& f,
+
18  const Eigen::Matrix<T1, Eigen::Dynamic, 1>& x,
+
19  const Eigen::Matrix<T2, Eigen::Dynamic, 1>& v,
+
20  T1& fx,
+
21  T1& grad_fx_dot_v) {
+
22  using stan::math::fvar;
+
23  using stan::math::var;
+
24  using Eigen::Matrix;
+
25  Matrix<fvar<T1>, Eigen::Dynamic, 1> x_fvar(x.size());
+
26  for (int i = 0; i < x.size(); ++i)
+
27  x_fvar(i) = fvar<T1>(x(i), v(i));
+
28  fvar<T1> fx_fvar = f(x_fvar);
+
29  fx = fx_fvar.val_;
+
30  grad_fx_dot_v = fx_fvar.d_;
+
31  }
+
32 
+
33  } // namespace math
+
34 } // namespace stan
+
35 #endif
+ + + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ + +
void gradient_dot_vector(const F &f, const Eigen::Matrix< T1, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< T2, Eigen::Dynamic, 1 > &v, T1 &fx, T1 &grad_fx_dot_v)
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/group__csr__format.html b/doc/api/html/group__csr__format.html new file mode 100644 index 00000000000..15d40bf7868 --- /dev/null +++ b/doc/api/html/group__csr__format.html @@ -0,0 +1,475 @@ + + + + + + +Stan Math Library: Compressed Sparse Row matrix format. + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + +
+ +
+
+ + +
+ +
+ +
+ +
+
Compressed Sparse Row matrix format.
+
+
+ +

A compressed Sparse Row (CSR) sparse matrix is defined by four component vectors labeled w, v, and u. +More...

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T >
const std::vector< int > stan::math::csr_extract_u (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 Extract the NZE index for each entry from a sparse matrix. More...
 
template<typename T , int R, int C>
const std::vector< int > stan::math::csr_extract_u (const Eigen::Matrix< T, R, C > &A)
 Extract the NZE index for each entry from a sparse matrix. More...
 
template<typename T >
const std::vector< int > stan::math::csr_extract_v (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 Extract the column indexes for non-zero value from a sparse matrix. More...
 
template<typename T , int R, int C>
const std::vector< int > stan::math::csr_extract_v (const Eigen::Matrix< T, R, C > &A)
 Extract the column indexes for non-zero values from a dense matrix by converting to sparse and calling the sparse matrix extractor. More...
 
template<typename T >
const Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::csr_extract_w (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 
template<typename T , int R, int C>
const Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::csr_extract_w (const Eigen::Matrix< T, R, C > &A)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::csr_to_dense_matrix (const int &m, const int &n, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &w, const std::vector< int > &v, const std::vector< int > &u)
 Construct a dense Eigen matrix from the CSR format components. More...
 
int stan::math::csr_u_to_z (const std::vector< int > &u, int i)
 Return the z vector computed from the specified u vector at the index for the z vector. More...
 
+

Detailed Description

+

A compressed Sparse Row (CSR) sparse matrix is defined by four component vectors labeled w, v, and u.

+

Return the multiplication of the sparse matrix (specified by by values and indexing) by the specified dense vector.

+

They are defined as:

    +
  • w: the non-zero values in the sparse matrix.
  • +
  • v: column index for each value in w, as a result this is the same length as w.
  • +
  • u: index of where each row starts in w, length is equal to the number of rows plus one. Last entry is one-past-the-end in w, following the Eigen spec. Indexing is either zero-based or one-based depending on the value of stan::error_index::value. Following the definition of the format in Eigen, we allow for unused garbage values in w/v which are never read. All indexing internal to a given function is zero-based.
  • +
+

With only m/n/w/v/u in hand, it is possible to check all dimensions are sane except the column dimension since it is implicit. The error-checking strategy is to check all dimensions except the column dimension before any work is done inside a function. The column index is checked as it is constructed and used for each entry. If the column index is not needed it is not checked. As a result indexing mistakes might produce non-sensical operations but out-of-bounds indexing will be caught.

+

Except for possible garbage values in w/v/u, memory usage is calculated from the number of non-zero entries (NNZE) and the number of rows (NR): 2*NNZE + 2*NR + 1.

+

The sparse matrix X of dimension m by n is represented by the vector w (of values), the integer array v (containing one-based column index of each value), the integer array u (containing one-based indexes of where each row starts in w).

+
Template Parameters
+ + + +
T1Type of sparse matrix entries.
T2Type of dense vector entries.
+
+
+
Parameters
+ + + + + + + +
mNumber of rows in matrix.
nNumber of columns in matrix.
wVector of non-zero values in matrix.
vColumn index of each non-zero value, same length as w.
uIndex of where each row starts in w, length equal to the number of rows plus one.
bEigen vector which the matrix is multiplied by.
+
+
+
Returns
Dense vector for the product.
+
Exceptions
+ + + + +
std::domain_errorif m and n are not positive or are nan.
std::domain_errorif the implied sparse matrix and b are not multiplicable.
std::domain_errorif m/n/w/v/u are not internally consistent, as defined by the indexing scheme. Extractors are defined in Stan which guarantee a consistent set of m/n/w/v/u for a given sparse matrix.
+
+
+

Function Documentation

+ +
+
+
+template<typename T >
+ + + + + + + + +
const std::vector<int> stan::math::csr_extract_u (const Eigen::SparseMatrix< T, Eigen::RowMajor > & A)
+
+ +

Extract the NZE index for each entry from a sparse matrix.

+
Template Parameters
+ + +
TType of matrix entries.
+
+
+
Parameters
+ + +
ASparse matrix.
+
+
+
Returns
Vector of indexes into non-zero entries of A.
+ +

Definition at line 27 of file csr_extract_u.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + + + + +
const std::vector<int> stan::math::csr_extract_u (const Eigen::Matrix< T, R, C > & A)
+
+ +

Extract the NZE index for each entry from a sparse matrix.

+
Template Parameters
+ + +
TType of matrix entries.
+
+
+
Parameters
+ + +
ADense matrix.
+
+
+
Returns
Vector of indexes into non-zero entries of A.
+ +

Definition at line 43 of file csr_extract_u.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
const std::vector<int> stan::math::csr_extract_v (const Eigen::SparseMatrix< T, Eigen::RowMajor > & A)
+
+ +

Extract the column indexes for non-zero value from a sparse matrix.

+
Template Parameters
+ + +
TType of matrix entries.
+
+
+
Parameters
+ + +
ASparse matrix.
+
+
+
Returns
Vector of column indexes for non-zero entries of A.
+ +

Definition at line 28 of file csr_extract_v.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + + + + +
const std::vector<int> stan::math::csr_extract_v (const Eigen::Matrix< T, R, C > & A)
+
+ +

Extract the column indexes for non-zero values from a dense matrix by converting to sparse and calling the sparse matrix extractor.

+
Template Parameters
+ + +
TType of matrix entries.
+
+
+
Parameters
+ + +
[in]Adense matrix.
+
+
+
Returns
Vector of column indexes to non-zero entries of A.
+ +

Definition at line 46 of file csr_extract_v.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
const Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::csr_extract_w (const Eigen::SparseMatrix< T, Eigen::RowMajor > & A)
+
+ +

Definition at line 24 of file csr_extract_w.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + + + + +
const Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::csr_extract_w (const Eigen::Matrix< T, R, C > & A)
+
+ +

Definition at line 41 of file csr_extract_w.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::csr_to_dense_matrix (const int & m,
const int & n,
const Eigen::Matrix< T, Eigen::Dynamic, 1 > & w,
const std::vector< int > & v,
const std::vector< int > & u 
)
+
+inline
+
+ +

Construct a dense Eigen matrix from the CSR format components.

+
Template Parameters
+ + +
TType of matrix entries.
+
+
+
Parameters
+ + + + + + +
[in]mNumber of matrix rows.
[in]nNumber of matrix columns.
[in]wValues of non-zero matrix entries.
[in]vColumn index for each value in w.
[in]uIndex of where each row starts in w.
+
+
+
Returns
Dense matrix defined by previous arguments.
+
Exceptions
+ + +
std::domain_errorIf the arguments do not define a matrix.
+
+
+ +

Definition at line 35 of file csr_to_dense_matrix.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + +
int stan::math::csr_u_to_z (const std::vector< int > & u,
int i 
)
+
+ +

Return the z vector computed from the specified u vector at the index for the z vector.

+
Parameters
+ + + +
[in]uU vector.
[in]iIndex into resulting z vector.
+
+
+
Returns
z[i] where z is conversion from u.
+ +

Definition at line 24 of file csr_u_to_z.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gumbel__ccdf__log_8hpp.html b/doc/api/html/gumbel__ccdf__log_8hpp.html new file mode 100644 index 00000000000..e6e06c1e881 --- /dev/null +++ b/doc/api/html/gumbel__ccdf__log_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_ccdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
gumbel_ccdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::gumbel_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gumbel__ccdf__log_8hpp_source.html b/doc/api/html/gumbel__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..17f0c242fbc --- /dev/null +++ b/doc/api/html/gumbel__ccdf__log_8hpp_source.html @@ -0,0 +1,231 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_ccdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
gumbel_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GUMBEL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GUMBEL_CCDF_LOG_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <typename T_y, typename T_loc, typename T_scale>
+
27  typename return_type<T_y, T_loc, T_scale>::type
+
28  gumbel_ccdf_log(const T_y& y, const T_loc& mu, const T_scale& beta) {
+
29  static const char* function("stan::math::gumbel_ccdf_log");
+ +
31  T_partials_return;
+
32 
+ + + + + +
38  using std::log;
+
39  using std::exp;
+
40 
+
41  T_partials_return ccdf_log(0.0);
+
42  // check if any vectors are zero length
+
43  if (!(stan::length(y)
+
44  && stan::length(mu)
+
45  && stan::length(beta)))
+
46  return ccdf_log;
+
47 
+
48  check_not_nan(function, "Random variable", y);
+
49  check_finite(function, "Location parameter", mu);
+
50  check_not_nan(function, "Scale parameter", beta);
+
51  check_positive(function, "Scale parameter", beta);
+
52  check_consistent_sizes(function,
+
53  "Random variable", y,
+
54  "Location parameter", mu,
+
55  "Scale parameter", beta);
+
56 
+ +
58  operands_and_partials(y, mu, beta);
+
59 
+
60  VectorView<const T_y> y_vec(y);
+
61  VectorView<const T_loc> mu_vec(mu);
+
62  VectorView<const T_scale> beta_vec(beta);
+
63  size_t N = max_size(y, mu, beta);
+
64 
+
65  for (size_t n = 0; n < N; n++) {
+
66  const T_partials_return y_dbl = value_of(y_vec[n]);
+
67  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
68  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
69  const T_partials_return scaled_diff = (y_dbl - mu_dbl) / beta_dbl;
+
70  const T_partials_return rep_deriv = exp(-scaled_diff
+
71  - exp(-scaled_diff))
+
72  / beta_dbl;
+
73  const T_partials_return ccdf_log_ = 1.0 - exp(-exp(-scaled_diff));
+
74  ccdf_log += log(ccdf_log_);
+
75 
+ +
77  operands_and_partials.d_x1[n] -= rep_deriv / ccdf_log_;
+ +
79  operands_and_partials.d_x2[n] += rep_deriv / ccdf_log_;
+ +
81  operands_and_partials.d_x3[n] += rep_deriv * scaled_diff / ccdf_log_;
+
82  }
+
83 
+
84  return operands_and_partials.value(ccdf_log);
+
85  }
+
86  }
+
87 }
+
88 #endif
+
89 
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
return_type< T_y, T_loc, T_scale >::type gumbel_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &beta)
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
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+
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diff --git a/doc/api/html/gumbel__cdf_8hpp.html b/doc/api/html/gumbel__cdf_8hpp.html new file mode 100644 index 00000000000..24363043f4a --- /dev/null +++ b/doc/api/html/gumbel__cdf_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_cdf.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::gumbel_cdf (const T_y &y, const T_loc &mu, const T_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gumbel__cdf_8hpp_source.html b/doc/api/html/gumbel__cdf_8hpp_source.html new file mode 100644 index 00000000000..ecf71050d65 --- /dev/null +++ b/doc/api/html/gumbel__cdf_8hpp_source.html @@ -0,0 +1,242 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_cdf.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
+
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gumbel_cdf.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GUMBEL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GUMBEL_CDF_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <typename T_y, typename T_loc, typename T_scale>
+
27  typename return_type<T_y, T_loc, T_scale>::type
+
28  gumbel_cdf(const T_y& y, const T_loc& mu, const T_scale& beta) {
+
29  static const char* function("stan::math::gumbel_cdf");
+ +
31  T_partials_return;
+
32 
+ + + + + +
38  using std::exp;
+
39 
+
40  T_partials_return cdf(1.0);
+
41  // check if any vectors are zero length
+
42  if (!(stan::length(y)
+
43  && stan::length(mu)
+
44  && stan::length(beta)))
+
45  return cdf;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_finite(function, "Location parameter", mu);
+
49  check_not_nan(function, "Scale parameter", beta);
+
50  check_positive(function, "Scale parameter", beta);
+
51  check_consistent_sizes(function,
+
52  "Random variable", y,
+
53  "Location parameter", mu,
+
54  "Scale parameter", beta);
+
55 
+ +
57  operands_and_partials(y, mu, beta);
+
58 
+
59  VectorView<const T_y> y_vec(y);
+
60  VectorView<const T_loc> mu_vec(mu);
+
61  VectorView<const T_scale> beta_vec(beta);
+
62  size_t N = max_size(y, mu, beta);
+
63 
+
64  for (size_t n = 0; n < N; n++) {
+
65  const T_partials_return y_dbl = value_of(y_vec[n]);
+
66  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
67  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
68  const T_partials_return scaled_diff = (y_dbl - mu_dbl) / beta_dbl;
+
69  const T_partials_return rep_deriv = exp(-scaled_diff
+
70  - exp(-scaled_diff))
+
71  / beta_dbl;
+
72  const T_partials_return cdf_ = exp(-exp(-scaled_diff));
+
73  cdf *= cdf_;
+
74 
+ +
76  operands_and_partials.d_x1[n] += rep_deriv / cdf_;
+ +
78  operands_and_partials.d_x2[n] -= rep_deriv / cdf_;
+ +
80  operands_and_partials.d_x3[n] -= rep_deriv * scaled_diff / cdf_;
+
81  }
+
82 
+ +
84  for (size_t n = 0; n < stan::length(y); ++n)
+
85  operands_and_partials.d_x1[n] *= cdf;
+
86  }
+ +
88  for (size_t n = 0; n < stan::length(mu); ++n)
+
89  operands_and_partials.d_x2[n] *= cdf;
+
90  }
+ +
92  for (size_t n = 0; n < stan::length(beta); ++n)
+
93  operands_and_partials.d_x3[n] *= cdf;
+
94  }
+
95 
+
96  return operands_and_partials.value(cdf);
+
97  }
+
98  }
+
99 }
+
100 #endif
+
101 
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
return_type< T_y, T_loc, T_scale >::type gumbel_cdf(const T_y &y, const T_loc &mu, const T_scale &beta)
Definition: gumbel_cdf.hpp:28
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gumbel__cdf__log_8hpp.html b/doc/api/html/gumbel__cdf__log_8hpp.html new file mode 100644 index 00000000000..2987978eddb --- /dev/null +++ b/doc/api/html/gumbel__cdf__log_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_cdf_log.hpp File Reference + + + + + + + + + + +
+
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+
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::gumbel_cdf_log (const T_y &y, const T_loc &mu, const T_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gumbel__cdf__log_8hpp_source.html b/doc/api/html/gumbel__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..86ba3cce669 --- /dev/null +++ b/doc/api/html/gumbel__cdf__log_8hpp_source.html @@ -0,0 +1,226 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
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gumbel_cdf_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GUMBEL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GUMBEL_CDF_LOG_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <typename T_y, typename T_loc, typename T_scale>
+
27  typename return_type<T_y, T_loc, T_scale>::type
+
28  gumbel_cdf_log(const T_y& y, const T_loc& mu, const T_scale& beta) {
+
29  static const char* function("stan::math::gumbel_cdf_log");
+ +
31  T_partials_return;
+
32 
+ + + + + +
38  using std::exp;
+
39 
+
40  T_partials_return cdf_log(0.0);
+
41  // check if any vectors are zero length
+
42  if (!(stan::length(y)
+
43  && stan::length(mu)
+
44  && stan::length(beta)))
+
45  return cdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_finite(function, "Location parameter", mu);
+
49  check_not_nan(function, "Scale parameter", beta);
+
50  check_positive(function, "Scale parameter", beta);
+
51  check_consistent_sizes(function,
+
52  "Random variable", y,
+
53  "Location parameter", mu,
+
54  "Scale parameter", beta);
+
55 
+ +
57  operands_and_partials(y, mu, beta);
+
58 
+
59  VectorView<const T_y> y_vec(y);
+
60  VectorView<const T_loc> mu_vec(mu);
+
61  VectorView<const T_scale> beta_vec(beta);
+
62  size_t N = max_size(y, mu, beta);
+
63 
+
64  for (size_t n = 0; n < N; n++) {
+
65  const T_partials_return y_dbl = value_of(y_vec[n]);
+
66  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
67  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
68  const T_partials_return scaled_diff = (y_dbl - mu_dbl) / beta_dbl;
+
69  const T_partials_return rep_deriv = exp(-scaled_diff) / beta_dbl;
+
70  cdf_log -= exp(-scaled_diff);
+
71 
+ +
73  operands_and_partials.d_x1[n] += rep_deriv;
+ +
75  operands_and_partials.d_x2[n] -= rep_deriv;
+ +
77  operands_and_partials.d_x3[n] -= rep_deriv * scaled_diff;
+
78  }
+
79 
+
80  return operands_and_partials.value(cdf_log);
+
81  }
+
82  }
+
83 }
+
84 #endif
+
85 
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
return_type< T_y, T_loc, T_scale >::type gumbel_cdf_log(const T_y &y, const T_loc &mu, const T_scale &beta)
+
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gumbel__log_8hpp.html b/doc/api/html/gumbel__log_8hpp.html new file mode 100644 index 00000000000..a0898cdaaf5 --- /dev/null +++ b/doc/api/html/gumbel__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::gumbel_log (const T_y &y, const T_loc &mu, const T_scale &beta)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::gumbel_log (const T_y &y, const T_loc &mu, const T_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/gumbel__log_8hpp_source.html b/doc/api/html/gumbel__log_8hpp_source.html new file mode 100644 index 00000000000..61eb023308c --- /dev/null +++ b/doc/api/html/gumbel__log_8hpp_source.html @@ -0,0 +1,269 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+ + +
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+
+
gumbel_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GUMBEL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GUMBEL_LOG_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <bool propto, typename T_y, typename T_loc, typename T_scale>
+
27  typename return_type<T_y, T_loc, T_scale>::type
+
28  gumbel_log(const T_y& y, const T_loc& mu, const T_scale& beta) {
+
29  static const char* function("stan::math::gumbel_log");
+ +
31  T_partials_return;
+
32 
+
33  using std::log;
+
34  using std::exp;
+ + + + + + + +
42  using std::log;
+
43  using std::exp;
+
44 
+
45  // check if any vectors are zero length
+
46  if (!(stan::length(y)
+
47  && stan::length(mu)
+
48  && stan::length(beta)))
+
49  return 0.0;
+
50 
+
51  // set up return value accumulator
+
52  T_partials_return logp(0.0);
+
53 
+
54  // validate args (here done over var, which should be OK)
+
55  check_not_nan(function, "Random variable", y);
+
56  check_finite(function, "Location parameter", mu);
+
57  check_positive(function, "Scale parameter", beta);
+
58  check_consistent_sizes(function,
+
59  "Random variable", y,
+
60  "Location parameter", mu,
+
61  "Scale parameter", beta);
+
62 
+
63  // check if no variables are involved and prop-to
+ +
65  return 0.0;
+
66 
+
67  // set up template expressions wrapping scalars into vector views
+ +
69  operands_and_partials(y, mu, beta);
+
70 
+
71  VectorView<const T_y> y_vec(y);
+
72  VectorView<const T_loc> mu_vec(mu);
+
73  VectorView<const T_scale> beta_vec(beta);
+
74  size_t N = max_size(y, mu, beta);
+
75 
+ + +
78  T_partials_return, T_scale> log_beta(length(beta));
+
79  for (size_t i = 0; i < length(beta); i++) {
+
80  inv_beta[i] = 1.0 / value_of(beta_vec[i]);
+ +
82  log_beta[i] = log(value_of(beta_vec[i]));
+
83  }
+
84 
+
85  for (size_t n = 0; n < N; n++) {
+
86  // pull out values of arguments
+
87  const T_partials_return y_dbl = value_of(y_vec[n]);
+
88  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
89 
+
90  // reusable subexpression values
+
91  const T_partials_return y_minus_mu_over_beta
+
92  = (y_dbl - mu_dbl) * inv_beta[n];
+
93 
+
94  // log probability
+ +
96  logp -= log_beta[n];
+ +
98  logp += -y_minus_mu_over_beta - exp(-y_minus_mu_over_beta);
+
99 
+
100  // gradients
+
101  T_partials_return scaled_diff = inv_beta[n]
+
102  * exp(-y_minus_mu_over_beta);
+ +
104  operands_and_partials.d_x1[n] -= inv_beta[n] - scaled_diff;
+ +
106  operands_and_partials.d_x2[n] += inv_beta[n] - scaled_diff;
+ +
108  operands_and_partials.d_x3[n]
+
109  += -inv_beta[n] + y_minus_mu_over_beta * inv_beta[n]
+
110  - scaled_diff * y_minus_mu_over_beta;
+
111  }
+
112  return operands_and_partials.value(logp);
+
113  }
+
114 
+
115  template <typename T_y, typename T_loc, typename T_scale>
+
116  inline
+ +
118  gumbel_log(const T_y& y, const T_loc& mu, const T_scale& beta) {
+
119  return gumbel_log<false>(y, mu, beta);
+
120  }
+
121  }
+
122 }
+
123 #endif
+
124 
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_y, T_loc, T_scale >::type gumbel_log(const T_y &y, const T_loc &mu, const T_scale &beta)
Definition: gumbel_log.hpp:28
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
+
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diff --git a/doc/api/html/gumbel__rng_8hpp.html b/doc/api/html/gumbel__rng_8hpp.html new file mode 100644 index 00000000000..2363404a39d --- /dev/null +++ b/doc/api/html/gumbel__rng_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::gumbel_rng (const double mu, const double beta, RNG &rng)
 
+
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diff --git a/doc/api/html/gumbel__rng_8hpp_source.html b/doc/api/html/gumbel__rng_8hpp_source.html new file mode 100644 index 00000000000..7c8cd24ec4c --- /dev/null +++ b/doc/api/html/gumbel__rng_8hpp_source.html @@ -0,0 +1,171 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/gumbel_rng.hpp Source File + + + + + + + + + + +
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gumbel_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GUMBEL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_GUMBEL_RNG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/uniform_01.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  template <class RNG>
+
23  inline double
+
24  gumbel_rng(const double mu,
+
25  const double beta,
+
26  RNG& rng) {
+
27  using boost::variate_generator;
+
28  using boost::uniform_01;
+
29 
+
30  static const char* function("stan::math::gumbel_rng");
+
31 
+ + +
34 
+
35 
+
36  check_finite(function, "Location parameter", mu);
+
37  check_positive(function, "Scale parameter", beta);
+
38 
+
39  variate_generator<RNG&, uniform_01<> >
+
40  uniform01_rng(rng, uniform_01<>());
+
41  return mu - beta * std::log(-std::log(uniform01_rng()));
+
42  }
+
43  }
+
44 }
+
45 #endif
+
46 
+ + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
double gumbel_rng(const double mu, const double beta, RNG &rng)
Definition: gumbel_rng.hpp:24
+ + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + +
+
+
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diff --git a/doc/api/html/head_8hpp.html b/doc/api/html/head_8hpp.html new file mode 100644 index 00000000000..b6642083f76 --- /dev/null +++ b/doc/api/html/head_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/head.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::head (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t n)
 Return the specified number of elements as a vector from the front of the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::head (const Eigen::Matrix< T, 1, Eigen::Dynamic > &rv, size_t n)
 Return the specified number of elements as a row vector from the front of the specified row vector. More...
 
template<typename T >
std::vector< T > stan::math::head (const std::vector< T > &sv, size_t n)
 Return the specified number of elements as a standard vector from the front of the specified standard vector. More...
 
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diff --git a/doc/api/html/head_8hpp_source.html b/doc/api/html/head_8hpp_source.html new file mode 100644 index 00000000000..de8abfd013c --- /dev/null +++ b/doc/api/html/head_8hpp_source.html @@ -0,0 +1,167 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/head.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_HEAD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_HEAD_HPP
+
3 
+ + + + +
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
21  template <typename T>
+
22  inline
+
23  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
24  head(const Eigen::Matrix<T, Eigen::Dynamic, 1>& v,
+
25  size_t n) {
+
26  if (n != 0)
+
27  stan::math::check_row_index("head", "n", v, n);
+
28  return v.head(n);
+
29  }
+
30 
+
39  template <typename T>
+
40  inline
+
41  Eigen::Matrix<T, 1, Eigen::Dynamic>
+
42  head(const Eigen::Matrix<T, 1, Eigen::Dynamic>& rv,
+
43  size_t n) {
+
44  if (n != 0)
+
45  stan::math::check_column_index("head", "n", rv, n);
+
46  return rv.head(n);
+
47  }
+
48 
+
57  template <typename T>
+
58  std::vector<T> head(const std::vector<T>& sv,
+
59  size_t n) {
+
60  if (n != 0)
+
61  stan::math::check_std_vector_index("head", "n", sv, n);
+
62 
+
63  std::vector<T> s;
+
64  for (size_t i = 0; i < n; ++i)
+
65  s.push_back(sv[i]);
+
66  return s;
+
67  }
+
68 
+
69 
+
70  }
+
71 }
+
72 
+
73 #endif
+ + + +
Eigen::Matrix< T, Eigen::Dynamic, 1 > head(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t n)
Return the specified number of elements as a vector from the front of the specified vector...
Definition: head.hpp:24
+
bool check_row_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
Return true if the specified index is a valid row of the matrix.
+ +
bool check_std_vector_index(const char *function, const char *name, const std::vector< T > &y, int i)
Return true if the specified index is valid in std vector.
+ +
bool check_column_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
Return true if the specified index is a valid column of the matrix.
+
+
+
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diff --git a/doc/api/html/hessian_8hpp.html b/doc/api/html/hessian_8hpp.html new file mode 100644 index 00000000000..7c97a784003 --- /dev/null +++ b/doc/api/html/hessian_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/hessian.hpp File Reference + + + + + + + + + + +
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hessian.hpp File Reference
+
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+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stdexcept>
+#include <vector>
+
+

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template<typename F >
void stan::math::hessian (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &H)
 Calculate the value, the gradient, and the Hessian, of the specified function at the specified argument in O(N^2) time and O(N^2) space. More...
 
template<typename T , typename F >
void stan::math::hessian (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &fx, Eigen::Matrix< T, Eigen::Dynamic, 1 > &grad, Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &H)
 
+
+
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diff --git a/doc/api/html/hessian_8hpp_source.html b/doc/api/html/hessian_8hpp_source.html new file mode 100644 index 00000000000..03cc1c61592 --- /dev/null +++ b/doc/api/html/hessian_8hpp_source.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/hessian.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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hessian.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_HESSIAN_HPP
+
2 #define STAN_MATH_MIX_MAT_FUNCTOR_HESSIAN_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <stan/math/rev/core.hpp>
+
7 #include <stdexcept>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
43  template <typename F>
+
44  void
+
45  hessian(const F& f,
+
46  const Eigen::Matrix<double, Eigen::Dynamic, 1>& x,
+
47  double& fx,
+
48  Eigen::Matrix<double, Eigen::Dynamic, 1>& grad,
+
49  Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& H) {
+
50  H.resize(x.size(), x.size());
+
51  grad.resize(x.size());
+
52  try {
+
53  for (int i = 0; i < x.size(); ++i) {
+
54  start_nested();
+
55  Eigen::Matrix<fvar<var>, Eigen::Dynamic, 1> x_fvar(x.size());
+
56  for (int j = 0; j < x.size(); ++j)
+
57  x_fvar(j) = fvar<var>(x(j), i == j);
+
58  fvar<var> fx_fvar = f(x_fvar);
+
59  grad(i) = fx_fvar.d_.val();
+
60  if (i == 0) fx = fx_fvar.val_.val();
+
61  stan::math::grad(fx_fvar.d_.vi_);
+
62  for (int j = 0; j < x.size(); ++j)
+
63  H(i, j) = x_fvar(j).val_.adj();
+ +
65  }
+
66  } catch (const std::exception& e) {
+ +
68  throw;
+
69  }
+
70  }
+
71  // time O(N^3); space O(N^2)
+
72  template <typename T, typename F>
+
73  void
+
74  hessian(const F& f,
+
75  const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
76  T& fx,
+
77  Eigen::Matrix<T, Eigen::Dynamic, 1>& grad,
+
78  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& H) {
+
79  H.resize(x.size(), x.size());
+
80  grad.resize(x.size());
+
81  Eigen::Matrix<fvar<fvar<T> >, Eigen::Dynamic, 1> x_fvar(x.size());
+
82  for (int i = 0; i < x.size(); ++i) {
+
83  for (int j = i; j < x.size(); ++j) {
+
84  for (int k = 0; k < x.size(); ++k)
+
85  x_fvar(k) = fvar<fvar<T> >(fvar<T>(x(k), j == k),
+
86  fvar<T>(i == k, 0));
+
87  fvar<fvar<T> > fx_fvar = f(x_fvar);
+
88  if (j == 0)
+
89  fx = fx_fvar.val_.val_;
+
90  if (i == j)
+
91  grad(i) = fx_fvar.d_.val_;
+
92  H(i, j) = fx_fvar.d_.d_;
+
93  H(j, i) = H(i, j);
+
94  }
+
95  }
+
96  }
+
97 
+
98  } // namespace math
+
99 } // namespace stan
+
100 #endif
+
void hessian(const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &H)
Calculate the value, the gradient, and the Hessian, of the specified function at the specified argume...
Definition: hessian.hpp:45
+ + + + +
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/hessian__times__vector_8hpp.html b/doc/api/html/hessian__times__vector_8hpp.html new file mode 100644 index 00000000000..db83b648133 --- /dev/null +++ b/doc/api/html/hessian__times__vector_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/hessian_times_vector.hpp File Reference + + + + + + + + + + +
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hessian_times_vector.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stdexcept>
+#include <vector>
+
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template<typename F >
void stan::math::hessian_times_vector (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &v, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &Hv)
 
template<typename T , typename F >
void stan::math::hessian_times_vector (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, T &fx, Eigen::Matrix< T, Eigen::Dynamic, 1 > &Hv)
 
+
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diff --git a/doc/api/html/hessian__times__vector_8hpp_source.html b/doc/api/html/hessian__times__vector_8hpp_source.html new file mode 100644 index 00000000000..c414060eeb5 --- /dev/null +++ b/doc/api/html/hessian__times__vector_8hpp_source.html @@ -0,0 +1,183 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/hessian_times_vector.hpp Source File + + + + + + + + + + +
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hessian_times_vector.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_HESSIAN_TIMES_VECTOR_HPP
+
2 #define STAN_MATH_MIX_MAT_FUNCTOR_HESSIAN_TIMES_VECTOR_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <stan/math/rev/core.hpp>
+
7 #include <stdexcept>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  template <typename F>
+
15  void
+ +
17  const Eigen::Matrix<double, Eigen::Dynamic, 1>& x,
+
18  const Eigen::Matrix<double, Eigen::Dynamic, 1>& v,
+
19  double& fx,
+
20  Eigen::Matrix<double, Eigen::Dynamic, 1>& Hv) {
+
21  using stan::math::fvar;
+
22  using stan::math::var;
+
23  using Eigen::Matrix;
+
24  start_nested();
+
25  try {
+
26  Matrix<var, Eigen::Dynamic, 1> x_var(x.size());
+
27  for (int i = 0; i < x_var.size(); ++i)
+
28  x_var(i) = x(i);
+
29  var fx_var;
+
30  var grad_fx_var_dot_v;
+
31  gradient_dot_vector(f, x_var, v, fx_var, grad_fx_var_dot_v);
+
32  fx = fx_var.val();
+
33  stan::math::grad(grad_fx_var_dot_v.vi_);
+
34  Hv.resize(x.size());
+
35  for (int i = 0; i < x.size(); ++i)
+
36  Hv(i) = x_var(i).adj();
+
37  } catch (const std::exception& e) {
+ +
39  throw;
+
40  }
+ +
42  }
+
43  template <typename T, typename F>
+
44  void
+ +
46  const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
47  const Eigen::Matrix<T, Eigen::Dynamic, 1>& v,
+
48  T& fx,
+
49  Eigen::Matrix<T, Eigen::Dynamic, 1>& Hv) {
+
50  using Eigen::Matrix;
+
51  Matrix<T, Eigen::Dynamic, 1> grad;
+
52  Matrix<T, Eigen::Dynamic, Eigen::Dynamic> H;
+
53  hessian(f, x, fx, grad, H);
+
54  Hv = H * v;
+
55  }
+
56 
+
57  } // namespace math
+
58 } // namespace stan
+
59 #endif
+
void hessian(const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &H)
Calculate the value, the gradient, and the Hessian, of the specified function at the specified argume...
Definition: hessian.hpp:45
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
void hessian_times_vector(const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &v, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &Hv)
+
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
void gradient_dot_vector(const F &f, const Eigen::Matrix< T1, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< T2, Eigen::Dynamic, 1 > &v, T1 &fx, T1 &grad_fx_dot_v)
+
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
+ +
+
+
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diff --git a/doc/api/html/hierarchy.html b/doc/api/html/hierarchy.html new file mode 100644 index 00000000000..7aced0afa92 --- /dev/null +++ b/doc/api/html/hierarchy.html @@ -0,0 +1,300 @@ + + + + + + +Stan Math Library: Class Hierarchy + + + + + + + + + + +
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This inheritance list is sorted roughly, but not completely, alphabetically:
+
[detail level 123]
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 Cstan::math::accumulator< T >Class to accumulate values and eventually return their sum
 Cstan::math::apply_scalar_unary< F, T >Base template class for vectorization of unary scalar functions defined by a template class F to a scalar, standard library vector, or Eigen dense matrix expression template
 Cstan::math::apply_scalar_unary< F, double >Template specialization for vectorized functions applying to double arguments
 Cstan::math::apply_scalar_unary< F, int >Template specialization for vectorized functions applying to integer arguments
 Cstan::math::apply_scalar_unary< F, stan::math::fvar< T > >Template specialization to fvar for vectorizing a unary scalar function
 Cstan::math::apply_scalar_unary< F, stan::math::var >Template specialization to var for vectorizing a unary scalar function
 Cstan::math::apply_scalar_unary< F, std::vector< T > >Template specialization for vectorized functions applying to standard vector containers
 Cstan::math::array_builder< T >Structure for building up arrays in an expression (rather than in statements) using an argumentchaining add() method and a getter method array() to return the result
 Cstan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >
 Cstan::math::detail::bounded< T_y, T_low, T_high, y_is_vec >
 Cstan::math::detail::bounded< T_y, T_low, T_high, true >
 Cstan::math::chainable_allocA chainable_alloc is an object which is constructed and destructed normally but the memory lifespan is managed along with the arena allocator for the gradient calculation
 Cstan::math::child_type< T >Primary template class for metaprogram to compute child type of T
 Cstan::math::child_type< T_struct< T_child > >Specialization for template classes / structs
 Cstan::math::common_type< T1, T2 >
 Cstan::math::common_type< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >
 Cstan::math::common_type< std::vector< T1 >, std::vector< T2 > >
 Cstan::math::container_view< T1, T2 >Primary template class for container view of array y with same structure as T1 and size as x
 Cstan::math::container_view< dummy, T2 >Dummy type specialization, used in conjunction with struct dummy as described above
 Cstan::math::container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >Template specialization for Eigen::Map view of array with scalar type T2 with size inferred from input Eigen::Matrix
 Cstan::math::container_view< Eigen::Matrix< T1, R, C >, T2 >Template specialization for scalar view of array y with scalar type T2
 Cstan::math::container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > >Template specialization for matrix view of array y with scalar type T2 with shape equal to x
 Cstan::math::container_view< std::vector< T1 >, T2 >Template specialization for scalar view of array y with scalar type T2 with proper indexing inferred from input vector x of scalar type T1
 Cstan::contains_fvar< T1, T2, T3, T4, T5, T6 >Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters
 Cstan::contains_nonconstant_struct< T1, T2, T3, T4, T5, T6 >
 Cstan::contains_vector< T1, T2, T3, T4, T5, T6 >
 Cstan::math::coupled_ode_observerObserver for the coupled states
 Cstan::math::coupled_ode_system< F, T1, T2 >Base template class for a coupled ordinary differential equation system, which adds sensitivities to the base system
 Cstan::math::coupled_ode_system< F, double, double >The coupled ode system for known initial values and known parameters
 Cstan::math::coupled_ode_system< F, double, stan::math::var >The coupled ODE system for known initial values and unknown parameters
 Cstan::math::coupled_ode_system< F, stan::math::var, double >The coupled ODE system for unknown initial values and known parameters
 Cstan::math::coupled_ode_system< F, stan::math::var, stan::math::var >The coupled ode system for unknown intial values and unknown parameters
 Cstan::math::cvodes_ode_data< F, T_initial, T_param >CVODES ode data holder object which is used during CVODES integration for CVODES callbacks
 Cstan::math::dummyEmpty struct for use in boost::condtional<is_constant_struct<T1>::value, T1, dummy>::type as false condtion for safe indexing
 Cstan::error_index
 Cstan::math::fvar< T >
 CEigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor >
 CEigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs >
 CEigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs >Override matrix-vector and matrix-matrix products to use more efficient implementation
 Cstan::math::include_summand< propto, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10 >Template metaprogram to calculate whether a summand needs to be included in a proportional (log) probability calculation
 Cstan::math::index_type< T >Primary template class for the metaprogram to compute the index type of a container
 Cstan::math::index_type< const T >Template class for metaprogram to compute the type of indexes used in a constant container type
 Cstan::math::index_type< Eigen::Matrix< T, R, C > >Template metaprogram defining typedef for the type of index for an Eigen matrix, vector, or row vector
 Cstan::math::index_type< std::vector< T > >Template metaprogram class to compute the type of index for a standard vector
 Cstan::is_constant< T >Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the C++ const sense)
 Cstan::is_constant_struct< T >Metaprogram to determine if a type has a base scalar type that can be assigned to type double
 Cstan::is_constant_struct< Eigen::Block< T > >
 Cstan::is_constant_struct< Eigen::Matrix< T, R, C > >
 Cstan::is_constant_struct< std::vector< T > >
 Cstan::is_fvar< T >
 Cstan::is_fvar< stan::math::fvar< T > >
 Cstan::is_var< T >
 Cstan::is_var< stan::math::var >
 Cstan::is_var_or_arithmetic< T1, T2, T3, T4, T5, T6 >
 Cstan::is_vector< T >
 Cstan::is_vector< const T >
 Cstan::is_vector< Eigen::Block< T > >
 Cstan::is_vector< Eigen::Matrix< T, 1, Eigen::Dynamic > >
 Cstan::is_vector< Eigen::Matrix< T, Eigen::Dynamic, 1 > >
 Cstan::is_vector< std::vector< T > >
 Cstan::is_vector_like< T >Template metaprogram indicates whether a type is vector_like
 Cstan::is_vector_like< const T >Template metaprogram indicates whether a type is vector_like
 Cstan::is_vector_like< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >Template metaprogram indicates whether a type is vector_like
 Cstan::is_vector_like< T * >Template metaprogram indicates whether a type is vector_like
 Cstan::math::LDLT_factor< T, R, C >
 Cstan::math::LDLT_factor< stan::math::var, R, C >A template specialization of src/stan/math/matrix/LDLT_factor.hpp for stan::math::var which can be used with all the *_ldlt functions
 Cstan::math::LDLT_factor< T, R, C >LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodiff of things like log determinants and solutions to linear systems
 Cstd::numeric_limits< stan::math::fvar< T > >
 Cstd::numeric_limits< stan::math::var >Specialization of numeric limits for var objects
 CEigen::NumTraits< stan::math::fvar< T > >Numerical traits template override for Eigen for automatic gradient variables
 CEigen::NumTraits< stan::math::var >Numerical traits template override for Eigen for automatic gradient variables
 Cstan::math::ode_system< F >Internal representation of an ODE model object which provides convenient Jacobian functions to obtain gradients wrt to states and parameters
 Cstan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >This class builds partial derivatives with respect to a set of operands
 Cstan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >This class builds partial derivatives with respect to a set of operands
 Cstan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >This class builds partial derivatives with respect to a set of operands
 Cstan::partials_return_type< T1, T2, T3, T4, T5, T6 >
 Cstan::partials_type< T >
 Cstan::partials_type< stan::math::fvar< T > >
 Cstan::partials_type< stan::math::var >
 Cstan::math::pass_type< T >
 Cstan::math::pass_type< double >
 Cstan::math::pass_type< int >
 Cstan::math::promote_scalar_struct< T, S >General struct to hold static function for promoting underlying scalar types
 Cstan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > >Struct to hold static function for promoting underlying scalar types
 Cstan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > >Struct to hold static function for promoting underlying scalar types
 Cstan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > >Struct to hold static function for promoting underlying scalar types
 Cstan::math::promote_scalar_struct< T, std::vector< S > >Struct to hold static function for promoting underlying scalar types
 Cstan::math::promote_scalar_struct< T, T >Struct to hold static function for promoting underlying scalar types
 Cstan::math::promote_scalar_type< T, S >Template metaprogram to calculate a type for converting a convertible type
 Cstan::math::promote_scalar_type< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >Template metaprogram to calculate a type for a row vector whose underlying scalar is converted from the second template parameter type to the first
 Cstan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >Template metaprogram to calculate a type for a matrix whose underlying scalar is converted from the second template parameter type to the first
 Cstan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >Template metaprogram to calculate a type for a vector whose underlying scalar is converted from the second template parameter type to the first
 Cstan::math::promote_scalar_type< T, std::vector< S > >Template metaprogram to calculate a type for a container whose underlying scalar is converted from the second template parameter type to the first
 Cstan::math::promoter< F, T >
 Cstan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > >
 Cstan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > >
 Cstan::math::promoter< std::vector< F >, std::vector< T > >
 Cstan::math::promoter< std::vector< T >, std::vector< T > >
 Cstan::math::promoter< T, T >
 Cstan::return_type< T1, T2, T3, T4, T5, T6 >Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters
 CEigen::internal::scalar_product_traits< double, stan::math::var >Scalar product traits override for Eigen for automatic gradient variables
 CEigen::internal::scalar_product_traits< stan::math::var, double >Scalar product traits override for Eigen for automatic gradient variables
 Cstan::scalar_type< T >Metaprogram structure to determine the base scalar type of a template argument
 Cstan::scalar_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >
 Cstan::scalar_type< T * >
 Cstan::scalar_type_pre< T >Metaprogram structure to determine the type of first container of the base scalar type of a template argument
 Cstan::math::seq_view< T, S >
 Cstan::math::seq_view< double, std::vector< int > >
 Cstan::math::seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >
 Cstan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >
 Cstan::math::seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >
 Cstan::math::seq_view< T, std::vector< S > >
 Cstan::math::seq_view< T, std::vector< std::vector< T > > >
 Cstan::math::seq_view< T, std::vector< T > >
 CEigen::internal::significant_decimals_default_impl< stan::math::fvar< T >, false >Implemented this for printing to stream
 CEigen::internal::significant_decimals_default_impl< stan::math::var, false >Implemented this for printing to stream
 Cstan::size_of_helper< T, is_vec >
 Cstan::size_of_helper< T, true >
 Cstan::math::stack_allocAn instance of this class provides a memory pool through which blocks of raw memory may be allocated and then collected simultaneously
 Cstan::math::store_type< T >
 Cstan::math::store_type< double >
 Cstan::math::store_type< Eigen::Matrix< S, 1, Eigen::Dynamic > >
 Cstan::math::store_type< Eigen::Matrix< S, Eigen::Dynamic, 1 > >
 Cstan::math::store_type< Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >
 Cstan::math::store_type< int >
 Cstan::math::store_type< S >
 Cstan::math::store_type< std::vector< int > >
 Cstan::math::store_type< std::vector< S > >
 Cstan::math::store_type< std::vector< std::vector< T > > >
 Cstan::math::store_type< std::vector< T > >
 Cstan::math::value_type< T >Primary template class for metaprogram to compute the type of values stored in a container
 Cstan::math::value_type< const T >Template class for metaprogram to compute the type of values stored in a constant container
 Cstan::math::value_type< Eigen::Matrix< T, R, C > >Template metaprogram defining the type of values stored in an Eigen matrix, vector, or row vector
 Cstan::math::value_type< std::vector< T > >Template metaprogram class to compute the type of values stored in a standard vector
 Cstan::math::varIndependent (input) and dependent (output) variables for gradients
 Cstan::math::variThe variable implementation base class
 Cstan::VectorBuilder< used, T1, T2, T3, T4, T5, T6, T7 >VectorBuilder allocates type T1 values to be used as intermediate values
 Cstan::VectorBuilderHelper< T1, used, is_vec >VectorBuilder allocates type T1 values to be used as intermediate values
 Cstan::VectorBuilderHelper< T1, true, false >
 Cstan::VectorBuilderHelper< T1, true, true >Template specialization for using a vector
 Cstan::VectorBuilderHelper< T1, used, stan::contains_vector< T2, T3, T4, T5, T6, T7 >::value >
 Cstan::VectorView< T, is_array, throw_if_accessed >VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[]
 Cstan::VectorView< const Eigen::Matrix< T, R, C >, true, false >
 Cstan::VectorView< const std::vector< T >, true, false >
 Cstan::VectorView< double, stan::is_vector< T1 >::value, stan::is_constant_struct< T1 >::value >
 Cstan::VectorView< double, stan::is_vector< T2 >::value, stan::is_constant_struct< T2 >::value >
 Cstan::VectorView< double, stan::is_vector< T3 >::value, stan::is_constant_struct< T3 >::value >
 Cstan::VectorView< double, stan::is_vector< T4 >::value, stan::is_constant_struct< T4 >::value >
 Cstan::VectorView< double, stan::is_vector< T5 >::value, stan::is_constant_struct< T5 >::value >
 Cstan::VectorView< double, stan::is_vector< T6 >::value, stan::is_constant_struct< T6 >::value >
 Cstan::VectorView< Eigen::Matrix< T, R, C >, true, false >
 Cstan::VectorView< std::vector< T >, true, false >
 Cstan::VectorView< T, false, false >
 Cstan::VectorView< T, is_array, true >
 Cstan::VectorView< T, true, false >
 Cstan::VectorView< T_partials_return, stan::is_vector< T1 >::value, stan::is_constant_struct< T1 >::value >
 Cstan::VectorView< T_partials_return, stan::is_vector< T2 >::value, stan::is_constant_struct< T2 >::value >
 Cstan::VectorView< T_partials_return, stan::is_vector< T3 >::value, stan::is_constant_struct< T3 >::value >
 Cstan::VectorView< T_partials_return, stan::is_vector< T4 >::value, stan::is_constant_struct< T4 >::value >
 Cstan::VectorView< T_partials_return, stan::is_vector< T5 >::value, stan::is_constant_struct< T5 >::value >
 Cstan::VectorView< T_partials_return, stan::is_vector< T6 >::value, stan::is_constant_struct< T6 >::value >
 Cstan::VectorView< T_return_type, false, true >
 Cstan::VectorViewMvt< T, is_array, throw_if_accessed >
 Cstan::VectorViewMvt< const T, is_array, throw_if_accessed >VectorViewMvt that has const correctness
 Cstan::math::welford_covar_estimator
 Cstan::math::welford_var_estimator
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diff --git a/doc/api/html/hypergeometric__log_8hpp.html b/doc/api/html/hypergeometric__log_8hpp.html new file mode 100644 index 00000000000..6b0dbb90c79 --- /dev/null +++ b/doc/api/html/hypergeometric__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/hypergeometric_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
hypergeometric_log.hpp File Reference
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Go to the source code of this file.

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 Matrices and templated mathematical functions.
 
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+Functions

template<bool propto, typename T_n , typename T_N , typename T_a , typename T_b >
double stan::math::hypergeometric_log (const T_n &n, const T_N &N, const T_a &a, const T_b &b)
 
template<typename T_n , typename T_N , typename T_a , typename T_b >
double stan::math::hypergeometric_log (const T_n &n, const T_N &N, const T_a &a, const T_b &b)
 
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diff --git a/doc/api/html/hypergeometric__log_8hpp_source.html b/doc/api/html/hypergeometric__log_8hpp_source.html new file mode 100644 index 00000000000..5f96438084a --- /dev/null +++ b/doc/api/html/hypergeometric__log_8hpp_source.html @@ -0,0 +1,227 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/hypergeometric_log.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
hypergeometric_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_HYPERGEOMETRIC_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_HYPERGEOMETRIC_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/math/distributions.hpp>
+
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  // Hypergeometric(n|N, a, b) [0 <= n <= a; 0 <= N-n <= b; 0 <= N <= a+b]
+
23  // n: #white balls drawn; N: #balls drawn;
+
24  // a: #white balls; b: #black balls
+
25  template <bool propto,
+
26  typename T_n, typename T_N,
+
27  typename T_a, typename T_b>
+
28  double
+
29  hypergeometric_log(const T_n& n, const T_N& N,
+
30  const T_a& a, const T_b& b) {
+
31  static const char* function("stan::math::hypergeometric_log");
+
32 
+ + + + + +
38 
+
39  // check if any vectors are zero length
+
40  if (!(stan::length(n)
+
41  && stan::length(N)
+
42  && stan::length(a)
+
43  && stan::length(b)))
+
44  return 0.0;
+
45 
+
46 
+
47  VectorView<const T_n> n_vec(n);
+
48  VectorView<const T_N> N_vec(N);
+
49  VectorView<const T_a> a_vec(a);
+
50  VectorView<const T_b> b_vec(b);
+
51  size_t size = max_size(n, N, a, b);
+
52 
+
53  double logp(0.0);
+
54  check_bounded(function, "Successes variable", n, 0, a);
+
55  check_greater(function, "Draws parameter", N, n);
+
56  for (size_t i = 0; i < size; i++) {
+
57  check_bounded(function, "Draws parameter minus successes variable",
+
58  N_vec[i]-n_vec[i], 0, b_vec[i]);
+
59  check_bounded(function, "Draws parameter", N_vec[i], 0,
+
60  a_vec[i]+b_vec[i]);
+
61  }
+
62  check_consistent_sizes(function,
+
63  "Successes variable", n,
+
64  "Draws parameter", N,
+
65  "Successes in population parameter", a,
+
66  "Failures in population parameter", b);
+
67 
+
68  // check if no variables are involved and prop-to
+ +
70  return 0.0;
+
71 
+
72 
+
73  for (size_t i = 0; i < size; i++)
+
74  logp += math::binomial_coefficient_log(a_vec[i], n_vec[i])
+
75  + math::binomial_coefficient_log(b_vec[i], N_vec[i]-n_vec[i])
+
76  - math::binomial_coefficient_log(a_vec[i]+b_vec[i], N_vec[i]);
+
77  return logp;
+
78  }
+
79 
+
80  template <typename T_n,
+
81  typename T_N,
+
82  typename T_a,
+
83  typename T_b>
+
84  inline
+
85  double
+
86  hypergeometric_log(const T_n& n,
+
87  const T_N& N,
+
88  const T_a& a,
+
89  const T_b& b) {
+
90  return hypergeometric_log<false>(n, N, a, b);
+
91  }
+
92  }
+
93 }
+
94 #endif
+
fvar< T > binomial_coefficient_log(const fvar< T > &x1, const fvar< T > &x2)
+
double hypergeometric_log(const T_n &n, const T_N &N, const T_a &a, const T_b &b)
+ + +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
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diff --git a/doc/api/html/hypergeometric__rng_8hpp.html b/doc/api/html/hypergeometric__rng_8hpp.html new file mode 100644 index 00000000000..5be01bc9f59 --- /dev/null +++ b/doc/api/html/hypergeometric__rng_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/hypergeometric_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + +
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+
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+
hypergeometric_rng.hpp File Reference
+
+
+
#include <boost/math/distributions/hypergeometric.hpp>
+#include <stan/math/prim/scal/err/check_bounded.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/prob/uniform_rng.hpp>
+
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template<class RNG >
int stan::math::hypergeometric_rng (int N, int a, int b, RNG &rng)
 
+
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diff --git a/doc/api/html/hypergeometric__rng_8hpp_source.html b/doc/api/html/hypergeometric__rng_8hpp_source.html new file mode 100644 index 00000000000..6a7f28c0017 --- /dev/null +++ b/doc/api/html/hypergeometric__rng_8hpp_source.html @@ -0,0 +1,168 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/hypergeometric_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_HYPERGEOMETRIC_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_HYPERGEOMETRIC_RNG_HPP
+
3 
+
4 #include <boost/math/distributions/hypergeometric.hpp>
+
5 
+ + + +
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  template <class RNG>
+
15  inline int
+
16  hypergeometric_rng(int N, int a, int b, RNG& rng) {
+
17  using boost::variate_generator;
+
18  using boost::math::hypergeometric_distribution;
+ + +
21 
+
22  static const char* function("stan::math::hypergeometric_rng");
+
23 
+
24  check_bounded(function, "Draws parameter", N, 0, a+b);
+
25  check_positive(function, "Draws parameter", N);
+
26  check_positive(function, "Successes in population parameter", a);
+
27  check_positive(function, "Failures in population parameter", b);
+
28 
+
29  hypergeometric_distribution<> dist(b, N, a + b);
+
30 
+
31  double u = uniform_rng(0.0, 1.0, rng);
+
32  int min = 0;
+
33  int max = a - 1;
+
34  while (min < max) {
+
35  int mid = (min + max) / 2;
+
36  if (cdf(dist, mid + 1) > u)
+
37  max = mid;
+
38  else
+
39  min = mid + 1;
+
40  }
+
41  return min + 1;
+
42  }
+
43 
+
44  }
+
45 
+
46 }
+
47 
+
48 #endif
+
int min(const std::vector< int > &x)
Returns the minimum coefficient in the specified column vector.
Definition: min.hpp:20
+ + +
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
double uniform_rng(const double alpha, const double beta, RNG &rng)
Definition: uniform_rng.hpp:21
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ +
double dist(const std::vector< double > &x, const std::vector< double > &y)
Definition: dist.hpp:11
+
int hypergeometric_rng(int N, int a, int b, RNG &rng)
+
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diff --git a/doc/api/html/identity__constrain_8hpp.html b/doc/api/html/identity__constrain_8hpp.html new file mode 100644 index 00000000000..20ead773291 --- /dev/null +++ b/doc/api/html/identity__constrain_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/identity_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::identity_constrain (T x)
 Returns the result of applying the identity constraint transform to the input. More...
 
template<typename T >
stan::math::identity_constrain (const T x, T &)
 Returns the result of applying the identity constraint transform to the input and increments the log probability reference with the log absolute Jacobian determinant. More...
 
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diff --git a/doc/api/html/identity__constrain_8hpp_source.html b/doc/api/html/identity__constrain_8hpp_source.html new file mode 100644 index 00000000000..3584596c36d --- /dev/null +++ b/doc/api/html/identity__constrain_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/identity_constrain.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_IDENTITY_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_IDENTITY_CONSTRAIN_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  namespace math {
+
7 
+
20  template <typename T>
+
21  inline
+ +
23  return x;
+
24  }
+
25 
+
39  template <typename T>
+
40  inline
+
41  T identity_constrain(const T x, T& /*lp*/) {
+
42  return x;
+
43  }
+
44 
+
45  }
+
46 
+
47 }
+
48 
+
49 #endif
+ +
T identity_constrain(T x)
Returns the result of applying the identity constraint transform to the input.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/identity__free_8hpp.html b/doc/api/html/identity__free_8hpp.html new file mode 100644 index 00000000000..38cc473a443 --- /dev/null +++ b/doc/api/html/identity__free_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/identity_free.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::identity_free (const T y)
 Returns the result of applying the inverse of the identity constraint transform to the input. More...
 
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diff --git a/doc/api/html/identity__free_8hpp_source.html b/doc/api/html/identity__free_8hpp_source.html new file mode 100644 index 00000000000..cefc89bb11b --- /dev/null +++ b/doc/api/html/identity__free_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/identity_free.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_IDENTITY_FREE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_IDENTITY_FREE_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  namespace math {
+
7 
+
19  template <typename T>
+
20  inline
+
21  T identity_free(const T y) {
+
22  return y;
+
23  }
+
24 
+
25  }
+
26 
+
27 }
+
28 
+
29 #endif
+ +
T identity_free(const T y)
Returns the result of applying the inverse of the identity constraint transform to the input...
+
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diff --git a/doc/api/html/inc__beta__dda_8hpp.html b/doc/api/html/inc__beta__dda_8hpp.html new file mode 100644 index 00000000000..d75c27b3a27 --- /dev/null +++ b/doc/api/html/inc__beta__dda_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inc_beta_dda.hpp File Reference + + + + + + + + + + +
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inc_beta_dda.hpp File Reference
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+
#include <stan/math/prim/scal/fun/inc_beta.hpp>
+#include <stan/math/prim/scal/fun/inc_beta_ddb.hpp>
+#include <cmath>
+#include <stdexcept>
+
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template<typename T >
stan::math::inc_beta_ddb (T a, T b, T z, T digamma_b, T digamma_ab)
 Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to b. More...
 
template<typename T >
stan::math::inc_beta_dda (T a, T b, T z, T digamma_a, T digamma_ab)
 Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a. More...
 
+
+
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diff --git a/doc/api/html/inc__beta__dda_8hpp_source.html b/doc/api/html/inc__beta__dda_8hpp_source.html new file mode 100644 index 00000000000..7783be58756 --- /dev/null +++ b/doc/api/html/inc__beta__dda_8hpp_source.html @@ -0,0 +1,192 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inc_beta_dda.hpp Source File + + + + + + + + + + +
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inc_beta_dda.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INC_BETA_DDA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INC_BETA_DDA_HPP
+
3 
+ + +
6 #include <cmath>
+
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  T inc_beta_ddb(T a, T b, T z,
+
14  T digamma_b, T digamma_ab);
+
15 
+
38  template <typename T>
+
39  T inc_beta_dda(T a, T b, T z,
+
40  T digamma_a, T digamma_ab) {
+
41  using std::log;
+
42 
+
43  if (b > a)
+
44  if ((0.1 < z && z <= 0.75 && b > 500)
+
45  || (0.01 < z && z <= 0.1 && b > 2500)
+
46  || (0.001 < z && z <= 0.01 && b > 1e5))
+
47  return -inc_beta_ddb(b, a, 1 - z, digamma_a, digamma_ab);
+
48 
+
49  if (z > 0.75 && a < 500)
+
50  return -inc_beta_ddb(b, a, 1 - z, digamma_a, digamma_ab);
+
51  if (z > 0.9 && a < 2500)
+
52  return -inc_beta_ddb(b, a, 1 - z, digamma_a, digamma_ab);
+
53  if (z > 0.99 && a < 1e5)
+
54  return -inc_beta_ddb(b, a, 1 - z, digamma_a, digamma_ab);
+
55  if (z > 0.999)
+
56  return -inc_beta_ddb(b, a, 1 - z, digamma_a, digamma_ab);
+
57 
+
58  double threshold = 1e-10;
+
59 
+
60  digamma_a += 1.0 / a; // Need digamma(a + 1), not digamma(a);
+
61 
+
62  // Common prefactor to regularize numerator and denomentator
+
63  T prefactor = (a + 1) / (a + b);
+
64  prefactor = prefactor * prefactor * prefactor;
+
65 
+
66  T sum_numer = (digamma_ab - digamma_a) * prefactor;
+
67  T sum_denom = prefactor;
+
68 
+
69  T summand = prefactor * z * (a + b) / (a + 1);
+
70 
+
71  T k = 1;
+
72  digamma_ab += 1.0 / (a + b);
+
73  digamma_a += 1.0 / (a + 1);
+
74 
+
75  while (fabs(summand) > threshold) {
+
76  sum_numer += (digamma_ab - digamma_a) * summand;
+
77  sum_denom += summand;
+
78 
+
79  summand *= (1 + (a + b) / k) * (1 + k) / (1 + (a + 1) / k);
+
80  digamma_ab += 1.0 / (a + b + k);
+
81  digamma_a += 1.0 / (a + 1 + k);
+
82  ++k;
+
83  summand *= z / k;
+
84 
+
85  if (k > 1e5)
+
86  throw std::domain_error("stan::math::inc_beta_dda did "
+
87  "not converge within 100000 iterations");
+
88  }
+
89  return inc_beta(a, b, z) * (log(z) + sum_numer / sum_denom);
+
90  }
+
91 
+
92  } // math
+
93 } // stan
+
94 
+
95 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
T inc_beta_dda(T a, T b, T z, T digamma_a, T digamma_ab)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a.
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T inc_beta_ddb(T a, T b, T z, T digamma_b, T digamma_ab)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to b.
+ +
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+ +
+
+
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diff --git a/doc/api/html/inc__beta__ddb_8hpp.html b/doc/api/html/inc__beta__ddb_8hpp.html new file mode 100644 index 00000000000..30dce2a7e94 --- /dev/null +++ b/doc/api/html/inc__beta__ddb_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inc_beta_ddb.hpp File Reference + + + + + + + + + + +
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inc_beta_ddb.hpp File Reference
+
+
+
#include <stan/math/prim/scal/fun/inc_beta.hpp>
+#include <stan/math/prim/scal/fun/inc_beta_dda.hpp>
+#include <cmath>
+#include <stdexcept>
+
+

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 Matrices and templated mathematical functions.
 
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template<typename T >
stan::math::inc_beta_dda (T a, T b, T z, T digamma_a, T digamma_ab)
 Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a. More...
 
template<typename T >
stan::math::inc_beta_ddb (T a, T b, T z, T digamma_b, T digamma_ab)
 Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to b. More...
 
+
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diff --git a/doc/api/html/inc__beta__ddb_8hpp_source.html b/doc/api/html/inc__beta__ddb_8hpp_source.html new file mode 100644 index 00000000000..53ffaf533f9 --- /dev/null +++ b/doc/api/html/inc__beta__ddb_8hpp_source.html @@ -0,0 +1,187 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inc_beta_ddb.hpp Source File + + + + + + + + + + +
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inc_beta_ddb.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INC_BETA_DDB_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INC_BETA_DDB_HPP
+
3 
+ + +
6 #include <cmath>
+
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  T inc_beta_dda(T a, T b, T z,
+
14  T digamma_a, T digamma_ab);
+
15 
+
38  template <typename T>
+
39  T inc_beta_ddb(T a, T b, T z,
+
40  T digamma_b, T digamma_ab) {
+
41  using std::log;
+
42 
+
43  if (b > a)
+
44  if ((0.1 < z && z <= 0.75 && b > 500)
+
45  || (0.01 < z && z <= 0.1 && b > 2500)
+
46  || (0.001 < z && z <= 0.01 && b > 1e5))
+
47  return -inc_beta_dda(b, a, 1 - z, digamma_b, digamma_ab);
+
48 
+
49  if ((z > 0.75 && a < 500)
+
50  || (z > 0.9 && a < 2500)
+
51  || (z > 0.99 && a < 1e5)
+
52  || (z > 0.999))
+
53  return -inc_beta_dda(b, a, 1 - z, digamma_b, digamma_ab);
+
54 
+
55  double threshold = 1e-10;
+
56 
+
57  // Common prefactor to regularize numerator and denomentator
+
58  T prefactor = (a + 1) / (a + b);
+
59  prefactor = prefactor * prefactor * prefactor;
+
60 
+
61  T sum_numer = digamma_ab * prefactor;
+
62  T sum_denom = prefactor;
+
63 
+
64  T summand = prefactor * z * (a + b) / (a + 1);
+
65 
+
66  T k = 1;
+
67  digamma_ab += 1.0 / (a + b);
+
68 
+
69  while (fabs(summand) > threshold) {
+
70  sum_numer += digamma_ab * summand;
+
71  sum_denom += summand;
+
72 
+
73  summand *= (1 + (a + b) / k) * (1 + k) / (1 + (a + 1) / k);
+
74  digamma_ab += 1.0 / (a + b + k);
+
75  ++k;
+
76  summand *= z / k;
+
77 
+
78  if (k > 1e5)
+
79  throw std::domain_error("stan::math::inc_beta_ddb did "
+
80  "not converge within 100000 iterations");
+
81  }
+
82 
+
83  return inc_beta(a, b, z)
+
84  * (log(1 - z) - digamma_b + sum_numer / sum_denom);
+
85  }
+
86 
+
87  } // math
+
88 } // stan
+
89 
+
90 #endif
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
T inc_beta_dda(T a, T b, T z, T digamma_a, T digamma_ab)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a.
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T inc_beta_ddb(T a, T b, T z, T digamma_b, T digamma_ab)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to b.
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+ + +
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diff --git a/doc/api/html/inc__beta__ddz_8hpp.html b/doc/api/html/inc__beta__ddz_8hpp.html new file mode 100644 index 00000000000..2a8b6d7fc8a --- /dev/null +++ b/doc/api/html/inc__beta__ddz_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inc_beta_ddz.hpp File Reference + + + + + + + + + + +
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+
#include <stan/math/prim/scal/fun/lgamma.hpp>
+#include <stan/math/prim/scal/fun/inc_beta.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <cmath>
+
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template<typename T >
stan::math::inc_beta_ddz (T a, T b, T z)
 Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to z. More...
 
template<>
double stan::math::inc_beta_ddz (double a, double b, double z)
 
+
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diff --git a/doc/api/html/inc__beta__ddz_8hpp_source.html b/doc/api/html/inc__beta__ddz_8hpp_source.html new file mode 100644 index 00000000000..e5c026c0f55 --- /dev/null +++ b/doc/api/html/inc__beta__ddz_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inc_beta_ddz.hpp Source File + + + + + + + + + + +
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inc_beta_ddz.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INC_BETA_DERIVATIVES_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INC_BETA_DERIVATIVES_HPP
+
3 
+ + +
6 #include <boost/math/special_functions/beta.hpp>
+
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
26  template <typename T>
+
27  T inc_beta_ddz(T a, T b, T z) {
+
28  using std::exp;
+
29  using std::log;
+
30  return exp((b - 1) * log(1 - z) + (a - 1) * log(z)
+
31  + lgamma(a + b) - lgamma(a) - lgamma(b));
+
32  }
+
33 
+
34  template <>
+
35  double inc_beta_ddz(double a, double b, double z) {
+
36  using boost::math::ibeta_derivative;
+
37  return ibeta_derivative(a, b, z);
+
38  }
+
39 
+
40  } // math
+
41 } // stan
+
42 
+
43 #endif
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T inc_beta_ddz(T a, T b, T z)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to z.
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
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diff --git a/doc/api/html/include__summand_8hpp.html b/doc/api/html/include__summand_8hpp.html new file mode 100644 index 00000000000..25bde9b1a77 --- /dev/null +++ b/doc/api/html/include__summand_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/include_summand.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/meta/is_constant.hpp>
+#include <stan/math/prim/scal/meta/scalar_type.hpp>
+#include <boost/math/tools/promotion.hpp>
+
+

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+Classes

struct  stan::math::include_summand< propto, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10 >
 Template metaprogram to calculate whether a summand needs to be included in a proportional (log) probability calculation. More...
 
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 Matrices and templated mathematical functions.
 
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diff --git a/doc/api/html/include__summand_8hpp_source.html b/doc/api/html/include__summand_8hpp_source.html new file mode 100644 index 00000000000..48d4ce1eee9 --- /dev/null +++ b/doc/api/html/include__summand_8hpp_source.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/include_summand.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_INCLUDE_SUMMAND_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_INCLUDE_SUMMAND_HPP
+
3 
+ + +
6 #include <boost/math/tools/promotion.hpp>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
30  template <bool propto,
+
31  typename T1 = double, typename T2 = double,
+
32  typename T3 = double, typename T4 = double,
+
33  typename T5 = double, typename T6 = double,
+
34  typename T7 = double, typename T8 = double,
+
35  typename T9 = double, typename T10 = double>
+
36  struct include_summand {
+
42  enum {
+
43  value = (!propto
+ + + + + + + + + + +
54  )
+
55  };
+
56  };
+
57 
+
58 
+
59  }
+
60 
+
61 }
+
62 
+
63 #endif
+
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Definition: is_constant.hpp:22
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
+
+
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diff --git a/doc/api/html/initialize_8hpp.html b/doc/api/html/initialize_8hpp.html new file mode 100644 index 00000000000..af1345c510d --- /dev/null +++ b/doc/api/html/initialize_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/initialize.hpp File Reference + + + + + + + + + + +
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initialize.hpp File Reference
+
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+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <boost/type_traits/is_arithmetic.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <vector>
+
+

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template<typename T >
void stan::math::initialize (T &x, const T &v)
 
template<typename T , typename V >
boost::enable_if_c< boost::is_arithmetic< V >::value, void >::type stan::math::initialize (T &x, V v)
 
template<typename T , int R, int C, typename V >
void stan::math::initialize (Eigen::Matrix< T, R, C > &x, const V &v)
 
template<typename T , typename V >
void stan::math::initialize (std::vector< T > &x, const V &v)
 
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diff --git a/doc/api/html/initialize_8hpp_source.html b/doc/api/html/initialize_8hpp_source.html new file mode 100644 index 00000000000..49800d0c18c --- /dev/null +++ b/doc/api/html/initialize_8hpp_source.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/initialize.hpp Source File + + + + + + + + + + +
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initialize.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_INITIALIZE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_INITIALIZE_HPP
+
3 
+ +
5 #include <boost/type_traits/is_arithmetic.hpp>
+
6 #include <boost/utility/enable_if.hpp>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  // initializations called for local variables generate in Stan
+
14  // code; fills in all cells in first arg with second arg
+
15 
+
16  template <typename T>
+
17  inline void initialize(T& x, const T& v) {
+
18  x = v;
+
19  }
+
20  template <typename T, typename V>
+
21  inline
+
22  typename boost::enable_if_c<boost::is_arithmetic<V>::value, void>::type
+
23  initialize(T& x, V v) {
+
24  x = v;
+
25  }
+
26  template <typename T, int R, int C, typename V>
+
27  inline void initialize(Eigen::Matrix<T, R, C>& x, const V& v) {
+
28  for (int i = 0; i < x.size(); ++i)
+
29  initialize(x(i), v);
+
30  }
+
31  template <typename T, typename V>
+
32  inline void initialize(std::vector<T>& x, const V& v) {
+
33  for (size_t i = 0; i < x.size(); ++i)
+
34  initialize(x[i], v);
+
35  }
+
36 
+
37  }
+
38 }
+
39 #endif
+ +
void initialize(T &x, const T &v)
Definition: initialize.hpp:17
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/initialize__variable_8hpp.html b/doc/api/html/initialize__variable_8hpp.html new file mode 100644 index 00000000000..0b4b3a57424 --- /dev/null +++ b/doc/api/html/initialize__variable_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/initialize_variable.hpp File Reference + + + + + + + + + + +
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initialize_variable.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <vector>
+
+

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 stan
 
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 Matrices and templated mathematical functions.
 
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+Functions

void stan::math::initialize_variable (var &variable, const var &value)
 Initialize variable to value. More...
 
template<int R, int C>
void stan::math::initialize_variable (Eigen::Matrix< var, R, C > &matrix, const var &value)
 Initialize every cell in the matrix to the specified value. More...
 
template<typename T >
void stan::math::initialize_variable (std::vector< T > &variables, const var &value)
 Initialize the variables in the standard vector recursively. More...
 
+
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diff --git a/doc/api/html/initialize__variable_8hpp_source.html b/doc/api/html/initialize__variable_8hpp_source.html new file mode 100644 index 00000000000..78f5e1a225c --- /dev/null +++ b/doc/api/html/initialize__variable_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/initialize_variable.hpp Source File + + + + + + + + + + +
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initialize_variable.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_INITIALIZE_VARIABLE_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_INITIALIZE_VARIABLE_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
15  inline void initialize_variable(var& variable, const var& value) {
+
16  variable = value;
+
17  }
+
18 
+
23  template <int R, int C>
+
24  inline void initialize_variable(Eigen::Matrix<var, R, C>& matrix,
+
25  const var& value) {
+
26  for (int i = 0; i < matrix.size(); ++i)
+
27  matrix(i) = value;
+
28  }
+
29 
+
33  template <typename T>
+
34  inline void initialize_variable(std::vector<T>& variables,
+
35  const var& value) {
+
36  for (size_t i = 0; i < variables.size(); ++i)
+
37  initialize_variable(variables[i], value);
+
38  }
+
39 
+
40  }
+
41 }
+
42 
+
43 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
void initialize_variable(var &variable, const var &value)
Initialize variable to value.
+ +
+
+
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diff --git a/doc/api/html/int__step_8hpp.html b/doc/api/html/int__step_8hpp.html new file mode 100644 index 00000000000..20fa5026c41 --- /dev/null +++ b/doc/api/html/int__step_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/int_step.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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template<typename T >
unsigned int stan::math::int_step (const T y)
 The integer step, or Heaviside, function. More...
 
+
+
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/int__step_8hpp_source.html b/doc/api/html/int__step_8hpp_source.html new file mode 100644 index 00000000000..dbd23d94f88 --- /dev/null +++ b/doc/api/html/int__step_8hpp_source.html @@ -0,0 +1,124 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/int_step.hpp Source File + + + + + + + + + + +
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int_step.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INT_STEP_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INT_STEP_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
24  template <typename T>
+
25  unsigned int int_step(const T y) {
+
26  return y > 0;
+
27  }
+
28  }
+
29 }
+
30 
+
31 #endif
+ +
unsigned int int_step(const T y)
The integer step, or Heaviside, function.
Definition: int_step.hpp:25
+
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diff --git a/doc/api/html/integrate__ode__bdf_8hpp.html b/doc/api/html/integrate__ode__bdf_8hpp.html new file mode 100644 index 00000000000..9a45d7342e4 --- /dev/null +++ b/doc/api/html/integrate__ode__bdf_8hpp.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/integrate_ode_bdf.hpp File Reference + + + + + + + + + + +
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integrate_ode_bdf.hpp File Reference
+
+
+
#include <stan/math/prim/arr/fun/value_of.hpp>
+#include <stan/math/prim/scal/err/check_less.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
+#include <stan/math/prim/arr/err/check_ordered.hpp>
+#include <stan/math/rev/scal/meta/is_var.hpp>
+#include <stan/math/prim/scal/meta/return_type.hpp>
+#include <stan/math/rev/mat/functor/cvodes_utils.hpp>
+#include <stan/math/rev/mat/functor/cvodes_ode_data.hpp>
+#include <stan/math/rev/arr/fun/decouple_ode_states.hpp>
+#include <cvodes/cvodes.h>
+#include <cvodes/cvodes_band.h>
+#include <cvodes/cvodes_dense.h>
+#include <nvector/nvector_serial.h>
+#include <algorithm>
+#include <ostream>
+#include <vector>
+
+

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void stan::math::free_cvodes_memory (N_Vector &cvodes_state, N_Vector *cvodes_state_sens, void *cvodes_mem, size_t S)
 Free memory allocated for CVODES state, sensitivity, and general memory. More...
 
template<typename F , typename T_initial , typename T_param >
std::vector< std::vector< typename stan::return_type< T_initial, T_param >::type > > stan::math::integrate_ode_bdf (const F &f, const std::vector< T_initial > &y0, const double t0, const std::vector< double > &ts, const std::vector< T_param > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs=0, double relative_tolerance=1e-10, double absolute_tolerance=1e-10, long int max_num_steps=1e8)
 Return the solutions for the specified system of ordinary differential equations given the specified initial state, initial times, times of desired solution, and parameters and data, writing error and warning messages to the specified stream. More...
 
+
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diff --git a/doc/api/html/integrate__ode__bdf_8hpp_source.html b/doc/api/html/integrate__ode__bdf_8hpp_source.html new file mode 100644 index 00000000000..ed26b41577f --- /dev/null +++ b/doc/api/html/integrate__ode__bdf_8hpp_source.html @@ -0,0 +1,303 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/integrate_ode_bdf.hpp Source File + + + + + + + + + + +
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integrate_ode_bdf.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUNCTOR_INTEGRATE_ODE_BDF_HPP
+
2 #define STAN_MATH_REV_MAT_FUNCTOR_INTEGRATE_ODE_BDF_HPP
+
3 
+ + + + + + + + + + +
14 #include <cvodes/cvodes.h>
+
15 #include <cvodes/cvodes_band.h>
+
16 #include <cvodes/cvodes_dense.h>
+
17 #include <nvector/nvector_serial.h>
+
18 #include <algorithm>
+
19 #include <ostream>
+
20 #include <vector>
+
21 
+
22 namespace stan {
+
23  namespace math {
+
24 
+
34  inline void free_cvodes_memory(N_Vector& cvodes_state,
+
35  N_Vector* cvodes_state_sens,
+
36  void* cvodes_mem, size_t S) {
+
37  N_VDestroy_Serial(cvodes_state);
+
38  if (cvodes_state_sens != NULL)
+
39  N_VDestroyVectorArray_Serial(cvodes_state_sens, S);
+
40  CVodeFree(&cvodes_mem);
+
41  }
+
42 
+
80  template <typename F, typename T_initial, typename T_param>
+
81  std::vector<std::vector<typename stan::return_type<T_initial,
+
82  T_param>::type> >
+
83  integrate_ode_bdf(const F& f,
+
84  const std::vector<T_initial>& y0,
+
85  const double t0,
+
86  const std::vector<double>& ts,
+
87  const std::vector<T_param>& theta,
+
88  const std::vector<double>& x,
+
89  const std::vector<int>& x_int,
+
90  std::ostream* msgs = 0,
+
91  double relative_tolerance = 1e-10,
+
92  double absolute_tolerance = 1e-10,
+
93  long int max_num_steps = 1e8) { // NOLINT(runtime/int)
+
94  typedef stan::is_var<T_initial> initial_var;
+
95  typedef stan::is_var<T_param> param_var;
+
96 
+
97  stan::math::check_finite("integrate_ode_bdf", "initial state", y0);
+
98  stan::math::check_finite("integrate_ode_bdf", "initial time", t0);
+
99  stan::math::check_finite("integrate_ode_bdf", "times", ts);
+
100  stan::math::check_finite("integrate_ode_bdf", "parameter vector", theta);
+
101  stan::math::check_finite("integrate_ode_bdf", "continuous data", x);
+
102  stan::math::check_nonzero_size("integrate_ode_bdf", "times", ts);
+
103  stan::math::check_nonzero_size("integrate_ode_bdf", "initial state", y0);
+
104  stan::math::check_ordered("integrate_ode_bdf", "times", ts);
+
105  stan::math::check_less("integrate_ode_bdf", "initial time", t0, ts[0]);
+
106  if (relative_tolerance <= 0)
+
107  invalid_argument("integrate_ode_bdf",
+
108  "relative_tolerance,", relative_tolerance,
+
109  "", ", must be greater than 0");
+
110  if (absolute_tolerance <= 0)
+
111  invalid_argument("integrate_ode_bdf",
+
112  "absolute_tolerance,", absolute_tolerance,
+
113  "", ", must be greater than 0");
+
114  if (max_num_steps <= 0)
+
115  invalid_argument("integrate_ode_bdf",
+
116  "max_num_steps,", max_num_steps,
+
117  "", ", must be greater than 0");
+
118 
+
119  const size_t N = y0.size();
+
120  const size_t M = theta.size();
+
121  // total number of sensitivities for initial values and params
+
122  const size_t S = (initial_var::value ? N : 0)
+
123  + (param_var::value ? M : 0);
+
124  const size_t size = N * (S + 1); // size of the coupled system
+
125  std::vector<double> state(value_of(y0));
+
126  N_Vector cvodes_state(N_VMake_Serial(N, &state[0]));
+
127  N_Vector* cvodes_state_sens = NULL;
+
128 
+ +
130  ode_data cvodes_data(f, y0, theta, x, x_int, msgs);
+
131 
+
132  void* cvodes_mem = CVodeCreate(CV_BDF, CV_NEWTON);
+
133  if (cvodes_mem == NULL)
+
134  throw std::runtime_error("CVodeCreate failed to allocate memory");
+
135 
+
136  std::vector<std::vector<double> >
+
137  y_coupled(ts.size(), std::vector<double>(size, 0));
+
138 
+
139  try {
+
140  cvodes_check_flag(CVodeInit(cvodes_mem, &ode_data::ode_rhs,
+
141  t0, cvodes_state),
+
142  "CVodeInit");
+
143 
+
144  // Assign pointer to this as user data
+
145  cvodes_check_flag(CVodeSetUserData(cvodes_mem,
+
146  reinterpret_cast<void*>(&cvodes_data)),
+
147  "CVodeSetUserData");
+
148 
+
149  cvodes_set_options(cvodes_mem,
+
150  relative_tolerance, absolute_tolerance,
+
151  max_num_steps);
+
152 
+
153  // for the stiff solvers we need to reserve additional
+
154  // memory and provide a Jacobian function call
+
155  cvodes_check_flag(CVDense(cvodes_mem, N), "CVDense");
+
156  cvodes_check_flag(CVDlsSetDenseJacFn(cvodes_mem,
+
157  &ode_data::dense_jacobian),
+
158  "CVDlsSetDenseJacFn");
+
159 
+
160  // initialize forward sensitivity system of CVODES as needed
+
161  if (S > 0) {
+
162  cvodes_state_sens = N_VCloneVectorArray_Serial(S, cvodes_state);
+
163  for (size_t s = 0; s < S; s++)
+
164  N_VConst(RCONST(0.0), cvodes_state_sens[s]);
+
165 
+
166  // for varying initials, first N sensitivity systems
+
167  // are for initials which have as initial the identity matrix
+
168  if (initial_var::value) {
+
169  for (size_t n = 0; n < N; n++)
+
170  NV_Ith_S(cvodes_state_sens[n], n) = 1.0;
+
171  }
+
172  cvodes_check_flag(CVodeSensInit(cvodes_mem, static_cast<int>(S),
+
173  CV_STAGGERED,
+
174  &ode_data::ode_rhs_sens,
+
175  cvodes_state_sens),
+
176  "CVodeSensInit");
+
177 
+
178  cvodes_check_flag(CVodeSensEEtolerances(cvodes_mem),
+
179  "CVodeSensEEtolerances");
+
180  }
+
181 
+
182  double t_init = t0;
+
183  for (size_t n = 0; n < ts.size(); ++n) {
+
184  double t_final = ts[n];
+
185  if (t_final != t_init)
+
186  cvodes_check_flag(CVode(cvodes_mem, t_final, cvodes_state,
+
187  &t_init, CV_NORMAL),
+
188  "CVode");
+
189  std::copy(state.begin(), state.end(), y_coupled[n].begin());
+
190  if (S > 0) {
+
191  cvodes_check_flag(CVodeGetSens(cvodes_mem, &t_init,
+
192  cvodes_state_sens),
+
193  "CVodeGetSens");
+
194  for (size_t s = 0; s < S; s++)
+
195  std::copy(NV_DATA_S(cvodes_state_sens[s]),
+
196  NV_DATA_S(cvodes_state_sens[s]) + N,
+
197  y_coupled[n].begin() + N + s * N);
+
198  }
+
199  t_init = t_final;
+
200  }
+
201  } catch (const std::exception& e) {
+
202  free_cvodes_memory(cvodes_state, cvodes_state_sens, cvodes_mem, S);
+
203  throw;
+
204  }
+
205 
+
206  free_cvodes_memory(cvodes_state, cvodes_state_sens, cvodes_mem, S);
+
207 
+
208  return decouple_ode_states(y_coupled, y0, theta);
+
209  }
+
210 
+
211  }
+
212 }
+
213 #endif
+
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+
void cvodes_set_options(void *cvodes_mem, double rel_tol, double abs_tol, long int max_num_steps)
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of...
Definition: return_type.hpp:19
+
std::vector< std::vector< typename stan::return_type< T_initial, T_param >::type > > integrate_ode_bdf(const F &f, const std::vector< T_initial > &y0, const double t0, const std::vector< double > &ts, const std::vector< T_param > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs=0, double relative_tolerance=1e-10, double absolute_tolerance=1e-10, long int max_num_steps=1e8)
Return the solutions for the specified system of ordinary differential equations given the specified ...
+ +
void free_cvodes_memory(N_Vector &cvodes_state, N_Vector *cvodes_state_sens, void *cvodes_mem, size_t S)
Free memory allocated for CVODES state, sensitivity, and general memory.
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
bool check_ordered(const char *function, const char *name, const std::vector< T_y > &y)
Return true if the specified vector is sorted into strictly increasing order.
+ +
CVODES ode data holder object which is used during CVODES integration for CVODES callbacks.
+
void cvodes_check_flag(int flag, const std::string &func_name)
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+ +
std::vector< std::vector< typename stan::return_type< T_initial, T_param >::type > > decouple_ode_states(const std::vector< std::vector< double > > &y, const std::vector< T_initial > &y0, const std::vector< T_param > &theta)
Takes sensitivity output from integrators and returns results in precomputed_gradients format...
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ + + + + +
+
+
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diff --git a/doc/api/html/integrate__ode__rk45_8hpp.html b/doc/api/html/integrate__ode__rk45_8hpp.html new file mode 100644 index 00000000000..65ff8c88f42 --- /dev/null +++ b/doc/api/html/integrate__ode__rk45_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/functor/integrate_ode_rk45.hpp File Reference + + + + + + + + + + +
+
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+
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template<typename F , typename T1 , typename T2 >
std::vector< std::vector< typename stan::return_type< T1, T2 >::type > > stan::math::integrate_ode_rk45 (const F &f, const std::vector< T1 > y0, const double t0, const std::vector< double > &ts, const std::vector< T2 > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs=0, double relative_tolerance=1e-6, double absolute_tolerance=1e-6, int max_num_steps=1E6)
 Return the solutions for the specified system of ordinary differential equations given the specified initial state, initial times, times of desired solution, and parameters and data, writing error and warning messages to the specified stream. More...
 
+
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diff --git a/doc/api/html/integrate__ode__rk45_8hpp_source.html b/doc/api/html/integrate__ode__rk45_8hpp_source.html new file mode 100644 index 00000000000..64199075de8 --- /dev/null +++ b/doc/api/html/integrate__ode__rk45_8hpp_source.html @@ -0,0 +1,233 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/functor/integrate_ode_rk45.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+
+
integrate_ode_rk45.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_FUNCTOR_INTEGRATE_ODE_RK45_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUNCTOR_INTEGRATE_ODE_RK45_HPP
+
3 
+ + + + + + + + + +
13 #include <boost/numeric/odeint.hpp>
+
14 #include <ostream>
+
15 #include <vector>
+
16 
+
17 namespace stan {
+
18 
+
19  namespace math {
+
20 
+
65  template <typename F, typename T1, typename T2>
+
66  std::vector<std::vector<typename stan::return_type<T1, T2>::type> >
+
67  integrate_ode_rk45(const F& f,
+
68  const std::vector<T1> y0,
+
69  const double t0,
+
70  const std::vector<double>& ts,
+
71  const std::vector<T2>& theta,
+
72  const std::vector<double>& x,
+
73  const std::vector<int>& x_int,
+
74  std::ostream* msgs = 0,
+
75  double relative_tolerance = 1e-6,
+
76  double absolute_tolerance = 1e-6,
+
77  int max_num_steps = 1E6) {
+
78  using boost::numeric::odeint::integrate_times;
+
79  using boost::numeric::odeint::make_dense_output;
+
80  using boost::numeric::odeint::runge_kutta_dopri5;
+
81  using boost::numeric::odeint::max_step_checker;
+
82 
+
83  check_finite("integrate_ode_rk45", "initial state", y0);
+
84  check_finite("integrate_ode_rk45", "initial time", t0);
+
85  check_finite("integrate_ode_rk45", "times", ts);
+
86  check_finite("integrate_ode_rk45", "parameter vector", theta);
+
87  check_finite("integrate_ode_rk45", "continuous data", x);
+
88 
+
89  check_nonzero_size("integrate_ode_rk45", "times", ts);
+
90  check_nonzero_size("integrate_ode_rk45", "initial state", y0);
+
91  check_ordered("integrate_ode_rk45", "times", ts);
+
92  check_less("integrate_ode_rk45", "initial time", t0, ts[0]);
+
93 
+
94  if (relative_tolerance <= 0)
+
95  invalid_argument("integrate_ode_rk45",
+
96  "relative_tolerance,", relative_tolerance,
+
97  "", ", must be greater than 0");
+
98  if (absolute_tolerance <= 0)
+
99  invalid_argument("integrate_ode_rk45",
+
100  "absolute_tolerance,", absolute_tolerance,
+
101  "", ", must be greater than 0");
+
102  if (max_num_steps <= 0)
+
103  invalid_argument("integrate_ode_rk45",
+
104  "max_num_steps,", max_num_steps,
+
105  "", ", must be greater than 0");
+
106 
+
107  // creates basic or coupled system by template specializations
+ +
109  coupled_system(f, y0, theta, x, x_int, msgs);
+
110 
+
111  // first time in the vector must be time of initial state
+
112  std::vector<double> ts_vec(ts.size() + 1);
+
113  ts_vec[0] = t0;
+
114  for (size_t n = 0; n < ts.size(); n++)
+
115  ts_vec[n+1] = ts[n];
+
116 
+
117  std::vector<std::vector<double> > y_coupled(ts_vec.size());
+
118  coupled_ode_observer observer(y_coupled);
+
119 
+
120  // the coupled system creates the coupled initial state
+
121  std::vector<double> initial_coupled_state
+
122  = coupled_system.initial_state();
+
123 
+
124  const double step_size = 0.1;
+
125  integrate_times(make_dense_output(absolute_tolerance,
+
126  relative_tolerance,
+
127  runge_kutta_dopri5<std::vector<double>,
+
128  double,
+
129  std::vector<double>,
+
130  double>() ),
+
131  coupled_system,
+
132  initial_coupled_state,
+
133  boost::begin(ts_vec), boost::end(ts_vec),
+
134  step_size,
+
135  observer,
+
136  max_step_checker(max_num_steps));
+
137 
+
138  // remove the first state corresponding to the initial value
+
139  y_coupled.erase(y_coupled.begin());
+
140 
+
141  // the coupled system also encapsulates the decoupling operation
+
142  return coupled_system.decouple_states(y_coupled);
+
143  }
+
144 
+
145  }
+
146 
+
147 }
+
148 
+
149 #endif
+
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+ + + + +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
bool check_ordered(const char *function, const char *name, const std::vector< T_y > &y)
Return true if the specified vector is sorted into strictly increasing order.
+
Observer for the coupled states.
+
std::vector< std::vector< typename stan::return_type< T1, T2 >::type > > integrate_ode_rk45(const F &f, const std::vector< T1 > y0, const double t0, const std::vector< double > &ts, const std::vector< T2 > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs=0, double relative_tolerance=1e-6, double absolute_tolerance=1e-6, int max_num_steps=1E6)
Return the solutions for the specified system of ordinary differential equations given the specified ...
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
Base template class for a coupled ordinary differential equation system, which adds sensitivities to ...
+ + + + +
+
+
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diff --git a/doc/api/html/inv__chi__square__ccdf__log_8hpp.html b/doc/api/html/inv__chi__square__ccdf__log_8hpp.html new file mode 100644 index 00000000000..9f5f98386b0 --- /dev/null +++ b/doc/api/html/inv__chi__square__ccdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_ccdf_log.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
+
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+
+
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template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::inv_chi_square_ccdf_log (const T_y &y, const T_dof &nu)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__chi__square__ccdf__log_8hpp_source.html b/doc/api/html/inv__chi__square__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..e08e1a4307b --- /dev/null +++ b/doc/api/html/inv__chi__square__ccdf__log_8hpp_source.html @@ -0,0 +1,283 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_ccdf_log.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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inv_chi_square_ccdf_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_CCDF_LOG_HPP
+
3 
+
4 #include <boost/random/chi_squared_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + +
24 #include <cmath>
+
25 #include <limits>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_y, typename T_dof>
+
32  typename return_type<T_y, T_dof>::type
+
33  inv_chi_square_ccdf_log(const T_y& y, const T_dof& nu) {
+ +
35  T_partials_return;
+
36 
+
37  // Size checks
+
38  if ( !( stan::length(y) && stan::length(nu) ) ) return 0.0;
+
39 
+
40  // Error checks
+
41  static const char* function("stan::math::inv_chi_square_ccdf_log");
+
42 
+ + + + +
47  using boost::math::tools::promote_args;
+ +
49  using std::exp;
+
50 
+
51  T_partials_return P(0.0);
+
52 
+
53  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
54  check_not_nan(function, "Random variable", y);
+
55  check_nonnegative(function, "Random variable", y);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Degrees of freedom parameter", nu);
+
59 
+
60  // Wrap arguments in vectors
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_dof> nu_vec(nu);
+
63  size_t N = max_size(y, nu);
+
64 
+
65  OperandsAndPartials<T_y, T_dof> operands_and_partials(y, nu);
+
66 
+
67  // Explicit return for extreme values
+
68  // The gradients are technically ill-defined, but treated as zero
+
69 
+
70  for (size_t i = 0; i < stan::length(y); i++)
+
71  if (value_of(y_vec[i]) == 0)
+
72  return operands_and_partials.value(0.0);
+
73 
+
74  // Compute ccdf_log and its gradients
+
75  using stan::math::gamma_q;
+
76  using stan::math::digamma;
+
77  using boost::math::tgamma;
+
78  using std::exp;
+
79  using std::pow;
+
80  using std::log;
+
81 
+
82  // Cache a few expensive function calls if nu is a parameter
+ +
84  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
86  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
87 
+ +
89  for (size_t i = 0; i < stan::length(nu); i++) {
+
90  const T_partials_return nu_dbl = value_of(nu_vec[i]);
+
91  gamma_vec[i] = tgamma(0.5 * nu_dbl);
+
92  digamma_vec[i] = digamma(0.5 * nu_dbl);
+
93  }
+
94  }
+
95 
+
96  // Compute vectorized ccdf_log and gradient
+
97  for (size_t n = 0; n < N; n++) {
+
98  // Explicit results for extreme values
+
99  // The gradients are technically ill-defined, but treated as zero
+
100  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
101  return operands_and_partials.value(stan::math::negative_infinity());
+
102  }
+
103 
+
104  // Pull out values
+
105  const T_partials_return y_dbl = value_of(y_vec[n]);
+
106  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
107  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+
108 
+
109  // Compute
+
110  const T_partials_return Pn = 1.0 - gamma_q(0.5 * nu_dbl, 0.5
+
111  * y_inv_dbl);
+
112 
+
113  P += log(Pn);
+
114 
+ +
116  operands_and_partials.d_x1[n] -= 0.5 * y_inv_dbl * y_inv_dbl
+
117  * exp(-0.5*y_inv_dbl) * pow(0.5*y_inv_dbl, 0.5*nu_dbl-1)
+
118  / tgamma(0.5*nu_dbl) / Pn;
+ +
120  operands_and_partials.d_x2[n]
+
121  -= 0.5 * stan::math::grad_reg_inc_gamma(0.5 * nu_dbl,
+
122  0.5 * y_inv_dbl,
+
123  gamma_vec[n],
+
124  digamma_vec[n]) / Pn;
+
125  }
+
126 
+
127  return operands_and_partials.value(P);
+
128  }
+
129  }
+
130 }
+
131 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_dof >::type inv_chi_square_ccdf_log(const T_y &y, const T_dof &nu)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__chi__square__cdf_8hpp.html b/doc/api/html/inv__chi__square__cdf_8hpp.html new file mode 100644 index 00000000000..15b6f038899 --- /dev/null +++ b/doc/api/html/inv__chi__square__cdf_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
inv_chi_square_cdf.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::inv_chi_square_cdf (const T_y &y, const T_dof &nu)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__chi__square__cdf_8hpp_source.html b/doc/api/html/inv__chi__square__cdf_8hpp_source.html new file mode 100644 index 00000000000..ebcfa20992b --- /dev/null +++ b/doc/api/html/inv__chi__square__cdf_8hpp_source.html @@ -0,0 +1,288 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
inv_chi_square_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_CDF_HPP
+
3 
+
4 #include <boost/random/chi_squared_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + +
24 #include <cmath>
+
25 #include <limits>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_y, typename T_dof>
+
32  typename return_type<T_y, T_dof>::type
+
33  inv_chi_square_cdf(const T_y& y, const T_dof& nu) {
+ +
35  T_partials_return;
+
36 
+
37  // Size checks
+
38  if ( !( stan::length(y) && stan::length(nu) ) ) return 1.0;
+
39 
+
40  // Error checks
+
41  static const char* function("stan::math::inv_chi_square_cdf");
+
42 
+ + + + +
47  using boost::math::tools::promote_args;
+ +
49  using std::exp;
+
50 
+
51  T_partials_return P(1.0);
+
52 
+
53  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
54  check_not_nan(function, "Random variable", y);
+
55  check_nonnegative(function, "Random variable", y);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Degrees of freedom parameter", nu);
+
59 
+
60  // Wrap arguments in vectors
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_dof> nu_vec(nu);
+
63  size_t N = max_size(y, nu);
+
64 
+
65  OperandsAndPartials<T_y, T_dof> operands_and_partials(y, nu);
+
66 
+
67  // Explicit return for extreme values
+
68  // The gradients are technically ill-defined, but treated as zero
+
69 
+
70  for (size_t i = 0; i < stan::length(y); i++)
+
71  if (value_of(y_vec[i]) == 0)
+
72  return operands_and_partials.value(0.0);
+
73 
+
74  // Compute CDF and its gradients
+
75  using stan::math::gamma_q;
+
76  using stan::math::digamma;
+
77  using boost::math::tgamma;
+
78  using std::exp;
+
79  using std::pow;
+
80 
+
81  // Cache a few expensive function calls if nu is a parameter
+ +
83  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
85  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
86 
+ +
88  for (size_t i = 0; i < stan::length(nu); i++) {
+
89  const T_partials_return nu_dbl = value_of(nu_vec[i]);
+
90  gamma_vec[i] = tgamma(0.5 * nu_dbl);
+
91  digamma_vec[i] = digamma(0.5 * nu_dbl);
+
92  }
+
93  }
+
94 
+
95  // Compute vectorized CDF and gradient
+
96  for (size_t n = 0; n < N; n++) {
+
97  // Explicit results for extreme values
+
98  // The gradients are technically ill-defined, but treated as zero
+
99  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
100  continue;
+
101  }
+
102 
+
103  // Pull out values
+
104  const T_partials_return y_dbl = value_of(y_vec[n]);
+
105  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
106  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+
107 
+
108  // Compute
+
109  const T_partials_return Pn = gamma_q(0.5 * nu_dbl, 0.5 * y_inv_dbl);
+
110 
+
111  P *= Pn;
+
112 
+ +
114  operands_and_partials.d_x1[n] += 0.5 * y_inv_dbl * y_inv_dbl
+
115  * exp(-0.5*y_inv_dbl) * pow(0.5*y_inv_dbl, 0.5*nu_dbl-1)
+
116  / tgamma(0.5*nu_dbl) / Pn;
+ +
118  operands_and_partials.d_x2[n]
+
119  += 0.5 * stan::math::grad_reg_inc_gamma(0.5 * nu_dbl,
+
120  0.5 * y_inv_dbl,
+
121  gamma_vec[n],
+
122  digamma_vec[n]) / Pn;
+
123  }
+
124 
+ +
126  for (size_t n = 0; n < stan::length(y); ++n)
+
127  operands_and_partials.d_x1[n] *= P;
+
128  }
+ +
130  for (size_t n = 0; n < stan::length(nu); ++n)
+
131  operands_and_partials.d_x2[n] *= P;
+
132  }
+
133 
+
134  return operands_and_partials.value(P);
+
135  }
+
136  }
+
137 }
+
138 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
return_type< T_y, T_dof >::type inv_chi_square_cdf(const T_y &y, const T_dof &nu)
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__chi__square__cdf__log_8hpp.html b/doc/api/html/inv__chi__square__cdf__log_8hpp.html new file mode 100644 index 00000000000..682d5a9e22d --- /dev/null +++ b/doc/api/html/inv__chi__square__cdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
inv_chi_square_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::inv_chi_square_cdf_log (const T_y &y, const T_dof &nu)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__chi__square__cdf__log_8hpp_source.html b/doc/api/html/inv__chi__square__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..4df17735189 --- /dev/null +++ b/doc/api/html/inv__chi__square__cdf__log_8hpp_source.html @@ -0,0 +1,282 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
inv_chi_square_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/chi_squared_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <cmath>
+
25 #include <limits>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_y, typename T_dof>
+
32  typename return_type<T_y, T_dof>::type
+
33  inv_chi_square_cdf_log(const T_y& y, const T_dof& nu) {
+ +
35  T_partials_return;
+
36 
+
37  // Size checks
+
38  if ( !( stan::length(y) && stan::length(nu) ) ) return 0.0;
+
39 
+
40  // Error checks
+
41  static const char* function("stan::math::inv_chi_square_cdf_log");
+
42 
+ + + + +
47  using boost::math::tools::promote_args;
+ +
49  using std::exp;
+
50 
+
51  T_partials_return P(0.0);
+
52 
+
53  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
54  check_not_nan(function, "Random variable", y);
+
55  check_nonnegative(function, "Random variable", y);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Degrees of freedom parameter", nu);
+
59 
+
60  // Wrap arguments in vectors
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_dof> nu_vec(nu);
+
63  size_t N = max_size(y, nu);
+
64 
+
65  OperandsAndPartials<T_y, T_dof> operands_and_partials(y, nu);
+
66 
+
67  // Explicit return for extreme values
+
68  // The gradients are technically ill-defined, but treated as zero
+
69 
+
70  for (size_t i = 0; i < stan::length(y); i++)
+
71  if (value_of(y_vec[i]) == 0)
+
72  return operands_and_partials.value(stan::math::negative_infinity());
+
73 
+
74  // Compute cdf_log and its gradients
+
75  using stan::math::gamma_q;
+
76  using stan::math::digamma;
+
77  using boost::math::tgamma;
+
78  using std::exp;
+
79  using std::pow;
+
80  using std::log;
+
81 
+
82  // Cache a few expensive function calls if nu is a parameter
+ +
84  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
86  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
87 
+ +
89  for (size_t i = 0; i < stan::length(nu); i++) {
+
90  const T_partials_return nu_dbl = value_of(nu_vec[i]);
+
91  gamma_vec[i] = tgamma(0.5 * nu_dbl);
+
92  digamma_vec[i] = digamma(0.5 * nu_dbl);
+
93  }
+
94  }
+
95 
+
96  // Compute vectorized cdf_log and gradient
+
97  for (size_t n = 0; n < N; n++) {
+
98  // Explicit results for extreme values
+
99  // The gradients are technically ill-defined, but treated as zero
+
100  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
101  continue;
+
102  }
+
103 
+
104  // Pull out values
+
105  const T_partials_return y_dbl = value_of(y_vec[n]);
+
106  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
107  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+
108 
+
109  // Compute
+
110  const T_partials_return Pn = gamma_q(0.5 * nu_dbl, 0.5 * y_inv_dbl);
+
111 
+
112  P += log(Pn);
+
113 
+ +
115  operands_and_partials.d_x1[n] += 0.5 * y_inv_dbl * y_inv_dbl
+
116  * exp(-0.5*y_inv_dbl) * pow(0.5*y_inv_dbl, 0.5*nu_dbl-1)
+
117  / tgamma(0.5*nu_dbl) / Pn;
+ +
119  operands_and_partials.d_x2[n]
+
120  += 0.5 * stan::math::grad_reg_inc_gamma(0.5 * nu_dbl,
+
121  0.5 * y_inv_dbl,
+
122  gamma_vec[n],
+
123  digamma_vec[n]) / Pn;
+
124  }
+
125 
+
126  return operands_and_partials.value(P);
+
127  }
+
128  }
+
129 }
+
130 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_dof >::type inv_chi_square_cdf_log(const T_y &y, const T_dof &nu)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__chi__square__log_8hpp.html b/doc/api/html/inv__chi__square__log_8hpp.html new file mode 100644 index 00000000000..5cd06cf1e2a --- /dev/null +++ b/doc/api/html/inv__chi__square__log_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
inv_chi_square_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::inv_chi_square_log (const T_y &y, const T_dof &nu)
 The log of an inverse chi-squared density for y with the specified degrees of freedom parameter. More...
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type stan::math::inv_chi_square_log (const T_y &y, const T_dof &nu)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__chi__square__log_8hpp_source.html b/doc/api/html/inv__chi__square__log_8hpp_source.html new file mode 100644 index 00000000000..be84afbe1ba --- /dev/null +++ b/doc/api/html/inv__chi__square__log_8hpp_source.html @@ -0,0 +1,279 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
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+
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+
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inv_chi_square_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_LOG_HPP
+
3 
+
4 #include <boost/random/chi_squared_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + +
24 #include <cmath>
+
25 
+
26 namespace stan {
+
27 
+
28  namespace math {
+
29 
+
49  template <bool propto,
+
50  typename T_y, typename T_dof>
+
51  typename return_type<T_y, T_dof>::type
+
52  inv_chi_square_log(const T_y& y, const T_dof& nu) {
+
53  static const char* function("stan::math::inv_chi_square_log");
+ +
55  T_partials_return;
+
56 
+
57  // check if any vectors are zero length
+
58  if (!(stan::length(y)
+
59  && stan::length(nu)))
+
60  return 0.0;
+
61 
+ + + + +
66 
+
67  T_partials_return logp(0.0);
+
68  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
69  check_not_nan(function, "Random variable", y);
+
70  check_consistent_sizes(function,
+
71  "Random variable", y,
+
72  "Degrees of freedom parameter", nu);
+
73 
+
74 
+
75  // set up template expressions wrapping scalars into vector views
+
76  VectorView<const T_y> y_vec(y);
+
77  VectorView<const T_dof> nu_vec(nu);
+
78  size_t N = max_size(y, nu);
+
79 
+
80  for (size_t n = 0; n < length(y); n++)
+
81  if (value_of(y_vec[n]) <= 0)
+
82  return LOG_ZERO;
+
83 
+ +
85  using boost::math::lgamma;
+ +
87  using std::log;
+
88 
+ +
90  T_partials_return, T_y> log_y(length(y));
+
91  for (size_t i = 0; i < length(y); i++)
+ +
93  log_y[i] = log(value_of(y_vec[i]));
+
94 
+ +
96  T_partials_return, T_y> inv_y(length(y));
+
97  for (size_t i = 0; i < length(y); i++)
+ +
99  inv_y[i] = 1.0 / value_of(y_vec[i]);
+
100 
+ +
102  T_partials_return, T_dof> lgamma_half_nu(length(nu));
+ +
104  T_partials_return, T_dof>
+
105  digamma_half_nu_over_two(length(nu));
+
106  for (size_t i = 0; i < length(nu); i++) {
+
107  T_partials_return half_nu = 0.5 * value_of(nu_vec[i]);
+ +
109  lgamma_half_nu[i] = lgamma(half_nu);
+ +
111  digamma_half_nu_over_two[i] = digamma(half_nu) * 0.5;
+
112  }
+
113 
+
114  OperandsAndPartials<T_y, T_dof> operands_and_partials(y, nu);
+
115  for (size_t n = 0; n < N; n++) {
+
116  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+
117  const T_partials_return half_nu = 0.5 * nu_dbl;
+
118 
+ +
120  logp += nu_dbl * NEG_LOG_TWO_OVER_TWO - lgamma_half_nu[n];
+ +
122  logp -= (half_nu+1.0) * log_y[n];
+ +
124  logp -= 0.5 * inv_y[n];
+
125 
+ +
127  operands_and_partials.d_x1[n]
+
128  += -(half_nu+1.0) * inv_y[n] + 0.5 * inv_y[n] * inv_y[n];
+
129  }
+ +
131  operands_and_partials.d_x2[n]
+
132  += NEG_LOG_TWO_OVER_TWO - digamma_half_nu_over_two[n]
+
133  - 0.5*log_y[n];
+
134  }
+
135  }
+
136  return operands_and_partials.value(logp);
+
137  }
+
138 
+
139  template <typename T_y, typename T_dof>
+
140  inline
+ +
142  inv_chi_square_log(const T_y& y, const T_dof& nu) {
+
143  return inv_chi_square_log<false>(y, nu);
+
144  }
+
145  }
+
146 }
+
147 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
VectorBuilder allocates type T1 values to be used as intermediate values.
+
return_type< T_y, T_dof >::type inv_chi_square_log(const T_y &y, const T_dof &nu)
The log of an inverse chi-squared density for y with the specified degrees of freedom parameter...
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
const double NEG_LOG_TWO_OVER_TWO
Definition: constants.hpp:191
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/inv__chi__square__rng_8hpp.html b/doc/api/html/inv__chi__square__rng_8hpp.html new file mode 100644 index 00000000000..2c0ff08e25c --- /dev/null +++ b/doc/api/html/inv__chi__square__rng_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_rng.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
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+
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+
inv_chi_square_rng.hpp File Reference
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<class RNG >
double stan::math::inv_chi_square_rng (const double nu, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__chi__square__rng_8hpp_source.html b/doc/api/html/inv__chi__square__rng_8hpp_source.html new file mode 100644 index 00000000000..edc32db01a2 --- /dev/null +++ b/doc/api/html/inv__chi__square__rng_8hpp_source.html @@ -0,0 +1,173 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_chi_square_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+
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inv_chi_square_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_CHI_SQUARE_RNG_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/chi_squared_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <class RNG>
+
27  inline double
+
28  inv_chi_square_rng(const double nu,
+
29  RNG& rng) {
+
30  using boost::variate_generator;
+
31  using boost::random::chi_squared_distribution;
+
32 
+
33  static const char* function("stan::math::inv_chi_square_rng");
+
34 
+ +
36 
+
37  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
38 
+
39  variate_generator<RNG&, chi_squared_distribution<> >
+
40  chi_square_rng(rng, chi_squared_distribution<>(nu));
+
41  return 1 / chi_square_rng();
+
42  }
+
43  }
+
44 }
+
45 #endif
+ +
double chi_square_rng(const double nu, RNG &rng)
+ + + +
double inv_chi_square_rng(const double nu, RNG &rng)
+ + + + + + + + + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__gamma__ccdf__log_8hpp.html b/doc/api/html/inv__gamma__ccdf__log_8hpp.html new file mode 100644 index 00000000000..43914098fa0 --- /dev/null +++ b/doc/api/html/inv__gamma__ccdf__log_8hpp.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_ccdf_log.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::inv_gamma_ccdf_log (const T_y &y, const T_shape &alpha, const T_scale &beta)
 
+
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diff --git a/doc/api/html/inv__gamma__ccdf__log_8hpp_source.html b/doc/api/html/inv__gamma__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..4084a91827f --- /dev/null +++ b/doc/api/html/inv__gamma__ccdf__log_8hpp_source.html @@ -0,0 +1,306 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_ccdf_log.hpp Source File + + + + + + + + + + +
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inv_gamma_ccdf_log.hpp
+
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_CCDF_LOG_HPP
+
3 
+
4 #include <boost/random/gamma_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + + + +
26 #include <cmath>
+
27 #include <limits>
+
28 
+
29 namespace stan {
+
30 
+
31  namespace math {
+
32 
+
33  template <typename T_y, typename T_shape, typename T_scale>
+
34  typename return_type<T_y, T_shape, T_scale>::type
+
35  inv_gamma_ccdf_log(const T_y& y, const T_shape& alpha,
+
36  const T_scale& beta) {
+ +
38  T_partials_return;
+
39 
+
40  // Size checks
+
41  if (!(stan::length(y) && stan::length(alpha) && stan::length(beta)))
+
42  return 0.0;
+
43 
+
44  // Error checks
+
45  static const char* function("stan::math::inv_gamma_ccdf_log");
+
46 
+ + + + + + + +
54  using boost::math::tools::promote_args;
+
55  using std::exp;
+
56 
+
57  T_partials_return P(0.0);
+
58 
+
59  check_positive_finite(function, "Shape parameter", alpha);
+
60  check_positive_finite(function, "Scale parameter", beta);
+
61  check_not_nan(function, "Random variable", y);
+
62  check_nonnegative(function, "Random variable", y);
+
63  check_consistent_sizes(function,
+
64  "Random variable", y,
+
65  "Shape parameter", alpha,
+
66  "Scale Parameter", beta);
+
67 
+
68  // Wrap arguments in vectors
+
69  VectorView<const T_y> y_vec(y);
+
70  VectorView<const T_shape> alpha_vec(alpha);
+
71  VectorView<const T_scale> beta_vec(beta);
+
72  size_t N = max_size(y, alpha, beta);
+
73 
+ +
75  operands_and_partials(y, alpha, beta);
+
76 
+
77  // Explicit return for extreme values
+
78  // The gradients are technically ill-defined, but treated as zero
+
79 
+
80  for (size_t i = 0; i < stan::length(y); i++) {
+
81  if (value_of(y_vec[i]) == 0)
+
82  return operands_and_partials.value(0.0);
+
83  }
+
84 
+
85  // Compute ccdf_log and its gradients
+
86  using stan::math::gamma_q;
+
87  using stan::math::digamma;
+
88  using boost::math::tgamma;
+
89  using std::exp;
+
90  using std::pow;
+
91  using std::log;
+
92 
+
93  // Cache a few expensive function calls if nu is a parameter
+ +
95  T_partials_return, T_shape> gamma_vec(stan::length(alpha));
+ +
97  T_partials_return, T_shape>
+
98  digamma_vec(stan::length(alpha));
+
99 
+ +
101  for (size_t i = 0; i < stan::length(alpha); i++) {
+
102  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
103  gamma_vec[i] = tgamma(alpha_dbl);
+
104  digamma_vec[i] = digamma(alpha_dbl);
+
105  }
+
106  }
+
107 
+
108  // Compute vectorized ccdf_log and gradient
+
109  for (size_t n = 0; n < N; n++) {
+
110  // Explicit results for extreme values
+
111  // The gradients are technically ill-defined, but treated as zero
+
112  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
113  return operands_and_partials.value(stan::math::negative_infinity());
+
114 
+
115  // Pull out values
+
116  const T_partials_return y_dbl = value_of(y_vec[n]);
+
117  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
118  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
119  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
120 
+
121  // Compute
+
122  const T_partials_return Pn = 1.0 - gamma_q(alpha_dbl, beta_dbl
+
123  * y_inv_dbl);
+
124 
+
125  P += log(Pn);
+
126 
+ +
128  operands_and_partials.d_x1[n] -= beta_dbl * y_inv_dbl * y_inv_dbl
+
129  * exp(-beta_dbl * y_inv_dbl) * pow(beta_dbl * y_inv_dbl,
+
130  alpha_dbl-1)
+
131  / tgamma(alpha_dbl) / Pn;
+ +
133  operands_and_partials.d_x2[n]
+
134  -= stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
135  * y_inv_dbl, gamma_vec[n],
+
136  digamma_vec[n]) / Pn;
+ +
138  operands_and_partials.d_x3[n] += y_inv_dbl
+
139  * exp(-beta_dbl * y_inv_dbl)
+
140  * pow(beta_dbl * y_inv_dbl, alpha_dbl-1)
+
141  / tgamma(alpha_dbl) / Pn;
+
142  }
+
143 
+
144  return operands_and_partials.value(P);
+
145  }
+
146  }
+
147 }
+
148 
+
149 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
return_type< T_y, T_shape, T_scale >::type inv_gamma_ccdf_log(const T_y &y, const T_shape &alpha, const T_scale &beta)
+ + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/inv__gamma__cdf_8hpp.html b/doc/api/html/inv__gamma__cdf_8hpp.html new file mode 100644 index 00000000000..89afaea52b3 --- /dev/null +++ b/doc/api/html/inv__gamma__cdf_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_cdf.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+Functions

template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::inv_gamma_cdf (const T_y &y, const T_shape &alpha, const T_scale &beta)
 The CDF of an inverse gamma density for y with the specified shape and scale parameters. More...
 
+
+
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__gamma__cdf_8hpp_source.html b/doc/api/html/inv__gamma__cdf_8hpp_source.html new file mode 100644 index 00000000000..e304473a072 --- /dev/null +++ b/doc/api/html/inv__gamma__cdf_8hpp_source.html @@ -0,0 +1,315 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
inv_gamma_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_CDF_HPP
+
3 
+
4 #include <boost/random/gamma_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + + + +
26 #include <cmath>
+
27 #include <limits>
+
28 
+
29 namespace stan {
+
30 
+
31  namespace math {
+
32 
+
49  template <typename T_y, typename T_shape, typename T_scale>
+
50  typename return_type<T_y, T_shape, T_scale>::type
+
51  inv_gamma_cdf(const T_y& y, const T_shape& alpha, const T_scale& beta) {
+ +
53  T_partials_return;
+
54 
+
55  // Size checks
+
56  if (!(stan::length(y) && stan::length(alpha) && stan::length(beta)))
+
57  return 1.0;
+
58 
+
59  // Error checks
+
60  static const char* function("stan::math::inv_gamma_cdf");
+
61 
+ + + + + + + +
69  using boost::math::tools::promote_args;
+
70  using std::exp;
+
71 
+
72  T_partials_return P(1.0);
+
73 
+
74  check_positive_finite(function, "Shape parameter", alpha);
+
75  check_positive_finite(function, "Scale parameter", beta);
+
76  check_not_nan(function, "Random variable", y);
+
77  check_nonnegative(function, "Random variable", y);
+
78  check_consistent_sizes(function,
+
79  "Random variable", y,
+
80  "Shape parameter", alpha,
+
81  "Scale Parameter", beta);
+
82 
+
83  // Wrap arguments in vectors
+
84  VectorView<const T_y> y_vec(y);
+
85  VectorView<const T_shape> alpha_vec(alpha);
+
86  VectorView<const T_scale> beta_vec(beta);
+
87  size_t N = max_size(y, alpha, beta);
+
88 
+ +
90  operands_and_partials(y, alpha, beta);
+
91 
+
92  // Explicit return for extreme values
+
93  // The gradients are technically ill-defined, but treated as zero
+
94 
+
95  for (size_t i = 0; i < stan::length(y); i++) {
+
96  if (value_of(y_vec[i]) == 0)
+
97  return operands_and_partials.value(0.0);
+
98  }
+
99 
+
100  // Compute CDF and its gradients
+
101  using stan::math::gamma_q;
+
102  using stan::math::digamma;
+
103  using boost::math::tgamma;
+
104  using std::exp;
+
105  using std::pow;
+
106 
+
107  // Cache a few expensive function calls if nu is a parameter
+ +
109  T_partials_return, T_shape>
+
110  gamma_vec(stan::length(alpha));
+ +
112  T_partials_return, T_shape>
+
113  digamma_vec(stan::length(alpha));
+
114 
+ +
116  for (size_t i = 0; i < stan::length(alpha); i++) {
+
117  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
118  gamma_vec[i] = tgamma(alpha_dbl);
+
119  digamma_vec[i] = digamma(alpha_dbl);
+
120  }
+
121  }
+
122 
+
123  // Compute vectorized CDF and gradient
+
124  for (size_t n = 0; n < N; n++) {
+
125  // Explicit results for extreme values
+
126  // The gradients are technically ill-defined, but treated as zero
+
127  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
128  continue;
+
129 
+
130  // Pull out values
+
131  const T_partials_return y_dbl = value_of(y_vec[n]);
+
132  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
133  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
134  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
135 
+
136  // Compute
+
137  const T_partials_return Pn = gamma_q(alpha_dbl, beta_dbl * y_inv_dbl);
+
138 
+
139  P *= Pn;
+
140 
+ +
142  operands_and_partials.d_x1[n] += beta_dbl * y_inv_dbl * y_inv_dbl
+
143  * exp(-beta_dbl * y_inv_dbl) * pow(beta_dbl
+
144  * y_inv_dbl, alpha_dbl-1)
+
145  / tgamma(alpha_dbl) / Pn;
+ +
147  operands_and_partials.d_x2[n]
+
148  += stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
149  * y_inv_dbl, gamma_vec[n],
+
150  digamma_vec[n]) / Pn;
+ +
152  operands_and_partials.d_x3[n] += - y_inv_dbl
+
153  * exp(-beta_dbl * y_inv_dbl)
+
154  * pow(beta_dbl * y_inv_dbl, alpha_dbl-1)
+
155  / tgamma(alpha_dbl) / Pn;
+
156  }
+
157 
+ +
159  for (size_t n = 0; n < stan::length(y); ++n)
+
160  operands_and_partials.d_x1[n] *= P;
+
161  }
+ +
163  for (size_t n = 0; n < stan::length(alpha); ++n)
+
164  operands_and_partials.d_x2[n] *= P;
+
165  }
+ +
167  for (size_t n = 0; n < stan::length(beta); ++n)
+
168  operands_and_partials.d_x3[n] *= P;
+
169  }
+
170 
+
171  return operands_and_partials.value(P);
+
172  }
+
173  }
+
174 }
+
175 
+
176 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
return_type< T_y, T_shape, T_scale >::type inv_gamma_cdf(const T_y &y, const T_shape &alpha, const T_scale &beta)
The CDF of an inverse gamma density for y with the specified shape and scale parameters.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__gamma__cdf__log_8hpp.html b/doc/api/html/inv__gamma__cdf__log_8hpp.html new file mode 100644 index 00000000000..0893ac3033f --- /dev/null +++ b/doc/api/html/inv__gamma__cdf__log_8hpp.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
inv_gamma_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::inv_gamma_cdf_log (const T_y &y, const T_shape &alpha, const T_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__gamma__cdf__log_8hpp_source.html b/doc/api/html/inv__gamma__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..cc3b696d25c --- /dev/null +++ b/doc/api/html/inv__gamma__cdf__log_8hpp_source.html @@ -0,0 +1,305 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
inv_gamma_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_CDF_LOG_HPP
+
3 
+
4 #include <boost/random/gamma_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + + + +
26 #include <cmath>
+
27 #include <limits>
+
28 
+
29 namespace stan {
+
30 
+
31  namespace math {
+
32 
+
33  template <typename T_y, typename T_shape, typename T_scale>
+
34  typename return_type<T_y, T_shape, T_scale>::type
+
35  inv_gamma_cdf_log(const T_y& y, const T_shape& alpha,
+
36  const T_scale& beta) {
+ +
38  T_partials_return;
+
39 
+
40  // Size checks
+
41  if (!(stan::length(y) && stan::length(alpha) && stan::length(beta)))
+
42  return 0.0;
+
43 
+
44  // Error checks
+
45  static const char* function("stan::math::inv_gamma_cdf_log");
+
46 
+ + + + + + + +
54  using boost::math::tools::promote_args;
+
55  using std::exp;
+
56 
+
57  T_partials_return P(0.0);
+
58 
+
59  check_positive_finite(function, "Shape parameter", alpha);
+
60  check_positive_finite(function, "Scale parameter", beta);
+
61  check_not_nan(function, "Random variable", y);
+
62  check_nonnegative(function, "Random variable", y);
+
63  check_consistent_sizes(function,
+
64  "Random variable", y,
+
65  "Shape parameter", alpha,
+
66  "Scale Parameter", beta);
+
67 
+
68  // Wrap arguments in vectors
+
69  VectorView<const T_y> y_vec(y);
+
70  VectorView<const T_shape> alpha_vec(alpha);
+
71  VectorView<const T_scale> beta_vec(beta);
+
72  size_t N = max_size(y, alpha, beta);
+
73 
+ +
75  operands_and_partials(y, alpha, beta);
+
76 
+
77  // Explicit return for extreme values
+
78  // The gradients are technically ill-defined, but treated as zero
+
79 
+
80  for (size_t i = 0; i < stan::length(y); i++) {
+
81  if (value_of(y_vec[i]) == 0)
+
82  return operands_and_partials.value(stan::math::negative_infinity());
+
83  }
+
84 
+
85  // Compute cdf_log and its gradients
+
86  using stan::math::gamma_q;
+
87  using stan::math::digamma;
+
88  using boost::math::tgamma;
+
89  using std::exp;
+
90  using std::pow;
+
91  using std::log;
+
92 
+
93  // Cache a few expensive function calls if nu is a parameter
+ +
95  T_partials_return, T_shape> gamma_vec(stan::length(alpha));
+ +
97  T_partials_return, T_shape>
+
98  digamma_vec(stan::length(alpha));
+
99 
+ +
101  for (size_t i = 0; i < stan::length(alpha); i++) {
+
102  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
103  gamma_vec[i] = tgamma(alpha_dbl);
+
104  digamma_vec[i] = digamma(alpha_dbl);
+
105  }
+
106  }
+
107 
+
108  // Compute vectorized cdf_log and gradient
+
109  for (size_t n = 0; n < N; n++) {
+
110  // Explicit results for extreme values
+
111  // The gradients are technically ill-defined, but treated as zero
+
112  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity())
+
113  continue;
+
114 
+
115  // Pull out values
+
116  const T_partials_return y_dbl = value_of(y_vec[n]);
+
117  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
118  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
119  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
120 
+
121  // Compute
+
122  const T_partials_return Pn = gamma_q(alpha_dbl, beta_dbl * y_inv_dbl);
+
123 
+
124  P += log(Pn);
+
125 
+ +
127  operands_and_partials.d_x1[n] += beta_dbl * y_inv_dbl * y_inv_dbl
+
128  * exp(-beta_dbl * y_inv_dbl) * pow(beta_dbl * y_inv_dbl,
+
129  alpha_dbl-1)
+
130  / tgamma(alpha_dbl) / Pn;
+ +
132  operands_and_partials.d_x2[n]
+
133  += stan::math::grad_reg_inc_gamma(alpha_dbl, beta_dbl
+
134  * y_inv_dbl, gamma_vec[n],
+
135  digamma_vec[n]) / Pn;
+ +
137  operands_and_partials.d_x3[n] += - y_inv_dbl
+
138  * exp(-beta_dbl * y_inv_dbl)
+
139  * pow(beta_dbl * y_inv_dbl, alpha_dbl-1)
+
140  / tgamma(alpha_dbl) / Pn;
+
141  }
+
142 
+
143  return operands_and_partials.value(P);
+
144  }
+
145  }
+
146 }
+
147 
+
148 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
return_type< T_y, T_shape, T_scale >::type inv_gamma_cdf_log(const T_y &y, const T_shape &alpha, const T_scale &beta)
+ + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__gamma__log_8hpp.html b/doc/api/html/inv__gamma__log_8hpp.html new file mode 100644 index 00000000000..04f176c45a9 --- /dev/null +++ b/doc/api/html/inv__gamma__log_8hpp.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
inv_gamma_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::inv_gamma_log (const T_y &y, const T_shape &alpha, const T_scale &beta)
 The log of an inverse gamma density for y with the specified shape and scale parameters. More...
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::inv_gamma_log (const T_y &y, const T_shape &alpha, const T_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__gamma__log_8hpp_source.html b/doc/api/html/inv__gamma__log_8hpp_source.html new file mode 100644 index 00000000000..8218dcd5e3b --- /dev/null +++ b/doc/api/html/inv__gamma__log_8hpp_source.html @@ -0,0 +1,307 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
inv_gamma_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_LOG_HPP
+
3 
+
4 #include <boost/random/gamma_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + + + +
26 #include <cmath>
+
27 
+
28 namespace stan {
+
29 
+
30  namespace math {
+
31 
+
48  template <bool propto,
+
49  typename T_y, typename T_shape, typename T_scale>
+
50  typename return_type<T_y, T_shape, T_scale>::type
+
51  inv_gamma_log(const T_y& y, const T_shape& alpha, const T_scale& beta) {
+
52  static const char* function("stan::math::inv_gamma_log");
+ +
54  T_partials_return;
+
55 
+ + + +
59  using boost::math::tools::promote_args;
+ + +
62 
+
63  // check if any vectors are zero length
+
64  if (!(stan::length(y)
+
65  && stan::length(alpha)
+
66  && stan::length(beta)))
+
67  return 0.0;
+
68 
+
69  // set up return value accumulator
+
70  T_partials_return logp(0.0);
+
71 
+
72  check_not_nan(function, "Random variable", y);
+
73  check_positive_finite(function, "Shape parameter", alpha);
+
74  check_positive_finite(function, "Scale parameter", beta);
+
75  check_consistent_sizes(function,
+
76  "Random variable", y,
+
77  "Shape parameter", alpha,
+
78  "Scale parameter", beta);
+
79 
+
80  // check if no variables are involved and prop-to
+ +
82  return 0.0;
+
83 
+
84  // set up template expressions wrapping scalars into vector views
+
85  VectorView<const T_y> y_vec(y);
+
86  VectorView<const T_shape> alpha_vec(alpha);
+
87  VectorView<const T_scale> beta_vec(beta);
+
88 
+
89  for (size_t n = 0; n < length(y); n++) {
+
90  const T_partials_return y_dbl = value_of(y_vec[n]);
+
91  if (y_dbl <= 0)
+
92  return LOG_ZERO;
+
93  }
+
94 
+
95  size_t N = max_size(y, alpha, beta);
+ +
97  operands_and_partials(y, alpha, beta);
+
98 
+
99  using stan::math::lgamma;
+
100  using stan::math::digamma;
+
101  using std::log;
+
102 
+ +
104  T_partials_return, T_y> log_y(length(y));
+ +
106  T_partials_return, T_y> inv_y(length(y));
+
107  for (size_t n = 0; n < length(y); n++) {
+ +
109  if (value_of(y_vec[n]) > 0)
+
110  log_y[n] = log(value_of(y_vec[n]));
+ +
112  inv_y[n] = 1.0 / value_of(y_vec[n]);
+
113  }
+
114 
+ +
116  T_partials_return, T_shape> lgamma_alpha(length(alpha));
+ +
118  T_partials_return, T_shape> digamma_alpha(length(alpha));
+
119  for (size_t n = 0; n < length(alpha); n++) {
+ +
121  lgamma_alpha[n] = lgamma(value_of(alpha_vec[n]));
+ +
123  digamma_alpha[n] = digamma(value_of(alpha_vec[n]));
+
124  }
+
125 
+ +
127  T_partials_return, T_scale> log_beta(length(beta));
+ +
129  for (size_t n = 0; n < length(beta); n++)
+
130  log_beta[n] = log(value_of(beta_vec[n]));
+
131  }
+
132 
+
133  for (size_t n = 0; n < N; n++) {
+
134  // pull out values of arguments
+
135  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
136  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
137 
+ +
139  logp -= lgamma_alpha[n];
+ +
141  logp += alpha_dbl * log_beta[n];
+ +
143  logp -= (alpha_dbl+1.0) * log_y[n];
+ +
145  logp -= beta_dbl * inv_y[n];
+
146 
+
147  // gradients
+
148  if (!is_constant<typename is_vector<T_y>::type>::value)
+
149  operands_and_partials.d_x1[n]
+
150  += -(alpha_dbl+1) * inv_y[n] + beta_dbl * inv_y[n] * inv_y[n];
+
151  if (!is_constant<typename is_vector<T_shape>::type>::value)
+
152  operands_and_partials.d_x2[n]
+
153  += -digamma_alpha[n] + log_beta[n] - log_y[n];
+
154  if (!is_constant<typename is_vector<T_scale>::type>::value)
+
155  operands_and_partials.d_x3[n] += alpha_dbl / beta_dbl - inv_y[n];
+
156  }
+
157  return operands_and_partials.value(logp);
+
158  }
+
159 
+
160  template <typename T_y, typename T_shape, typename T_scale>
+
161  inline
+ +
163  inv_gamma_log(const T_y& y, const T_shape& alpha, const T_scale& beta) {
+
164  return inv_gamma_log<false>(y, alpha, beta);
+
165  }
+
166  }
+
167 }
+
168 
+
169 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Definition: is_constant.hpp:22
+ +
return_type< T_y, T_shape, T_scale >::type inv_gamma_log(const T_y &y, const T_shape &alpha, const T_scale &beta)
The log of an inverse gamma density for y with the specified shape and scale parameters.
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/inv__gamma__rng_8hpp.html b/doc/api/html/inv__gamma__rng_8hpp.html new file mode 100644 index 00000000000..35f6de3099e --- /dev/null +++ b/doc/api/html/inv__gamma__rng_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_rng.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/inv__gamma__rng_8hpp_source.html b/doc/api/html/inv__gamma__rng_8hpp_source.html new file mode 100644 index 00000000000..cc0316e81e3 --- /dev/null +++ b/doc/api/html/inv__gamma__rng_8hpp_source.html @@ -0,0 +1,180 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/inv_gamma_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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+
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+
+
+
inv_gamma_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_INV_GAMMA_RNG_HPP
+
3 
+ + + + + + + + + + + + + + + + + +
21 #include <boost/random/gamma_distribution.hpp>
+
22 #include <boost/random/variate_generator.hpp>
+
23 
+
24 namespace stan {
+
25 
+
26  namespace math {
+
27 
+
28  template <class RNG>
+
29  inline double
+
30  inv_gamma_rng(const double alpha,
+
31  const double beta,
+
32  RNG& rng) {
+
33  using boost::variate_generator;
+
34  using boost::random::gamma_distribution;
+
35 
+
36  static const char* function("stan::math::inv_gamma_rng");
+
37 
+ +
39 
+
40  check_positive_finite(function, "Shape parameter", alpha);
+
41  check_positive_finite(function, "Scale parameter", beta);
+
42 
+
43  variate_generator<RNG&, gamma_distribution<> >
+
44  gamma_rng(rng, gamma_distribution<>(alpha, 1 / beta));
+
45  return 1 / gamma_rng();
+
46  }
+
47  }
+
48 }
+
49 
+
50 #endif
+ +
double gamma_rng(const double alpha, const double beta, RNG &rng)
Definition: gamma_rng.hpp:30
+ + + + + + + + + +
double inv_gamma_rng(const double alpha, const double beta, RNG &rng)
+ + + + + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/inv__wishart__log_8hpp.html b/doc/api/html/inv__wishart__log_8hpp.html new file mode 100644 index 00000000000..3d8cedaac9f --- /dev/null +++ b/doc/api/html/inv__wishart__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/inv_wishart_log.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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inv_wishart_log.hpp File Reference
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+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_dof , typename T_scale >
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type stan::math::inv_wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
 The log of the Inverse-Wishart density for the given W, degrees of freedom, and scale matrix. More...
 
template<typename T_y , typename T_dof , typename T_scale >
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type stan::math::inv_wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
 
+
+
+
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diff --git a/doc/api/html/inv__wishart__log_8hpp_source.html b/doc/api/html/inv__wishart__log_8hpp_source.html new file mode 100644 index 00000000000..4932b80f99b --- /dev/null +++ b/doc/api/html/inv__wishart__log_8hpp_source.html @@ -0,0 +1,241 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/inv_wishart_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+ + +
+
+
+
inv_wishart_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_INV_WISHART_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_INV_WISHART_LOG_HPP
+
3 
+ + + + + + + +
11 
+ + + + +
16 
+
17 namespace stan {
+
18  namespace math {
+
19  // InvWishart(Sigma|n, Omega) [W, S symmetric, non-neg, definite;
+
20  // W.dims() = S.dims();
+
21  // n > S.rows() - 1]
+
49  template <bool propto,
+
50  typename T_y, typename T_dof, typename T_scale>
+
51  typename boost::math::tools::promote_args<T_y, T_dof, T_scale>::type
+
52  inv_wishart_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& W,
+
53  const T_dof& nu,
+
54  const Eigen::Matrix
+
55  <T_scale, Eigen::Dynamic, Eigen::Dynamic>& S) {
+
56  static const char* function("stan::math::inv_wishart_log");
+
57 
+
58  using boost::math::tools::promote_args;
+
59  using Eigen::Dynamic;
+
60  using Eigen::Matrix;
+ + + + +
65 
+ +
67  = S.rows();
+
68  typename promote_args<T_y, T_dof, T_scale>::type lp(0.0);
+
69 
+
70  check_greater(function, "Degrees of freedom parameter", nu, k-1);
+
71  check_square(function, "random variable", W);
+
72  check_square(function, "scale parameter", S);
+
73  check_size_match(function,
+
74  "Rows of random variable", W.rows(),
+
75  "columns of scale parameter", S.rows());
+
76 
+
77  // FIXME: domain checks
+
78 
+
79  using stan::math::lmgamma;
+ + +
82  using stan::math::trace;
+ + +
85 
+ +
87  check_ldlt_factor(function, "LDLT_Factor of random variable", ldlt_W);
+ +
89  check_ldlt_factor(function, "LDLT_Factor of scale parameter", ldlt_S);
+
90 
+ +
92  lp -= lmgamma(k, 0.5 * nu);
+ +
94  lp += 0.5 * nu * log_determinant_ldlt(ldlt_S);
+
95  }
+ +
97  lp -= 0.5 * (nu + k + 1.0) * log_determinant_ldlt(ldlt_W);
+
98  }
+ +
100  // L = crossprod(mdivide_left_tri_low(L));
+
101  // Eigen::Matrix<T_y, Eigen::Dynamic, 1> W_inv_vec = Eigen::Map<
+
102  // const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic> >(
+
103  // &L(0), L.size(), 1);
+
104  // Eigen::Matrix<T_scale, Eigen::Dynamic, 1> S_vec = Eigen::Map<
+
105  // const Eigen::Matrix<T_scale, Eigen::Dynamic, Eigen::Dynamic> >(
+
106  // &S(0), S.size(), 1);
+
107  // lp -= 0.5 * dot_product(S_vec, W_inv_vec); // trace(S * W^-1)
+
108  Eigen::Matrix<typename promote_args<T_y, T_scale>::type,
+
109  Eigen::Dynamic, Eigen::Dynamic>
+
110  Winv_S(mdivide_left_ldlt
+
111  (ldlt_W,
+
112  static_cast<Eigen::Matrix
+
113  <T_scale, Eigen::Dynamic, Eigen::Dynamic> >
+
114  (S.template selfadjointView<Eigen::Lower>())));
+
115  lp -= 0.5*trace(Winv_S);
+
116  }
+ +
118  lp += nu * k * NEG_LOG_TWO_OVER_TWO;
+
119  return lp;
+
120  }
+
121 
+
122  template <typename T_y, typename T_dof, typename T_scale>
+
123  inline
+
124  typename boost::math::tools::promote_args<T_y, T_dof, T_scale>::type
+
125  inv_wishart_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& W,
+
126  const T_dof& nu,
+
127  const Eigen::Matrix
+
128  <T_scale, Eigen::Dynamic, Eigen::Dynamic>& S) {
+
129  return inv_wishart_log<false>(W, nu, S);
+
130  }
+
131 
+
132  }
+
133 }
+
134 #endif
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + + +
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt(const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
Returns the solution of the system Ax=b given an LDLT_factor of A.
+
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type inv_wishart_log(const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
The log of the Inverse-Wishart density for the given W, degrees of freedom, and scale matrix...
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ + +
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+
const double NEG_LOG_TWO_OVER_TWO
Definition: constants.hpp:191
+ +
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+
fvar< typename stan::return_type< T, int >::type > lmgamma(int x1, const fvar< T > &x2)
Definition: lmgamma.hpp:16
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.
+ + +
+
+
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diff --git a/doc/api/html/inv__wishart__rng_8hpp.html b/doc/api/html/inv__wishart__rng_8hpp.html new file mode 100644 index 00000000000..ec582a47b96 --- /dev/null +++ b/doc/api/html/inv__wishart__rng_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/inv_wishart_rng.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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template<class RNG >
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > stan::math::inv_wishart_rng (const double nu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
 
+
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diff --git a/doc/api/html/inv__wishart__rng_8hpp_source.html b/doc/api/html/inv__wishart__rng_8hpp_source.html new file mode 100644 index 00000000000..7b87f907a77 --- /dev/null +++ b/doc/api/html/inv__wishart__rng_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/inv_wishart_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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inv_wishart_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_INV_WISHART_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_INV_WISHART_RNG_HPP
+
3 
+ + + + + + + +
11 
+ + + +
15 
+
16 namespace stan {
+
17  namespace math {
+
18 
+
19  template <class RNG>
+
20  inline Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>
+
21  inv_wishart_rng(const double nu,
+
22  const Eigen::Matrix
+
23  <double, Eigen::Dynamic, Eigen::Dynamic>& S,
+
24  RNG& rng) {
+
25  static const char* function("stan::math::inv_wishart_rng");
+
26 
+ + +
29  using Eigen::MatrixXd;
+ +
31 
+
32  typename index_type<MatrixXd>::type k = S.rows();
+
33 
+
34  check_greater(function, "Degrees of freedom parameter", nu, k-1);
+
35  check_square(function, "scale parameter", S);
+
36 
+
37  MatrixXd S_inv = MatrixXd::Identity(k, k);
+
38  S_inv = S.ldlt().solve(S_inv);
+
39 
+
40  return wishart_rng(nu, S_inv, rng).inverse();
+
41  }
+
42  }
+
43 }
+
44 #endif
+ + + + + + +
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > wishart_rng(const double nu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
Definition: wishart_rng.hpp:29
+ + +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > inv_wishart_rng(const double nu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
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diff --git a/doc/api/html/invalid__argument_8hpp.html b/doc/api/html/invalid__argument_8hpp.html new file mode 100644 index 00000000000..4c4f2ec46e6 --- /dev/null +++ b/doc/api/html/invalid__argument_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/invalid_argument.hpp File Reference + + + + + + + + + + +
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#include <typeinfo>
+#include <string>
+#include <sstream>
+#include <stdexcept>
+
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template<typename T >
void stan::math::invalid_argument (const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
 Throw an invalid_argument exception with a consistently formatted message. More...
 
template<typename T >
void stan::math::invalid_argument (const char *function, const char *name, const T &y, const char *msg1)
 Throw an invalid_argument exception with a consistently formatted message. More...
 
+
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diff --git a/doc/api/html/invalid__argument_8hpp_source.html b/doc/api/html/invalid__argument_8hpp_source.html new file mode 100644 index 00000000000..98f39484bfb --- /dev/null +++ b/doc/api/html/invalid__argument_8hpp_source.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/invalid_argument.hpp Source File + + + + + + + + + + +
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invalid_argument.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_INVALID_ARGUMENT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_INVALID_ARGUMENT_HPP
+
3 
+
4 #include <typeinfo>
+
5 #include <string>
+
6 #include <sstream>
+
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
30  template <typename T>
+
31  inline void invalid_argument(const char* function,
+
32  const char* name,
+
33  const T& y,
+
34  const char* msg1,
+
35  const char* msg2) {
+
36  std::ostringstream message;
+
37 
+
38  message << function << ": "
+
39  << name << " "
+
40  << msg1
+
41  << y
+
42  << msg2;
+
43 
+
44  throw std::invalid_argument(message.str());
+
45  }
+
46 
+
65  template <typename T>
+
66  inline void invalid_argument(const char* function,
+
67  const char* name,
+
68  const T& y,
+
69  const char* msg1) {
+
70  invalid_argument(function, name, y, msg1, "");
+
71  }
+
72 
+
73  }
+
74 }
+
75 #endif
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1)
Throw an invalid_argument exception with a consistently formatted message.
+ +
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
+
+
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diff --git a/doc/api/html/invalid__argument__vec_8hpp.html b/doc/api/html/invalid__argument__vec_8hpp.html new file mode 100644 index 00000000000..72800d1387b --- /dev/null +++ b/doc/api/html/invalid__argument__vec_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/invalid_argument_vec.hpp File Reference + + + + + + + + + + +
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template<typename T >
void stan::math::invalid_argument_vec (const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
 Throw an invalid argument exception with a consistently formatted message. More...
 
template<typename T >
void stan::math::invalid_argument_vec (const char *function, const char *name, const T &y, const size_t i, const char *msg)
 Throw an invalid argument exception with a consistently formatted message. More...
 
+
+
+
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diff --git a/doc/api/html/invalid__argument__vec_8hpp_source.html b/doc/api/html/invalid__argument__vec_8hpp_source.html new file mode 100644 index 00000000000..215e8438cf8 --- /dev/null +++ b/doc/api/html/invalid__argument__vec_8hpp_source.html @@ -0,0 +1,159 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/invalid_argument_vec.hpp Source File + + + + + + + + + + +
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invalid_argument_vec.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_ERR_INVALID_ARGUMENT_VEC_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_INVALID_ARGUMENT_VEC_HPP
+
3 
+ + + + +
8 #include <sstream>
+
9 #include <string>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
37  template <typename T>
+
38  inline void invalid_argument_vec(const char* function,
+
39  const char* name,
+
40  const T& y,
+
41  const size_t i,
+
42  const char* msg1,
+
43  const char* msg2) {
+
44  std::ostringstream vec_name_stream;
+
45  vec_name_stream << name
+
46  << "[" << stan::error_index::value + i << "]";
+
47  std::string vec_name(vec_name_stream.str());
+
48  invalid_argument(function, vec_name.c_str(),
+
49  stan::get(y, i), msg1, msg2);
+
50  }
+
51 
+
73  template <typename T>
+
74  inline void invalid_argument_vec(const char* function,
+
75  const char* name,
+
76  const T& y,
+
77  const size_t i,
+
78  const char* msg) {
+
79  invalid_argument_vec(function, name, y, i, msg, "");
+
80  }
+
81 
+
82  }
+
83 }
+
84 #endif
+ + + + +
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
T get(const std::vector< T > &x, size_t n)
Definition: get.hpp:10
+ + +
void invalid_argument_vec(const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
Throw an invalid argument exception with a consistently formatted message.
+
+
+
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diff --git a/doc/api/html/inverse__softmax_8hpp.html b/doc/api/html/inverse__softmax_8hpp.html new file mode 100644 index 00000000000..cf0b2da7678 --- /dev/null +++ b/doc/api/html/inverse__softmax_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inverse_softmax.hpp File Reference + + + + + + + + + + +
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inverse_softmax.hpp File Reference
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#include <boost/math/tools/promotion.hpp>
+#include <boost/throw_exception.hpp>
+#include <stdexcept>
+
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 Matrices and templated mathematical functions.
 
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template<typename Vector >
void stan::math::inverse_softmax (const Vector &simplex, Vector &y)
 Writes the inverse softmax of the simplex argument into the second argument. More...
 
+
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diff --git a/doc/api/html/inverse__softmax_8hpp_source.html b/doc/api/html/inverse__softmax_8hpp_source.html new file mode 100644 index 00000000000..968d46f559a --- /dev/null +++ b/doc/api/html/inverse__softmax_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inverse_softmax.hpp Source File + + + + + + + + + + +
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inverse_softmax.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INVERSE_SOFTMAX_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INVERSE_SOFTMAX_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 #include <boost/throw_exception.hpp>
+
6 #include <stdexcept>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
33  template <typename Vector>
+
34  void inverse_softmax(const Vector& simplex, Vector& y) {
+
35  using std::log;
+
36  if (simplex.size() != y.size())
+
37  BOOST_THROW_EXCEPTION(std::invalid_argument
+
38  ("simplex.size() != y.size()"));
+
39  for (size_t i = 0; i < simplex.size(); ++i)
+
40  y[i] = log(simplex[i]);
+
41  }
+
42 
+
43  }
+
44 }
+
45 
+
46 #endif
+
void inverse_softmax(const Vector &simplex, Vector &y)
Writes the inverse softmax of the simplex argument into the second argument.
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+
+
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diff --git a/doc/api/html/inverse__spd_8hpp.html b/doc/api/html/inverse__spd_8hpp.html new file mode 100644 index 00000000000..cb34e7765f9 --- /dev/null +++ b/doc/api/html/inverse__spd_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/inverse_spd.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::inverse_spd (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Returns the inverse of the specified symmetric, pos/neg-definite matrix. More...
 
+
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diff --git a/doc/api/html/inverse__spd_8hpp_source.html b/doc/api/html/inverse__spd_8hpp_source.html new file mode 100644 index 00000000000..1ed332f04c2 --- /dev/null +++ b/doc/api/html/inverse__spd_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/inverse_spd.hpp Source File + + + + + + + + + + +
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inverse_spd.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_INVERSE_SPD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_INVERSE_SPD_HPP
+
3 
+ + + +
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
17  template <typename T>
+
18  inline
+
19  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
20  inverse_spd(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
21  using Eigen::Dynamic;
+
22  using Eigen::LDLT;
+
23  using Eigen::Matrix;
+
24  stan::math::check_square("inverse_spd", "m", m);
+
25  stan::math::check_symmetric("inverse_spd", "m", m);
+
26  Matrix<T, Dynamic, Dynamic> mmt = T(0.5) * (m + m.transpose());
+
27  // mmt = T(0.5) * mmt;
+
28  LDLT<Matrix<T, Dynamic, Dynamic> > ldlt(mmt); // 0.5*(m+m.transpose()));
+
29  if (ldlt.info() != Eigen::Success)
+
30  throw std::domain_error("Error in inverse_spd, LDLT "
+
31  "factorization failed");
+
32  if (!ldlt.isPositive())
+
33  throw std::domain_error("Error in inverse_spd, matrix "
+
34  "not positive definite");
+
35  Matrix<T, Dynamic, 1> diag_ldlt = ldlt.vectorD();
+
36  for (int i = 0; i < diag_ldlt.size(); ++i)
+
37  if (diag_ldlt(i) <= 0)
+
38  throw std::domain_error("Error in inverse_spd, matrix "
+
39  "not positive definite");
+
40  return ldlt.solve(Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
41  ::Identity(m.rows(), m.cols()));
+
42  }
+
43 
+
44  }
+
45 }
+
46 #endif
+ + +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > inverse_spd(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the inverse of the specified symmetric, pos/neg-definite matrix.
Definition: inverse_spd.hpp:20
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
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diff --git a/doc/api/html/is__constant_8hpp.html b/doc/api/html/is__constant_8hpp.html new file mode 100644 index 00000000000..c8066856e64 --- /dev/null +++ b/doc/api/html/is__constant_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_constant.hpp File Reference + + + + + + + + + + +
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#include <boost/type_traits/is_convertible.hpp>
+
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struct  stan::is_constant< T >
 Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the C++ const sense). More...
 
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diff --git a/doc/api/html/is__constant_8hpp_source.html b/doc/api/html/is__constant_8hpp_source.html new file mode 100644 index 00000000000..8b3a049d848 --- /dev/null +++ b/doc/api/html/is__constant_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_constant.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_IS_CONSTANT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_IS_CONSTANT_HPP
+
3 
+
4 #include <boost/type_traits/is_convertible.hpp>
+
5 
+
6 namespace stan {
+
7 
+
21  template <typename T>
+
22  struct is_constant {
+
27  enum { value = boost::is_convertible<T, double>::value };
+
28  };
+
29 
+
30 }
+
31 #endif
+
32 
+
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Definition: is_constant.hpp:22
+ + +
+
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diff --git a/doc/api/html/is__var__or__arithmetic_8hpp.html b/doc/api/html/is__var__or__arithmetic_8hpp.html new file mode 100644 index 00000000000..97daec0f50d --- /dev/null +++ b/doc/api/html/is__var__or__arithmetic_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_var_or_arithmetic.hpp File Reference + + + + + + + + + + +
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is_var_or_arithmetic.hpp File Reference
+
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#include <stan/math/prim/scal/meta/is_var.hpp>
+#include <stan/math/prim/scal/meta/scalar_type.hpp>
+#include <boost/type_traits/is_arithmetic.hpp>
+
+

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struct  stan::is_var_or_arithmetic< T1, T2, T3, T4, T5, T6 >
 
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diff --git a/doc/api/html/is__var__or__arithmetic_8hpp_source.html b/doc/api/html/is__var__or__arithmetic_8hpp_source.html new file mode 100644 index 00000000000..f43b4001902 --- /dev/null +++ b/doc/api/html/is__var__or__arithmetic_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_var_or_arithmetic.hpp Source File + + + + + + + + + + +
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is_var_or_arithmetic.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_META_IS_VAR_OR_ARITHMETIC_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_IS_VAR_OR_ARITHMETIC_HPP
+
3 
+ + +
6 #include <boost/type_traits/is_arithmetic.hpp>
+
7 
+
8 namespace stan {
+
9 
+
10  template <typename T1,
+
11  typename T2 = double,
+
12  typename T3 = double,
+
13  typename T4 = double,
+
14  typename T5 = double,
+
15  typename T6 = double>
+ +
17  enum {
+ + +
20  || boost::is_arithmetic<typename scalar_type<T1>::type>::value)
+
21  && (is_var<typename scalar_type<T2>::type>::value
+
22  || boost::is_arithmetic<typename scalar_type<T2>::type>::value)
+ +
24  || boost::is_arithmetic<typename scalar_type<T3>::type>::value)
+
25  && (is_var<typename scalar_type<T4>::type>::value
+
26  || boost::is_arithmetic<typename scalar_type<T4>::type>::value)
+ +
28  || boost::is_arithmetic<typename scalar_type<T5>::type>::value)
+
29  && (is_var<typename scalar_type<T6>::type>::value
+
30  || boost::is_arithmetic<typename scalar_type<T6>::type>::value)
+
31  };
+
32  };
+
33 
+
34 }
+
35 #endif
+
36 
+ + + +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
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0},disableSelection:function(){return this.bind((a.support.selectstart?"selectstart":"mousedown")+".ui-disableSelection",function(e){e.preventDefault()})},enableSelection:function(){return this.unbind(".ui-disableSelection")}});a.each(["Width","Height"],function(g,e){var f=e==="Width"?["Left","Right"]:["Top","Bottom"],h=e.toLowerCase(),k={innerWidth:a.fn.innerWidth,innerHeight:a.fn.innerHeight,outerWidth:a.fn.outerWidth,outerHeight:a.fn.outerHeight};function j(m,l,i,n){a.each(f,function(){l-=parseFloat(a.curCSS(m,"padding"+this,true))||0;if(i){l-=parseFloat(a.curCSS(m,"border"+this+"Width",true))||0}if(n){l-=parseFloat(a.curCSS(m,"margin"+this,true))||0}});return l}a.fn["inner"+e]=function(i){if(i===d){return k["inner"+e].call(this)}return this.each(function(){a(this).css(h,j(this,i)+"px")})};a.fn["outer"+e]=function(i,l){if(typeof i!=="number"){return k["outer"+e].call(this,i)}return this.each(function(){a(this).css(h,j(this,i,true,l)+"px")})}});function c(g,e){var j=g.nodeName.toLowerCase();if("area"===j){var i=g.parentNode,h=i.name,f;if(!g.href||!h||i.nodeName.toLowerCase()!=="map"){return false}f=a("img[usemap=#"+h+"]")[0];return !!f&&b(f)}return(/input|select|textarea|button|object/.test(j)?!g.disabled:"a"==j?g.href||e:e)&&b(g)}function b(e){return !a(e).parents().andSelf().filter(function(){return a.curCSS(this,"visibility")==="hidden"||a.expr.filters.hidden(this)}).length}a.extend(a.expr[":"],{data:function(g,f,e){return !!a.data(g,e[3])},focusable:function(e){return c(e,!isNaN(a.attr(e,"tabindex")))},tabbable:function(g){var e=a.attr(g,"tabindex"),f=isNaN(e);return(f||e>=0)&&c(g,!f)}});a(function(){var e=document.body,f=e.appendChild(f=document.createElement("div"));f.offsetHeight;a.extend(f.style,{minHeight:"100px",height:"auto",padding:0,borderWidth:0});a.support.minHeight=f.offsetHeight===100;a.support.selectstart="onselectstart" in f;e.removeChild(f).style.display="none"});a.extend(a.ui,{plugin:{add:function(f,g,j){var h=a.ui[f].prototype;for(var e in j){h.plugins[e]=h.plugins[e]||[];h.plugins[e].push([g,j[e]])}},call:function(e,g,f){var j=e.plugins[g];if(!j||!e.element[0].parentNode){return}for(var h=0;h0){return true}h[e]=1;g=(h[e]>0);h[e]=0;return g},isOverAxis:function(f,e,g){return(f>e)&&(f<(e+g))},isOver:function(j,f,i,h,e,g){return a.ui.isOverAxis(j,i,e)&&a.ui.isOverAxis(f,h,g)}})})(jQuery);/*! + * jQuery UI Widget 1.8.18 + * + * Copyright 2011, AUTHORS.txt (http://jqueryui.com/about) + * Dual licensed under the MIT or GPL Version 2 licenses. + * http://jquery.org/license + * + * http://docs.jquery.com/UI/Widget + */ +(function(b,d){if(b.cleanData){var c=b.cleanData;b.cleanData=function(f){for(var g=0,h;(h=f[g])!=null;g++){try{b(h).triggerHandler("remove")}catch(j){}}c(f)}}else{var a=b.fn.remove;b.fn.remove=function(e,f){return this.each(function(){if(!f){if(!e||b.filter(e,[this]).length){b("*",this).add([this]).each(function(){try{b(this).triggerHandler("remove")}catch(g){}})}}return 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http://jquery.org/license + * + * http://docs.jquery.com/UI/Mouse + * + * Depends: + * jquery.ui.widget.js + */ +(function(b,c){var a=false;b(document).mouseup(function(d){a=false});b.widget("ui.mouse",{options:{cancel:":input,option",distance:1,delay:0},_mouseInit:function(){var d=this;this.element.bind("mousedown."+this.widgetName,function(e){return d._mouseDown(e)}).bind("click."+this.widgetName,function(e){if(true===b.data(e.target,d.widgetName+".preventClickEvent")){b.removeData(e.target,d.widgetName+".preventClickEvent");e.stopImmediatePropagation();return false}});this.started=false},_mouseDestroy:function(){this.element.unbind("."+this.widgetName)},_mouseDown:function(f){if(a){return}(this._mouseStarted&&this._mouseUp(f));this._mouseDownEvent=f;var e=this,g=(f.which==1),d=(typeof this.options.cancel=="string"&&f.target.nodeName?b(f.target).closest(this.options.cancel).length:false);if(!g||d||!this._mouseCapture(f)){return true}this.mouseDelayMet=!this.options.delay;if(!this.mouseDelayMet){this._mouseDelayTimer=setTimeout(function(){e.mouseDelayMet=true},this.options.delay)}if(this._mouseDistanceMet(f)&&this._mouseDelayMet(f)){this._mouseStarted=(this._mouseStart(f)!==false);if(!this._mouseStarted){f.preventDefault();return true}}if(true===b.data(f.target,this.widgetName+".preventClickEvent")){b.removeData(f.target,this.widgetName+".preventClickEvent")}this._mouseMoveDelegate=function(h){return e._mouseMove(h)};this._mouseUpDelegate=function(h){return e._mouseUp(h)};b(document).bind("mousemove."+this.widgetName,this._mouseMoveDelegate).bind("mouseup."+this.widgetName,this._mouseUpDelegate);f.preventDefault();a=true;return true},_mouseMove:function(d){if(b.browser.msie&&!(document.documentMode>=9)&&!d.button){return this._mouseUp(d)}if(this._mouseStarted){this._mouseDrag(d);return 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true}})})(jQuery);(function(c,d){c.widget("ui.resizable",c.ui.mouse,{widgetEventPrefix:"resize",options:{alsoResize:false,animate:false,animateDuration:"slow",animateEasing:"swing",aspectRatio:false,autoHide:false,containment:false,ghost:false,grid:false,handles:"e,s,se",helper:false,maxHeight:null,maxWidth:null,minHeight:10,minWidth:10,zIndex:1000},_create:function(){var f=this,k=this.options;this.element.addClass("ui-resizable");c.extend(this,{_aspectRatio:!!(k.aspectRatio),aspectRatio:k.aspectRatio,originalElement:this.element,_proportionallyResizeElements:[],_helper:k.helper||k.ghost||k.animate?k.helper||"ui-resizable-helper":null});if(this.element[0].nodeName.match(/canvas|textarea|input|select|button|img/i)){this.element.wrap(c('
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');if(/sw|se|ne|nw/.test(j)){h.css({zIndex:++k.zIndex})}if("se"==j){h.addClass("ui-icon ui-icon-gripsmall-diagonal-se")}this.handles[j]=".ui-resizable-"+j;this.element.append(h)}}this._renderAxis=function(q){q=q||this.element;for(var n in this.handles){if(this.handles[n].constructor==String){this.handles[n]=c(this.handles[n],this.element).show()}if(this.elementIsWrapper&&this.originalElement[0].nodeName.match(/textarea|input|select|button/i)){var o=c(this.handles[n],this.element),p=0;p=/sw|ne|nw|se|n|s/.test(n)?o.outerHeight():o.outerWidth();var m=["padding",/ne|nw|n/.test(n)?"Top":/se|sw|s/.test(n)?"Bottom":/^e$/.test(n)?"Right":"Left"].join("");q.css(m,p);this._proportionallyResize()}if(!c(this.handles[n]).length){continue}}};this._renderAxis(this.element);this._handles=c(".ui-resizable-handle",this.element).disableSelection();this._handles.mouseover(function(){if(!f.resizing){if(this.className){var i=this.className.match(/ui-resizable-(se|sw|ne|nw|n|e|s|w)/i)}f.axis=i&&i[1]?i[1]:"se"}});if(k.autoHide){this._handles.hide();c(this.element).addClass("ui-resizable-autohide").hover(function(){if(k.disabled){return}c(this).removeClass("ui-resizable-autohide");f._handles.show()},function(){if(k.disabled){return}if(!f.resizing){c(this).addClass("ui-resizable-autohide");f._handles.hide()}})}this._mouseInit()},destroy:function(){this._mouseDestroy();var e=function(g){c(g).removeClass("ui-resizable ui-resizable-disabled ui-resizable-resizing").removeData("resizable").unbind(".resizable").find(".ui-resizable-handle").remove()};if(this.elementIsWrapper){e(this.element);var f=this.element;f.after(this.originalElement.css({position:f.css("position"),width:f.outerWidth(),height:f.outerHeight(),top:f.css("top"),left:f.css("left")})).remove()}this.originalElement.css("resize",this.originalResizeStyle);e(this.originalElement);return this},_mouseCapture:function(f){var g=false;for(var e in this.handles){if(c(this.handles[e])[0]==f.target){g=true}}return !this.options.disabled&&g},_mouseStart:function(g){var j=this.options,f=this.element.position(),e=this.element;this.resizing=true;this.documentScroll={top:c(document).scrollTop(),left:c(document).scrollLeft()};if(e.is(".ui-draggable")||(/absolute/).test(e.css("position"))){e.css({position:"absolute",top:f.top,left:f.left})}this._renderProxy();var k=b(this.helper.css("left")),h=b(this.helper.css("top"));if(j.containment){k+=c(j.containment).scrollLeft()||0;h+=c(j.containment).scrollTop()||0}this.offset=this.helper.offset();this.position={left:k,top:h};this.size=this._helper?{width:e.outerWidth(),height:e.outerHeight()}:{width:e.width(),height:e.height()};this.originalSize=this._helper?{width:e.outerWidth(),height:e.outerHeight()}:{width:e.width(),height:e.height()};this.originalPosition={left:k,top:h};this.sizeDiff={width:e.outerWidth()-e.width(),height:e.outerHeight()-e.height()};this.originalMousePosition={left:g.pageX,top:g.pageY};this.aspectRatio=(typeof j.aspectRatio=="number")?j.aspectRatio:((this.originalSize.width/this.originalSize.height)||1);var i=c(".ui-resizable-"+this.axis).css("cursor");c("body").css("cursor",i=="auto"?this.axis+"-resize":i);e.addClass("ui-resizable-resizing");this._propagate("start",g);return true},_mouseDrag:function(e){var h=this.helper,g=this.options,m={},q=this,j=this.originalMousePosition,n=this.axis;var r=(e.pageX-j.left)||0,p=(e.pageY-j.top)||0;var i=this._change[n];if(!i){return false}var l=i.apply(this,[e,r,p]),k=c.browser.msie&&c.browser.version<7,f=this.sizeDiff;this._updateVirtualBoundaries(e.shiftKey);if(this._aspectRatio||e.shiftKey){l=this._updateRatio(l,e)}l=this._respectSize(l,e);this._propagate("resize",e);h.css({top:this.position.top+"px",left:this.position.left+"px",width:this.size.width+"px",height:this.size.height+"px"});if(!this._helper&&this._proportionallyResizeElements.length){this._proportionallyResize()}this._updateCache(l);this._trigger("resize",e,this.ui());return false},_mouseStop:function(h){this.resizing=false;var i=this.options,m=this;if(this._helper){var g=this._proportionallyResizeElements,e=g.length&&(/textarea/i).test(g[0].nodeName),f=e&&c.ui.hasScroll(g[0],"left")?0:m.sizeDiff.height,k=e?0:m.sizeDiff.width;var n={width:(m.helper.width()-k),height:(m.helper.height()-f)},j=(parseInt(m.element.css("left"),10)+(m.position.left-m.originalPosition.left))||null,l=(parseInt(m.element.css("top"),10)+(m.position.top-m.originalPosition.top))||null;if(!i.animate){this.element.css(c.extend(n,{top:l,left:j}))}m.helper.height(m.size.height);m.helper.width(m.size.width);if(this._helper&&!i.animate){this._proportionallyResize()}}c("body").css("cursor","auto");this.element.removeClass("ui-resizable-resizing");this._propagate("stop",h);if(this._helper){this.helper.remove()}return false},_updateVirtualBoundaries:function(g){var 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+ +
+
lb_constrain.hpp File Reference
+
+
+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/fun/identity_constrain.hpp>
+#include <cmath>
+#include <limits>
+
+

Go to the source code of this file.

+
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + +

+Functions

template<typename T , typename TL >
stan::math::lb_constrain (const T x, const TL lb)
 Return the lower-bounded value for the specified unconstrained input and specified lower bound. More...
 
template<typename T , typename TL >
boost::math::tools::promote_args< T, TL >::type stan::math::lb_constrain (const T x, const TL lb, T &lp)
 Return the lower-bounded value for the speicifed unconstrained input and specified lower bound, incrementing the specified reference with the log absolute Jacobian determinant of the transform. More...
 
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lb__constrain_8hpp_source.html b/doc/api/html/lb__constrain_8hpp_source.html new file mode 100644 index 00000000000..9e526547de7 --- /dev/null +++ b/doc/api/html/lb__constrain_8hpp_source.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lb_constrain.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
lb_constrain.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LB_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LB_CONSTRAIN_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ +
6 #include <cmath>
+
7 #include <limits>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12  // LOWER BOUND
+
13 
+
33  template <typename T, typename TL>
+
34  inline
+
35  T lb_constrain(const T x, const TL lb) {
+
36  using std::exp;
+
37  if (lb == -std::numeric_limits<double>::infinity())
+
38  return identity_constrain(x);
+
39  return exp(x) + lb;
+
40  }
+
41 
+
58  template <typename T, typename TL>
+
59  inline
+
60  typename boost::math::tools::promote_args<T, TL>::type
+
61  lb_constrain(const T x, const TL lb, T& lp) {
+
62  using std::exp;
+
63  if (lb == -std::numeric_limits<double>::infinity())
+
64  return identity_constrain(x, lp);
+
65  lp += x;
+
66  return exp(x) + lb;
+
67  }
+
68 
+
69 
+
70  }
+
71 
+
72 }
+
73 
+
74 #endif
+ +
T lb_constrain(const T x, const TL lb)
Return the lower-bounded value for the specified unconstrained input and specified lower bound...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
T identity_constrain(T x)
Returns the result of applying the identity constraint transform to the input.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lb__free_8hpp.html b/doc/api/html/lb__free_8hpp.html new file mode 100644 index 00000000000..97ff8eaee0c --- /dev/null +++ b/doc/api/html/lb__free_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lb_free.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
lb_free.hpp File Reference
+
+
+
#include <stan/math/prim/scal/fun/identity_free.hpp>
+#include <stan/math/prim/scal/err/check_greater_or_equal.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <cmath>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T , typename TL >
boost::math::tools::promote_args< T, TL >::type stan::math::lb_free (const T y, const TL lb)
 Return the unconstrained value that produces the specified lower-bound constrained value. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lb__free_8hpp_source.html b/doc/api/html/lb__free_8hpp_source.html new file mode 100644 index 00000000000..f30a176f271 --- /dev/null +++ b/doc/api/html/lb__free_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lb_free.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
lb_free.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LB_FREE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LB_FREE_HPP
+
3 
+ + +
6 #include <boost/math/tools/promotion.hpp>
+
7 #include <cmath>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
29  template <typename T, typename TL>
+
30  inline
+
31  typename boost::math::tools::promote_args<T, TL>::type
+
32  lb_free(const T y, const TL lb) {
+
33  using std::log;
+
34  if (lb == -std::numeric_limits<double>::infinity())
+
35  return identity_free(y);
+
36  stan::math::check_greater_or_equal("stan::math::lb_free",
+
37  "Lower bounded variable", y, lb);
+
38  return log(y - lb);
+
39  }
+
40 
+
41  }
+
42 
+
43 }
+
44 
+
45 #endif
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
T identity_free(const T y)
Returns the result of applying the inverse of the identity constraint transform to the input...
+
boost::math::tools::promote_args< T, TL >::type lb_free(const T y, const TL lb)
Return the unconstrained value that produces the specified lower-bound constrained value...
Definition: lb_free.hpp:32
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/likely_8hpp.html b/doc/api/html/likely_8hpp.html new file mode 100644 index 00000000000..49e4889f95a --- /dev/null +++ b/doc/api/html/likely_8hpp.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/likely.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
likely.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + +

+Macros

#define likely(x)    (x)
 
#define unlikely(x)    (x)
 
+

Macro Definition Documentation

+ +
+
+ + + + + + + + +
#define likely( x)   (x)
+
+ +

Definition at line 8 of file likely.hpp.

+ +
+
+ +
+
+ + + + + + + + +
#define unlikely( x)   (x)
+
+ +

Definition at line 9 of file likely.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/likely_8hpp_source.html b/doc/api/html/likely_8hpp_source.html new file mode 100644 index 00000000000..b5ffc72e8a8 --- /dev/null +++ b/doc/api/html/likely_8hpp_source.html @@ -0,0 +1,121 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/likely.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
likely.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_LIKELY_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_LIKELY_HPP
+
3 
+
4 #ifdef __GNUC__
+
5 #define likely(x) __builtin_expect(!!(x), 1)
+
6 #define unlikely(x) __builtin_expect(!!(x), 0)
+
7 #else
+
8 #define likely(x) (x)
+
9 #define unlikely(x) (x)
+
10 #endif
+
11 
+
12 #endif
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__corr__cholesky__log_8hpp.html b/doc/api/html/lkj__corr__cholesky__log_8hpp.html new file mode 100644 index 00000000000..0599929fb83 --- /dev/null +++ b/doc/api/html/lkj__corr__cholesky__log_8hpp.html @@ -0,0 +1,175 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_corr_cholesky_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
lkj_corr_cholesky_log.hpp File Reference
+
+
+
#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/mat/fun/factor_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/factor_U.hpp>
+#include <stan/math/prim/mat/fun/read_corr_L.hpp>
+#include <stan/math/prim/mat/fun/read_corr_matrix.hpp>
+#include <stan/math/prim/mat/fun/read_cov_L.hpp>
+#include <stan/math/prim/mat/fun/read_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/make_nu.hpp>
+#include <stan/math/prim/scal/fun/identity_constrain.hpp>
+#include <stan/math/prim/scal/fun/identity_free.hpp>
+#include <stan/math/prim/scal/fun/positive_constrain.hpp>
+#include <stan/math/prim/scal/fun/positive_free.hpp>
+#include <stan/math/prim/scal/fun/lb_constrain.hpp>
+#include <stan/math/prim/scal/fun/lb_free.hpp>
+#include <stan/math/prim/scal/fun/ub_constrain.hpp>
+#include <stan/math/prim/scal/fun/ub_free.hpp>
+#include <stan/math/prim/scal/fun/lub_constrain.hpp>
+#include <stan/math/prim/scal/fun/lub_free.hpp>
+#include <stan/math/prim/scal/fun/prob_constrain.hpp>
+#include <stan/math/prim/scal/fun/prob_free.hpp>
+#include <stan/math/prim/scal/fun/corr_constrain.hpp>
+#include <stan/math/prim/scal/fun/corr_free.hpp>
+#include <stan/math/prim/mat/fun/simplex_constrain.hpp>
+#include <stan/math/prim/mat/fun/simplex_free.hpp>
+#include <stan/math/prim/mat/fun/ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/ordered_free.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_free.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain_lkj.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free_lkj.hpp>
+#include <stan/math/prim/mat/prob/lkj_corr_log.hpp>
+#include <stan/math/prim/mat/fun/multiply.hpp>
+
+

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_covar , typename T_shape >
boost::math::tools::promote_args< T_covar, T_shape >::type stan::math::lkj_corr_cholesky_log (const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const T_shape &eta)
 
template<typename T_covar , typename T_shape >
boost::math::tools::promote_args< T_covar, T_shape >::type stan::math::lkj_corr_cholesky_log (const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const T_shape &eta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__corr__cholesky__log_8hpp_source.html b/doc/api/html/lkj__corr__cholesky__log_8hpp_source.html new file mode 100644 index 00000000000..1ea6972fe29 --- /dev/null +++ b/doc/api/html/lkj__corr__cholesky__log_8hpp_source.html @@ -0,0 +1,268 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_corr_cholesky_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
lkj_corr_cholesky_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_LKJ_CORR_CHOLESKY_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_LKJ_CORR_CHOLESKY_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
47 
+
48 namespace stan {
+
49  namespace math {
+
50 
+
51  // LKJ_Corr(L|eta) [ L Cholesky factor of correlation matrix
+
52  // eta > 0; eta == 1 <-> uniform]
+
53  template <bool propto,
+
54  typename T_covar, typename T_shape>
+
55  typename boost::math::tools::promote_args<T_covar, T_shape>::type
+
56  lkj_corr_cholesky_log(const Eigen::Matrix
+
57  <T_covar, Eigen::Dynamic, Eigen::Dynamic>& L,
+
58  const T_shape& eta) {
+
59  static const char* function("stan::math::lkj_corr_cholesky_log");
+
60 
+
61  using boost::math::tools::promote_args;
+ + +
64  using stan::math::sum;
+
65 
+
66  typedef typename promote_args<T_covar, T_shape>::type lp_ret;
+
67  lp_ret lp(0.0);
+
68  check_positive(function, "Shape parameter", eta);
+
69  check_lower_triangular(function, "Random variable", L);
+
70 
+
71  const unsigned int K = L.rows();
+
72  if (K == 0)
+
73  return 0.0;
+
74 
+ +
76  lp += do_lkj_constant(eta, K);
+ +
78  const int Km1 = K - 1;
+
79  Eigen::Matrix<T_covar, Eigen::Dynamic, 1> log_diagonals =
+
80  L.diagonal().tail(Km1).array().log();
+
81  Eigen::Matrix<lp_ret, Eigen::Dynamic, 1> values(Km1);
+
82  for (int k = 0; k < Km1; k++)
+
83  values(k) = (Km1 - k - 1) * log_diagonals(k);
+
84  if ( (eta == 1.0) &&
+ +
86  lp += sum(values);
+
87  return(lp);
+
88  }
+
89  values += multiply(2.0 * eta - 2.0, log_diagonals);
+
90  lp += sum(values);
+
91  }
+
92 
+
93  return lp;
+
94  }
+
95 
+
96  template <typename T_covar, typename T_shape>
+
97  inline
+
98  typename boost::math::tools::promote_args<T_covar, T_shape>::type
+
99  lkj_corr_cholesky_log(const Eigen::Matrix
+
100  <T_covar, Eigen::Dynamic, Eigen::Dynamic>& L,
+
101  const T_shape& eta) {
+
102  return lkj_corr_cholesky_log<false>(L, eta);
+
103  }
+
104 
+
105  }
+
106 }
+
107 #endif
+ +
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + + +
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Definition: is_constant.hpp:22
+ + + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ + + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + +
bool check_lower_triangular(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is lower triangular.
+ + +
boost::math::tools::promote_args< T_covar, T_shape >::type lkj_corr_cholesky_log(const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const T_shape &eta)
+ + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ + + + + + + + + + + + + + + + +
T_shape do_lkj_constant(const T_shape &eta, const unsigned int &K)
+ + + + + + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__corr__cholesky__rng_8hpp.html b/doc/api/html/lkj__corr__cholesky__rng_8hpp.html new file mode 100644 index 00000000000..9c1b0c0d872 --- /dev/null +++ b/doc/api/html/lkj__corr__cholesky__rng_8hpp.html @@ -0,0 +1,171 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_corr_cholesky_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
lkj_corr_cholesky_rng.hpp File Reference
+
+
+
#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/prob/beta_rng.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/mat/fun/factor_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/factor_U.hpp>
+#include <stan/math/prim/mat/fun/read_corr_L.hpp>
+#include <stan/math/prim/mat/fun/read_corr_matrix.hpp>
+#include <stan/math/prim/mat/fun/read_cov_L.hpp>
+#include <stan/math/prim/mat/fun/read_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/make_nu.hpp>
+#include <stan/math/prim/scal/fun/identity_constrain.hpp>
+#include <stan/math/prim/scal/fun/identity_free.hpp>
+#include <stan/math/prim/scal/fun/positive_constrain.hpp>
+#include <stan/math/prim/scal/fun/positive_free.hpp>
+#include <stan/math/prim/scal/fun/lb_constrain.hpp>
+#include <stan/math/prim/scal/fun/lb_free.hpp>
+#include <stan/math/prim/scal/fun/ub_constrain.hpp>
+#include <stan/math/prim/scal/fun/ub_free.hpp>
+#include <stan/math/prim/scal/fun/lub_constrain.hpp>
+#include <stan/math/prim/scal/fun/lub_free.hpp>
+#include <stan/math/prim/scal/fun/prob_constrain.hpp>
+#include <stan/math/prim/scal/fun/prob_free.hpp>
+#include <stan/math/prim/scal/fun/corr_constrain.hpp>
+#include <stan/math/prim/scal/fun/corr_free.hpp>
+#include <stan/math/prim/mat/fun/simplex_constrain.hpp>
+#include <stan/math/prim/mat/fun/simplex_free.hpp>
+#include <stan/math/prim/mat/fun/ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/ordered_free.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_free.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain_lkj.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free_lkj.hpp>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<class RNG >
Eigen::MatrixXd stan::math::lkj_corr_cholesky_rng (const size_t K, const double eta, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__corr__cholesky__rng_8hpp_source.html b/doc/api/html/lkj__corr__cholesky__rng_8hpp_source.html new file mode 100644 index 00000000000..5ca946f1106 --- /dev/null +++ b/doc/api/html/lkj__corr__cholesky__rng_8hpp_source.html @@ -0,0 +1,232 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_corr_cholesky_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
lkj_corr_cholesky_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_LKJ_CORR_CHOLESKY_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_LKJ_CORR_CHOLESKY_RNG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
46 
+
47 namespace stan {
+
48  namespace math {
+
49 
+
50  template <class RNG>
+
51  inline Eigen::MatrixXd
+
52  lkj_corr_cholesky_rng(const size_t K,
+
53  const double eta,
+
54  RNG& rng) {
+
55  static const char* function("stan::math::lkj_corr_cholesky_rng");
+
56 
+ +
58 
+
59  check_positive(function, "Shape parameter", eta);
+
60 
+
61  Eigen::ArrayXd CPCs((K * (K - 1)) / 2);
+
62  double alpha = eta + 0.5 * (K - 1);
+
63  unsigned int count = 0;
+
64  for (size_t i = 0; i < (K - 1); i++) {
+
65  alpha -= 0.5;
+
66  for (size_t j = i + 1; j < K; j++) {
+
67  CPCs(count) = 2.0 * stan::math::beta_rng(alpha, alpha, rng) - 1.0;
+
68  count++;
+
69  }
+
70  }
+
71  return stan::math::read_corr_L(CPCs, K);
+
72  }
+
73 
+
74  }
+
75 }
+
76 #endif
+ + +
double beta_rng(const double alpha, const double beta, RNG &rng)
Definition: beta_rng.hpp:29
+ + + + + + + + + + + + + + + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ + + + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_L(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to...
Definition: read_corr_L.hpp:41
+
Eigen::MatrixXd lkj_corr_cholesky_rng(const size_t K, const double eta, RNG &rng)
+ + + + + + + + + + + + + + + + + + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__corr__log_8hpp.html b/doc/api/html/lkj__corr__log_8hpp.html new file mode 100644 index 00000000000..7cb95879351 --- /dev/null +++ b/doc/api/html/lkj__corr__log_8hpp.html @@ -0,0 +1,179 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_corr_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
lkj_corr_log.hpp File Reference
+
+
+
#include <stan/math/prim/mat/err/check_corr_matrix.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/scal/fun/lgamma.hpp>
+#include <stan/math/prim/mat/fun/factor_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/factor_U.hpp>
+#include <stan/math/prim/mat/fun/read_corr_L.hpp>
+#include <stan/math/prim/mat/fun/read_corr_matrix.hpp>
+#include <stan/math/prim/mat/fun/read_cov_L.hpp>
+#include <stan/math/prim/mat/fun/read_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/make_nu.hpp>
+#include <stan/math/prim/scal/fun/identity_constrain.hpp>
+#include <stan/math/prim/scal/fun/identity_free.hpp>
+#include <stan/math/prim/scal/fun/positive_constrain.hpp>
+#include <stan/math/prim/scal/fun/positive_free.hpp>
+#include <stan/math/prim/scal/fun/lb_constrain.hpp>
+#include <stan/math/prim/scal/fun/lb_free.hpp>
+#include <stan/math/prim/scal/fun/ub_constrain.hpp>
+#include <stan/math/prim/scal/fun/ub_free.hpp>
+#include <stan/math/prim/scal/fun/lub_constrain.hpp>
+#include <stan/math/prim/scal/fun/lub_free.hpp>
+#include <stan/math/prim/scal/fun/prob_constrain.hpp>
+#include <stan/math/prim/scal/fun/prob_free.hpp>
+#include <stan/math/prim/scal/fun/corr_constrain.hpp>
+#include <stan/math/prim/scal/fun/corr_free.hpp>
+#include <stan/math/prim/mat/fun/simplex_constrain.hpp>
+#include <stan/math/prim/mat/fun/simplex_free.hpp>
+#include <stan/math/prim/mat/fun/ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/ordered_free.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_free.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain_lkj.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free_lkj.hpp>
+#include <stan/math/prim/mat/fun/sum.hpp>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

template<typename T_shape >
T_shape stan::math::do_lkj_constant (const T_shape &eta, const unsigned int &K)
 
template<bool propto, typename T_y , typename T_shape >
boost::math::tools::promote_args< T_y, T_shape >::type stan::math::lkj_corr_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_shape &eta)
 
template<typename T_y , typename T_shape >
boost::math::tools::promote_args< T_y, T_shape >::type stan::math::lkj_corr_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_shape &eta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__corr__log_8hpp_source.html b/doc/api/html/lkj__corr__log_8hpp_source.html new file mode 100644 index 00000000000..8fe01fa3b04 --- /dev/null +++ b/doc/api/html/lkj__corr__log_8hpp_source.html @@ -0,0 +1,294 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_corr_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
lkj_corr_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_LKJ_CORR_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_LKJ_CORR_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
48 
+
49 namespace stan {
+
50  namespace math {
+
51 
+
52  template <typename T_shape>
+
53  T_shape do_lkj_constant(const T_shape& eta, const unsigned int& K) {
+
54  using stan::math::sum;
+
55  using stan::math::lgamma;
+
56 
+
57  // Lewandowski, Kurowicka, and Joe (2009) theorem 5
+
58  T_shape constant;
+
59  const int Km1 = K - 1;
+
60  if (eta == 1.0) {
+
61  // C++ integer division is appropriate in this block
+
62  Eigen::VectorXd numerator(Km1 / 2);
+
63  for (int k = 1; k <= numerator.rows(); k++)
+
64  numerator(k-1) = lgamma(2 * k);
+
65  constant = sum(numerator);
+
66  if ( (K % 2) == 1 )
+
67  constant += 0.25 * (K * K - 1) * LOG_PI
+
68  - 0.25 * (Km1 * Km1) * LOG_TWO - Km1 * lgamma((K + 1) / 2);
+
69  else
+
70  constant += 0.25 * K * (K - 2) * LOG_PI
+
71  + 0.25 * (3 * K * K - 4 * K) * LOG_TWO
+
72  + K * lgamma(K / 2) - Km1 * lgamma(K);
+
73  } else {
+
74  constant = -Km1 * lgamma(eta + 0.5 * Km1);
+
75  for (int k = 1; k <= Km1; k++)
+
76  constant += 0.5 * k * LOG_PI + lgamma(eta + 0.5 * (Km1 - k));
+
77  }
+
78  return constant;
+
79  }
+
80 
+
81  // LKJ_Corr(y|eta) [ y correlation matrix (not covariance matrix)
+
82  // eta > 0; eta == 1 <-> uniform]
+
83  template <bool propto,
+
84  typename T_y, typename T_shape>
+
85  typename boost::math::tools::promote_args<T_y, T_shape>::type
+
86  lkj_corr_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
87  const T_shape& eta) {
+
88  static const char* function("stan::math::lkj_corr_log");
+
89 
+ + +
92  using stan::math::sum;
+
93  using boost::math::tools::promote_args;
+
94 
+
95  typename promote_args<T_y, T_shape>::type lp(0.0);
+
96  check_positive(function, "Shape parameter", eta);
+
97  check_corr_matrix(function, "Correlation matrix", y);
+
98 
+
99  const unsigned int K = y.rows();
+
100  if (K == 0)
+
101  return 0.0;
+
102 
+ +
104  lp += do_lkj_constant(eta, K);
+
105 
+
106  if ( (eta == 1.0) &&
+ +
108  return lp;
+
109 
+ +
111  return lp;
+
112 
+
113  Eigen::Matrix<T_y, Eigen::Dynamic, 1> values =
+
114  y.ldlt().vectorD().array().log().matrix();
+
115  lp += (eta - 1.0) * sum(values);
+
116  return lp;
+
117  }
+
118 
+
119  template <typename T_y, typename T_shape>
+
120  inline
+
121  typename boost::math::tools::promote_args<T_y, T_shape>::type
+
122  lkj_corr_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
123  const T_shape& eta) {
+
124  return lkj_corr_log<false>(y, eta);
+
125  }
+
126 
+
127  }
+
128 }
+
129 #endif
+ +
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Definition: is_constant.hpp:22
+ +
Metaprogram structure to determine the base scalar type of a template argument.
Definition: scalar_type.hpp:34
+
boost::math::tools::promote_args< T_y, T_shape >::type lkj_corr_log(const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_shape &eta)
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + + + +
const double LOG_PI
Definition: constants.hpp:170
+ + + + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
const double LOG_TWO
Definition: constants.hpp:177
+ + + + + + + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ + + + +
bool check_corr_matrix(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is a valid correlation matrix.
+ + + + + + + + + + + + + +
T_shape do_lkj_constant(const T_shape &eta, const unsigned int &K)
+ + + + + + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__corr__rng_8hpp.html b/doc/api/html/lkj__corr__rng_8hpp.html new file mode 100644 index 00000000000..16c4849059c --- /dev/null +++ b/doc/api/html/lkj__corr__rng_8hpp.html @@ -0,0 +1,171 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_corr_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
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lkj_corr_rng.hpp File Reference
+
+
+
#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/mat/fun/factor_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/factor_U.hpp>
+#include <stan/math/prim/mat/fun/read_corr_L.hpp>
+#include <stan/math/prim/mat/fun/read_corr_matrix.hpp>
+#include <stan/math/prim/mat/fun/read_cov_L.hpp>
+#include <stan/math/prim/mat/fun/read_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/make_nu.hpp>
+#include <stan/math/prim/scal/fun/identity_constrain.hpp>
+#include <stan/math/prim/scal/fun/identity_free.hpp>
+#include <stan/math/prim/scal/fun/positive_constrain.hpp>
+#include <stan/math/prim/scal/fun/positive_free.hpp>
+#include <stan/math/prim/scal/fun/lb_constrain.hpp>
+#include <stan/math/prim/scal/fun/lb_free.hpp>
+#include <stan/math/prim/scal/fun/ub_constrain.hpp>
+#include <stan/math/prim/scal/fun/ub_free.hpp>
+#include <stan/math/prim/scal/fun/lub_constrain.hpp>
+#include <stan/math/prim/scal/fun/lub_free.hpp>
+#include <stan/math/prim/scal/fun/prob_constrain.hpp>
+#include <stan/math/prim/scal/fun/prob_free.hpp>
+#include <stan/math/prim/scal/fun/corr_constrain.hpp>
+#include <stan/math/prim/scal/fun/corr_free.hpp>
+#include <stan/math/prim/mat/fun/simplex_constrain.hpp>
+#include <stan/math/prim/mat/fun/simplex_free.hpp>
+#include <stan/math/prim/mat/fun/ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/ordered_free.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_free.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain_lkj.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free_lkj.hpp>
+#include <stan/math/prim/mat/prob/lkj_corr_cholesky_rng.hpp>
+
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+Functions

template<class RNG >
Eigen::MatrixXd stan::math::lkj_corr_rng (const size_t K, const double eta, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__corr__rng_8hpp_source.html b/doc/api/html/lkj__corr__rng_8hpp_source.html new file mode 100644 index 00000000000..209816c9e3b --- /dev/null +++ b/doc/api/html/lkj__corr__rng_8hpp_source.html @@ -0,0 +1,224 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_corr_rng.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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lkj_corr_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_LKJ_CORR_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_LKJ_CORR_RNG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
46 
+
47 namespace stan {
+
48  namespace math {
+
49 
+
50  template <class RNG>
+
51  inline Eigen::MatrixXd
+
52  lkj_corr_rng(const size_t K,
+
53  const double eta,
+
54  RNG& rng) {
+
55  static const char* function("stan::math::lkj_corr_rng");
+
56 
+ +
58 
+
59  check_positive(function, "Shape parameter", eta);
+
60 
+ + +
63  rng));
+
64  }
+
65 
+
66  }
+
67 }
+
68 #endif
+ + +
Eigen::MatrixXd lkj_corr_rng(const size_t K, const double eta, RNG &rng)
+ + + + + + + + + +
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose(const Eigen::Matrix< fvar< T >, R, C > &m)
+ + + + + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ + + + +
Eigen::MatrixXd lkj_corr_cholesky_rng(const size_t K, const double eta, RNG &rng)
+ + + + + + + + + + + + + + + + + + + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lkj__cov__log_8hpp.html b/doc/api/html/lkj__cov__log_8hpp.html new file mode 100644 index 00000000000..8ef93a8d13c --- /dev/null +++ b/doc/api/html/lkj__cov__log_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_cov_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
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+
lkj_cov_log.hpp File Reference
+
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+Functions

template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type stan::math::lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_loc, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< T_scale, Eigen::Dynamic, 1 > &sigma, const T_shape &eta)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type stan::math::lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_loc, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< T_scale, Eigen::Dynamic, 1 > &sigma, const T_shape &eta)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type stan::math::lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_loc &mu, const T_scale &sigma, const T_shape &eta)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type stan::math::lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_loc &mu, const T_scale &sigma, const T_shape &eta)
 
+
+
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diff --git a/doc/api/html/lkj__cov__log_8hpp_source.html b/doc/api/html/lkj__cov__log_8hpp_source.html new file mode 100644 index 00000000000..39b20c49108 --- /dev/null +++ b/doc/api/html/lkj__cov__log_8hpp_source.html @@ -0,0 +1,259 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/lkj_cov_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
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lkj_cov_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_LKJ_COV_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_LKJ_COV_LOG_HPP
+
3 
+ + + + +
8 
+ + + + +
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
17 
+
18  // LKJ_cov(y|mu, sigma, eta) [ y covariance matrix (not correlation matrix)
+
19  // mu vector, sigma > 0 vector, eta > 0 ]
+
20  template <bool propto,
+
21  typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
22  typename
+
23  boost::math::tools::promote_args<T_y, T_loc, T_scale, T_shape>::type
+
24  lkj_cov_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
25  const Eigen::Matrix<T_loc, Eigen::Dynamic, 1>& mu,
+
26  const Eigen::Matrix<T_scale, Eigen::Dynamic, 1>& sigma,
+
27  const T_shape& eta) {
+
28  static const char* function("stan::math::lkj_cov_log");
+
29 
+ + + + +
34  using boost::math::tools::promote_args;
+
35 
+
36  typename promote_args<T_y, T_loc, T_scale, T_shape>::type lp(0.0);
+
37  check_size_match(function,
+
38  "Rows of location parameter", mu.rows(),
+
39  "columns of scale parameter", sigma.rows());
+
40  check_square(function, "random variable", y);
+
41  check_size_match(function,
+
42  "Rows of random variable", y.rows(),
+
43  "rows of location parameter", mu.rows());
+
44  check_positive(function, "Shape parameter", eta);
+
45  check_finite(function, "Location parameter", mu);
+
46  check_finite(function, "Scale parameter", sigma);
+
47  // FIXME: build vectorized versions
+
48  for (int m = 0; m < y.rows(); ++m)
+
49  for (int n = 0; n < y.cols(); ++n)
+
50  check_finite(function, "Covariance matrix", y(m, n));
+
51 
+
52  const unsigned int K = y.rows();
+
53  const Eigen::Array<T_y, Eigen::Dynamic, 1> sds
+
54  = y.diagonal().array().sqrt();
+
55  for (unsigned int k = 0; k < K; k++) {
+
56  lp += lognormal_log<propto>(sds(k), mu(k), sigma(k));
+
57  }
+
58  if (stan::is_constant<typename stan::scalar_type<T_shape> >::value
+
59  && eta == 1.0) {
+
60  // no need to rescale y into a correlation matrix
+
61  lp += lkj_corr_log<propto, T_y, T_shape>(y, eta);
+
62  return lp;
+
63  }
+
64  Eigen::DiagonalMatrix<T_y, Eigen::Dynamic> D(K);
+
65  D.diagonal() = sds.inverse();
+
66  lp += lkj_corr_log<propto, T_y, T_shape>(D * y * D, eta);
+
67  return lp;
+
68  }
+
69 
+
70  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
71  inline
+
72  typename
+
73  boost::math::tools::promote_args<T_y, T_loc, T_scale, T_shape>::type
+
74  lkj_cov_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
75  const Eigen::Matrix<T_loc, Eigen::Dynamic, 1>& mu,
+
76  const Eigen::Matrix<T_scale, Eigen::Dynamic, 1>& sigma,
+
77  const T_shape& eta) {
+
78  return lkj_cov_log<false>(y, mu, sigma, eta);
+
79  }
+
80 
+
81  // LKJ_Cov(y|mu, sigma, eta) [ y covariance matrix (not correlation matrix)
+
82  // mu scalar, sigma > 0 scalar, eta > 0 ]
+
83  template <bool propto,
+
84  typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
85  typename
+
86  boost::math::tools::promote_args<T_y, T_loc, T_scale, T_shape>::type
+
87  lkj_cov_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
88  const T_loc& mu,
+
89  const T_scale& sigma,
+
90  const T_shape& eta) {
+
91  static const char* function("stan::math::lkj_cov_log");
+
92 
+ + +
95  using boost::math::tools::promote_args;
+
96 
+
97  typename promote_args<T_y, T_loc, T_scale, T_shape>::type lp(0.0);
+
98  check_positive(function, "Shape parameter", eta);
+
99  check_finite(function, "Location parameter", mu);
+
100  check_finite(function, "Scale parameter", sigma);
+
101 
+
102  const unsigned int K = y.rows();
+
103  const Eigen::Array<T_y, Eigen::Dynamic, 1> sds
+
104  = y.diagonal().array().sqrt();
+
105  for (unsigned int k = 0; k < K; k++) {
+
106  lp += lognormal_log<propto>(sds(k), mu, sigma);
+
107  }
+
108  if (stan::is_constant<typename stan::scalar_type<T_shape> >::value
+
109  && eta == 1.0) {
+
110  // no need to rescale y into a correlation matrix
+
111  lp += lkj_corr_log<propto>(y, eta);
+
112  return lp;
+
113  }
+
114  Eigen::DiagonalMatrix<T_y, Eigen::Dynamic> D(K);
+
115  D.diagonal() = sds.inverse();
+
116  lp += lkj_corr_log<propto, T_y, T_shape>(D * y * D, eta);
+
117  return lp;
+
118  }
+
119 
+
120  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
121  inline
+
122  typename boost::math::tools::promote_args
+
123  <T_y, T_loc, T_scale, T_shape>::type
+
124  lkj_cov_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
125  const T_loc& mu,
+
126  const T_scale& sigma,
+
127  const T_shape& eta) {
+
128  return lkj_cov_log<false>(y, mu, sigma, eta);
+
129  }
+
130 
+
131 
+
132  }
+
133 }
+
134 #endif
+
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type lkj_cov_log(const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_loc, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< T_scale, Eigen::Dynamic, 1 > &sigma, const T_shape &eta)
Definition: lkj_cov_log.hpp:24
+ +
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Definition: is_constant.hpp:22
+
Metaprogram structure to determine the base scalar type of a template argument.
Definition: scalar_type.hpp:34
+ + + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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+
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diff --git a/doc/api/html/logical__and_8hpp.html b/doc/api/html/logical__and_8hpp.html new file mode 100644 index 00000000000..326e7e9d870 --- /dev/null +++ b/doc/api/html/logical__and_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_and.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
int stan::math::logical_and (const T1 x1, const T2 x2)
 The logical and function which returns 1 if both arguments are unequal to zero and 0 otherwise. More...
 
+
+
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/logical__and_8hpp_source.html b/doc/api/html/logical__and_8hpp_source.html new file mode 100644 index 00000000000..564715f7e27 --- /dev/null +++ b/doc/api/html/logical__and_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_and.hpp Source File + + + + + + + + + + +
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logical_and.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_AND_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_AND_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
28  template <typename T1, typename T2>
+
29  inline int
+
30  logical_and(const T1 x1, const T2 x2) {
+
31  return (x1 != 0) && (x2 != 0);
+
32  }
+
33 
+
34  }
+
35 }
+
36 
+
37 #endif
+
int logical_and(const T1 x1, const T2 x2)
The logical and function which returns 1 if both arguments are unequal to zero and 0 otherwise...
Definition: logical_and.hpp:30
+ +
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diff --git a/doc/api/html/logical__eq_8hpp.html b/doc/api/html/logical__eq_8hpp.html new file mode 100644 index 00000000000..441963e37b4 --- /dev/null +++ b/doc/api/html/logical__eq_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_eq.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
int stan::math::logical_eq (const T1 x1, const T2 x2)
 Return 1 if the first argument is equal to the second. More...
 
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diff --git a/doc/api/html/logical__eq_8hpp_source.html b/doc/api/html/logical__eq_8hpp_source.html new file mode 100644 index 00000000000..38bb430269a --- /dev/null +++ b/doc/api/html/logical__eq_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_eq.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_EQ_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_EQ_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
17  template <typename T1, typename T2>
+
18  inline int
+
19  logical_eq(const T1 x1, const T2 x2) {
+
20  return x1 == x2;
+
21  }
+
22 
+
23  }
+
24 }
+
25 
+
26 #endif
+ +
int logical_eq(const T1 x1, const T2 x2)
Return 1 if the first argument is equal to the second.
Definition: logical_eq.hpp:19
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diff --git a/doc/api/html/logical__gt_8hpp.html b/doc/api/html/logical__gt_8hpp.html new file mode 100644 index 00000000000..aa2d610024f --- /dev/null +++ b/doc/api/html/logical__gt_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_gt.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
int stan::math::logical_gt (const T1 x1, const T2 x2)
 Return 1 if the first argument is strictly greater than the second. More...
 
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diff --git a/doc/api/html/logical__gt_8hpp_source.html b/doc/api/html/logical__gt_8hpp_source.html new file mode 100644 index 00000000000..fefb91e709c --- /dev/null +++ b/doc/api/html/logical__gt_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_gt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_GT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_GT_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
17  template <typename T1, typename T2>
+
18  inline int
+
19  logical_gt(const T1 x1, const T2 x2) {
+
20  return x1 > x2;
+
21  }
+
22 
+
23  }
+
24 }
+
25 
+
26 #endif
+ +
int logical_gt(const T1 x1, const T2 x2)
Return 1 if the first argument is strictly greater than the second.
Definition: logical_gt.hpp:19
+
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diff --git a/doc/api/html/logical__gte_8hpp.html b/doc/api/html/logical__gte_8hpp.html new file mode 100644 index 00000000000..214e7b8682a --- /dev/null +++ b/doc/api/html/logical__gte_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_gte.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
int stan::math::logical_gte (const T1 x1, const T2 x2)
 Return 1 if the first argument is greater than or equal to the second. More...
 
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diff --git a/doc/api/html/logical__gte_8hpp_source.html b/doc/api/html/logical__gte_8hpp_source.html new file mode 100644 index 00000000000..ce01d036fa9 --- /dev/null +++ b/doc/api/html/logical__gte_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_gte.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_GTE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_GTE_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
17  template <typename T1, typename T2>
+
18  inline int
+
19  logical_gte(const T1 x1, const T2 x2) {
+
20  return x1 >= x2;
+
21  }
+
22 
+
23  }
+
24 }
+
25 
+
26 #endif
+ +
int logical_gte(const T1 x1, const T2 x2)
Return 1 if the first argument is greater than or equal to the second.
Definition: logical_gte.hpp:19
+
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diff --git a/doc/api/html/logical__lt_8hpp.html b/doc/api/html/logical__lt_8hpp.html new file mode 100644 index 00000000000..3824d327487 --- /dev/null +++ b/doc/api/html/logical__lt_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_lt.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
int stan::math::logical_lt (T1 x1, T2 x2)
 Return 1 if the first argument is strictly less than the second. More...
 
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diff --git a/doc/api/html/logical__lt_8hpp_source.html b/doc/api/html/logical__lt_8hpp_source.html new file mode 100644 index 00000000000..248b4f3e159 --- /dev/null +++ b/doc/api/html/logical__lt_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_lt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_LT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_LT_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
17  template <typename T1, typename T2>
+
18  inline
+
19  int
+
20  logical_lt(T1 x1, T2 x2) {
+
21  return x1 < x2;
+
22  }
+
23 
+
24  }
+
25 }
+
26 
+
27 #endif
+ +
int logical_lt(T1 x1, T2 x2)
Return 1 if the first argument is strictly less than the second.
Definition: logical_lt.hpp:20
+
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diff --git a/doc/api/html/logical__lte_8hpp.html b/doc/api/html/logical__lte_8hpp.html new file mode 100644 index 00000000000..78518cbea9f --- /dev/null +++ b/doc/api/html/logical__lte_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_lte.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
int stan::math::logical_lte (const T1 x1, const T2 x2)
 Return 1 if the first argument is less than or equal to the second. More...
 
+
+
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diff --git a/doc/api/html/logical__lte_8hpp_source.html b/doc/api/html/logical__lte_8hpp_source.html new file mode 100644 index 00000000000..cc2983f3df5 --- /dev/null +++ b/doc/api/html/logical__lte_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_lte.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_LTE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_LTE_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
17  template <typename T1, typename T2>
+
18  inline int
+
19  logical_lte(const T1 x1, const T2 x2) {
+
20  return x1 <= x2;
+
21  }
+
22 
+
23  }
+
24 }
+
25 
+
26 #endif
+ +
int logical_lte(const T1 x1, const T2 x2)
Return 1 if the first argument is less than or equal to the second.
Definition: logical_lte.hpp:19
+
+
+
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diff --git a/doc/api/html/logical__negation_8hpp.html b/doc/api/html/logical__negation_8hpp.html new file mode 100644 index 00000000000..406556b638a --- /dev/null +++ b/doc/api/html/logical__negation_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_negation.hpp File Reference + + + + + + + + + + +
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template<typename T >
int stan::math::logical_negation (const T x)
 The logical negation function which returns 1 if the input is equal to zero and 0 otherwise. More...
 
+
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diff --git a/doc/api/html/logical__negation_8hpp_source.html b/doc/api/html/logical__negation_8hpp_source.html new file mode 100644 index 00000000000..fc250ec5f45 --- /dev/null +++ b/doc/api/html/logical__negation_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_negation.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_NEGATION_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_NEGATION_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
15  template <typename T>
+
16  inline int
+
17  logical_negation(const T x) {
+
18  return (x == 0);
+
19  }
+
20 
+
21  }
+
22 }
+
23 
+
24 #endif
+ +
int logical_negation(const T x)
The logical negation function which returns 1 if the input is equal to zero and 0 otherwise...
+
+
+
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diff --git a/doc/api/html/logical__neq_8hpp.html b/doc/api/html/logical__neq_8hpp.html new file mode 100644 index 00000000000..39908bd3a4c --- /dev/null +++ b/doc/api/html/logical__neq_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_neq.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
int stan::math::logical_neq (const T1 x1, const T2 x2)
 Return 1 if the first argument is unequal to the second. More...
 
+
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diff --git a/doc/api/html/logical__neq_8hpp_source.html b/doc/api/html/logical__neq_8hpp_source.html new file mode 100644 index 00000000000..741a824f6f5 --- /dev/null +++ b/doc/api/html/logical__neq_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_neq.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_NEQ_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_NEQ_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
17  template <typename T1, typename T2>
+
18  inline int
+
19  logical_neq(const T1 x1, const T2 x2) {
+
20  return x1 != x2;
+
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ +
int logical_neq(const T1 x1, const T2 x2)
Return 1 if the first argument is unequal to the second.
Definition: logical_neq.hpp:19
+
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diff --git a/doc/api/html/logical__or_8hpp.html b/doc/api/html/logical__or_8hpp.html new file mode 100644 index 00000000000..d0bf5d04f3c --- /dev/null +++ b/doc/api/html/logical__or_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_or.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
int stan::math::logical_or (T1 x1, T2 x2)
 The logical or function which returns 1 if either argument is unequal to zero and 0 otherwise. More...
 
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diff --git a/doc/api/html/logical__or_8hpp_source.html b/doc/api/html/logical__or_8hpp_source.html new file mode 100644 index 00000000000..c0172ec2316 --- /dev/null +++ b/doc/api/html/logical__or_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logical_or.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGICAL_OR_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGICAL_OR_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
27  template <typename T1, typename T2>
+
28  inline int
+
29  logical_or(T1 x1, T2 x2) {
+
30  return (x1 != 0) || (x2 != 0);
+
31  }
+
32 
+
33  }
+
34 }
+
35 
+
36 #endif
+ +
int logical_or(T1 x1, T2 x2)
The logical or function which returns 1 if either argument is unequal to zero and 0 otherwise...
Definition: logical_or.hpp:29
+
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diff --git a/doc/api/html/logistic__ccdf__log_8hpp.html b/doc/api/html/logistic__ccdf__log_8hpp.html new file mode 100644 index 00000000000..a352056e2e1 --- /dev/null +++ b/doc/api/html/logistic__ccdf__log_8hpp.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::logistic_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
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diff --git a/doc/api/html/logistic__ccdf__log_8hpp_source.html b/doc/api/html/logistic__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..9089bd17fb4 --- /dev/null +++ b/doc/api/html/logistic__ccdf__log_8hpp_source.html @@ -0,0 +1,259 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_ccdf_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_CCDF_LOG_HPP
+
3 
+
4 #include <boost/random/exponential_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + +
23 #include <cmath>
+
24 #include <limits>
+
25 
+
26 namespace stan {
+
27  namespace math {
+
28 
+
29  template <typename T_y, typename T_loc, typename T_scale>
+
30  typename return_type<T_y, T_loc, T_scale>::type
+
31  logistic_ccdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+ +
33  T_partials_return;
+
34 
+
35  // Size checks
+
36  if ( !( stan::length(y) && stan::length(mu) && stan::length(sigma) ) )
+
37  return 0.0;
+
38 
+
39  // Error checks
+
40  static const char* function("stan::math::logistic_cdf_log");
+
41 
+ + + + + +
47  using boost::math::tools::promote_args;
+
48  using std::log;
+
49  using std::exp;
+
50 
+
51  T_partials_return P(0.0);
+
52 
+
53  check_not_nan(function, "Random variable", y);
+
54  check_finite(function, "Location parameter", mu);
+
55  check_positive_finite(function, "Scale parameter", sigma);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Location parameter", mu,
+
59  "Scale parameter", sigma);
+
60 
+
61  // Wrap arguments in vectors
+
62  VectorView<const T_y> y_vec(y);
+
63  VectorView<const T_loc> mu_vec(mu);
+
64  VectorView<const T_scale> sigma_vec(sigma);
+
65  size_t N = max_size(y, mu, sigma);
+
66 
+ +
68  operands_and_partials(y, mu, sigma);
+
69 
+
70  // Explicit return for extreme values
+
71  // The gradients are technically ill-defined, but treated as zero
+
72 
+
73  for (size_t i = 0; i < stan::length(y); i++) {
+
74  if (value_of(y_vec[i]) == -std::numeric_limits<double>::infinity())
+
75  return operands_and_partials.value(0.0);
+
76  }
+
77 
+
78  // Compute vectorized cdf_log and its gradients
+
79  for (size_t n = 0; n < N; n++) {
+
80  // Explicit results for extreme values
+
81  // The gradients are technically ill-defined, but treated as zero
+
82  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
83  return operands_and_partials.value(stan::math::negative_infinity());
+
84  }
+
85 
+
86  // Pull out values
+
87  const T_partials_return y_dbl = value_of(y_vec[n]);
+
88  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
89  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
90  const T_partials_return sigma_inv_vec = 1.0 / value_of(sigma_vec[n]);
+
91 
+
92  // Compute
+
93  const T_partials_return Pn = 1.0 - 1.0 / (1.0 + exp(-(y_dbl - mu_dbl)
+
94  * sigma_inv_vec));
+
95  P += log(Pn);
+
96 
+ +
98  operands_and_partials.d_x1[n]
+
99  -= exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+ +
101  operands_and_partials.d_x2[n]
+
102  -= - exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+ +
104  operands_and_partials.d_x3[n] -= - (y_dbl - mu_dbl) * sigma_inv_vec
+
105  * exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+
106  }
+
107 
+
108  return operands_and_partials.value(P);
+
109  }
+
110  }
+
111 }
+
112 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
return_type< T_y, T_loc, T_scale >::type logistic_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
return_type< T_y, T_loc, T_scale >::type logistic_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
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diff --git a/doc/api/html/logistic__cdf_8hpp.html b/doc/api/html/logistic__cdf_8hpp.html new file mode 100644 index 00000000000..eaa837acedc --- /dev/null +++ b/doc/api/html/logistic__cdf_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::logistic_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/logistic__cdf_8hpp_source.html b/doc/api/html/logistic__cdf_8hpp_source.html new file mode 100644 index 00000000000..fbec00129cd --- /dev/null +++ b/doc/api/html/logistic__cdf_8hpp_source.html @@ -0,0 +1,270 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
+ + +
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+
logistic_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_CDF_HPP
+
3 
+
4 #include <boost/random/exponential_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + +
22 #include <cmath>
+
23 #include <limits>
+
24 
+
25 namespace stan {
+
26  namespace math {
+
27 
+
28  // Logistic(y|mu, sigma) [sigma > 0]
+
29  template <typename T_y, typename T_loc, typename T_scale>
+
30  typename return_type<T_y, T_loc, T_scale>::type
+
31  logistic_cdf(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+ +
33  T_partials_return;
+
34 
+
35  // Size checks
+
36  if ( !( stan::length(y) && stan::length(mu)
+
37  && stan::length(sigma) ) )
+
38  return 1.0;
+
39 
+
40  // Error checks
+
41  static const char* function("stan::math::logistic_cdf");
+
42 
+ + + + + +
48  using boost::math::tools::promote_args;
+
49  using std::exp;
+
50 
+
51  T_partials_return P(1.0);
+
52 
+
53  check_not_nan(function, "Random variable", y);
+
54  check_finite(function, "Location parameter", mu);
+
55  check_positive_finite(function, "Scale parameter", sigma);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Location parameter", mu,
+
59  "Scale parameter", sigma);
+
60 
+
61  // Wrap arguments in vectors
+
62  VectorView<const T_y> y_vec(y);
+
63  VectorView<const T_loc> mu_vec(mu);
+
64  VectorView<const T_scale> sigma_vec(sigma);
+
65  size_t N = max_size(y, mu, sigma);
+
66 
+ +
68  operands_and_partials(y, mu, sigma);
+
69 
+
70  // Explicit return for extreme values
+
71  // The gradients are technically ill-defined, but treated as zero
+
72 
+
73  for (size_t i = 0; i < stan::length(y); i++) {
+
74  if (value_of(y_vec[i]) == -std::numeric_limits<double>::infinity())
+
75  return operands_and_partials.value(0.0);
+
76  }
+
77 
+
78  // Compute vectorized CDF and its gradients
+
79  for (size_t n = 0; n < N; n++) {
+
80  // Explicit results for extreme values
+
81  // The gradients are technically ill-defined, but treated as zero
+
82  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
83  continue;
+
84  }
+
85 
+
86  // Pull out values
+
87  const T_partials_return y_dbl = value_of(y_vec[n]);
+
88  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
89  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
90  const T_partials_return sigma_inv_vec = 1.0 / value_of(sigma_vec[n]);
+
91 
+
92  // Compute
+
93  const T_partials_return Pn = 1.0 / (1.0 + exp(-(y_dbl - mu_dbl)
+
94  * sigma_inv_vec));
+
95 
+
96  P *= Pn;
+
97 
+ +
99  operands_and_partials.d_x1[n]
+
100  += exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+ +
102  operands_and_partials.d_x2[n]
+
103  += - exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+ +
105  operands_and_partials.d_x3[n] += - (y_dbl - mu_dbl) * sigma_inv_vec
+
106  * exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+
107  }
+
108 
+ +
110  for (size_t n = 0; n < stan::length(y); ++n)
+
111  operands_and_partials.d_x1[n] *= P;
+
112  }
+ +
114  for (size_t n = 0; n < stan::length(mu); ++n)
+
115  operands_and_partials.d_x2[n] *= P;
+
116  }
+ +
118  for (size_t n = 0; n < stan::length(sigma); ++n)
+
119  operands_and_partials.d_x3[n] *= P;
+
120  }
+
121 
+
122  return operands_and_partials.value(P);
+
123  }
+
124  }
+
125 }
+
126 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_loc, T_scale >::type logistic_cdf(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
return_type< T_y, T_loc, T_scale >::type logistic_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/logistic__cdf__log_8hpp.html b/doc/api/html/logistic__cdf__log_8hpp.html new file mode 100644 index 00000000000..16f4368104f --- /dev/null +++ b/doc/api/html/logistic__cdf__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
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+
+ +
+
logistic_cdf_log.hpp File Reference
+
+
+ +

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+ + + + + + + +

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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::logistic_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/logistic__cdf__log_8hpp_source.html b/doc/api/html/logistic__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..becbe856a5e --- /dev/null +++ b/doc/api/html/logistic__cdf__log_8hpp_source.html @@ -0,0 +1,257 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
logistic_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_CDF_LOG_HPP
+
3 
+
4 #include <boost/random/exponential_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + +
22 #include <cmath>
+
23 #include <limits>
+
24 
+
25 namespace stan {
+
26  namespace math {
+
27 
+
28  template <typename T_y, typename T_loc, typename T_scale>
+
29  typename return_type<T_y, T_loc, T_scale>::type
+
30  logistic_cdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+ +
32  T_partials_return;
+
33 
+
34  // Size checks
+
35  if ( !( stan::length(y) && stan::length(mu) && stan::length(sigma) ) )
+
36  return 0.0;
+
37 
+
38  // Error checks
+
39  static const char* function("stan::math::logistic_cdf_log");
+
40 
+ + + + + +
46  using boost::math::tools::promote_args;
+
47  using std::log;
+
48  using std::exp;
+
49 
+
50  T_partials_return P(0.0);
+
51 
+
52  check_not_nan(function, "Random variable", y);
+
53  check_finite(function, "Location parameter", mu);
+
54  check_positive_finite(function, "Scale parameter", sigma);
+
55  check_consistent_sizes(function,
+
56  "Random variable", y,
+
57  "Location parameter", mu,
+
58  "Scale parameter", sigma);
+
59 
+
60  // Wrap arguments in vectors
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_loc> mu_vec(mu);
+
63  VectorView<const T_scale> sigma_vec(sigma);
+
64  size_t N = max_size(y, mu, sigma);
+
65 
+ +
67  operands_and_partials(y, mu, sigma);
+
68 
+
69  // Explicit return for extreme values
+
70  // The gradients are technically ill-defined, but treated as zero
+
71 
+
72  for (size_t i = 0; i < stan::length(y); i++) {
+
73  if (value_of(y_vec[i]) == -std::numeric_limits<double>::infinity())
+
74  return operands_and_partials
+
75  .value(-std::numeric_limits<double>::infinity());
+
76  }
+
77 
+
78  // Compute vectorized cdf_log and its gradients
+
79  for (size_t n = 0; n < N; n++) {
+
80  // Explicit results for extreme values
+
81  // The gradients are technically ill-defined, but treated as zero
+
82  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
83  continue;
+
84  }
+
85 
+
86  // Pull out values
+
87  const T_partials_return y_dbl = value_of(y_vec[n]);
+
88  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
89  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
90  const T_partials_return sigma_inv_vec = 1.0 / value_of(sigma_vec[n]);
+
91 
+
92  // Compute
+
93  const T_partials_return Pn = 1.0 / (1.0 + exp(-(y_dbl - mu_dbl)
+
94  *sigma_inv_vec));
+
95  P += log(Pn);
+
96 
+ +
98  operands_and_partials.d_x1[n]
+
99  += exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+ +
101  operands_and_partials.d_x2[n]
+
102  += - exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+ +
104  operands_and_partials.d_x3[n] += - (y_dbl - mu_dbl) * sigma_inv_vec
+
105  * exp(logistic_log(y_dbl, mu_dbl, sigma_dbl)) / Pn;
+
106  }
+
107 
+
108  return operands_and_partials.value(P);
+
109  }
+
110  }
+
111 }
+
112 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
return_type< T_y, T_loc, T_scale >::type logistic_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
return_type< T_y, T_loc, T_scale >::type logistic_cdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/logistic__log_8hpp.html b/doc/api/html/logistic__log_8hpp.html new file mode 100644 index 00000000000..62210bef733 --- /dev/null +++ b/doc/api/html/logistic__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
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+
+ +
+
logistic_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::logistic_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::logistic_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
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diff --git a/doc/api/html/logistic__log_8hpp_source.html b/doc/api/html/logistic__log_8hpp_source.html new file mode 100644 index 00000000000..e1c40ea8ffd --- /dev/null +++ b/doc/api/html/logistic__log_8hpp_source.html @@ -0,0 +1,295 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_log.hpp Source File + + + + + + + + + + +
+
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+
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logistic_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_LOG_HPP
+
3 
+
4 #include <boost/random/exponential_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + +
22 #include <cmath>
+
23 
+
24 namespace stan {
+
25  namespace math {
+
26 
+
27  // Logistic(y|mu, sigma) [sigma > 0]
+
28  // FIXME: document
+
29  template <bool propto,
+
30  typename T_y, typename T_loc, typename T_scale>
+
31  typename return_type<T_y, T_loc, T_scale>::type
+
32  logistic_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
33  static const char* function("stan::math::logistic_log");
+ +
35  T_partials_return;
+
36 
+ + + + + +
42  using std::log;
+
43  using std::exp;
+
44 
+
45  // check if any vectors are zero length
+
46  if (!(stan::length(y)
+
47  && stan::length(mu)
+
48  && stan::length(sigma)))
+
49  return 0.0;
+
50 
+
51  // set up return value accumulator
+
52  T_partials_return logp(0.0);
+
53 
+
54  // validate args (here done over var, which should be OK)
+
55  check_finite(function, "Random variable", y);
+
56  check_finite(function, "Location parameter", mu);
+
57  check_positive_finite(function, "Scale parameter", sigma);
+
58  check_consistent_sizes(function,
+
59  "Random variable", y,
+
60  "Location parameter", mu,
+
61  "Scale parameter", sigma);
+
62 
+
63  // check if no variables are involved and prop-to
+ +
65  return 0.0;
+
66 
+
67 
+
68  // set up template expressions wrapping scalars into vector views
+ +
70  operands_and_partials(y, mu, sigma);
+
71 
+
72  VectorView<const T_y> y_vec(y);
+
73  VectorView<const T_loc> mu_vec(mu);
+
74  VectorView<const T_scale> sigma_vec(sigma);
+
75  size_t N = max_size(y, mu, sigma);
+
76 
+ + +
79  T_partials_return, T_scale> log_sigma(length(sigma));
+
80  for (size_t i = 0; i < length(sigma); i++) {
+
81  inv_sigma[i] = 1.0 / value_of(sigma_vec[i]);
+ +
83  log_sigma[i] = log(value_of(sigma_vec[i]));
+
84  }
+
85 
+ +
87  T_partials_return, T_loc, T_scale>
+
88  exp_mu_div_sigma(max_size(mu, sigma));
+ +
90  T_partials_return, T_y, T_scale>
+
91  exp_y_div_sigma(max_size(y, sigma));
+ +
93  for (size_t n = 0; n < max_size(mu, sigma); n++)
+
94  exp_mu_div_sigma[n] = exp(value_of(mu_vec[n])
+
95  / value_of(sigma_vec[n]));
+
96  for (size_t n = 0; n < max_size(y, sigma); n++)
+
97  exp_y_div_sigma[n] = exp(value_of(y_vec[n])
+
98  / value_of(sigma_vec[n]));
+
99  }
+
100 
+
101  using stan::math::log1p;
+
102  for (size_t n = 0; n < N; n++) {
+
103  const T_partials_return y_dbl = value_of(y_vec[n]);
+
104  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
105 
+
106  const T_partials_return y_minus_mu = y_dbl - mu_dbl;
+
107  const T_partials_return y_minus_mu_div_sigma = y_minus_mu
+
108  * inv_sigma[n];
+
109  T_partials_return exp_m_y_minus_mu_div_sigma(0);
+ +
111  exp_m_y_minus_mu_div_sigma = exp(-y_minus_mu_div_sigma);
+
112  T_partials_return inv_1p_exp_y_minus_mu_div_sigma(0);
+ +
114  inv_1p_exp_y_minus_mu_div_sigma = 1 / (1 + exp(y_minus_mu_div_sigma));
+
115 
+ +
117  logp -= y_minus_mu_div_sigma;
+ +
119  logp -= log_sigma[n];
+ +
121  logp -= 2.0 * log1p(exp_m_y_minus_mu_div_sigma);
+
122 
+ +
124  operands_and_partials.d_x1[n]
+
125  += (2 * inv_1p_exp_y_minus_mu_div_sigma - 1) * inv_sigma[n];
+ +
127  operands_and_partials.d_x2[n] +=
+
128  (1 - 2 * exp_mu_div_sigma[n] / (exp_mu_div_sigma[n]
+
129  + exp_y_div_sigma[n]))
+
130  * inv_sigma[n];
+ +
132  operands_and_partials.d_x3[n] +=
+
133  ((1 - 2 * inv_1p_exp_y_minus_mu_div_sigma)
+
134  *y_minus_mu*inv_sigma[n] - 1) * inv_sigma[n];
+
135  }
+
136  return operands_and_partials.value(logp);
+
137  }
+
138 
+
139  template <typename T_y, typename T_loc, typename T_scale>
+
140  inline
+ +
142  logistic_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
143  return logistic_log<false>(y, mu, sigma);
+
144  }
+
145  }
+
146 }
+
147 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
return_type< T_y, T_loc, T_scale >::type logistic_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/logistic__rng_8hpp.html b/doc/api/html/logistic__rng_8hpp.html new file mode 100644 index 00000000000..66e32f00343 --- /dev/null +++ b/doc/api/html/logistic__rng_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::logistic_rng (const double mu, const double sigma, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/logistic__rng_8hpp_source.html b/doc/api/html/logistic__rng_8hpp_source.html new file mode 100644 index 00000000000..53ef78f87f3 --- /dev/null +++ b/doc/api/html/logistic__rng_8hpp_source.html @@ -0,0 +1,170 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/logistic_rng.hpp Source File + + + + + + + + + + +
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logistic_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGISTIC_RNG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/exponential_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 
+
19 namespace stan {
+
20  namespace math {
+
21 
+
22  template <class RNG>
+
23  inline double
+
24  logistic_rng(const double mu,
+
25  const double sigma,
+
26  RNG& rng) {
+
27  using boost::variate_generator;
+
28  using boost::random::exponential_distribution;
+
29 
+
30  static const char* function("stan::math::logistic_rng");
+
31 
+ + +
34 
+
35  check_finite(function, "Location parameter", mu);
+
36  check_positive_finite(function, "Scale parameter", sigma);
+
37 
+
38  variate_generator<RNG&, exponential_distribution<> >
+
39  exp_rng(rng, exponential_distribution<>(1));
+
40  return mu - sigma * std::log(exp_rng() / exp_rng());
+
41  }
+
42  }
+
43 }
+
44 #endif
+ + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ + + +
double logistic_rng(const double mu, const double sigma, RNG &rng)
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
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diff --git a/doc/api/html/lognormal__ccdf__log_8hpp.html b/doc/api/html/lognormal__ccdf__log_8hpp.html new file mode 100644 index 00000000000..3dc5f9ca128 --- /dev/null +++ b/doc/api/html/lognormal__ccdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::lognormal_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
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diff --git a/doc/api/html/lognormal__ccdf__log_8hpp_source.html b/doc/api/html/lognormal__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..74976494d48 --- /dev/null +++ b/doc/api/html/lognormal__ccdf__log_8hpp_source.html @@ -0,0 +1,240 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_ccdf_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/lognormal_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_loc, typename T_scale>
+
24  typename return_type<T_y, T_loc, T_scale>::type
+
25  lognormal_ccdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
26  static const char* function("stan::math::lognormal_ccdf_log");
+ +
28  T_partials_return;
+
29 
+
30  T_partials_return ccdf_log = 0.0;
+
31 
+ + + + +
36  using boost::math::tools::promote_args;
+ +
38  using std::log;
+
39  using std::exp;
+
40 
+
41  // check if any vectors are zero length
+
42  if (!(stan::length(y)
+
43  && stan::length(mu)
+
44  && stan::length(sigma)))
+
45  return ccdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_nonnegative(function, "Random variable", y);
+
49  check_finite(function, "Location parameter", mu);
+
50  check_positive_finite(function, "Scale parameter", sigma);
+
51 
+ +
53  operands_and_partials(y, mu, sigma);
+
54 
+
55  VectorView<const T_y> y_vec(y);
+
56  VectorView<const T_loc> mu_vec(mu);
+
57  VectorView<const T_scale> sigma_vec(sigma);
+
58  size_t N = max_size(y, mu, sigma);
+
59 
+
60  const double sqrt_pi = std::sqrt(stan::math::pi());
+
61 
+
62  for (size_t i = 0; i < stan::length(y); i++) {
+
63  if (value_of(y_vec[i]) == 0.0)
+
64  return operands_and_partials.value(0.0);
+
65  }
+
66 
+
67  const double log_half = std::log(0.5);
+
68 
+
69  for (size_t n = 0; n < N; n++) {
+
70  const T_partials_return y_dbl = value_of(y_vec[n]);
+
71  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
72  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
73  const T_partials_return scaled_diff = (log(y_dbl) - mu_dbl)
+
74  / (sigma_dbl * SQRT_2);
+
75  const T_partials_return rep_deriv = SQRT_2 / sqrt_pi
+
76  * exp(-scaled_diff * scaled_diff) / sigma_dbl;
+
77 
+
78  // ccdf_log
+
79  const T_partials_return erfc_calc = erfc(scaled_diff);
+
80  ccdf_log += log_half + log(erfc_calc);
+
81 
+
82  // gradients
+ +
84  operands_and_partials.d_x1[n] -= rep_deriv / erfc_calc / y_dbl;
+ +
86  operands_and_partials.d_x2[n] += rep_deriv / erfc_calc;
+ +
88  operands_and_partials.d_x3[n] += rep_deriv * scaled_diff * SQRT_2
+
89  / erfc_calc;
+
90  }
+
91 
+
92  return operands_and_partials.value(ccdf_log);
+
93  }
+
94  }
+
95 }
+
96 #endif
+ +
return_type< T_y, T_loc, T_scale >::type lognormal_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lognormal__cdf_8hpp.html b/doc/api/html/lognormal__cdf_8hpp.html new file mode 100644 index 00000000000..20434b43fcd --- /dev/null +++ b/doc/api/html/lognormal__cdf_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_cdf.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::lognormal_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
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diff --git a/doc/api/html/lognormal__cdf_8hpp_source.html b/doc/api/html/lognormal__cdf_8hpp_source.html new file mode 100644 index 00000000000..21e84f71517 --- /dev/null +++ b/doc/api/html/lognormal__cdf_8hpp_source.html @@ -0,0 +1,252 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_cdf.hpp Source File + + + + + + + + + + +
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lognormal_cdf.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_CDF_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/lognormal_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_loc, typename T_scale>
+
24  typename return_type<T_y, T_loc, T_scale>::type
+
25  lognormal_cdf(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
26  static const char* function("stan::math::lognormal_cdf");
+
27 
+ +
29  T_partials_return;
+
30 
+
31  T_partials_return cdf = 1.0;
+
32 
+ + + + +
37  using boost::math::tools::promote_args;
+ +
39  using std::exp;
+
40  using std::log;
+
41 
+
42  // check if any vectors are zero length
+
43  if (!(stan::length(y)
+
44  && stan::length(mu)
+
45  && stan::length(sigma)))
+
46  return cdf;
+
47 
+
48  check_not_nan(function, "Random variable", y);
+
49  check_nonnegative(function, "Random variable", y);
+
50  check_finite(function, "Location parameter", mu);
+
51  check_positive_finite(function, "Scale parameter", sigma);
+
52 
+ +
54  operands_and_partials(y, mu, sigma);
+
55 
+
56  VectorView<const T_y> y_vec(y);
+
57  VectorView<const T_loc> mu_vec(mu);
+
58  VectorView<const T_scale> sigma_vec(sigma);
+
59  size_t N = max_size(y, mu, sigma);
+
60 
+
61  const double sqrt_pi = std::sqrt(stan::math::pi());
+
62 
+
63  for (size_t i = 0; i < stan::length(y); i++) {
+
64  if (value_of(y_vec[i]) == 0.0)
+
65  return operands_and_partials.value(0.0);
+
66  }
+
67 
+
68  for (size_t n = 0; n < N; n++) {
+
69  const T_partials_return y_dbl = value_of(y_vec[n]);
+
70  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
71  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
72  const T_partials_return scaled_diff = (log(y_dbl) - mu_dbl)
+
73  / (sigma_dbl * SQRT_2);
+
74  const T_partials_return rep_deriv = SQRT_2 * 0.5 / sqrt_pi
+
75  * exp(-scaled_diff * scaled_diff) / sigma_dbl;
+
76 
+
77  // cdf
+
78  const T_partials_return cdf_ = 0.5 * erfc(-scaled_diff);
+
79  cdf *= cdf_;
+
80 
+
81  // gradients
+ +
83  operands_and_partials.d_x1[n] += rep_deriv / cdf_ / y_dbl;
+ +
85  operands_and_partials.d_x2[n] -= rep_deriv / cdf_;
+ +
87  operands_and_partials.d_x3[n] -= rep_deriv * scaled_diff * SQRT_2
+
88  / cdf_;
+
89  }
+
90 
+ +
92  for (size_t n = 0; n < stan::length(y); ++n)
+
93  operands_and_partials.d_x1[n] *= cdf;
+
94  }
+ +
96  for (size_t n = 0; n < stan::length(mu); ++n)
+
97  operands_and_partials.d_x2[n] *= cdf;
+
98  }
+ +
100  for (size_t n = 0; n < stan::length(sigma); ++n)
+
101  operands_and_partials.d_x3[n] *= cdf;
+
102  }
+
103 
+
104  return operands_and_partials.value(cdf);
+
105  }
+
106  }
+
107 }
+
108 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
return_type< T_y, T_loc, T_scale >::type lognormal_cdf(const T_y &y, const T_loc &mu, const T_scale &sigma)
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lognormal__cdf__log_8hpp.html b/doc/api/html/lognormal__cdf__log_8hpp.html new file mode 100644 index 00000000000..67106a6d819 --- /dev/null +++ b/doc/api/html/lognormal__cdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
lognormal_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::lognormal_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lognormal__cdf__log_8hpp_source.html b/doc/api/html/lognormal__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..aac7c1bd81a --- /dev/null +++ b/doc/api/html/lognormal__cdf__log_8hpp_source.html @@ -0,0 +1,241 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
lognormal_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/lognormal_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_loc, typename T_scale>
+
24  typename return_type<T_y, T_loc, T_scale>::type
+
25  lognormal_cdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
26  static const char* function("stan::math::lognormal_cdf_log");
+ +
28  T_partials_return;
+
29 
+
30  T_partials_return cdf_log = 0.0;
+
31 
+ + + + +
36  using boost::math::tools::promote_args;
+ +
38  using std::log;
+
39  using std::exp;
+
40 
+
41  // check if any vectors are zero length
+
42  if (!(stan::length(y)
+
43  && stan::length(mu)
+
44  && stan::length(sigma)))
+
45  return cdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_nonnegative(function, "Random variable", y);
+
49  check_finite(function, "Location parameter", mu);
+
50  check_positive_finite(function, "Scale parameter", sigma);
+
51 
+ +
53  operands_and_partials(y, mu, sigma);
+
54 
+
55  VectorView<const T_y> y_vec(y);
+
56  VectorView<const T_loc> mu_vec(mu);
+
57  VectorView<const T_scale> sigma_vec(sigma);
+
58  size_t N = max_size(y, mu, sigma);
+
59 
+
60  const double sqrt_pi = std::sqrt(stan::math::pi());
+
61 
+
62  for (size_t i = 0; i < stan::length(y); i++) {
+
63  if (value_of(y_vec[i]) == 0.0)
+
64  return operands_and_partials.value(stan::math::negative_infinity());
+
65  }
+
66 
+
67  const double log_half = std::log(0.5);
+
68 
+
69  for (size_t n = 0; n < N; n++) {
+
70  const T_partials_return y_dbl = value_of(y_vec[n]);
+
71  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
72  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
73  const T_partials_return scaled_diff = (log(y_dbl) - mu_dbl)
+
74  / (sigma_dbl * SQRT_2);
+
75  const T_partials_return rep_deriv = SQRT_2 / sqrt_pi
+
76  * exp(-scaled_diff * scaled_diff) / sigma_dbl;
+
77 
+
78  // cdf_log
+
79  const T_partials_return erfc_calc = erfc(-scaled_diff);
+
80  cdf_log += log_half + log(erfc_calc);
+
81 
+
82  // gradients
+ +
84  operands_and_partials.d_x1[n] += rep_deriv / erfc_calc / y_dbl;
+ +
86  operands_and_partials.d_x2[n] -= rep_deriv / erfc_calc;
+ +
88  operands_and_partials.d_x3[n] -= rep_deriv * scaled_diff * SQRT_2
+
89  / erfc_calc;
+
90  }
+
91 
+
92  return operands_and_partials.value(cdf_log);
+
93  }
+
94  }
+
95 }
+
96 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
return_type< T_y, T_loc, T_scale >::type lognormal_cdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lognormal__log_8hpp.html b/doc/api/html/lognormal__log_8hpp.html new file mode 100644 index 00000000000..e2da56bae61 --- /dev/null +++ b/doc/api/html/lognormal__log_8hpp.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
lognormal_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::lognormal_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::lognormal_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lognormal__log_8hpp_source.html b/doc/api/html/lognormal__log_8hpp_source.html new file mode 100644 index 00000000000..3ed145c2cec --- /dev/null +++ b/doc/api/html/lognormal__log_8hpp_source.html @@ -0,0 +1,315 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
lognormal_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_LOG_HPP
+
3 
+
4 #include <boost/random/lognormal_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + +
23 #include <cmath>
+
24 
+
25 namespace stan {
+
26  namespace math {
+
27 
+
28  // LogNormal(y|mu, sigma) [y >= 0; sigma > 0]
+
29  // FIXME: document
+
30  template <bool propto,
+
31  typename T_y, typename T_loc, typename T_scale>
+
32  typename return_type<T_y, T_loc, T_scale>::type
+
33  lognormal_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
34  static const char* function("stan::math::lognormal_log");
+ +
36  T_partials_return;
+
37 
+ + + + + + + + +
46 
+
47 
+
48  // check if any vectors are zero length
+
49  if (!(stan::length(y)
+
50  && stan::length(mu)
+
51  && stan::length(sigma)))
+
52  return 0.0;
+
53 
+
54  // set up return value accumulator
+
55  T_partials_return logp(0.0);
+
56 
+
57  // validate args (here done over var, which should be OK)
+
58  check_not_nan(function, "Random variable", y);
+
59  check_nonnegative(function, "Random variable", y);
+
60  check_finite(function, "Location parameter", mu);
+
61  check_positive_finite(function, "Scale parameter", sigma);
+
62  check_consistent_sizes(function,
+
63  "Random variable", y,
+
64  "Location parameter", mu,
+
65  "Scale parameter", sigma);
+
66 
+
67  VectorView<const T_y> y_vec(y);
+
68  VectorView<const T_loc> mu_vec(mu);
+
69  VectorView<const T_scale> sigma_vec(sigma);
+
70  size_t N = max_size(y, mu, sigma);
+
71 
+
72  for (size_t n = 0; n < length(y); n++)
+
73  if (value_of(y_vec[n]) <= 0)
+
74  return LOG_ZERO;
+
75 
+ +
77  operands_and_partials(y, mu, sigma);
+
78 
+
79  using stan::math::square;
+
80  using std::log;
+ +
82  using std::log;
+
83 
+
84 
+ +
86  T_partials_return, T_scale> log_sigma(length(sigma));
+ +
88  for (size_t n = 0; n < length(sigma); n++)
+
89  log_sigma[n] = log(value_of(sigma_vec[n]));
+
90  }
+
91 
+ +
93  T_partials_return, T_scale> inv_sigma(length(sigma));
+ +
95  T_partials_return, T_scale> inv_sigma_sq(length(sigma));
+ +
97  for (size_t n = 0; n < length(sigma); n++)
+
98  inv_sigma[n] = 1 / value_of(sigma_vec[n]);
+
99  }
+ +
101  for (size_t n = 0; n < length(sigma); n++)
+
102  inv_sigma_sq[n] = inv_sigma[n] * inv_sigma[n];
+
103  }
+
104 
+ +
106  T_partials_return, T_y> log_y(length(y));
+ +
108  for (size_t n = 0; n < length(y); n++)
+
109  log_y[n] = log(value_of(y_vec[n]));
+
110  }
+
111 
+ +
113  T_partials_return, T_y> inv_y(length(y));
+ +
115  for (size_t n = 0; n < length(y); n++)
+
116  inv_y[n] = 1 / value_of(y_vec[n]);
+
117  }
+
118 
+ +
120  logp += N * NEG_LOG_SQRT_TWO_PI;
+
121 
+
122  for (size_t n = 0; n < N; n++) {
+
123  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
124 
+
125  T_partials_return logy_m_mu(0);
+ +
127  logy_m_mu = log_y[n] - mu_dbl;
+
128 
+
129  T_partials_return logy_m_mu_sq = logy_m_mu * logy_m_mu;
+
130  T_partials_return logy_m_mu_div_sigma(0);
+ +
132  logy_m_mu_div_sigma = logy_m_mu * inv_sigma_sq[n];
+
133 
+
134 
+
135  // log probability
+ +
137  logp -= log_sigma[n];
+ +
139  logp -= log_y[n];
+ +
141  logp -= 0.5 * logy_m_mu_sq * inv_sigma_sq[n];
+
142 
+
143  // gradients
+ +
145  operands_and_partials.d_x1[n] -= (1 + logy_m_mu_div_sigma) * inv_y[n];
+ +
147  operands_and_partials.d_x2[n] += logy_m_mu_div_sigma;
+ +
149  operands_and_partials.d_x3[n]
+
150  += (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma[n];
+
151  }
+
152  return operands_and_partials.value(logp);
+
153  }
+
154 
+
155  template <typename T_y, typename T_loc, typename T_scale>
+
156  inline
+ +
158  lognormal_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
159  return lognormal_log<false>(y, mu, sigma);
+
160  }
+
161  }
+
162 }
+
163 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ + +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
return_type< T_y, T_loc, T_scale >::type lognormal_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/lognormal__rng_8hpp.html b/doc/api/html/lognormal__rng_8hpp.html new file mode 100644 index 00000000000..567e4905c12 --- /dev/null +++ b/doc/api/html/lognormal__rng_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::lognormal_rng (const double mu, const double sigma, RNG &rng)
 
+
+
+
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diff --git a/doc/api/html/lognormal__rng_8hpp_source.html b/doc/api/html/lognormal__rng_8hpp_source.html new file mode 100644 index 00000000000..90e2e86a89c --- /dev/null +++ b/doc/api/html/lognormal__rng_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/lognormal_rng.hpp Source File + + + + + + + + + + +
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lognormal_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_LOGNORMAL_RNG_HPP
+
3 
+
4 #include <boost/random/lognormal_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + +
15 
+
16 namespace stan {
+
17  namespace math {
+
18 
+
19  template <class RNG>
+
20  inline double
+
21  lognormal_rng(const double mu,
+
22  const double sigma,
+
23  RNG& rng) {
+
24  using boost::variate_generator;
+
25  using boost::random::lognormal_distribution;
+
26 
+
27  static const char* function("stan::math::lognormal_rng");
+
28 
+ + +
31 
+
32  check_finite(function, "Location parameter", mu);
+
33  check_positive_finite(function, "Scale parameter", sigma);
+
34 
+
35  variate_generator<RNG&, lognormal_distribution<> >
+
36  lognorm_rng(rng, lognormal_distribution<>(mu, sigma));
+
37  return lognorm_rng();
+
38  }
+
39  }
+
40 }
+
41 #endif
+ + + + +
double lognormal_rng(const double mu, const double sigma, RNG &rng)
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
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diff --git a/doc/api/html/lub__constrain_8hpp.html b/doc/api/html/lub__constrain_8hpp.html new file mode 100644 index 00000000000..18fbce1779e --- /dev/null +++ b/doc/api/html/lub__constrain_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lub_constrain.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/err/check_less.hpp>
+#include <stan/math/prim/scal/fun/lb_constrain.hpp>
+#include <stan/math/prim/scal/fun/ub_constrain.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <cmath>
+#include <limits>
+#include <stdexcept>
+
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template<typename T , typename TL , typename TU >
boost::math::tools::promote_args< T, TL, TU >::type stan::math::lub_constrain (const T x, TL lb, TU ub)
 Return the lower- and upper-bounded scalar derived by transforming the specified free scalar given the specified lower and upper bounds. More...
 
template<typename T , typename TL , typename TU >
boost::math::tools::promote_args< T, TL, TU >::type stan::math::lub_constrain (const T x, const TL lb, const TU ub, T &lp)
 Return the lower- and upper-bounded scalar derived by transforming the specified free scalar given the specified lower and upper bounds and increment the specified log probability with the log absolute Jacobian determinant. More...
 
+
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diff --git a/doc/api/html/lub__constrain_8hpp_source.html b/doc/api/html/lub__constrain_8hpp_source.html new file mode 100644 index 00000000000..30cf1216089 --- /dev/null +++ b/doc/api/html/lub__constrain_8hpp_source.html @@ -0,0 +1,207 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lub_constrain.hpp Source File + + + + + + + + + + +
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lub_constrain.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LUB_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LUB_CONSTRAIN_HPP
+
3 
+ + + +
7 #include <boost/math/tools/promotion.hpp>
+
8 #include <cmath>
+
9 #include <limits>
+
10 #include <stdexcept>
+
11 
+
12 namespace stan {
+
13 
+
14  namespace math {
+
42  template <typename T, typename TL, typename TU>
+
43  inline
+
44  typename boost::math::tools::promote_args<T, TL, TU>::type
+
45  lub_constrain(const T x, TL lb, TU ub) {
+
46  using std::exp;
+
47  stan::math::check_less("lub_constrain", "lb", lb, ub);
+
48  if (lb == -std::numeric_limits<double>::infinity())
+
49  return ub_constrain(x, ub);
+
50  if (ub == std::numeric_limits<double>::infinity())
+
51  return lb_constrain(x, lb);
+
52 
+
53  T inv_logit_x;
+
54  if (x > 0) {
+
55  T exp_minus_x = exp(-x);
+
56  inv_logit_x = 1.0 / (1.0 + exp_minus_x);
+
57  // Prevent x from reaching one unless it really really should.
+
58  if ((x < std::numeric_limits<double>::infinity())
+
59  && (inv_logit_x == 1))
+
60  inv_logit_x = 1 - 1e-15;
+
61  } else {
+
62  T exp_x = exp(x);
+
63  inv_logit_x = 1.0 - 1.0 / (1.0 + exp_x);
+
64  // Prevent x from reaching zero unless it really really should.
+
65  if ((x > -std::numeric_limits<double>::infinity())
+
66  && (inv_logit_x== 0))
+
67  inv_logit_x = 1e-15;
+
68  }
+
69  return lb + (ub - lb) * inv_logit_x;
+
70  }
+
71 
+
113  template <typename T, typename TL, typename TU>
+
114  typename boost::math::tools::promote_args<T, TL, TU>::type
+
115  lub_constrain(const T x, const TL lb, const TU ub, T& lp) {
+
116  using std::log;
+
117  using std::exp;
+
118  if (!(lb < ub)) {
+
119  std::stringstream s;
+
120  s << "domain error in lub_constrain; lower bound = " << lb
+
121  << " must be strictly less than upper bound = " << ub;
+
122  throw std::domain_error(s.str());
+
123  }
+
124  if (lb == -std::numeric_limits<double>::infinity())
+
125  return ub_constrain(x, ub, lp);
+
126  if (ub == std::numeric_limits<double>::infinity())
+
127  return lb_constrain(x, lb, lp);
+
128  T inv_logit_x;
+
129  if (x > 0) {
+
130  T exp_minus_x = exp(-x);
+
131  inv_logit_x = 1.0 / (1.0 + exp_minus_x);
+
132  lp += log(ub - lb) - x - 2 * log1p(exp_minus_x);
+
133  // Prevent x from reaching one unless it really really should.
+
134  if ((x < std::numeric_limits<double>::infinity())
+
135  && (inv_logit_x == 1))
+
136  inv_logit_x = 1 - 1e-15;
+
137  } else {
+
138  T exp_x = exp(x);
+
139  inv_logit_x = 1.0 - 1.0 / (1.0 + exp_x);
+
140  lp += log(ub - lb) + x - 2 * log1p(exp_x);
+
141  // Prevent x from reaching zero unless it really really should.
+
142  if ((x > -std::numeric_limits<double>::infinity())
+
143  && (inv_logit_x== 0))
+
144  inv_logit_x = 1e-15;
+
145  }
+
146  return lb + (ub - lb) * inv_logit_x;
+
147  }
+
148 
+
149  }
+
150 
+
151 }
+
152 
+
153 #endif
+ +
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T lb_constrain(const T x, const TL lb)
Return the lower-bounded value for the specified unconstrained input and specified lower bound...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+
boost::math::tools::promote_args< T, TU >::type ub_constrain(const T x, const TU ub)
Return the upper-bounded value for the specified unconstrained scalar and upper bound.
+ +
boost::math::tools::promote_args< T, TL, TU >::type lub_constrain(const T x, TL lb, TU ub)
Return the lower- and upper-bounded scalar derived by transforming the specified free scalar given th...
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/lub__free_8hpp.html b/doc/api/html/lub__free_8hpp.html new file mode 100644 index 00000000000..82e51d2c4e1 --- /dev/null +++ b/doc/api/html/lub__free_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lub_free.hpp File Reference + + + + + + + + + + +
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template<typename T , typename TL , typename TU >
boost::math::tools::promote_args< T, TL, TU >::type stan::math::lub_free (const T y, TL lb, TU ub)
 Return the unconstrained scalar that transforms to the specified lower- and upper-bounded scalar given the specified bounds. More...
 
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diff --git a/doc/api/html/lub__free_8hpp_source.html b/doc/api/html/lub__free_8hpp_source.html new file mode 100644 index 00000000000..551bc3708a3 --- /dev/null +++ b/doc/api/html/lub__free_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lub_free.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LUB_FREE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LUB_FREE_HPP
+
3 
+ + + + +
8 #include <limits>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
44  template <typename T, typename TL, typename TU>
+
45  inline
+
46  typename boost::math::tools::promote_args<T, TL, TU>::type
+
47  lub_free(const T y, TL lb, TU ub) {
+
48  using stan::math::logit;
+
49  stan::math::check_bounded<T, TL, TU>
+
50  ("stan::math::lub_free",
+
51  "Bounded variable",
+
52  y, lb, ub);
+
53  if (lb == -std::numeric_limits<double>::infinity())
+
54  return ub_free(y, ub);
+
55  if (ub == std::numeric_limits<double>::infinity())
+
56  return lb_free(y, lb);
+
57  return logit((y - lb) / (ub - lb));
+
58  }
+
59 
+
60  }
+
61 
+
62 }
+
63 
+
64 #endif
+ + +
boost::math::tools::promote_args< T, TL, TU >::type lub_free(const T y, TL lb, TU ub)
Return the unconstrained scalar that transforms to the specified lower- and upper-bounded scalar give...
Definition: lub_free.hpp:47
+
boost::math::tools::promote_args< T, TU >::type ub_free(const T y, const TU ub)
Return the free scalar that corresponds to the specified upper-bounded value with respect to the spec...
Definition: ub_free.hpp:39
+
boost::math::tools::promote_args< T, TL >::type lb_free(const T y, const TL lb)
Return the unconstrained value that produces the specified lower-bound constrained value...
Definition: lb_free.hpp:32
+ + +
fvar< T > logit(const fvar< T > &x)
Definition: logit.hpp:17
+ +
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diff --git a/doc/api/html/mainpage_8dox.html b/doc/api/html/mainpage_8dox.html new file mode 100644 index 00000000000..d5fa99a55c0 --- /dev/null +++ b/doc/api/html/mainpage_8dox.html @@ -0,0 +1,105 @@ + + + + + + +Stan Math Library: doxygen/mainpage.dox File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/make__nu_8hpp.html b/doc/api/html/make__nu_8hpp.html new file mode 100644 index 00000000000..42025737d92 --- /dev/null +++ b/doc/api/html/make__nu_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/make_nu.hpp File Reference + + + + + + + + + + +
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template<typename T >
const Eigen::Array< T, Eigen::Dynamic, 1 > stan::math::make_nu (const T eta, const size_t K)
 This function calculates the degrees of freedom for the t distribution that corresponds to the shape parameter in the Lewandowski et. More...
 
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diff --git a/doc/api/html/make__nu_8hpp_source.html b/doc/api/html/make__nu_8hpp_source.html new file mode 100644 index 00000000000..faaa38ce78f --- /dev/null +++ b/doc/api/html/make__nu_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/make_nu.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MAKE_NU_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MAKE_NU_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
20  template<typename T>
+
21  const Eigen::Array<T, Eigen::Dynamic, 1>
+
22  make_nu(const T eta, const size_t K) {
+
23  using Eigen::Array;
+
24  using Eigen::Dynamic;
+
25  using Eigen::Matrix;
+ +
27  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
28 
+
29  Array<T, Dynamic, 1> nu(K * (K - 1) / 2);
+
30 
+
31  T alpha = eta + (K - 2.0) / 2.0; // from Lewandowski et. al.
+
32 
+
33  // Best (1978) implies nu = 2 * alpha for the dof in a t
+
34  // distribution that generates a beta variate on (-1, 1)
+
35  T alpha2 = 2.0 * alpha;
+
36  for (size_type j = 0; j < (K - 1); j++) {
+
37  nu(j) = alpha2;
+
38  }
+
39  size_t counter = K - 1;
+
40  for (size_type i = 1; i < (K - 1); i++) {
+
41  alpha -= 0.5;
+
42  alpha2 = 2.0 * alpha;
+
43  for (size_type j = i + 1; j < K; j++) {
+
44  nu(counter) = alpha2;
+
45  counter++;
+
46  }
+
47  }
+
48  return nu;
+
49  }
+
50 
+
51  }
+
52 
+
53 }
+
54 
+
55 #endif
+ +
const Eigen::Array< T, Eigen::Dynamic, 1 > make_nu(const T eta, const size_t K)
This function calculates the degrees of freedom for the t distribution that corresponds to the shape ...
Definition: make_nu.hpp:22
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
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diff --git a/doc/api/html/mat_2err_2check__ordered_8hpp.html b/doc/api/html/mat_2err_2check__ordered_8hpp.html new file mode 100644 index 00000000000..d52967b679b --- /dev/null +++ b/doc/api/html/mat_2err_2check__ordered_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_ordered.hpp File Reference + + + + + + + + + + +
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+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stan/math/prim/scal/err/domain_error.hpp>
+#include <stan/math/prim/scal/meta/error_index.hpp>
+#include <sstream>
+#include <string>
+#include <vector>
+
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template<typename T_y >
bool stan::math::check_ordered (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, 1 > &y)
 Return true if the specified vector is sorted into strictly increasing order. More...
 
+
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diff --git a/doc/api/html/mat_2err_2check__ordered_8hpp_source.html b/doc/api/html/mat_2err_2check__ordered_8hpp_source.html new file mode 100644 index 00000000000..5f5f190b4c2 --- /dev/null +++ b/doc/api/html/mat_2err_2check__ordered_8hpp_source.html @@ -0,0 +1,167 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/check_ordered.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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1 #ifndef STAN_MATH_PRIM_MAT_ERR_CHECK_ORDERED_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_CHECK_ORDERED_HPP
+
3 
+ + + + +
8 #include <sstream>
+
9 #include <string>
+
10 #include <vector>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
30  template <typename T_y>
+
31  bool check_ordered(const char* function,
+
32  const char* name,
+
33  const Eigen::Matrix<T_y, Eigen::Dynamic, 1>& y) {
+
34  using Eigen::Dynamic;
+
35  using Eigen::Matrix;
+ +
37 
+
38  typedef typename index_type<Matrix<T_y, Dynamic, 1> >::type size_t;
+
39 
+
40  if (y.size() == 0)
+
41  return true;
+
42 
+
43  for (size_t n = 1; n < y.size(); n++) {
+
44  if (!(y[n] > y[n-1])) {
+
45  std::ostringstream msg1;
+
46  msg1 << "is not a valid ordered vector."
+
47  << " The element at " << stan::error_index::value + n
+
48  << " is ";
+
49  std::string msg1_str(msg1.str());
+
50  std::ostringstream msg2;
+
51  msg2 << ", but should be greater than the previous element, "
+
52  << y[n-1];
+
53  std::string msg2_str(msg2.str());
+
54  domain_error(function, name, y[n],
+
55  msg1_str.c_str(), msg2_str.c_str());
+
56  return false;
+
57  }
+
58  }
+
59  return true;
+
60  }
+
61 
+
62  }
+
63 }
+
64 #endif
+ +
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
bool check_ordered(const char *function, const char *name, const std::vector< T_y > &y)
Return true if the specified vector is sorted into strictly increasing order.
+ + +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ + + +
+
+
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diff --git a/doc/api/html/mat_2fun_2fill_8hpp.html b/doc/api/html/mat_2fun_2fill_8hpp.html new file mode 100644 index 00000000000..c0ed43e5544 --- /dev/null +++ b/doc/api/html/mat_2fun_2fill_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/fill.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C, typename S >
void stan::math::fill (Eigen::Matrix< T, R, C > &x, const S &y)
 Fill the specified container with the specified value. More...
 
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diff --git a/doc/api/html/mat_2fun_2fill_8hpp_source.html b/doc/api/html/mat_2fun_2fill_8hpp_source.html new file mode 100644 index 00000000000..9efa0bff51b --- /dev/null +++ b/doc/api/html/mat_2fun_2fill_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/fill.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_FILL_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_FILL_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
21  template <typename T, int R, int C, typename S>
+
22  void fill(Eigen::Matrix<T, R, C>& x, const S& y) {
+
23  x.fill(y);
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+ + +
void fill(std::vector< T > &x, const S &y)
Fill the specified container with the specified value.
Definition: fill.hpp:22
+
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diff --git a/doc/api/html/mat_2fun_2grad_8hpp.html b/doc/api/html/mat_2fun_2grad_8hpp.html new file mode 100644 index 00000000000..135da18eab1 --- /dev/null +++ b/doc/api/html/mat_2fun_2grad_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/grad.hpp File Reference + + + + + + + + + + +
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void stan::math::grad (var &v, Eigen::Matrix< var, Eigen::Dynamic, 1 > &x, Eigen::VectorXd &g)
 Propagate chain rule to calculate gradients starting from the specified variable. More...
 
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diff --git a/doc/api/html/mat_2fun_2grad_8hpp_source.html b/doc/api/html/mat_2fun_2grad_8hpp_source.html new file mode 100644 index 00000000000..597ce843946 --- /dev/null +++ b/doc/api/html/mat_2fun_2grad_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/grad.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_MAT_FUN_GRAD_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_GRAD_HPP
+
3 
+
4 
+ + +
7 #include <stan/math/rev/core.hpp>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
26  void grad(var& v,
+
27  Eigen::Matrix<var, Eigen::Dynamic, 1>& x,
+
28  Eigen::VectorXd& g) {
+ +
30  g.resize(x.size());
+
31  for (int i = 0; i < x.size(); ++i)
+
32  g(i) = x(i).vi_->adj_;
+
33  }
+
34 
+
35  }
+
36 }
+
37 
+
38 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
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diff --git a/doc/api/html/mat_2fun_2promote__scalar_8hpp.html b/doc/api/html/mat_2fun_2promote__scalar_8hpp.html new file mode 100644 index 00000000000..0831217fc1a --- /dev/null +++ b/doc/api/html/mat_2fun_2promote__scalar_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/promote_scalar.hpp File Reference + + + + + + + + + + +
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promote_scalar.hpp File Reference
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+ + + + + + + + + + + +

+Classes

struct  stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > >
 Struct to hold static function for promoting underlying scalar types. More...
 
struct  stan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > >
 Struct to hold static function for promoting underlying scalar types. More...
 
struct  stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > >
 Struct to hold static function for promoting underlying scalar types. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2fun_2promote__scalar_8hpp_source.html b/doc/api/html/mat_2fun_2promote__scalar_8hpp_source.html new file mode 100644 index 00000000000..587241d1c18 --- /dev/null +++ b/doc/api/html/mat_2fun_2promote__scalar_8hpp_source.html @@ -0,0 +1,178 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/promote_scalar.hpp Source File + + + + + + + + + + +
+
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promote_scalar.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_PROMOTE_SCALAR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_PROMOTE_SCALAR_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
20  template <typename T, typename S>
+
21  struct promote_scalar_struct<T, Eigen::Matrix<S, -1, -1> > {
+
30  static Eigen::Matrix<typename promote_scalar_type<T, S>::type, -1, -1>
+
31  apply(const Eigen::Matrix<S, -1, -1>& x) {
+
32  Eigen::Matrix<typename promote_scalar_type<T, S>::type, -1, -1>
+
33  y(x.rows(), x.cols());
+
34  for (int i = 0; i < x.size(); ++i)
+ +
36  return y;
+
37  }
+
38  };
+
39 
+
40 
+
49  template <typename T, typename S>
+
50  struct promote_scalar_struct<T, Eigen::Matrix<S, 1, -1> > {
+
59  static Eigen::Matrix<typename promote_scalar_type<T, S>::type, 1, -1>
+
60  apply(const Eigen::Matrix<S, 1, -1>& x) {
+
61  Eigen::Matrix<typename promote_scalar_type<T, S>::type, 1, -1>
+
62  y(x.rows(), x.cols());
+
63  for (int i = 0; i < x.size(); ++i)
+ +
65  return y;
+
66  }
+
67  };
+
68 
+
69 
+
78  template <typename T, typename S>
+
79  struct promote_scalar_struct<T, Eigen::Matrix<S, -1, 1> > {
+
88  static Eigen::Matrix<typename promote_scalar_type<T, S>::type, -1, 1>
+
89  apply(const Eigen::Matrix<S, -1, 1>& x) {
+
90  Eigen::Matrix<typename promote_scalar_type<T, S>::type, -1, 1>
+
91  y(x.rows(), x.cols());
+
92  for (int i = 0; i < x.size(); ++i)
+ +
94  return y;
+
95  }
+
96  };
+
97 
+
98 
+
99  }
+
100 }
+
101 
+
102 
+
103 #endif
+
104 
+
105 
+
106 
+
107 
+ + +
(Expert) Numerical traits for algorithmic differentiation variables.
+
General struct to hold static function for promoting underlying scalar types.
+ +
static Eigen::Matrix< typename promote_scalar_type< T, S >::type, 1,-1 > apply(const Eigen::Matrix< S, 1,-1 > &x)
Return the column vector consisting of the recursive promotion of the elements of the input column ve...
+ +
static T apply(S x)
Return the value of the input argument promoted to the type specified by the template parameter...
+
static Eigen::Matrix< typename promote_scalar_type< T, S >::type,-1,-1 > apply(const Eigen::Matrix< S,-1,-1 > &x)
Return the matrix consisting of the recursive promotion of the elements of the input matrix to the sc...
+
static Eigen::Matrix< typename promote_scalar_type< T, S >::type,-1, 1 > apply(const Eigen::Matrix< S,-1, 1 > &x)
Return the row vector consisting of the recursive promotion of the elements of the input row vector t...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2fun_2promote__scalar__type_8hpp.html b/doc/api/html/mat_2fun_2promote__scalar__type_8hpp.html new file mode 100644 index 00000000000..bf64df690c5 --- /dev/null +++ b/doc/api/html/mat_2fun_2promote__scalar__type_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/promote_scalar_type.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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+ + + + + + + + + + + +

+Classes

struct  stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >
 Template metaprogram to calculate a type for a matrix whose underlying scalar is converted from the second template parameter type to the first. More...
 
struct  stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >
 Template metaprogram to calculate a type for a vector whose underlying scalar is converted from the second template parameter type to the first. More...
 
struct  stan::math::promote_scalar_type< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >
 Template metaprogram to calculate a type for a row vector whose underlying scalar is converted from the second template parameter type to the first. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
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diff --git a/doc/api/html/mat_2fun_2promote__scalar__type_8hpp_source.html b/doc/api/html/mat_2fun_2promote__scalar__type_8hpp_source.html new file mode 100644 index 00000000000..db17df94946 --- /dev/null +++ b/doc/api/html/mat_2fun_2promote__scalar__type_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/promote_scalar_type.hpp Source File + + + + + + + + + + +
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promote_scalar_type.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_PROMOTE_SCALAR_TYPE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_PROMOTE_SCALAR_TYPE_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
22  template <typename T, typename S>
+
23  struct promote_scalar_type<T, Eigen::Matrix<S, Eigen::Dynamic,
+
24  Eigen::Dynamic> > {
+
28  typedef Eigen::Matrix<typename promote_scalar_type<T, S>::type,
+
29  Eigen::Dynamic, Eigen::Dynamic>
+ +
31  };
+
32 
+
33 
+
42  template <typename T, typename S>
+
43  struct promote_scalar_type<T, Eigen::Matrix<S, Eigen::Dynamic, 1> > {
+
47  typedef Eigen::Matrix<typename promote_scalar_type<T, S>::type,
+
48  Eigen::Dynamic, 1>
+ +
50  };
+
51 
+
52 
+
61  template <typename T, typename S>
+
62  struct promote_scalar_type<T, Eigen::Matrix<S, 1, Eigen::Dynamic> > {
+
66  typedef Eigen::Matrix<typename promote_scalar_type<T, S>::type,
+
67  1, Eigen::Dynamic>
+ +
69  };
+
70 
+
71 
+
72  }
+
73 
+
74 }
+
75 
+
76 #endif
+ +
(Expert) Numerical traits for algorithmic differentiation variables.
+
Eigen::Matrix< typename promote_scalar_type< T, S >::type, Eigen::Dynamic, 1 > type
The promoted type.
+
Template metaprogram to calculate a type for converting a convertible type.
+
Eigen::Matrix< typename promote_scalar_type< T, S >::type, Eigen::Dynamic, Eigen::Dynamic > type
The promoted type.
+
Eigen::Matrix< typename promote_scalar_type< T, S >::type, 1, Eigen::Dynamic > type
The promoted type.
+ + +
+
+
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diff --git a/doc/api/html/mat_2fun_2to__fvar_8hpp.html b/doc/api/html/mat_2fun_2to__fvar_8hpp.html new file mode 100644 index 00000000000..bfb09bb63b6 --- /dev/null +++ b/doc/api/html/mat_2fun_2to__fvar_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/to_fvar.hpp File Reference + + + + + + + + + + +
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template<int R, int C, typename T >
Eigen::Matrix< T, R, C > stan::math::to_fvar (const Eigen::Matrix< T, R, C > &m)
 
template<int R, int C>
Eigen::Matrix< fvar< double >, R, C > stan::math::to_fvar (const Eigen::Matrix< double, R, C > &m)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > stan::math::to_fvar (const Eigen::Matrix< T, R, C > &val, const Eigen::Matrix< T, R, C > &deriv)
 
+
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diff --git a/doc/api/html/mat_2fun_2to__fvar_8hpp_source.html b/doc/api/html/mat_2fun_2to__fvar_8hpp_source.html new file mode 100644 index 00000000000..ee54dad1cbe --- /dev/null +++ b/doc/api/html/mat_2fun_2to__fvar_8hpp_source.html @@ -0,0 +1,165 @@ + + + + + + +Stan Math Library: stan/math/fwd/mat/fun/to_fvar.hpp Source File + + + + + + + + + + +
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+
to_fvar.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_MAT_FUN_TO_FVAR_HPP
+
2 #define STAN_MATH_FWD_MAT_FUN_TO_FVAR_HPP
+
3 
+ +
5 #include <stan/math/fwd/core.hpp>
+ + +
8 
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template<int R, int C, typename T>
+
14  inline
+
15  Eigen::Matrix<T, R, C>
+
16  to_fvar(const Eigen::Matrix<T, R, C>& m) {
+
17  return m;
+
18  }
+
19 
+
20  template<int R, int C>
+
21  inline
+
22  Eigen::Matrix<fvar<double>, R, C>
+
23  to_fvar(const Eigen::Matrix<double, R, C>& m) {
+
24  Eigen::Matrix<fvar<double>, R, C> m_fd(m.rows(), m.cols());
+
25  for (int i = 0; i < m.size(); ++i)
+
26  m_fd(i) = m(i);
+
27  return m_fd;
+
28  }
+
29 
+
30  template<typename T, int R, int C>
+
31  inline
+
32  Eigen::Matrix<fvar<T>, R, C>
+
33  to_fvar(const Eigen::Matrix<T, R, C>& val,
+
34  const Eigen::Matrix<T, R, C>& deriv) {
+ +
36  "value", val,
+
37  "deriv", deriv);
+
38  Eigen::Matrix<fvar<T>, R, C> ret(val.rows(), val.cols());
+
39  for (int i = 0; i < val.rows(); i++) {
+
40  for (int j = 0; j < val.cols(); j++) {
+
41  ret(i, j).val_ = val(i, j);
+
42  ret(i, j).d_ = deriv(i, j);
+
43  }
+
44  }
+
45  return ret;
+
46  }
+
47  }
+
48 }
+
49 #endif
+ + + +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
+ + +
+
+
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diff --git a/doc/api/html/mat_2fun_2to__var_8hpp.html b/doc/api/html/mat_2fun_2to__var_8hpp.html new file mode 100644 index 00000000000..e0eac30a2ea --- /dev/null +++ b/doc/api/html/mat_2fun_2to__var_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/to_var.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
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 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + +

+Functions

matrix_v stan::math::to_var (const stan::math::matrix_d &m)
 Converts argument to an automatic differentiation variable. More...
 
matrix_v stan::math::to_var (const matrix_v &m)
 Converts argument to an automatic differentiation variable. More...
 
vector_v stan::math::to_var (const stan::math::vector_d &v)
 Converts argument to an automatic differentiation variable. More...
 
vector_v stan::math::to_var (const vector_v &v)
 Converts argument to an automatic differentiation variable. More...
 
row_vector_v stan::math::to_var (const stan::math::row_vector_d &rv)
 Converts argument to an automatic differentiation variable. More...
 
row_vector_v stan::math::to_var (const row_vector_v &rv)
 Converts argument to an automatic differentiation variable. More...
 
+
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diff --git a/doc/api/html/mat_2fun_2to__var_8hpp_source.html b/doc/api/html/mat_2fun_2to__var_8hpp_source.html new file mode 100644 index 00000000000..ee64b2cabe2 --- /dev/null +++ b/doc/api/html/mat_2fun_2to__var_8hpp_source.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/to_var.hpp Source File + + + + + + + + + + +
+
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to_var.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_TO_VAR_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_TO_VAR_HPP
+
3 
+ + +
6 #include <stan/math/rev/core.hpp>
+ + +
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+ +
22  matrix_v m_v(m.rows(), m.cols());
+
23  for (int j = 0; j < m.cols(); ++j)
+
24  for (int i = 0; i < m.rows(); ++i)
+
25  m_v(i, j) = m(i, j);
+
26  return m_v;
+
27  }
+
36  inline matrix_v to_var(const matrix_v& m) {
+
37  return m;
+
38  }
+ +
49  vector_v v_v(v.size());
+
50  for (int i = 0; i < v.size(); ++i)
+
51  v_v[i] = v[i];
+
52  return v_v;
+
53  }
+
63  inline vector_v to_var(const vector_v& v) {
+
64  return v;
+
65  }
+ +
76  row_vector_v rv_v(rv.size());
+
77  for (int i = 0; i < rv.size(); ++i)
+
78  rv_v[i] = rv[i];
+
79  return rv_v;
+
80  }
+
90  inline row_vector_v to_var(const row_vector_v& rv) {
+
91  return rv;
+
92  }
+
93 
+
94  }
+
95 }
+
96 #endif
+ +
Eigen::Matrix< var, Eigen::Dynamic, 1 > vector_v
The type of a (column) vector holding stan::math::var values.
Definition: typedefs.hpp:29
+
Eigen::Matrix< double, Eigen::Dynamic, 1 > vector_d
Type for (column) vector of double values.
Definition: typedefs.hpp:30
+ +
Eigen::Matrix< double, 1, Eigen::Dynamic > row_vector_d
Type for (row) vector of double values.
Definition: typedefs.hpp:37
+
Eigen::Matrix< var, Eigen::Dynamic, Eigen::Dynamic > matrix_v
The type of a matrix holding stan::math::var values.
Definition: typedefs.hpp:21
+ + + +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > matrix_d
Type for matrix of double values.
Definition: typedefs.hpp:23
+
Eigen::Matrix< var, 1, Eigen::Dynamic > row_vector_v
The type of a row vector holding stan::math::var values.
Definition: typedefs.hpp:37
+
std::vector< var > to_var(const std::vector< double > &v)
Converts argument to an automatic differentiation variable.
Definition: to_var.hpp:20
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2meta_2_vector_view_8hpp.html b/doc/api/html/mat_2meta_2_vector_view_8hpp.html new file mode 100644 index 00000000000..cfd46274b0b --- /dev/null +++ b/doc/api/html/mat_2meta_2_vector_view_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/VectorView.hpp File Reference + + + + + + + + + + +
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VectorView.hpp File Reference
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diff --git a/doc/api/html/mat_2meta_2_vector_view_8hpp_source.html b/doc/api/html/mat_2meta_2_vector_view_8hpp_source.html new file mode 100644 index 00000000000..f54b7c93c4b --- /dev/null +++ b/doc/api/html/mat_2meta_2_vector_view_8hpp_source.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/VectorView.hpp Source File + + + + + + + + + + +
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VectorView.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_MAT_SCAL_META_VECTORVIEW_HPP
+
2 #define STAN_MATH_MAT_SCAL_META_VECTORVIEW_HPP
+
3 
+ + + +
7 #include <boost/type_traits.hpp>
+
8 
+
9 namespace stan {
+
10 
+
11  template <typename T, int R, int C>
+
12  class VectorView<Eigen::Matrix<T, R, C>, true, false> {
+
13  public:
+
14  typedef typename scalar_type<T>::type scalar_t;
+
15 
+
16  template <typename X>
+
17  explicit VectorView(X& x) : x_(x.data()) { }
+
18 
+
19  scalar_t& operator[](int i) {
+
20  return x_[i];
+
21  }
+
22  private:
+
23  scalar_t* x_;
+
24  };
+
25 
+
26  template <typename T, int R, int C>
+
27  class VectorView<const Eigen::Matrix<T, R, C>, true, false> {
+
28  public:
+
29  typedef typename boost::add_const<typename scalar_type<T>::type>::type
+ +
31 
+
32  template <typename X>
+
33  explicit VectorView(X& x) : x_(x.data()) { }
+
34 
+
35  scalar_t& operator[](int i) const {
+
36  return x_[i];
+
37  }
+
38  private:
+
39  scalar_t* x_;
+
40  };
+
41 
+
42 }
+
43 #endif
+ + +
boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
Definition: VectorView.hpp:54
+ +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+
(Expert) Numerical traits for algorithmic differentiation variables.
+ +
boost::add_const< typename scalar_type< T >::type >::type scalar_t
Definition: VectorView.hpp:30
+ + + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2meta_2container__view_8hpp.html b/doc/api/html/mat_2meta_2container__view_8hpp.html new file mode 100644 index 00000000000..a1824554424 --- /dev/null +++ b/doc/api/html/mat_2meta_2container__view_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/container_view.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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container_view.hpp File Reference
+
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+ +

Go to the source code of this file.

+ + + + + + + + + + + +

+Classes

class  stan::math::container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >
 Template specialization for Eigen::Map view of array with scalar type T2 with size inferred from input Eigen::Matrix. More...
 
class  stan::math::container_view< Eigen::Matrix< T1, R, C >, T2 >
 Template specialization for scalar view of array y with scalar type T2. More...
 
class  stan::math::container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > >
 Template specialization for matrix view of array y with scalar type T2 with shape equal to x. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2meta_2container__view_8hpp_source.html b/doc/api/html/mat_2meta_2container__view_8hpp_source.html new file mode 100644 index 00000000000..fc38d2a6ab5 --- /dev/null +++ b/doc/api/html/mat_2meta_2container__view_8hpp_source.html @@ -0,0 +1,190 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/container_view.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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container_view.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_META_CONTAINER_VIEW_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_CONTAINER_VIEW_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
22  template <typename T1, typename T2, int R, int C>
+
23  class container_view<Eigen::Matrix<T1, R, C>, Eigen::Matrix<T2, R, C> > {
+
24  public:
+
32  container_view(const Eigen::Matrix<T1, R, C>& x, T2* y)
+
33  : y_(y, x.rows(), x.cols()) { }
+
34 
+
40  Eigen::Map<Eigen::Matrix<T2, R, C> >& operator[](int i) {
+
41  return y_;
+
42  }
+
43  private:
+
44  Eigen::Map<Eigen::Matrix<T2, R, C> > y_;
+
45  };
+
46 
+
57  template <typename T1, typename T2, int R, int C>
+
58  class container_view<Eigen::Matrix<T1, R, C>, T2> {
+
59  public:
+
66  container_view(const Eigen::Matrix<T1, R, C>& x, T2* y)
+
67  : y_(y) { }
+
68 
+
73  T2& operator[](int i) {
+
74  return y_[i];
+
75  }
+
76  private:
+
77  T2* y_;
+
78  };
+
79 
+
90  template <typename T1, typename T2, int R, int C>
+
91  class container_view<std::vector<Eigen::Matrix<T1, R, C> >,
+
92  Eigen::Matrix<T2, R, C> > {
+
93  public:
+
104  container_view(const std::vector<Eigen::Matrix<T1, R, C> >& x, T2* y)
+
105  : y_view(y, 1, 1), y_(y) {
+
106  if (x.size() > 0) {
+
107  rows = x[0].rows();
+
108  cols = x[0].cols();
+
109  } else {
+
110  rows = 0;
+
111  cols = 0;
+
112  }
+
113  }
+
114 
+
119  Eigen::Map<Eigen::Matrix<T2, R, C> >& operator[](int i) {
+
120  int offset = i * rows * cols;
+
121  new (&y_view) Eigen::Map<Eigen::Matrix<T2, R, C> >
+
122  (y_ + offset, rows, cols);
+
123  return y_view;
+
124  }
+
125  private:
+
126  Eigen::Map<Eigen::Matrix<T2, R, C> > y_view;
+
127  T2* y_;
+
128  int rows;
+
129  int cols;
+
130  };
+
131  }
+
132 }
+
133 #endif
+
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ +
Eigen::Map< Eigen::Matrix< T2, R, C > > & operator[](int i)
operator[](int i) returns matrix view of scalartype T2 at appropriate index i in array y ...
+ +
(Expert) Numerical traits for algorithmic differentiation variables.
+
container_view(const Eigen::Matrix< T1, R, C > &x, T2 *y)
Constructor.
+
Eigen::Map< Eigen::Matrix< T2, R, C > > & operator[](int i)
operator[](int i) returns Eigen::Map y
+
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ +
T2 & operator[](int i)
operator[](int i) returns reference to scalar of type T2 at appropriate index i in array y ...
+
Primary template class for container view of array y with same structure as T1 and size as x...
+ +
container_view(const Eigen::Matrix< T1, R, C > &x, T2 *y)
Initialize Map dimensions with input matrix dimensions.
+
container_view(const std::vector< Eigen::Matrix< T1, R, C > > &x, T2 *y)
Constructor assumes all matrix elements in std::vector are of same dimension.
+
+
+
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diff --git a/doc/api/html/mat_2meta_2get_8hpp.html b/doc/api/html/mat_2meta_2get_8hpp.html new file mode 100644 index 00000000000..e2c0407fac9 --- /dev/null +++ b/doc/api/html/mat_2meta_2get_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/get.hpp File Reference + + + + + + + + + + +
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+Functions

template<typename T , int R, int C>
stan::get (const Eigen::Matrix< T, R, C > &m, size_t n)
 
+
+
+
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diff --git a/doc/api/html/mat_2meta_2get_8hpp_source.html b/doc/api/html/mat_2meta_2get_8hpp_source.html new file mode 100644 index 00000000000..cf683b21433 --- /dev/null +++ b/doc/api/html/mat_2meta_2get_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/get.hpp Source File + + + + + + + + + + +
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get.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_META_GET_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_GET_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  template <typename T, int R, int C>
+
9  inline T get(const Eigen::Matrix<T, R, C>& m, size_t n) {
+
10  return m(static_cast<int>(n));
+
11  }
+
12 
+
13 }
+
14 #endif
+
15 
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2meta_2index__type_8hpp.html b/doc/api/html/mat_2meta_2index__type_8hpp.html new file mode 100644 index 00000000000..81e4646d844 --- /dev/null +++ b/doc/api/html/mat_2meta_2index__type_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/index_type.hpp File Reference + + + + + + + + + + +
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index_type.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/index_type.hpp>
+#include <Eigen/Core>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::math::index_type< Eigen::Matrix< T, R, C > >
 Template metaprogram defining typedef for the type of index for an Eigen matrix, vector, or row vector. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2meta_2index__type_8hpp_source.html b/doc/api/html/mat_2meta_2index__type_8hpp_source.html new file mode 100644 index 00000000000..20ca767aa3b --- /dev/null +++ b/doc/api/html/mat_2meta_2index__type_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/index_type.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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index_type.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_META_INDEX_TYPE_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_INDEX_TYPE_HPP
+
3 
+ +
5 #include <Eigen/Core>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
19  template <typename T, int R, int C>
+
20  struct index_type<Eigen::Matrix<T, R, C> > {
+
21  typedef typename Eigen::Matrix<T, R, C>::Index type;
+
22  };
+
23 
+
24 
+
25  }
+
26 
+
27 }
+
28 
+
29 
+
30 #endif
+ + +
(Expert) Numerical traits for algorithmic differentiation variables.
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2meta_2is__constant__struct_8hpp.html b/doc/api/html/mat_2meta_2is__constant__struct_8hpp.html new file mode 100644 index 00000000000..9075439dfa4 --- /dev/null +++ b/doc/api/html/mat_2meta_2is__constant__struct_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/is_constant_struct.hpp File Reference + + + + + + + + + + +
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is_constant_struct.hpp File Reference
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diff --git a/doc/api/html/mat_2meta_2is__constant__struct_8hpp_source.html b/doc/api/html/mat_2meta_2is__constant__struct_8hpp_source.html new file mode 100644 index 00000000000..3ae1d2c87ee --- /dev/null +++ b/doc/api/html/mat_2meta_2is__constant__struct_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/is_constant_struct.hpp Source File + + + + + + + + + + +
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is_constant_struct.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_META_IS_CONSTANT_STRUCT_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_IS_CONSTANT_STRUCT_HPP
+
3 
+ + + +
7 
+
8 
+
9 namespace stan {
+
10 
+
11  template <typename T, int R, int C>
+
12  struct is_constant_struct<Eigen::Matrix<T, R, C> > {
+ +
14  };
+
15 
+
16  template <typename T>
+
17  struct is_constant_struct<Eigen::Block<T> > {
+ +
19  };
+
20 
+
21 }
+
22 #endif
+
23 
+ + + +
(Expert) Numerical traits for algorithmic differentiation variables.
+
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/mat_2meta_2is__vector_8hpp.html b/doc/api/html/mat_2meta_2is__vector_8hpp.html new file mode 100644 index 00000000000..171afae76a2 --- /dev/null +++ b/doc/api/html/mat_2meta_2is__vector_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/is_vector.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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is_vector.hpp File Reference
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diff --git a/doc/api/html/mat_2meta_2is__vector_8hpp_source.html b/doc/api/html/mat_2meta_2is__vector_8hpp_source.html new file mode 100644 index 00000000000..8a39bafce24 --- /dev/null +++ b/doc/api/html/mat_2meta_2is__vector_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/is_vector.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_META_IS_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_IS_VECTOR_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  // FIXME: use boost::type_traits::remove_all_extents to
+
10  // extend to array/ptr types
+
11 
+
12  template <typename T>
+
13  struct is_vector<Eigen::Matrix<T, Eigen::Dynamic, 1> > {
+
14  enum { value = 1 };
+
15  typedef T type;
+
16  };
+
17  template <typename T>
+
18  struct is_vector<Eigen::Matrix<T, 1, Eigen::Dynamic> > {
+
19  enum { value = 1 };
+
20  typedef T type;
+
21  };
+
22  template <typename T>
+
23  struct is_vector<Eigen::Block<T> > {
+
24  enum { value = 1 };
+
25  typedef T type;
+
26  };
+
27 }
+
28 #endif
+
29 
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diff --git a/doc/api/html/mat_2meta_2is__vector__like_8hpp.html b/doc/api/html/mat_2meta_2is__vector__like_8hpp.html new file mode 100644 index 00000000000..dd8317a7b4f --- /dev/null +++ b/doc/api/html/mat_2meta_2is__vector__like_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/is_vector_like.hpp File Reference + + + + + + + + + + +
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struct  stan::is_vector_like< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >
 Template metaprogram indicates whether a type is vector_like. More...
 
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diff --git a/doc/api/html/mat_2meta_2is__vector__like_8hpp_source.html b/doc/api/html/mat_2meta_2is__vector__like_8hpp_source.html new file mode 100644 index 00000000000..e6e8fdefe0a --- /dev/null +++ b/doc/api/html/mat_2meta_2is__vector__like_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/is_vector_like.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_META_IS_VECTOR_LIKE_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_IS_VECTOR_LIKE_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
21  template <typename T>
+
22  struct is_vector_like<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> > {
+
23  enum { value = true };
+
24  };
+
25 }
+
26 #endif
+
27 
+
Template metaprogram indicates whether a type is vector_like.
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diff --git a/doc/api/html/mat_2meta_2length_8hpp.html b/doc/api/html/mat_2meta_2length_8hpp.html new file mode 100644 index 00000000000..fecc4958b14 --- /dev/null +++ b/doc/api/html/mat_2meta_2length_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/length.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
size_t stan::length (const Eigen::Matrix< T, R, C > &m)
 
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diff --git a/doc/api/html/mat_2meta_2length_8hpp_source.html b/doc/api/html/mat_2meta_2length_8hpp_source.html new file mode 100644 index 00000000000..de7a783d70b --- /dev/null +++ b/doc/api/html/mat_2meta_2length_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/length.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_META_LENGTH_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_LENGTH_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  template <typename T, int R, int C>
+
9  size_t length(const Eigen::Matrix<T, R, C>& m) {
+
10  return m.size();
+
11  }
+
12 }
+
13 #endif
+
14 
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
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diff --git a/doc/api/html/mat_2meta_2length__mvt_8hpp.html b/doc/api/html/mat_2meta_2length__mvt_8hpp.html new file mode 100644 index 00000000000..cee2e9ab2c3 --- /dev/null +++ b/doc/api/html/mat_2meta_2length__mvt_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/length_mvt.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/meta/length_mvt.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stdexcept>
+#include <vector>
+
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template<typename T , int R, int C>
size_t stan::length_mvt (const Eigen::Matrix< T, R, C > &)
 
template<typename T , int R, int C>
size_t stan::length_mvt (const std::vector< Eigen::Matrix< T, R, C > > &x)
 
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diff --git a/doc/api/html/mat_2meta_2length__mvt_8hpp_source.html b/doc/api/html/mat_2meta_2length__mvt_8hpp_source.html new file mode 100644 index 00000000000..2eaf613f8ee --- /dev/null +++ b/doc/api/html/mat_2meta_2length__mvt_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/length_mvt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_META_LENGTH_MVT_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_LENGTH_MVT_HPP
+
3 
+ + +
6 #include <stdexcept>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  template <typename T, int R, int C>
+
12  size_t length_mvt(const Eigen::Matrix<T, R, C>& ) {
+
13  return 1U;
+
14  }
+
15 
+
16  template <typename T, int R, int C>
+
17  size_t length_mvt(const std::vector<Eigen::Matrix<T, R, C> >& x) {
+
18  return x.size();
+
19  }
+
20 
+
21 }
+
22 #endif
+
23 
+ + + +
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12
+
+
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diff --git a/doc/api/html/mat_2meta_2scalar__type_8hpp.html b/doc/api/html/mat_2meta_2scalar__type_8hpp.html new file mode 100644 index 00000000000..c1d3191e2fa --- /dev/null +++ b/doc/api/html/mat_2meta_2scalar__type_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/scalar_type.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/mat_2meta_2scalar__type_8hpp_source.html b/doc/api/html/mat_2meta_2scalar__type_8hpp_source.html new file mode 100644 index 00000000000..d62598e9dbf --- /dev/null +++ b/doc/api/html/mat_2meta_2scalar__type_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/scalar_type.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_META_SCALAR_TYPE_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_SCALAR_TYPE_HPP
+
3 
+ + + + +
8 
+
9 namespace stan {
+
10 
+
11  template <typename T>
+
12  struct scalar_type<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> > {
+
13  typedef typename scalar_type<T>::type type;
+
14  };
+
15 
+
16 }
+
17 #endif
+
Metaprogram structure to determine the base scalar type of a template argument.
Definition: scalar_type.hpp:34
+ + +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+
(Expert) Numerical traits for algorithmic differentiation variables.
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diff --git a/doc/api/html/mat_2meta_2value__type_8hpp.html b/doc/api/html/mat_2meta_2value__type_8hpp.html new file mode 100644 index 00000000000..6d525cb42be --- /dev/null +++ b/doc/api/html/mat_2meta_2value__type_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/value_type.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/meta/value_type.hpp>
+#include <Eigen/Core>
+
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struct  stan::math::value_type< Eigen::Matrix< T, R, C > >
 Template metaprogram defining the type of values stored in an Eigen matrix, vector, or row vector. More...
 
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 Matrices and templated mathematical functions.
 
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diff --git a/doc/api/html/mat_2meta_2value__type_8hpp_source.html b/doc/api/html/mat_2meta_2value__type_8hpp_source.html new file mode 100644 index 00000000000..c7fea305bc2 --- /dev/null +++ b/doc/api/html/mat_2meta_2value__type_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/value_type.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_META_VALUE_TYPE_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_VALUE_TYPE_HPP
+
3 
+ +
5 #include <Eigen/Core>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
19  template <typename T, int R, int C>
+
20  struct value_type<Eigen::Matrix<T, R, C> > {
+
21  typedef typename Eigen::Matrix<T, R, C>::Scalar type;
+
22  };
+
23 
+
24 
+
25  }
+
26 
+
27 }
+
28 
+
29 
+
30 #endif
+ +
(Expert) Numerical traits for algorithmic differentiation variables.
+
Eigen::Matrix< T, R, C >::Scalar type
Definition: value_type.hpp:21
+ +
Primary template class for metaprogram to compute the type of values stored in a container.
Definition: value_type.hpp:18
+
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diff --git a/doc/api/html/math_8hpp.html b/doc/api/html/math_8hpp.html new file mode 100644 index 00000000000..4f61da2b4dd --- /dev/null +++ b/doc/api/html/math_8hpp.html @@ -0,0 +1,112 @@ + + + + + + +Stan Math Library: stan/math.hpp File Reference + + + + + + + + + + +
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1 #ifndef STAN_MATH_HPP
+
2 #define STAN_MATH_HPP
+
3 
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4 #include <stan/math/rev/mat.hpp>
+
5 
+
6 #endif
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diff --git a/doc/api/html/matrix__normal__prec__log_8hpp.html b/doc/api/html/matrix__normal__prec__log_8hpp.html new file mode 100644 index 00000000000..8c5b92a4b28 --- /dev/null +++ b/doc/api/html/matrix__normal__prec__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/matrix_normal_prec_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_y , typename T_Mu , typename T_Sigma , typename T_D >
boost::math::tools::promote_args< T_y, T_Mu, T_Sigma, T_D >::type stan::math::matrix_normal_prec_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_Mu, Eigen::Dynamic, Eigen::Dynamic > &Mu, const Eigen::Matrix< T_Sigma, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_D, Eigen::Dynamic, Eigen::Dynamic > &D)
 The log of the matrix normal density for the given y, mu, Sigma and D where Sigma and D are given as precision matrices, not covariance matrices. More...
 
template<typename T_y , typename T_Mu , typename T_Sigma , typename T_D >
boost::math::tools::promote_args< T_y, T_Mu, T_Sigma, T_D >::type stan::math::matrix_normal_prec_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_Mu, Eigen::Dynamic, Eigen::Dynamic > &Mu, const Eigen::Matrix< T_Sigma, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_D, Eigen::Dynamic, Eigen::Dynamic > &D)
 
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diff --git a/doc/api/html/matrix__normal__prec__log_8hpp_source.html b/doc/api/html/matrix__normal__prec__log_8hpp_source.html new file mode 100644 index 00000000000..9ded4124c62 --- /dev/null +++ b/doc/api/html/matrix__normal__prec__log_8hpp_source.html @@ -0,0 +1,244 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/matrix_normal_prec_log.hpp Source File + + + + + + + + + + +
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matrix_normal_prec_log.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_MATRIX_NORMAL_PREC_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MATRIX_NORMAL_PREC_LOG_HPP
+
3 
+ + + + + + +
10 
+ + + + + + + + +
19 
+
20 namespace stan {
+
21  namespace math {
+
40  template <bool propto,
+
41  typename T_y, typename T_Mu, typename T_Sigma, typename T_D>
+
42  typename boost::math::tools::promote_args<T_y, T_Mu, T_Sigma, T_D>::type
+
43  matrix_normal_prec_log(const Eigen::Matrix
+
44  <T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
45  const Eigen::Matrix
+
46  <T_Mu, Eigen::Dynamic, Eigen::Dynamic>& Mu,
+
47  const Eigen::Matrix
+
48  <T_Sigma, Eigen::Dynamic, Eigen::Dynamic>& Sigma,
+
49  const Eigen::Matrix
+
50  <T_D, Eigen::Dynamic, Eigen::Dynamic>& D) {
+
51  static const char* function("stan::math::matrix_normal_prec_log");
+
52  typename
+
53  boost::math::tools::promote_args<T_y, T_Mu, T_Sigma, T_D>::type lp(0.0);
+
54 
+ + + + + + + + + + +
65 
+
66  check_positive(function, "Sigma rows", Sigma.rows());
+
67  check_finite(function, "Sigma", Sigma);
+
68  check_symmetric(function, "Sigma", Sigma);
+
69 
+ +
71  check_ldlt_factor(function, "LDLT_Factor of Sigma", ldlt_Sigma);
+
72  check_positive(function, "D rows", D.rows());
+
73  check_finite(function, "D", D);
+
74  check_symmetric(function, "Sigma", D);
+
75 
+ +
77  check_ldlt_factor(function, "LDLT_Factor of D", ldlt_D);
+
78  check_size_match(function,
+
79  "Rows of random variable", y.rows(),
+
80  "Rows of location parameter", Mu.rows());
+
81  check_size_match(function,
+
82  "Columns of random variable", y.cols(),
+
83  "Columns of location parameter", Mu.cols());
+
84  check_size_match(function,
+
85  "Rows of random variable", y.rows(),
+
86  "Rows of Sigma", Sigma.rows());
+
87  check_size_match(function,
+
88  "Columns of random variable", y.cols(),
+
89  "Rows of D", D.rows());
+
90  check_finite(function, "Location parameter", Mu);
+
91  check_finite(function, "Random variable", y);
+
92 
+ +
94  lp += NEG_LOG_SQRT_TWO_PI * y.cols() * y.rows();
+
95 
+ +
97  lp += log_determinant_ldlt(ldlt_Sigma) * (0.5 * y.rows());
+
98  }
+
99 
+ +
101  lp += log_determinant_ldlt(ldlt_D) * (0.5 * y.cols());
+
102  }
+
103 
+ +
105  lp -= 0.5 * trace_gen_quad_form(D, Sigma, subtract(y, Mu));
+
106  }
+
107  return lp;
+
108  }
+
109 
+
110  template <typename T_y, typename T_Mu, typename T_Sigma, typename T_D>
+
111  typename boost::math::tools::promote_args<T_y, T_Mu, T_Sigma, T_D>::type
+
112  matrix_normal_prec_log(const Eigen::Matrix
+
113  <T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
114  const Eigen::Matrix
+
115  <T_Mu, Eigen::Dynamic, Eigen::Dynamic>& Mu,
+
116  const Eigen::Matrix
+
117  <T_Sigma, Eigen::Dynamic, Eigen::Dynamic>& Sigma,
+
118  const Eigen::Matrix
+
119  <T_D, Eigen::Dynamic, Eigen::Dynamic>& D) {
+
120  return matrix_normal_prec_log<false>(y, Mu, Sigma, D);
+
121  }
+
122  }
+
123 }
+
124 
+
125 #endif
+ +
boost::math::tools::promote_args< T_y, T_Mu, T_Sigma, T_D >::type matrix_normal_prec_log(const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_Mu, Eigen::Dynamic, Eigen::Dynamic > &Mu, const Eigen::Matrix< T_Sigma, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_D, Eigen::Dynamic, Eigen::Dynamic > &D)
The log of the matrix normal density for the given y, mu, Sigma and D where Sigma and D are given as ...
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the result of subtracting the second specified matrix from the first specified matrix...
Definition: subtract.hpp:27
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
fvar< T > trace_gen_quad_form(const Eigen::Matrix< fvar< T >, RD, CD > &D, const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+ + + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+ +
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.
+ +
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diff --git a/doc/api/html/matrix__vari_8hpp.html b/doc/api/html/matrix__vari_8hpp.html new file mode 100644 index 00000000000..b794991f1ef --- /dev/null +++ b/doc/api/html/matrix__vari_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/core/matrix_vari.hpp File Reference + + + + + + + + + + +
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class  stan::math::op_matrix_vari
 
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diff --git a/doc/api/html/matrix__vari_8hpp_source.html b/doc/api/html/matrix__vari_8hpp_source.html new file mode 100644 index 00000000000..746ae41aa29 --- /dev/null +++ b/doc/api/html/matrix__vari_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/rev/core/matrix_vari.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_MATRIX_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_MATRIX_VARI_HPP
+
3 
+ + + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  class op_matrix_vari : public vari {
+
13  protected:
+
14  const size_t size_;
+ +
16  public:
+
17  template <int R, int C>
+
18  op_matrix_vari(double f,
+
19  const Eigen::Matrix<stan::math::var, R, C>& vs) :
+
20  vari(f),
+
21  size_(vs.size()) {
+
22  vis_ = reinterpret_cast<vari**>
+
23  (operator new(sizeof(vari*) * vs.size()));
+
24  for (int i = 0; i < vs.size(); ++i)
+
25  vis_[i] = vs(i).vi_;
+
26  }
+
27  vari* operator[](size_t n) const {
+
28  return vis_[n];
+
29  }
+
30  size_t size() {
+
31  return size_;
+
32  }
+
33  };
+
34 
+
35  }
+
36 }
+
37 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+
vari * operator[](size_t n) const
Definition: matrix_vari.hpp:27
+
op_matrix_vari(double f, const Eigen::Matrix< stan::math::var, R, C > &vs)
Definition: matrix_vari.hpp:18
+ + + + + + +
+
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diff --git a/doc/api/html/max_8hpp.html b/doc/api/html/max_8hpp.html new file mode 100644 index 00000000000..7a8acd8ab72 --- /dev/null +++ b/doc/api/html/max_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/max.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <algorithm>
+#include <limits>
+#include <stdexcept>
+#include <vector>
+
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int stan::math::max (const std::vector< int > &x)
 Returns the maximum coefficient in the specified column vector. More...
 
template<typename T >
stan::math::max (const std::vector< T > &x)
 Returns the maximum coefficient in the specified column vector. More...
 
template<typename T , int R, int C>
stan::math::max (const Eigen::Matrix< T, R, C > &m)
 Returns the maximum coefficient in the specified vector, row vector, or matrix. More...
 
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diff --git a/doc/api/html/max_8hpp_source.html b/doc/api/html/max_8hpp_source.html new file mode 100644 index 00000000000..5a54da1811d --- /dev/null +++ b/doc/api/html/max_8hpp_source.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/max.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MAX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MAX_HPP
+
3 
+ +
5 #include <algorithm>
+
6 #include <limits>
+
7 #include <stdexcept>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
21  inline int max(const std::vector<int>& x) {
+
22  if (x.size() == 0)
+
23  throw std::domain_error("error: cannot take max of empty int vector");
+
24  int max = x[0];
+
25  for (size_t i = 1; i < x.size(); ++i)
+
26  if (x[i] > max)
+
27  max = x[i];
+
28  return max;
+
29  }
+
30 
+
38  template <typename T>
+
39  inline T max(const std::vector<T>& x) {
+
40  if (x.size() == 0)
+
41  return -std::numeric_limits<T>::infinity();
+
42  T max = x[0];
+
43  for (size_t i = 1; i < x.size(); ++i)
+
44  if (x[i] > max)
+
45  max = x[i];
+
46  return max;
+
47  }
+
48 
+
55  template <typename T, int R, int C>
+
56  inline T max(const Eigen::Matrix<T, R, C>& m) {
+
57  if (m.size() == 0)
+
58  return -std::numeric_limits<double>::infinity();
+
59  return m.maxCoeff();
+
60  }
+
61 
+
62  }
+
63 }
+
64 #endif
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+
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diff --git a/doc/api/html/max__size_8hpp.html b/doc/api/html/max__size_8hpp.html new file mode 100644 index 00000000000..997097996e0 --- /dev/null +++ b/doc/api/html/max__size_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/max_size.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
size_t stan::max_size (const T1 &x1, const T2 &x2)
 
template<typename T1 , typename T2 , typename T3 >
size_t stan::max_size (const T1 &x1, const T2 &x2, const T3 &x3)
 
template<typename T1 , typename T2 , typename T3 , typename T4 >
size_t stan::max_size (const T1 &x1, const T2 &x2, const T3 &x3, const T4 &x4)
 
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diff --git a/doc/api/html/max__size_8hpp_source.html b/doc/api/html/max__size_8hpp_source.html new file mode 100644 index 00000000000..a0f82affead --- /dev/null +++ b/doc/api/html/max__size_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/max_size.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_MAX_SIZE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_MAX_SIZE_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  template <typename T1, typename T2>
+
9  size_t max_size(const T1& x1, const T2& x2) {
+
10  size_t result = length(x1);
+
11  result = result > length(x2) ? result : length(x2);
+
12  return result;
+
13  }
+
14 
+
15  template <typename T1, typename T2, typename T3>
+
16  size_t max_size(const T1& x1, const T2& x2, const T3& x3) {
+
17  size_t result = length(x1);
+
18  result = result > length(x2) ? result : length(x2);
+
19  result = result > length(x3) ? result : length(x3);
+
20  return result;
+
21  }
+
22 
+
23  template <typename T1, typename T2, typename T3, typename T4>
+
24  size_t max_size(const T1& x1, const T2& x2, const T3& x3, const T4& x4) {
+
25  size_t result = length(x1);
+
26  result = result > length(x2) ? result : length(x2);
+
27  result = result > length(x3) ? result : length(x3);
+
28  result = result > length(x4) ? result : length(x4);
+
29  return result;
+
30  }
+
31 
+
32 }
+
33 #endif
+
34 
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
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diff --git a/doc/api/html/max__size__mvt_8hpp.html b/doc/api/html/max__size__mvt_8hpp.html new file mode 100644 index 00000000000..d6ae2fc60ed --- /dev/null +++ b/doc/api/html/max__size__mvt_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/max_size_mvt.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/meta/length_mvt.hpp>
+#include <cstdlib>
+
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template<typename T1 , typename T2 >
size_t stan::max_size_mvt (const T1 &x1, const T2 &x2)
 
template<typename T1 , typename T2 , typename T3 >
size_t stan::max_size_mvt (const T1 &x1, const T2 &x2, const T3 &x3)
 
template<typename T1 , typename T2 , typename T3 , typename T4 >
size_t stan::max_size_mvt (const T1 &x1, const T2 &x2, const T3 &x3, const T4 &x4)
 
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diff --git a/doc/api/html/max__size__mvt_8hpp_source.html b/doc/api/html/max__size__mvt_8hpp_source.html new file mode 100644 index 00000000000..4fb215afdf3 --- /dev/null +++ b/doc/api/html/max__size__mvt_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/max_size_mvt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_MAX_SIZE_MVT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_MAX_SIZE_MVT_HPP
+
3 
+ +
5 #include <cstdlib>
+
6 
+
7 namespace stan {
+
8 
+
9  template <typename T1, typename T2>
+
10  size_t max_size_mvt(const T1& x1, const T2& x2) {
+
11  size_t result = length_mvt(x1);
+
12  result = result > length_mvt(x2) ? result : length_mvt(x2);
+
13  return result;
+
14  }
+
15 
+
16  template <typename T1, typename T2, typename T3>
+
17  size_t max_size_mvt(const T1& x1, const T2& x2, const T3& x3) {
+
18  size_t result = length_mvt(x1);
+
19  result = result > length_mvt(x2) ? result : length_mvt(x2);
+
20  result = result > length_mvt(x3) ? result : length_mvt(x3);
+
21  return result;
+
22  }
+
23 
+
24  template <typename T1, typename T2, typename T3, typename T4>
+
25  size_t max_size_mvt(const T1& x1, const T2& x2, const T3& x3, const T4& x4) {
+
26  size_t result = length_mvt(x1);
+
27  result = result > length_mvt(x2) ? result : length_mvt(x2);
+
28  result = result > length_mvt(x3) ? result : length_mvt(x3);
+
29  result = result > length_mvt(x4) ? result : length_mvt(x4);
+
30  return result;
+
31  }
+
32 
+
33 }
+
34 #endif
+
35 
+
size_t max_size_mvt(const T1 &x1, const T2 &x2)
+ + +
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12
+
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diff --git a/doc/api/html/mdivide__right__ldlt_8hpp.html b/doc/api/html/mdivide__right__ldlt_8hpp.html new file mode 100644 index 00000000000..b75adc16c4f --- /dev/null +++ b/doc/api/html/mdivide__right__ldlt_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right_ldlt.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_right_ldlt (const Eigen::Matrix< T1, R1, C1 > &b, const stan::math::LDLT_factor< T2, R2, C2 > &A)
 Returns the solution of the system xA=b given an LDLT_factor of A. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< double, R1, C2 > stan::math::mdivide_right_ldlt (const Eigen::Matrix< double, R1, C1 > &b, const stan::math::LDLT_factor< double, R2, C2 > &A)
 
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diff --git a/doc/api/html/mdivide__right__ldlt_8hpp_source.html b/doc/api/html/mdivide__right__ldlt_8hpp_source.html new file mode 100644 index 00000000000..585902ed3c0 --- /dev/null +++ b/doc/api/html/mdivide__right__ldlt_8hpp_source.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right_ldlt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_LDLT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_LDLT_HPP
+
3 
+ + + + + +
9 #include <boost/math/tools/promotion.hpp>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
22  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
23  inline
+
24  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
25  R1, C2>
+
26  mdivide_right_ldlt(const Eigen::Matrix<T1, R1, C1> &b,
+ + +
29  stan::math::check_multiplicable("mdivide_right_ldlt",
+
30  "b", b,
+
31  "A", A);
+
32 
+
33  return transpose(mdivide_left_ldlt(A, transpose(b)));
+
34  }
+
35 
+
36  template <int R1, int C1, int R2, int C2>
+
37  inline Eigen::Matrix<double, R1, C2>
+
38  mdivide_right_ldlt(const Eigen::Matrix<double, R1, C1> &b,
+ +
40  stan::math::check_multiplicable("mdivide_right_ldlt",
+
41  "b", b,
+
42  "A", A);
+
43  return A.solveRight(b);
+
44  }
+
45 
+
46  }
+
47 }
+
48 #endif
+ + + + + +
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt(const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
Returns the solution of the system Ax=b given an LDLT_factor of A.
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_right_ldlt(const Eigen::Matrix< T1, R1, C1 > &b, const stan::math::LDLT_factor< T2, R2, C2 > &A)
Returns the solution of the system xA=b given an LDLT_factor of A.
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
+
+
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diff --git a/doc/api/html/mdivide__right__spd_8hpp.html b/doc/api/html/mdivide__right__spd_8hpp.html new file mode 100644 index 00000000000..068e9c273fe --- /dev/null +++ b/doc/api/html/mdivide__right__spd_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right_spd.hpp File Reference + + + + + + + + + + +
+
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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_right_spd (const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
 Returns the solution of the system Ax=b where A is symmetric positive definite. More...
 
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diff --git a/doc/api/html/mdivide__right__spd_8hpp_source.html b/doc/api/html/mdivide__right__spd_8hpp_source.html new file mode 100644 index 00000000000..f7bd23eccb4 --- /dev/null +++ b/doc/api/html/mdivide__right__spd_8hpp_source.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right_spd.hpp Source File + + + + + + + + + + +
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mdivide_right_spd.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_SPD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_SPD_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + + + + + +
12 
+
13 namespace stan {
+
14  namespace math {
+
15 
+
25  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
26  inline
+
27  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
28  R1, C2>
+
29  mdivide_right_spd(const Eigen::Matrix<T1, R1, C1> &b,
+
30  const Eigen::Matrix<T2, R2, C2> &A) {
+
31  stan::math::check_square("mdivide_right_spd", "A", A);
+
32  stan::math::check_multiplicable("mdivide_right_spd",
+
33  "b", b,
+
34  "A", A);
+
35  stan::math::check_symmetric("mdivide_right_spd", "A", A);
+
36  stan::math::check_pos_definite("mdivide_right_spd", "A", A);
+
37  // FIXME: This is nice and general but likely slow.
+
38  // FIXME: After allowing for general MatrixBase in mdivide_left_spd,
+
39  // change to b.transpose()
+
40  return mdivide_left_spd(A, transpose(b)).transpose();
+
41  }
+
42 
+
43  }
+
44 }
+
45 #endif
+ + + + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_spd(const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
Returns the solution of the system Ax=b where A is symmetric positive definite.
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_right_spd(const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
Returns the solution of the system Ax=b where A is symmetric positive definite.
+ +
bool check_pos_definite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified square, symmetric matrix is positive definite.
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
+
+
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diff --git a/doc/api/html/mdivide__right__tri_8hpp.html b/doc/api/html/mdivide__right__tri_8hpp.html new file mode 100644 index 00000000000..7a4e9af9682 --- /dev/null +++ b/doc/api/html/mdivide__right__tri_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right_tri.hpp File Reference + + + + + + + + + + +
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template<int TriView, typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_right_tri (const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
 Returns the solution of the system Ax=b when A is triangular. More...
 
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diff --git a/doc/api/html/mdivide__right__tri_8hpp_source.html b/doc/api/html/mdivide__right__tri_8hpp_source.html new file mode 100644 index 00000000000..c7562ca6b04 --- /dev/null +++ b/doc/api/html/mdivide__right__tri_8hpp_source.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right_tri.hpp Source File + + + + + + + + + + +
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mdivide_right_tri.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_TRI_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_TRI_HPP
+
3 
+ + + + + +
9 #include <boost/math/tools/promotion.hpp>
+
10 #include <stdexcept>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
24  template <int TriView, typename T1, typename T2,
+
25  int R1, int C1, int R2, int C2>
+
26  inline
+
27  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
28  R1, C2>
+
29  mdivide_right_tri(const Eigen::Matrix<T1, R1, C1> &b,
+
30  const Eigen::Matrix<T2, R2, C2> &A) {
+
31  stan::math::check_square("mdivide_right_tri", "A", A);
+
32  stan::math::check_multiplicable("mdivide_right_tri",
+
33  "b", b,
+
34  "A", A);
+
35  // FIXME: This is nice and general but requires some extra memory
+
36  // and copying.
+
37  if (TriView == Eigen::Lower) {
+
38  return transpose(mdivide_left_tri<Eigen::Upper>(transpose(A),
+
39  transpose(b)));
+
40  } else if (TriView == Eigen::Upper) {
+
41  return transpose(mdivide_left_tri<Eigen::Lower>(transpose(A),
+
42  transpose(b)));
+
43  } else {
+
44  throw std::domain_error("triangular view must be Eigen::Lower or "
+
45  "Eigen::Upper");
+
46  }
+
47  }
+
48 
+
49  }
+
50 }
+
51 #endif
+
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_right_tri(const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
Returns the solution of the system Ax=b when A is triangular.
+ + + + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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diff --git a/doc/api/html/mean_8hpp.html b/doc/api/html/mean_8hpp.html new file mode 100644 index 00000000000..c0b2c80b022 --- /dev/null +++ b/doc/api/html/mean_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mean.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <vector>
+
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::mean (const std::vector< T > &v)
 Returns the sample mean (i.e., average) of the coefficients in the specified standard vector. More...
 
template<typename T , int R, int C>
boost::math::tools::promote_args< T >::type stan::math::mean (const Eigen::Matrix< T, R, C > &m)
 Returns the sample mean (i.e., average) of the coefficients in the specified vector, row vector, or matrix. More...
 
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diff --git a/doc/api/html/mean_8hpp_source.html b/doc/api/html/mean_8hpp_source.html new file mode 100644 index 00000000000..1a0de191c07 --- /dev/null +++ b/doc/api/html/mean_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mean.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MEAN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MEAN_HPP
+
3 
+ + +
6 #include <boost/math/tools/promotion.hpp>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
20  template <typename T>
+
21  inline
+
22  typename boost::math::tools::promote_args<T>::type
+
23  mean(const std::vector<T>& v) {
+
24  stan::math::check_nonzero_size("mean", "v", v);
+
25  T sum(v[0]);
+
26  for (size_t i = 1; i < v.size(); ++i)
+
27  sum += v[i];
+
28  return sum / v.size();
+
29  }
+
30 
+
37  template <typename T, int R, int C>
+
38  inline
+
39  typename boost::math::tools::promote_args<T>::type
+
40  mean(const Eigen::Matrix<T, R, C>& m) {
+
41  stan::math::check_nonzero_size("mean", "m", m);
+
42  return m.mean();
+
43  }
+
44 
+
45  }
+
46 }
+
47 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
boost::math::tools::promote_args< T >::type mean(const std::vector< T > &v)
Returns the sample mean (i.e., average) of the coefficients in the specified standard vector...
Definition: mean.hpp:23
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diff --git a/doc/api/html/min_8hpp.html b/doc/api/html/min_8hpp.html new file mode 100644 index 00000000000..97908b166b0 --- /dev/null +++ b/doc/api/html/min_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/min.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <algorithm>
+#include <limits>
+#include <stdexcept>
+#include <vector>
+
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int stan::math::min (const std::vector< int > &x)
 Returns the minimum coefficient in the specified column vector. More...
 
template<typename T >
stan::math::min (const std::vector< T > &x)
 Returns the minimum coefficient in the specified column vector. More...
 
template<typename T , int R, int C>
stan::math::min (const Eigen::Matrix< T, R, C > &m)
 Returns the minimum coefficient in the specified matrix, vector, or row vector. More...
 
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diff --git a/doc/api/html/min_8hpp_source.html b/doc/api/html/min_8hpp_source.html new file mode 100644 index 00000000000..c7bd28106c8 --- /dev/null +++ b/doc/api/html/min_8hpp_source.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/min.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MIN_HPP
+
3 
+ +
5 #include <algorithm>
+
6 #include <limits>
+
7 #include <stdexcept>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
20  inline int min(const std::vector<int>& x) {
+
21  if (x.size() == 0)
+
22  throw std::domain_error("error: cannot take min of empty int vector");
+
23  int min = x[0];
+
24  for (size_t i = 1; i < x.size(); ++i)
+
25  if (x[i] < min)
+
26  min = x[i];
+
27  return min;
+
28  }
+
29 
+
37  template <typename T>
+
38  inline T min(const std::vector<T>& x) {
+
39  if (x.size() == 0)
+
40  return std::numeric_limits<T>::infinity();
+
41  T min = x[0];
+
42  for (size_t i = 1; i < x.size(); ++i)
+
43  if (x[i] < min)
+
44  min = x[i];
+
45  return min;
+
46  }
+
47 
+
54  template <typename T, int R, int C>
+
55  inline T min(const Eigen::Matrix<T, R, C>& m) {
+
56  if (m.size() == 0)
+
57  return std::numeric_limits<double>::infinity();
+
58  return m.minCoeff();
+
59  }
+
60 
+
61  }
+
62 }
+
63 #endif
+
int min(const std::vector< int > &x)
Returns the minimum coefficient in the specified column vector.
Definition: min.hpp:20
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
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diff --git a/doc/api/html/minus_8hpp.html b/doc/api/html/minus_8hpp.html new file mode 100644 index 00000000000..7df369a5cd3 --- /dev/null +++ b/doc/api/html/minus_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/minus.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::minus (const T &x)
 Returns the negation of the specified scalar or matrix. More...
 
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diff --git a/doc/api/html/minus_8hpp_source.html b/doc/api/html/minus_8hpp_source.html new file mode 100644 index 00000000000..896e0ef4198 --- /dev/null +++ b/doc/api/html/minus_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/minus.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MINUS_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MINUS_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
14  template <typename T>
+
15  inline
+
16  T minus(const T& x) {
+
17  return -x;
+
18  }
+
19 
+
20  }
+
21 }
+
22 #endif
+ +
T minus(const T &x)
Returns the negation of the specified scalar or matrix.
Definition: minus.hpp:16
+
+
+
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diff --git a/doc/api/html/mix_2arr_8hpp.html b/doc/api/html/mix_2arr_8hpp.html new file mode 100644 index 00000000000..7c4a375bc47 --- /dev/null +++ b/doc/api/html/mix_2arr_8hpp.html @@ -0,0 +1,120 @@ + + + + + + +Stan Math Library: stan/math/mix/arr.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/mix_2arr_8hpp_source.html b/doc/api/html/mix_2arr_8hpp_source.html new file mode 100644 index 00000000000..5962f8c57ff --- /dev/null +++ b/doc/api/html/mix_2arr_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/mix/arr.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_MIX_ARR_HPP
+
2 #define STAN_MATH_MIX_ARR_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ + +
7 
+
8 #include <stan/math/rev/core.hpp>
+ + +
11 
+
12 #include <stan/math/prim/arr.hpp>
+
13 #include <stan/math/fwd/arr.hpp>
+
14 #include <stan/math/rev/arr.hpp>
+
15 
+
16 #endif
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diff --git a/doc/api/html/mix_2mat_2fun_2typedefs_8hpp.html b/doc/api/html/mix_2mat_2fun_2typedefs_8hpp.html new file mode 100644 index 00000000000..b9d12f05c96 --- /dev/null +++ b/doc/api/html/mix_2mat_2fun_2typedefs_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/fun/typedefs.hpp File Reference + + + + + + + + + + +
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+Typedefs

typedef Eigen::Matrix< fvar< var >, Eigen::Dynamic, Eigen::Dynamic > stan::math::matrix_fv
 
typedef Eigen::Matrix< fvar< fvar< var > >, Eigen::Dynamic, Eigen::Dynamic > stan::math::matrix_ffv
 
typedef Eigen::Matrix< fvar< var >, Eigen::Dynamic, 1 > stan::math::vector_fv
 
typedef Eigen::Matrix< fvar< fvar< var > >, Eigen::Dynamic, 1 > stan::math::vector_ffv
 
typedef Eigen::Matrix< fvar< var >, 1, Eigen::Dynamic > stan::math::row_vector_fv
 
typedef Eigen::Matrix< fvar< fvar< var > >, 1, Eigen::Dynamic > stan::math::row_vector_ffv
 
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diff --git a/doc/api/html/mix_2mat_2fun_2typedefs_8hpp_source.html b/doc/api/html/mix_2mat_2fun_2typedefs_8hpp_source.html new file mode 100644 index 00000000000..1dd1f76da6f --- /dev/null +++ b/doc/api/html/mix_2mat_2fun_2typedefs_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/fun/typedefs.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_MIX_MAT_FUN_TYPEDEFS_HPP
+
2 #define STAN_MATH_MIX_MAT_FUN_TYPEDEFS_HPP
+
3 
+ +
5 #include <stan/math/fwd/core.hpp>
+
6 #include <stan/math/rev/core.hpp>
+ +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  typedef
+
13  Eigen::Matrix<fvar<var>, Eigen::Dynamic, Eigen::Dynamic>
+ +
15 
+
16  typedef
+
17  Eigen::Matrix<fvar<fvar<var> >, Eigen::Dynamic, Eigen::Dynamic>
+ +
19 
+
20  typedef
+
21  Eigen::Matrix<fvar<var>, Eigen::Dynamic, 1>
+ +
23 
+
24  typedef
+
25  Eigen::Matrix<fvar<fvar<var> >, Eigen::Dynamic, 1>
+ +
27 
+
28  typedef
+
29  Eigen::Matrix<fvar<var>, 1, Eigen::Dynamic>
+ +
31 
+
32  typedef
+
33  Eigen::Matrix<fvar<fvar<var> >, 1, Eigen::Dynamic>
+ +
35 
+
36  }
+
37 }
+
38 #endif
+
Eigen::Matrix< fvar< var >, Eigen::Dynamic, Eigen::Dynamic > matrix_fv
Definition: typedefs.hpp:14
+ + +
Eigen::Matrix< fvar< fvar< var > >, Eigen::Dynamic, 1 > vector_ffv
Definition: typedefs.hpp:26
+ + +
Eigen::Matrix< fvar< var >, 1, Eigen::Dynamic > row_vector_fv
Definition: typedefs.hpp:30
+
Eigen::Matrix< fvar< fvar< var > >, 1, Eigen::Dynamic > row_vector_ffv
Definition: typedefs.hpp:34
+ +
Eigen::Matrix< fvar< var >, Eigen::Dynamic, 1 > vector_fv
Definition: typedefs.hpp:22
+
Eigen::Matrix< fvar< fvar< var > >, Eigen::Dynamic, Eigen::Dynamic > matrix_ffv
Definition: typedefs.hpp:18
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diff --git a/doc/api/html/modulus_8hpp.html b/doc/api/html/modulus_8hpp.html new file mode 100644 index 00000000000..b7fc7595ff9 --- /dev/null +++ b/doc/api/html/modulus_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/modulus.hpp File Reference + + + + + + + + + + +
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int stan::math::modulus (const int x, const int y)
 
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diff --git a/doc/api/html/modulus_8hpp_source.html b/doc/api/html/modulus_8hpp_source.html new file mode 100644 index 00000000000..9d38a46ceb9 --- /dev/null +++ b/doc/api/html/modulus_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/modulus.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_MODULUS_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_MODULUS_HPP
+
3 
+
4 #include <cstddef>
+
5 #include <cstdlib>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  inline int modulus(const int x, const int y) {
+
11  return std::div(x, y).rem;
+
12  }
+
13 
+
14  }
+
15 }
+
16 
+
17 #endif
+ +
int modulus(const int x, const int y)
Definition: modulus.hpp:10
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diff --git a/doc/api/html/multi__gp__cholesky__log_8hpp.html b/doc/api/html/multi__gp__cholesky__log_8hpp.html new file mode 100644 index 00000000000..b48437618db --- /dev/null +++ b/doc/api/html/multi__gp__cholesky__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_gp_cholesky_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_y , typename T_covar , typename T_w >
boost::math::tools::promote_args< T_y, T_covar, T_w >::type stan::math::multi_gp_cholesky_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
 The log of a multivariate Gaussian Process for the given y, w, and a Cholesky factor L of the kernel matrix Sigma. More...
 
template<typename T_y , typename T_covar , typename T_w >
boost::math::tools::promote_args< T_y, T_covar, T_w >::type stan::math::multi_gp_cholesky_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
 
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diff --git a/doc/api/html/multi__gp__cholesky__log_8hpp_source.html b/doc/api/html/multi__gp__cholesky__log_8hpp_source.html new file mode 100644 index 00000000000..1c42a31939b --- /dev/null +++ b/doc/api/html/multi__gp__cholesky__log_8hpp_source.html @@ -0,0 +1,228 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_gp_cholesky_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_GP_CHOLESKY_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_GP_CHOLESKY_LOG_HPP
+
3 
+ + + + + +
9 
+ + + + + + +
16 
+
17 namespace stan {
+
18  namespace math {
+
19  // MultiGPCholesky(y|L, w) [y.rows() = w.size(), y.cols() = Sigma.rows();
+
20  // Sigma symmetric, non-negative, definite]
+
40  template <bool propto,
+
41  typename T_y, typename T_covar, typename T_w>
+
42  typename boost::math::tools::promote_args<T_y, T_covar, T_w>::type
+
43  multi_gp_cholesky_log(const Eigen::Matrix
+
44  <T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
45  const Eigen::Matrix
+
46  <T_covar, Eigen::Dynamic, Eigen::Dynamic>& L,
+
47  const Eigen::Matrix<T_w, Eigen::Dynamic, 1>& w) {
+
48  static const char* function("stan::math::multi_gp_cholesky_log");
+
49  typedef
+
50  typename boost::math::tools::promote_args<T_y, T_covar, T_w>::type T_lp;
+
51  T_lp lp(0.0);
+
52 
+ + +
55  using stan::math::sum;
+
56  using stan::math::log;
+
57 
+ + + +
61 
+
62  check_size_match(function,
+
63  "Size of random variable (rows y)", y.rows(),
+
64  "Size of kernel scales (w)", w.size());
+
65  check_size_match(function,
+
66  "Size of random variable", y.cols(),
+
67  "rows of covariance parameter", L.rows());
+
68  check_finite(function, "Kernel scales", w);
+
69  check_positive(function, "Kernel scales", w);
+
70  check_finite(function, "Random variable", y);
+
71 
+
72  if (y.rows() == 0)
+
73  return lp;
+
74 
+ +
76  lp += NEG_LOG_SQRT_TWO_PI * y.rows() * y.cols();
+
77  }
+
78 
+ +
80  lp -= L.diagonal().array().log().sum() * y.rows();
+
81  }
+
82 
+ +
84  lp += 0.5 * y.cols() * sum(log(w));
+
85  }
+
86 
+ +
88  T_lp sum_lp_vec(0.0);
+
89  for (int i = 0; i < y.rows(); i++) {
+
90  Eigen::Matrix<T_y, Eigen::Dynamic, 1> y_row(y.row(i));
+
91  Eigen::Matrix<typename boost::math::tools::promote_args
+
92  <T_y, T_covar>::type,
+
93  Eigen::Dynamic, 1>
+
94  half(mdivide_left_tri_low(L, y_row));
+
95  sum_lp_vec += w(i) * dot_self(half);
+
96  }
+
97  lp -= 0.5*sum_lp_vec;
+
98  }
+
99 
+
100  return lp;
+
101  }
+
102 
+
103  template <typename T_y, typename T_covar, typename T_w>
+
104  inline
+
105  typename boost::math::tools::promote_args<T_y, T_covar, T_w>::type
+
106  multi_gp_cholesky_log(const Eigen::Matrix
+
107  <T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
108  const Eigen::Matrix
+
109  <T_covar, Eigen::Dynamic, Eigen::Dynamic>& L,
+
110  const Eigen::Matrix<T_w, Eigen::Dynamic, 1>& w) {
+
111  return multi_gp_cholesky_log<false>(y, L, w);
+
112  }
+
113  }
+
114 }
+
115 
+
116 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ +
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_left_tri_low(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ + + +
boost::math::tools::promote_args< T_y, T_covar, T_w >::type multi_gp_cholesky_log(const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
The log of a multivariate Gaussian Process for the given y, w, and a Cholesky factor L of the kernel ...
+
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diff --git a/doc/api/html/multi__gp__log_8hpp.html b/doc/api/html/multi__gp__log_8hpp.html new file mode 100644 index 00000000000..8cd37960857 --- /dev/null +++ b/doc/api/html/multi__gp__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_gp_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_y , typename T_covar , typename T_w >
boost::math::tools::promote_args< T_y, T_covar, T_w >::type stan::math::multi_gp_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
 The log of a multivariate Gaussian Process for the given y, Sigma, and w. More...
 
template<typename T_y , typename T_covar , typename T_w >
boost::math::tools::promote_args< T_y, T_covar, T_w >::type stan::math::multi_gp_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
 
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diff --git a/doc/api/html/multi__gp__log_8hpp_source.html b/doc/api/html/multi__gp__log_8hpp_source.html new file mode 100644 index 00000000000..74e01e54cb6 --- /dev/null +++ b/doc/api/html/multi__gp__log_8hpp_source.html @@ -0,0 +1,242 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_gp_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_GP_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_GP_LOG_HPP
+
3 
+ + + + + + + +
11 
+ + + + + + + +
19 
+
20 namespace stan {
+
21  namespace math {
+
22  // MultiGP(y|Sigma, w) [y.rows() = w.size(), y.cols() = Sigma.rows();
+
23  // Sigma symmetric, non-negative, definite]
+
42  template <bool propto,
+
43  typename T_y, typename T_covar, typename T_w>
+
44  typename boost::math::tools::promote_args<T_y, T_covar, T_w>::type
+
45  multi_gp_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
46  const Eigen::Matrix
+
47  <T_covar, Eigen::Dynamic, Eigen::Dynamic>& Sigma,
+
48  const Eigen::Matrix<T_w, Eigen::Dynamic, 1>& w) {
+
49  static const char* function("stan::math::multi_gp_log");
+
50  typedef typename boost::math::tools::promote_args<T_y, T_covar, T_w>::type
+
51  T_lp;
+
52  T_lp lp(0.0);
+
53 
+
54  using stan::math::sum;
+
55  using stan::math::log;
+ + + +
59 
+ + + + + + + +
67 
+
68  check_positive(function, "Kernel rows", Sigma.rows());
+
69  check_finite(function, "Kernel", Sigma);
+
70  check_symmetric(function, "Kernel", Sigma);
+
71 
+ +
73  check_ldlt_factor(function, "LDLT_Factor of Sigma", ldlt_Sigma);
+
74 
+
75  check_size_match(function,
+
76  "Size of random variable (rows y)", y.rows(),
+
77  "Size of kernel scales (w)", w.size());
+
78  check_size_match(function,
+
79  "Size of random variable", y.cols(),
+
80  "rows of covariance parameter", Sigma.rows());
+
81  check_positive_finite(function, "Kernel scales", w);
+
82  check_finite(function, "Random variable", y);
+
83 
+
84  if (y.rows() == 0)
+
85  return lp;
+
86 
+ +
88  lp += NEG_LOG_SQRT_TWO_PI * y.rows() * y.cols();
+
89  }
+
90 
+ +
92  lp -= 0.5 * log_determinant_ldlt(ldlt_Sigma) * y.rows();
+
93  }
+
94 
+ +
96  lp += (0.5 * y.cols()) * sum(log(w));
+
97  }
+
98 
+ +
100  Eigen::Matrix<T_w, Eigen::Dynamic, Eigen::Dynamic>
+
101  w_mat(w.asDiagonal());
+
102  Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic> yT(y.transpose());
+
103  lp -= 0.5 * trace_gen_inv_quad_form_ldlt(w_mat, ldlt_Sigma, yT);
+
104  }
+
105 
+
106  return lp;
+
107  }
+
108 
+
109  template <typename T_y, typename T_covar, typename T_w>
+
110  inline
+
111  typename boost::math::tools::promote_args<T_y, T_covar, T_w>::type
+
112  multi_gp_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& y,
+
113  const Eigen::Matrix<T_covar, Eigen::Dynamic, Eigen::Dynamic>&
+
114  Sigma,
+
115  const Eigen::Matrix<T_w, Eigen::Dynamic, 1>& w) {
+
116  return multi_gp_log<false>(y, Sigma, w);
+
117  }
+
118  }
+
119 }
+
120 
+
121 #endif
+ +
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value &&!stan::is_var< T3 >::value, typename boost::math::tools::promote_args< T1, T2, T3 >::type >::type trace_gen_inv_quad_form_ldlt(const Eigen::Matrix< T1, R1, C1 > &D, const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
boost::math::tools::promote_args< T_y, T_covar, T_w >::type multi_gp_log(const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
The log of a multivariate Gaussian Process for the given y, Sigma, and w.
+
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.
+ +
+
+
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diff --git a/doc/api/html/multi__normal__cholesky__log_8hpp.html b/doc/api/html/multi__normal__cholesky__log_8hpp.html new file mode 100644 index 00000000000..c7801b2b4f6 --- /dev/null +++ b/doc/api/html/multi__normal__cholesky__log_8hpp.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_cholesky_log.hpp File Reference + + + + + + + + + + +
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+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type stan::math::multi_normal_cholesky_log (const T_y &y, const T_loc &mu, const T_covar &L)
 The log of the multivariate normal density for the given y, mu, and a Cholesky factor L of the variance matrix. More...
 
template<typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type stan::math::multi_normal_cholesky_log (const T_y &y, const T_loc &mu, const T_covar &L)
 
+
+
+
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diff --git a/doc/api/html/multi__normal__cholesky__log_8hpp_source.html b/doc/api/html/multi__normal__cholesky__log_8hpp_source.html new file mode 100644 index 00000000000..8ae926f794b --- /dev/null +++ b/doc/api/html/multi__normal__cholesky__log_8hpp_source.html @@ -0,0 +1,287 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_cholesky_log.hpp Source File + + + + + + + + + + +
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multi_normal_cholesky_log.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_CHOLESKY_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_CHOLESKY_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/normal_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 
+
25 namespace stan {
+
26  namespace math {
+
44  template <bool propto,
+
45  typename T_y, typename T_loc, typename T_covar>
+
46  typename return_type<T_y, T_loc, T_covar>::type
+ +
48  const T_loc& mu,
+
49  const T_covar& L) {
+
50  static const char* function("stan::math::multi_normal_cholesky_log");
+
51  typedef typename scalar_type<T_covar>::type T_covar_elem;
+
52  typedef typename return_type<T_y, T_loc, T_covar>::type lp_type;
+
53  lp_type lp(0.0);
+
54 
+ + + + +
59  using stan::math::sum;
+
60 
+ + + +
64 
+
65  VectorViewMvt<const T_y> y_vec(y);
+
66  VectorViewMvt<const T_loc> mu_vec(mu);
+
67  // size of std::vector of Eigen vectors
+
68  size_t size_vec = max_size_mvt(y, mu);
+
69 
+
70  // Check if every vector of the array has the same size
+
71  int size_y = y_vec[0].size();
+
72  int size_mu = mu_vec[0].size();
+
73  if (size_vec > 1) {
+
74  int size_y_old = size_y;
+
75  int size_y_new;
+
76  for (size_t i = 1, size_ = length_mvt(y); i < size_; i++) {
+
77  int size_y_new = y_vec[i].size();
+
78  check_size_match(function,
+
79  "Size of one of the vectors of "
+
80  "the random variable", size_y_new,
+
81  "Size of another vector of the "
+
82  "random variable", size_y_old);
+
83  size_y_old = size_y_new;
+
84  }
+
85  int size_mu_old = size_mu;
+
86  int size_mu_new;
+
87  for (size_t i = 1, size_ = length_mvt(mu); i < size_; i++) {
+
88  int size_mu_new = mu_vec[i].size();
+
89  check_size_match(function,
+
90  "Size of one of the vectors of "
+
91  "the location variable", size_mu_new,
+
92  "Size of another vector of the "
+
93  "location variable", size_mu_old);
+
94  size_mu_old = size_mu_new;
+
95  }
+
96  (void) size_y_old;
+
97  (void) size_y_new;
+
98  (void) size_mu_old;
+
99  (void) size_mu_new;
+
100  }
+
101 
+
102  check_size_match(function,
+
103  "Size of random variable", size_y,
+
104  "size of location parameter", size_mu);
+
105  check_size_match(function,
+
106  "Size of random variable", size_y,
+
107  "rows of covariance parameter", L.rows());
+
108  check_size_match(function,
+
109  "Size of random variable", size_y,
+
110  "columns of covariance parameter", L.cols());
+
111 
+
112  for (size_t i = 0; i < size_vec; i++) {
+
113  check_finite(function, "Location parameter", mu_vec[i]);
+
114  check_not_nan(function, "Random variable", y_vec[i]);
+
115  }
+
116 
+
117  if (size_y == 0)
+
118  return lp;
+
119 
+ +
121  lp += NEG_LOG_SQRT_TWO_PI * size_y * size_vec;
+
122 
+ +
124  lp -= L.diagonal().array().log().sum() * size_vec;
+
125 
+ +
127  lp_type sum_lp_vec(0.0);
+
128  for (size_t i = 0; i < size_vec; i++) {
+
129  Eigen::Matrix<typename return_type<T_y, T_loc>::type,
+
130  Eigen::Dynamic, 1> y_minus_mu(size_y);
+
131  for (int j = 0; j < size_y; j++)
+
132  y_minus_mu(j) = y_vec[i](j)-mu_vec[i](j);
+
133  Eigen::Matrix<typename return_type<T_y, T_loc, T_covar>::type,
+
134  Eigen::Dynamic, 1>
+
135  half(mdivide_left_tri_low(L, y_minus_mu));
+
136  // FIXME: this code does not compile. revert after fixing subtract()
+
137  // Eigen::Matrix<typename
+
138  // boost::math::tools::promote_args<T_covar,
+
139  // typename value_type<T_loc>::type,
+
140  // typename value_type<T_y>::type>::type>::type,
+
141  // Eigen::Dynamic, 1>
+
142  // half(mdivide_left_tri_low(L, subtract(y, mu)));
+
143  sum_lp_vec += dot_self(half);
+
144  }
+
145  lp -= 0.5*sum_lp_vec;
+
146  }
+
147  return lp;
+
148  }
+
149 
+
150  template <typename T_y, typename T_loc, typename T_covar>
+
151  inline
+ +
153  multi_normal_cholesky_log(const T_y& y, const T_loc& mu, const T_covar& L) {
+
154  return multi_normal_cholesky_log<false>(y, mu, L);
+
155  }
+
156 
+
157  }
+
158 }
+
159 #endif
+ +
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + +
size_t max_size_mvt(const T1 &x1, const T2 &x2)
+ + +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the result of subtracting the second specified matrix from the first specified matrix...
Definition: subtract.hpp:27
+ +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
return_type< T_y, T_loc, T_covar >::type multi_normal_cholesky_log(const T_y &y, const T_loc &mu, const T_covar &L)
The log of the multivariate normal density for the given y, mu, and a Cholesky factor L of the varian...
+
size_t size_
Definition: dot_self.hpp:18
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ +
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_left_tri_low(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ + + + + + +
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multi__normal__cholesky__rng_8hpp.html b/doc/api/html/multi__normal__cholesky__rng_8hpp.html new file mode 100644 index 00000000000..2e2be5062b7 --- /dev/null +++ b/doc/api/html/multi__normal__cholesky__rng_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_cholesky_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
Eigen::VectorXd stan::math::multi_normal_cholesky_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
 
+
+
+
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diff --git a/doc/api/html/multi__normal__cholesky__rng_8hpp_source.html b/doc/api/html/multi__normal__cholesky__rng_8hpp_source.html new file mode 100644 index 00000000000..c8aab644c43 --- /dev/null +++ b/doc/api/html/multi__normal__cholesky__rng_8hpp_source.html @@ -0,0 +1,183 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_cholesky_rng.hpp Source File + + + + + + + + + + +
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multi_normal_cholesky_rng.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_CHOLESKY_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_CHOLESKY_RNG_HPP
+
3 
+
4 #include <boost/random/normal_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 
+ + +
23 
+
24 namespace stan {
+
25 
+
26  namespace math {
+
27  template <class RNG>
+
28  inline Eigen::VectorXd
+ +
30  const Eigen::Matrix<double, Eigen::Dynamic, 1>& mu,
+
31  const Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& S,
+
32  RNG& rng
+
33  ) {
+
34  using boost::variate_generator;
+
35  using boost::normal_distribution;
+
36 
+
37  static const char* function("stan::math::multi_normal_cholesky_rng");
+
38 
+ +
40 
+
41  check_finite(function, "Location parameter", mu);
+
42 
+
43  variate_generator<RNG&, normal_distribution<> >
+
44  std_normal_rng(rng, normal_distribution<>(0, 1));
+
45 
+
46  Eigen::VectorXd z(S.cols());
+
47  for (int i = 0; i < S.cols(); i++)
+
48  z(i) = std_normal_rng();
+
49 
+
50  return mu + S * z;
+
51  }
+
52  }
+
53 }
+
54 
+
55 #endif
+ + + + + + + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
Eigen::VectorXd multi_normal_cholesky_rng(const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
+ + + + +
+
+
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diff --git a/doc/api/html/multi__normal__log_8hpp.html b/doc/api/html/multi__normal__log_8hpp.html new file mode 100644 index 00000000000..f6890e1220e --- /dev/null +++ b/doc/api/html/multi__normal__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_log.hpp File Reference + + + + + + + + + + +
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+Functions

template<bool propto, typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type stan::math::multi_normal_log (const T_y &y, const T_loc &mu, const T_covar &Sigma)
 
template<typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type stan::math::multi_normal_log (const T_y &y, const T_loc &mu, const T_covar &Sigma)
 
+
+
+
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diff --git a/doc/api/html/multi__normal__log_8hpp_source.html b/doc/api/html/multi__normal__log_8hpp_source.html new file mode 100644 index 00000000000..83f42f98308 --- /dev/null +++ b/doc/api/html/multi__normal__log_8hpp_source.html @@ -0,0 +1,278 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_log.hpp Source File + + + + + + + + + + +
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+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_LOG_HPP
+
3 
+ + + + + + + + + + + + + +
17 #include <boost/random/normal_distribution.hpp>
+
18 #include <boost/random/variate_generator.hpp>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <bool propto,
+
25  typename T_y, typename T_loc, typename T_covar>
+
26  typename return_type<T_y, T_loc, T_covar>::type
+
27  multi_normal_log(const T_y& y,
+
28  const T_loc& mu,
+
29  const T_covar& Sigma) {
+
30  static const char* function("stan::math::multi_normal_log");
+
31  typedef typename scalar_type<T_covar>::type T_covar_elem;
+
32  typedef typename return_type<T_y, T_loc, T_covar>::type lp_type;
+
33  lp_type lp(0.0);
+
34 
+ + + + + + +
41  using Eigen::Dynamic;
+
42 
+
43  check_positive(function, "Covariance matrix rows", Sigma.rows());
+
44  check_symmetric(function, "Covariance matrix", Sigma);
+
45 
+ +
47  check_ldlt_factor(function,
+
48  "LDLT_Factor of covariance parameter", ldlt_Sigma);
+
49 
+
50  VectorViewMvt<const T_y> y_vec(y);
+
51  VectorViewMvt<const T_loc> mu_vec(mu);
+
52  // size of std::vector of Eigen vectors
+
53  size_t size_vec = max_size_mvt(y, mu);
+
54 
+
55  // Check if every vector of the array has the same size
+
56  int size_y = y_vec[0].size();
+
57  int size_mu = mu_vec[0].size();
+
58  if (size_vec > 1) {
+
59  int size_y_old = size_y;
+
60  int size_y_new;
+
61  for (size_t i = 1, size_ = length_mvt(y); i < size_; i++) {
+
62  int size_y_new = y_vec[i].size();
+
63  check_size_match(function,
+
64  "Size of one of the vectors of "
+
65  "the random variable", size_y_new,
+
66  "Size of another vector of the "
+
67  "random variable", size_y_old);
+
68  size_y_old = size_y_new;
+
69  }
+
70  int size_mu_old = size_mu;
+
71  int size_mu_new;
+
72  for (size_t i = 1, size_ = length_mvt(mu); i < size_; i++) {
+
73  int size_mu_new = mu_vec[i].size();
+
74  check_size_match(function,
+
75  "Size of one of the vectors of "
+
76  "the location variable", size_mu_new,
+
77  "Size of another vector of the "
+
78  "location variable", size_mu_old);
+
79  size_mu_old = size_mu_new;
+
80  }
+
81  (void) size_y_old;
+
82  (void) size_y_new;
+
83  (void) size_mu_old;
+
84  (void) size_mu_new;
+
85  }
+
86 
+
87  check_size_match(function,
+
88  "Size of random variable", size_y,
+
89  "size of location parameter", size_mu);
+
90  check_size_match(function,
+
91  "Size of random variable", size_y,
+
92  "rows of covariance parameter", Sigma.rows());
+
93  check_size_match(function,
+
94  "Size of random variable", size_y,
+
95  "columns of covariance parameter", Sigma.cols());
+
96 
+
97  for (size_t i = 0; i < size_vec; i++) {
+
98  check_finite(function, "Location parameter", mu_vec[i]);
+
99  check_not_nan(function, "Random variable", y_vec[i]);
+
100  }
+
101 
+
102  if (size_y == 0) // y_vec[0].size() == 0
+
103  return lp;
+
104 
+ +
106  lp += NEG_LOG_SQRT_TWO_PI * size_y * size_vec;
+
107 
+ +
109  lp -= 0.5 * log_determinant_ldlt(ldlt_Sigma) * size_vec;
+
110 
+ +
112  lp_type sum_lp_vec(0.0);
+
113  for (size_t i = 0; i < size_vec; i++) {
+
114  Eigen::Matrix<typename return_type<T_y, T_loc>::type, Dynamic, 1>
+
115  y_minus_mu(size_y);
+
116  for (int j = 0; j < size_y; j++)
+
117  y_minus_mu(j) = y_vec[i](j)-mu_vec[i](j);
+
118  sum_lp_vec += trace_inv_quad_form_ldlt(ldlt_Sigma, y_minus_mu);
+
119  }
+
120  lp -= 0.5*sum_lp_vec;
+
121  }
+
122  return lp;
+
123  }
+
124 
+
125  template <typename T_y, typename T_loc, typename T_covar>
+
126  inline
+ +
128  multi_normal_log(const T_y& y,
+
129  const T_loc& mu,
+
130  const T_covar& Sigma) {
+
131  return multi_normal_log<false>(y, mu, Sigma);
+
132  }
+
133 
+
134  }
+
135 }
+
136 
+
137 #endif
+ + +
size_t max_size_mvt(const T1 &x1, const T2 &x2)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + + +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value, typename boost::math::tools::promote_args< T1, T2 >::type >::type trace_inv_quad_form_ldlt(const stan::math::LDLT_factor< T1, R2, C2 > &A, const Eigen::Matrix< T2, R3, C3 > &B)
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
size_t size_
Definition: dot_self.hpp:18
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+
return_type< T_y, T_loc, T_covar >::type multi_normal_log(const T_y &y, const T_loc &mu, const T_covar &Sigma)
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12
+
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.
+ +
+
+
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diff --git a/doc/api/html/multi__normal__prec__log_8hpp.html b/doc/api/html/multi__normal__prec__log_8hpp.html new file mode 100644 index 00000000000..9eeb29ecd2f --- /dev/null +++ b/doc/api/html/multi__normal__prec__log_8hpp.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_prec_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
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+ +
+
multi_normal_prec_log.hpp File Reference
+
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+ + + + + + + +

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+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type stan::math::multi_normal_prec_log (const T_y &y, const T_loc &mu, const T_covar &Sigma)
 
template<typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type stan::math::multi_normal_prec_log (const T_y &y, const T_loc &mu, const T_covar &Sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multi__normal__prec__log_8hpp_source.html b/doc/api/html/multi__normal__prec__log_8hpp_source.html new file mode 100644 index 00000000000..442ac8f9944 --- /dev/null +++ b/doc/api/html/multi__normal__prec__log_8hpp_source.html @@ -0,0 +1,302 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_prec_log.hpp Source File + + + + + + + + + + +
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+
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multi_normal_prec_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_PREC_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_PREC_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + + + +
27 
+
28 namespace stan {
+
29 
+
30  namespace math {
+
31 
+
32  template <bool propto,
+
33  typename T_y, typename T_loc, typename T_covar>
+
34  typename return_type<T_y, T_loc, T_covar>::type
+
35  multi_normal_prec_log(const T_y& y,
+
36  const T_loc& mu,
+
37  const T_covar& Sigma) {
+
38  static const char* function("stan::math::multi_normal_prec_log");
+
39  typedef typename scalar_type<T_covar>::type T_covar_elem;
+
40  typedef typename return_type<T_y, T_loc, T_covar>::type lp_type;
+
41  lp_type lp(0.0);
+
42 
+ + + + + +
48  using stan::math::sum;
+ + + + +
53 
+
54  check_positive(function, "Precision matrix rows", Sigma.rows());
+
55  check_symmetric(function, "Precision matrix", Sigma);
+
56 
+
57  LDLT_factor<T_covar_elem,
+
58  Eigen::Dynamic, Eigen::Dynamic> ldlt_Sigma(Sigma);
+
59  check_ldlt_factor(function, "LDLT_Factor of precision parameter",
+
60  ldlt_Sigma);
+
61 
+
62  using Eigen::Matrix;
+
63  using std::vector;
+
64  VectorViewMvt<const T_y> y_vec(y);
+
65  VectorViewMvt<const T_loc> mu_vec(mu);
+
66  // size of std::vector of Eigen vectors
+
67  size_t size_vec = max_size_mvt(y, mu);
+
68 
+
69 
+
70  // Check if every vector of the array has the same size
+
71  int size_y = y_vec[0].size();
+
72  int size_mu = mu_vec[0].size();
+
73  if (size_vec > 1) {
+
74  int size_y_old = size_y;
+
75  int size_y_new;
+
76  for (size_t i = 1, size_ = length_mvt(y); i < size_; i++) {
+
77  int size_y_new = y_vec[i].size();
+
78  check_size_match(function,
+
79  "Size of one of the vectors "
+
80  "of the random variable", size_y_new,
+
81  "Size of another vector of "
+
82  "the random variable", size_y_old);
+
83  size_y_old = size_y_new;
+
84  }
+
85  int size_mu_old = size_mu;
+
86  int size_mu_new;
+
87  for (size_t i = 1, size_ = length_mvt(mu); i < size_; i++) {
+
88  int size_mu_new = mu_vec[i].size();
+
89  check_size_match(function,
+
90  "Size of one of the vectors "
+
91  "of the location variable", size_mu_new,
+
92  "Size of another vector of "
+
93  "the location variable", size_mu_old);
+
94  size_mu_old = size_mu_new;
+
95  }
+
96  (void) size_y_old;
+
97  (void) size_y_new;
+
98  (void) size_mu_old;
+
99  (void) size_mu_new;
+
100  }
+
101 
+
102  check_size_match(function,
+
103  "Size of random variable", size_y,
+
104  "size of location parameter", size_mu);
+
105  check_size_match(function,
+
106  "Size of random variable", size_y,
+
107  "rows of covariance parameter", Sigma.rows());
+
108  check_size_match(function,
+
109  "Size of random variable", size_y,
+
110  "columns of covariance parameter", Sigma.cols());
+
111 
+
112  for (size_t i = 0; i < size_vec; i++) {
+
113  check_finite(function, "Location parameter", mu_vec[i]);
+
114  check_not_nan(function, "Random variable", y_vec[i]);
+
115  }
+
116 
+
117  if (size_y == 0) // y_vec[0].size() == 0
+
118  return lp;
+
119 
+ +
121  lp += 0.5 * log_determinant_ldlt(ldlt_Sigma) * size_vec;
+
122 
+ +
124  lp += NEG_LOG_SQRT_TWO_PI * size_y * size_vec;
+
125 
+ +
127  lp_type sum_lp_vec(0.0);
+
128  for (size_t i = 0; i < size_vec; i++) {
+
129  Eigen::Matrix<typename return_type<T_y, T_loc>::type,
+
130  Eigen::Dynamic, 1> y_minus_mu(size_y);
+
131  for (int j = 0; j < size_y; j++)
+
132  y_minus_mu(j) = y_vec[i](j) - mu_vec[i](j);
+
133  sum_lp_vec += trace_quad_form(Sigma, y_minus_mu);
+
134  }
+
135  lp -= 0.5*sum_lp_vec;
+
136  }
+
137  return lp;
+
138  }
+
139 
+
140  template <typename T_y, typename T_loc, typename T_covar>
+
141  inline
+ +
143  multi_normal_prec_log(const T_y& y, const T_loc& mu, const T_covar& Sigma) {
+
144  return multi_normal_prec_log<false>(y, mu, Sigma);
+
145  }
+
146 
+
147  }
+
148 }
+
149 #endif
+
150 
+ +
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + +
size_t max_size_mvt(const T1 &x1, const T2 &x2)
+
fvar< T > trace_quad_form(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+ + +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
return_type< T_y, T_loc, T_covar >::type multi_normal_prec_log(const T_y &y, const T_loc &mu, const T_covar &Sigma)
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + + +
size_t size_
Definition: dot_self.hpp:18
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ +
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+ + + + +
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12
+
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multi__normal__rng_8hpp.html b/doc/api/html/multi__normal__rng_8hpp.html new file mode 100644 index 00000000000..74336dc63bb --- /dev/null +++ b/doc/api/html/multi__normal__rng_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
multi_normal_rng.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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+ + + + +

+Functions

template<class RNG >
Eigen::VectorXd stan::math::multi_normal_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multi__normal__rng_8hpp_source.html b/doc/api/html/multi__normal__rng_8hpp_source.html new file mode 100644 index 00000000000..0977d4c2e21 --- /dev/null +++ b/doc/api/html/multi__normal__rng_8hpp_source.html @@ -0,0 +1,178 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_normal_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + +
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+ + +
+
+
+
multi_normal_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_NORMAL_RNG_HPP
+
3 
+
4 #include <boost/random/normal_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + +
14 
+ + +
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  template <class RNG>
+
23  inline Eigen::VectorXd
+ +
25  const Eigen::Matrix<double, Eigen::Dynamic, 1>& mu,
+
26  const Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& S,
+
27  RNG& rng
+
28  ) {
+
29  using boost::variate_generator;
+
30  using boost::normal_distribution;
+
31 
+
32  static const char* function("stan::math::multi_normal_rng");
+
33 
+ + + +
37 
+
38  check_positive(function, "Covariance matrix rows", S.rows());
+
39  check_symmetric(function, "Covariance matrix", S);
+
40  check_finite(function, "Location parameter", mu);
+
41 
+
42  variate_generator<RNG&, normal_distribution<> >
+
43  std_normal_rng(rng, normal_distribution<>(0, 1));
+
44 
+
45  Eigen::VectorXd z(S.cols());
+
46  for (int i = 0; i < S.cols(); i++)
+
47  z(i) = std_normal_rng();
+
48 
+
49  return mu + S.llt().matrixL() * z;
+
50  }
+
51  }
+
52 }
+
53 
+
54 #endif
+ + + + + + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
Eigen::VectorXd multi_normal_rng(const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multi__student__t__log_8hpp.html b/doc/api/html/multi__student__t__log_8hpp.html new file mode 100644 index 00000000000..f82cf2a81a2 --- /dev/null +++ b/doc/api/html/multi__student__t__log_8hpp.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_student_t_log.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
multi_student_t_log.hpp File Reference
+
+
+
#include <stan/math/prim/mat/err/check_ldlt_factor.hpp>
+#include <stan/math/prim/mat/err/check_symmetric.hpp>
+#include <stan/math/prim/mat/fun/multiply.hpp>
+#include <stan/math/prim/mat/fun/dot_product.hpp>
+#include <stan/math/prim/mat/fun/subtract.hpp>
+#include <stan/math/prim/mat/meta/VectorViewMvt.hpp>
+#include <stan/math/prim/mat/prob/multi_normal_log.hpp>
+#include <stan/math/prim/scal/err/check_size_match.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/log1p.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+#include <cstdlib>
+
+

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+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type stan::math::multi_student_t_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &Sigma)
 Return the log of the multivariate Student t distribution at the specified arguments. More...
 
template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type stan::math::multi_student_t_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &Sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multi__student__t__log_8hpp_source.html b/doc/api/html/multi__student__t__log_8hpp_source.html new file mode 100644 index 00000000000..bf5fbcf720a --- /dev/null +++ b/doc/api/html/multi__student__t__log_8hpp_source.html @@ -0,0 +1,322 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_student_t_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
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multi_student_t_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_STUDENT_T_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_STUDENT_T_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/math/special_functions/gamma.hpp>
+
19 #include <boost/math/special_functions/fpclassify.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 #include <cstdlib>
+
23 
+
24 namespace stan {
+
25  namespace math {
+
32  template <bool propto,
+
33  typename T_y, typename T_dof, typename T_loc, typename T_scale>
+
34  typename return_type<T_y, T_dof, T_loc, T_scale>::type
+
35  multi_student_t_log(const T_y& y,
+
36  const T_dof& nu,
+
37  const T_loc& mu,
+
38  const T_scale& Sigma) {
+
39  static const char* function("stan::math::multi_student_t");
+
40 
+ + + + + +
46  using boost::math::lgamma;
+ + + +
50  using stan::math::log1p;
+
51  using std::log;
+
52 
+
53  typedef typename scalar_type<T_scale>::type T_scale_elem;
+
54  typedef typename return_type<T_y, T_dof, T_loc, T_scale>::type lp_type;
+
55  lp_type lp(0.0);
+
56 
+
57  // allows infinities
+
58  check_not_nan(function, "Degrees of freedom parameter", nu);
+
59  check_positive(function, "Degrees of freedom parameter", nu);
+
60 
+
61  using boost::math::isinf;
+
62 
+
63  if (isinf(nu)) // already checked nu > 0
+
64  return multi_normal_log(y, mu, Sigma);
+
65 
+
66  using Eigen::Matrix;
+
67  using std::vector;
+
68  VectorViewMvt<const T_y> y_vec(y);
+
69  VectorViewMvt<const T_loc> mu_vec(mu);
+
70  // size of std::vector of Eigen vectors
+
71  size_t size_vec = max_size_mvt(y, mu);
+
72 
+
73 
+
74  // Check if every vector of the array has the same size
+
75  int size_y = y_vec[0].size();
+
76  int size_mu = mu_vec[0].size();
+
77  if (size_vec > 1) {
+
78  int size_y_old = size_y;
+
79  int size_y_new;
+
80  for (size_t i = 1, size_ = length_mvt(y); i < size_; i++) {
+
81  int size_y_new = y_vec[i].size();
+
82  check_size_match(function,
+
83  "Size of one of the vectors of the random variable",
+
84  size_y_new,
+
85  "Size of another vector of the random variable",
+
86  size_y_old);
+
87  size_y_old = size_y_new;
+
88  }
+
89  int size_mu_old = size_mu;
+
90  int size_mu_new;
+
91  for (size_t i = 1, size_ = length_mvt(mu); i < size_; i++) {
+
92  int size_mu_new = mu_vec[i].size();
+
93  check_size_match(function,
+
94  "Size of one of the vectors "
+
95  "of the location variable",
+
96  size_mu_new,
+
97  "Size of another vector of "
+
98  "the location variable",
+
99  size_mu_old);
+
100  size_mu_old = size_mu_new;
+
101  }
+
102  (void) size_y_old;
+
103  (void) size_y_new;
+
104  (void) size_mu_old;
+
105  (void) size_mu_new;
+
106  }
+
107 
+
108 
+
109  check_size_match(function,
+
110  "Size of random variable", size_y,
+
111  "size of location parameter", size_mu);
+
112  check_size_match(function,
+
113  "Size of random variable", size_y,
+
114  "rows of scale parameter", Sigma.rows());
+
115  check_size_match(function,
+
116  "Size of random variable", size_y,
+
117  "columns of scale parameter", Sigma.cols());
+
118 
+
119  for (size_t i = 0; i < size_vec; i++) {
+
120  check_finite(function, "Location parameter", mu_vec[i]);
+
121  check_not_nan(function, "Random variable", y_vec[i]);
+
122  }
+
123  check_symmetric(function, "Scale parameter", Sigma);
+
124 
+
125 
+
126  LDLT_factor<T_scale_elem,
+
127  Eigen::Dynamic, Eigen::Dynamic> ldlt_Sigma(Sigma);
+
128  check_ldlt_factor(function, "LDLT_Factor of scale parameter", ldlt_Sigma);
+
129 
+
130  if (size_y == 0) // y_vec[0].size() == 0
+
131  return lp;
+
132 
+ +
134  lp += lgamma(0.5 * (nu + size_y)) * size_vec;
+
135  lp -= lgamma(0.5 * nu) * size_vec;
+
136  lp -= (0.5 * size_y) * log(nu) * size_vec;
+
137  }
+
138 
+ +
140  lp -= (0.5 * size_y) * LOG_PI * size_vec;
+
141 
+
142  using stan::math::multiply;
+ +
144  using stan::math::subtract;
+
145  using Eigen::Array;
+
146 
+
147 
+ +
149  lp -= 0.5 * log_determinant_ldlt(ldlt_Sigma) * size_vec;
+
150  }
+
151 
+ +
153  lp_type sum_lp_vec(0.0);
+
154  for (size_t i = 0; i < size_vec; i++) {
+
155  Eigen::Matrix<typename return_type<T_y, T_loc>::type,
+
156  Eigen::Dynamic, 1> y_minus_mu(size_y);
+
157  for (int j = 0; j < size_y; j++)
+
158  y_minus_mu(j) = y_vec[i](j)-mu_vec[i](j);
+
159  sum_lp_vec += log1p(trace_inv_quad_form_ldlt(ldlt_Sigma, y_minus_mu)
+
160  / nu);
+
161  }
+
162  lp -= 0.5 * (nu + size_y) * sum_lp_vec;
+
163  }
+
164  return lp;
+
165  }
+
166 
+
167  template <typename T_y, typename T_dof, typename T_loc, typename T_scale>
+
168  inline
+ +
170  multi_student_t_log(const T_y& y, const T_dof& nu, const T_loc& mu,
+
171  const T_scale& Sigma) {
+
172  return multi_student_t_log<false>(y, nu, mu, Sigma);
+
173  }
+
174 
+
175  }
+
176 }
+
177 #endif
+ + +
int isinf(const stan::math::var &a)
Checks if the given number is infinite.
Definition: std_isinf.hpp:18
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
size_t max_size_mvt(const T1 &x1, const T2 &x2)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the result of subtracting the second specified matrix from the first specified matrix...
Definition: subtract.hpp:27
+
const double LOG_PI
Definition: constants.hpp:170
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value, typename boost::math::tools::promote_args< T1, T2 >::type >::type trace_inv_quad_form_ldlt(const stan::math::LDLT_factor< T1, R2, C2 > &A, const Eigen::Matrix< T2, R3, C3 > &B)
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+ + +
size_t size_
Definition: dot_self.hpp:18
+
return_type< T_y, T_dof, T_loc, T_scale >::type multi_student_t_log(const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &Sigma)
Return the log of the multivariate Student t distribution at the specified arguments.
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ +
return_type< T_y, T_loc, T_covar >::type multi_normal_log(const T_y &y, const T_loc &mu, const T_covar &Sigma)
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+ +
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12
+
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multi__student__t__rng_8hpp.html b/doc/api/html/multi__student__t__rng_8hpp.html new file mode 100644 index 00000000000..23f08828162 --- /dev/null +++ b/doc/api/html/multi__student__t__rng_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_student_t_rng.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
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multi_student_t_rng.hpp File Reference
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template<class RNG >
Eigen::VectorXd stan::math::multi_student_t_rng (const double nu, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &s, RNG &rng)
 
+
+
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diff --git a/doc/api/html/multi__student__t__rng_8hpp_source.html b/doc/api/html/multi__student__t__rng_8hpp_source.html new file mode 100644 index 00000000000..3b5712163e2 --- /dev/null +++ b/doc/api/html/multi__student__t__rng_8hpp_source.html @@ -0,0 +1,187 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multi_student_t_rng.hpp Source File + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
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multi_student_t_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_STUDENT_T_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_STUDENT_T_RNG_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 #include <boost/math/special_functions/fpclassify.hpp>
+
6 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
21 #include <cstdlib>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <class RNG>
+
28  inline Eigen::VectorXd
+ +
30  const double nu,
+
31  const Eigen::Matrix<double, Eigen::Dynamic, 1>& mu,
+
32  const Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& s,
+
33  RNG& rng
+
34  ) {
+
35  static const char* function("stan::math::multi_student_t_rng");
+
36 
+ + + + +
41 
+
42  check_finite(function, "Location parameter", mu);
+
43  check_symmetric(function, "Scale parameter", s);
+
44  check_not_nan(function, "Degrees of freedom parameter", nu);
+
45  check_positive(function, "Degrees of freedom parameter", nu);
+
46 
+
47  Eigen::VectorXd z(s.cols());
+
48  z.setZero();
+
49 
+
50  double w = stan::math::inv_gamma_rng(nu / 2, nu / 2, rng);
+
51  return mu + std::sqrt(w) * stan::math::multi_normal_rng(z, s, rng);
+
52  }
+
53  }
+
54 }
+
55 #endif
+ + +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + + + + +
double inv_gamma_rng(const double alpha, const double beta, RNG &rng)
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
Eigen::VectorXd multi_normal_rng(const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
+ +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+ +
Eigen::VectorXd multi_student_t_rng(const double nu, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &s, RNG &rng)
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multinomial__log_8hpp.html b/doc/api/html/multinomial__log_8hpp.html new file mode 100644 index 00000000000..c7375978125 --- /dev/null +++ b/doc/api/html/multinomial__log_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multinomial_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+ +
+
multinomial_log.hpp File Reference
+
+
+
#include <boost/math/special_functions/gamma.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <stan/math/prim/mat/err/check_simplex.hpp>
+#include <stan/math/prim/scal/err/check_size_match.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <vector>
+
+

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+Functions

template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::multinomial_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type stan::math::multinomial_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multinomial__log_8hpp_source.html b/doc/api/html/multinomial__log_8hpp_source.html new file mode 100644 index 00000000000..a7a993db356 --- /dev/null +++ b/doc/api/html/multinomial__log_8hpp_source.html @@ -0,0 +1,191 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multinomial_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
+
+
multinomial_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTINOMIAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTINOMIAL_LOG_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 #include <boost/random/uniform_01.hpp>
+
6 #include <boost/random/variate_generator.hpp>
+ + + + + + + +
14 #include <vector>
+
15 
+
16 namespace stan {
+
17 
+
18  namespace math {
+
19  // Multinomial(ns|N, theta) [0 <= n <= N; SUM ns = N;
+
20  // 0 <= theta[n] <= 1; SUM theta = 1]
+
21  template <bool propto,
+
22  typename T_prob>
+
23  typename boost::math::tools::promote_args<T_prob>::type
+
24  multinomial_log(const std::vector<int>& ns,
+
25  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta) {
+
26  static const char* function("stan::math::multinomial_log");
+
27 
+ + + +
31  using boost::math::tools::promote_args;
+
32  using boost::math::lgamma;
+
33 
+
34  typename promote_args<T_prob>::type lp(0.0);
+
35  check_nonnegative(function, "Number of trials variable", ns);
+
36  check_simplex(function, "Probabilites parameter", theta);
+
37  check_size_match(function,
+
38  "Size of number of trials variable", ns.size(),
+
39  "rows of probabilities parameter", theta.rows());
+ +
41 
+ +
43  double sum = 1.0;
+
44  for (unsigned int i = 0; i < ns.size(); ++i)
+
45  sum += ns[i];
+
46  lp += lgamma(sum);
+
47  for (unsigned int i = 0; i < ns.size(); ++i)
+
48  lp -= lgamma(ns[i] + 1.0);
+
49  }
+ +
51  for (unsigned int i = 0; i < ns.size(); ++i)
+
52  lp += multiply_log(ns[i], theta[i]);
+
53  }
+
54  return lp;
+
55  }
+
56 
+
57  template <typename T_prob>
+
58  typename boost::math::tools::promote_args<T_prob>::type
+
59  multinomial_log(const std::vector<int>& ns,
+
60  const Eigen::Matrix<T_prob, Eigen::Dynamic, 1>& theta) {
+
61  return multinomial_log<false>(ns, theta);
+
62  }
+
63 
+
64  }
+
65 }
+
66 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
bool check_simplex(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is simplex.
+
boost::math::tools::promote_args< T_prob >::type multinomial_log(const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multinomial__rng_8hpp.html b/doc/api/html/multinomial__rng_8hpp.html new file mode 100644 index 00000000000..f51d768922f --- /dev/null +++ b/doc/api/html/multinomial__rng_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multinomial_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
multinomial_rng.hpp File Reference
+
+
+
#include <stan/math/prim/mat/err/check_simplex.hpp>
+#include <stan/math/prim/scal/err/check_size_match.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/prob/binomial_rng.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/random/uniform_01.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <vector>
+
+

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 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<class RNG >
std::vector< int > stan::math::multinomial_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &theta, const int N, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/multinomial__rng_8hpp_source.html b/doc/api/html/multinomial__rng_8hpp_source.html new file mode 100644 index 00000000000..3eebf06cc93 --- /dev/null +++ b/doc/api/html/multinomial__rng_8hpp_source.html @@ -0,0 +1,171 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/multinomial_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+
+
+
multinomial_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTINOMIAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_MULTINOMIAL_RNG_HPP
+
3 
+ + + + + + + + +
12 #include <boost/math/special_functions/gamma.hpp>
+
13 #include <boost/random/uniform_01.hpp>
+
14 #include <boost/random/variate_generator.hpp>
+
15 #include <vector>
+
16 
+
17 namespace stan {
+
18 
+
19  namespace math {
+
20 
+
21  template <class RNG>
+
22  inline std::vector<int>
+
23  multinomial_rng(const Eigen::Matrix<double, Eigen::Dynamic, 1>& theta,
+
24  const int N,
+
25  RNG& rng) {
+
26  static const char* function("stan::math::multinomial_rng");
+ + +
29 
+
30  check_simplex(function, "Probabilites parameter", theta);
+
31  check_positive(function, "number of trials variables", N);
+
32 
+
33  std::vector<int> result(theta.size(), 0);
+
34  double mass_left = 1.0;
+
35  int n_left = N;
+
36  for (int k = 0; n_left > 0 && k < theta.size(); ++k) {
+
37  double p = theta[k] / mass_left;
+
38  if (p > 1.0) p = 1.0;
+
39  result[k] = binomial_rng(n_left, p, rng);
+
40  n_left -= result[k];
+
41  mass_left -= theta[k];
+
42  }
+
43  return result;
+
44  }
+
45 
+
46 
+
47  }
+
48 }
+
49 #endif
+ + + + + + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
std::vector< int > multinomial_rng(const Eigen::Matrix< double, Eigen::Dynamic, 1 > &theta, const int N, RNG &rng)
+ +
bool check_simplex(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is simplex.
+
int binomial_rng(const int N, const double theta, RNG &rng)
+ +
+
+
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diff --git a/doc/api/html/namespace_eigen.html b/doc/api/html/namespace_eigen.html new file mode 100644 index 00000000000..e2f4b30f3e2 --- /dev/null +++ b/doc/api/html/namespace_eigen.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: Eigen Namespace Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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Eigen Namespace Reference
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(Expert) Numerical traits for algorithmic differentiation variables. +More...

+ + + + + +

+Namespaces

 internal
 (Expert) Product traits for algorithmic differentiation variables.
 
+ + + + + + + +

+Classes

struct  NumTraits< stan::math::fvar< T > >
 Numerical traits template override for Eigen for automatic gradient variables. More...
 
struct  NumTraits< stan::math::var >
 Numerical traits template override for Eigen for automatic gradient variables. More...
 
+

Detailed Description

+

(Expert) Numerical traits for algorithmic differentiation variables.

+
+
+
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diff --git a/doc/api/html/namespace_eigen_1_1internal.html b/doc/api/html/namespace_eigen_1_1internal.html new file mode 100644 index 00000000000..c2741cf31ab --- /dev/null +++ b/doc/api/html/namespace_eigen_1_1internal.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: Eigen::internal Namespace Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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Eigen::internal Namespace Reference
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(Expert) Product traits for algorithmic differentiation variables. +More...

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+Classes

struct  general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor >
 
struct  general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs >
 
struct  general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs >
 Override matrix-vector and matrix-matrix products to use more efficient implementation. More...
 
struct  scalar_product_traits< double, stan::math::var >
 Scalar product traits override for Eigen for automatic gradient variables. More...
 
struct  scalar_product_traits< stan::math::var, double >
 Scalar product traits override for Eigen for automatic gradient variables. More...
 
struct  significant_decimals_default_impl< stan::math::fvar< T >, false >
 Implemented this for printing to stream. More...
 
struct  significant_decimals_default_impl< stan::math::var, false >
 Implemented this for printing to stream. More...
 
+

Detailed Description

+

(Expert) Product traits for algorithmic differentiation variables.

+
+
+
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boost Namespace Reference
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Reimplementing boost functionality. +More...

+ + + + + +

+Namespaces

 math
 Reimplmeneting boost functionality for stan::math::var and and bugs in classification of integer types.
 
+

Detailed Description

+

Reimplementing boost functionality.

+
+
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diff --git a/doc/api/html/namespaceboost_1_1math.html b/doc/api/html/namespaceboost_1_1math.html new file mode 100644 index 00000000000..5873666f159 --- /dev/null +++ b/doc/api/html/namespaceboost_1_1math.html @@ -0,0 +1,332 @@ + + + + + + +Stan Math Library: boost::math Namespace Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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Reimplmeneting boost functionality for stan::math::var and and bugs in classification of integer types. +More...

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+Functions

template<>
int fpclassify (const stan::math::var &v)
 Categorizes the given stan::math::var value. More...
 
template<>
bool isfinite (const stan::math::var &v)
 Checks if the given number has finite value. More...
 
template<>
bool isinf (const stan::math::var &v)
 Checks if the given number is infinite. More...
 
template<>
bool isnan (const stan::math::var &v)
 Checks if the given number is NaN. More...
 
template<>
bool isnormal (const stan::math::var &v)
 Checks if the given number is normal. More...
 
+

Detailed Description

+

Reimplmeneting boost functionality for stan::math::var and and bugs in classification of integer types.

+

FIXME: remove when BOOST fixes isfinite(). See ticket #6517. (Boost 1.48.0) https://svn.boost.org/trac/boost/ticket/6517

+

Function Documentation

+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
int boost::math::fpclassify (const stan::math::varv)
+
+inline
+
+ +

Categorizes the given stan::math::var value.

+

Categorizes the stan::math::var value, v, into the following categories: zero, subnormal, normal, infinite, or NAN.

+
Parameters
+ + +
vVariable to classify.
+
+
+
Returns
One of FP_ZERO, FP_NORMAL, FP_FINITE, FP_INFINITE, FP_NAN, or FP_SUBZERO, specifying the category of v.
+ +

Definition at line 24 of file boost_fpclassify.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
bool boost::math::isfinite (const stan::math::varv)
+
+inline
+
+ +

Checks if the given number has finite value.

+

Return true if the specified variable's value is finite.

+
Parameters
+ + +
vVariable to test.
+
+
+
Returns
true if variable is finite.
+ +

Definition at line 22 of file boost_isfinite.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
bool boost::math::isinf (const stan::math::varv)
+
+inline
+
+ +

Checks if the given number is infinite.

+

Return true if the specified variable's value is infinite.

+
Parameters
+ + +
vVariable to test.
+
+
+
Returns
true if variable is infinite.
+ +

Definition at line 22 of file boost_isinf.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
bool boost::math::isnan (const stan::math::varv)
+
+inline
+
+ +

Checks if the given number is NaN.

+

Return true if the specified variable has a value that is NaN.

+
Parameters
+ + +
vVariable to test.
+
+
+
Returns
true if variable is NaN.
+ +

Definition at line 22 of file boost_isnan.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
bool boost::math::isnormal (const stan::math::varv)
+
+inline
+
+ +

Checks if the given number is normal.

+

Return true if the specified variable has a value that is normal.

+
Parameters
+ + +
vVariable to test.
+
+
+
Returns
true if variable is normal.
+ +

Definition at line 22 of file boost_isnormal.hpp.

+ +
+
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diff --git a/doc/api/html/namespacemembers.html b/doc/api/html/namespacemembers.html new file mode 100644 index 00000000000..52ba0793d8c --- /dev/null +++ b/doc/api/html/namespacemembers.html @@ -0,0 +1,187 @@ + + + + + + +Stan Math Library: Namespace Members + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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Here is a list of all namespace members with links to the namespace documentation for each member:
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Here is a list of all namespace members with links to the namespace documentation for each member:
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Stan Math Library +  2.10.0 +
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+
Here is a list of all namespace members with links to the namespace documentation for each member:
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- c -

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diff --git a/doc/api/html/namespacemembers_d.html b/doc/api/html/namespacemembers_d.html new file mode 100644 index 00000000000..1308b247e6b --- /dev/null +++ b/doc/api/html/namespacemembers_d.html @@ -0,0 +1,214 @@ + + + + + + +Stan Math Library: Namespace Members + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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Here is a list of all namespace members with links to the namespace documentation for each member:
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- d -

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Here is a list of all namespace members with links to the namespace documentation for each member:
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- e -

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Here is a list of all namespace members with links to the namespace documentation for each member:
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diff --git a/doc/api/html/namespacemembers_func.html b/doc/api/html/namespacemembers_func.html new file mode 100644 index 00000000000..2324ca4c16a --- /dev/null +++ b/doc/api/html/namespacemembers_func.html @@ -0,0 +1,187 @@ + + + + + + +Stan Math Library: Namespace Members + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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- a -

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Stan Math Library +  2.10.0 +
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- b -

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Stan Math Library +  2.10.0 +
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- c -

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- l -

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- m -

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- n -

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 NboostReimplementing boost functionality
 NmathReimplmeneting boost functionality for stan::math::var and and bugs in classification of integer types
 NEigen(Expert) Numerical traits for algorithmic differentiation variables
 Ninternal(Expert) Product traits for algorithmic differentiation variables
 Nstan
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 Nstd
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stan Namespace Reference
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+Namespaces

 math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Classes

struct  contains_fvar
 Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters. More...
 
struct  contains_nonconstant_struct
 
struct  contains_vector
 
struct  error_index
 
struct  is_constant
 Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the C++ const sense). More...
 
struct  is_constant_struct
 Metaprogram to determine if a type has a base scalar type that can be assigned to type double. More...
 
struct  is_constant_struct< Eigen::Block< T > >
 
struct  is_constant_struct< Eigen::Matrix< T, R, C > >
 
struct  is_constant_struct< std::vector< T > >
 
struct  is_fvar
 
struct  is_fvar< stan::math::fvar< T > >
 
struct  is_var
 
struct  is_var< stan::math::var >
 
struct  is_var_or_arithmetic
 
struct  is_vector
 
struct  is_vector< const T >
 
struct  is_vector< Eigen::Block< T > >
 
struct  is_vector< Eigen::Matrix< T, 1, Eigen::Dynamic > >
 
struct  is_vector< Eigen::Matrix< T, Eigen::Dynamic, 1 > >
 
struct  is_vector< std::vector< T > >
 
struct  is_vector_like
 Template metaprogram indicates whether a type is vector_like. More...
 
struct  is_vector_like< const T >
 Template metaprogram indicates whether a type is vector_like. More...
 
struct  is_vector_like< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >
 Template metaprogram indicates whether a type is vector_like. More...
 
struct  is_vector_like< T * >
 Template metaprogram indicates whether a type is vector_like. More...
 
struct  partials_return_type
 
struct  partials_type
 
struct  partials_type< stan::math::fvar< T > >
 
struct  partials_type< stan::math::var >
 
struct  return_type
 Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters. More...
 
struct  scalar_type
 Metaprogram structure to determine the base scalar type of a template argument. More...
 
struct  scalar_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >
 
struct  scalar_type< T * >
 
struct  scalar_type_pre
 Metaprogram structure to determine the type of first container of the base scalar type of a template argument. More...
 
struct  size_of_helper
 
struct  size_of_helper< T, true >
 
class  VectorBuilder
 VectorBuilder allocates type T1 values to be used as intermediate values. More...
 
class  VectorBuilderHelper
 VectorBuilder allocates type T1 values to be used as intermediate values. More...
 
class  VectorBuilderHelper< T1, true, false >
 
class  VectorBuilderHelper< T1, true, true >
 Template specialization for using a vector. More...
 
class  VectorView
 VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[]. More...
 
class  VectorView< const Eigen::Matrix< T, R, C >, true, false >
 
class  VectorView< const std::vector< T >, true, false >
 
class  VectorView< Eigen::Matrix< T, R, C >, true, false >
 
class  VectorView< std::vector< T >, true, false >
 
class  VectorView< T, false, false >
 
class  VectorView< T, is_array, true >
 
class  VectorView< T, true, false >
 
class  VectorViewMvt
 
class  VectorViewMvt< const T, is_array, throw_if_accessed >
 VectorViewMvt that has const correctness. More...
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T >
get (const std::vector< T > &x, size_t n)
 
template<typename T >
size_t length (const std::vector< T > &x)
 
template<typename T , int R, int C>
get (const Eigen::Matrix< T, R, C > &m, size_t n)
 
template<typename T , int R, int C>
size_t length (const Eigen::Matrix< T, R, C > &m)
 
template<typename T , int R, int C>
size_t length_mvt (const Eigen::Matrix< T, R, C > &)
 
template<typename T , int R, int C>
size_t length_mvt (const std::vector< Eigen::Matrix< T, R, C > > &x)
 
template<typename T >
get (const T &x, size_t n)
 
template<typename T >
size_t length (const T &)
 
template<typename T >
size_t length_mvt (const T &)
 
template<typename T1 , typename T2 >
size_t max_size (const T1 &x1, const T2 &x2)
 
template<typename T1 , typename T2 , typename T3 >
size_t max_size (const T1 &x1, const T2 &x2, const T3 &x3)
 
template<typename T1 , typename T2 , typename T3 , typename T4 >
size_t max_size (const T1 &x1, const T2 &x2, const T3 &x3, const T4 &x4)
 
template<typename T1 , typename T2 >
size_t max_size_mvt (const T1 &x1, const T2 &x2)
 
template<typename T1 , typename T2 , typename T3 >
size_t max_size_mvt (const T1 &x1, const T2 &x2, const T3 &x3)
 
template<typename T1 , typename T2 , typename T3 , typename T4 >
size_t max_size_mvt (const T1 &x1, const T2 &x2, const T3 &x3, const T4 &x4)
 
template<typename T >
size_t size_of (const T &x)
 
+

Function Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::get (const Eigen::Matrix< T, R, C > & m,
size_t n 
)
+
+inline
+
+ +

Definition at line 9 of file get.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::get (const std::vector< T > & x,
size_t n 
)
+
+inline
+
+ +

Definition at line 10 of file get.hpp.

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+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::get (const T & x,
size_t n 
)
+
+inline
+
+ +

Definition at line 10 of file get.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + + + + +
size_t stan::length (const Eigen::Matrix< T, R, C > & m)
+
+ +

Definition at line 9 of file length.hpp.

+ +
+
+ +
+
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+template<typename T >
+ + + + + + + + +
size_t stan::length (const T & )
+
+ +

Definition at line 9 of file length.hpp.

+ +
+
+ +
+
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+template<typename T >
+ + + + + + + + +
size_t stan::length (const std::vector< T > & x)
+
+ +

Definition at line 10 of file length.hpp.

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+
+ +
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+template<typename T >
+ + + + + + + + +
size_t stan::length_mvt (const T & )
+
+ +

Definition at line 9 of file length_mvt.hpp.

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+
+ +
+
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+template<typename T , int R, int C>
+ + + + + + + + +
size_t stan::length_mvt (const Eigen::Matrix< T, R, C > & )
+
+ +

Definition at line 12 of file length_mvt.hpp.

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+
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+template<typename T , int R, int C>
+ + + + + + + + +
size_t stan::length_mvt (const std::vector< Eigen::Matrix< T, R, C > > & x)
+
+ +

Definition at line 17 of file length_mvt.hpp.

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+ +
+
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+template<typename T1 , typename T2 >
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size_t stan::max_size (const T1 & x1,
const T2 & x2 
)
+
+ +

Definition at line 9 of file max_size.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + + + + + + + + + + + + + + + + + + + + +
size_t stan::max_size (const T1 & x1,
const T2 & x2,
const T3 & x3 
)
+
+ +

Definition at line 16 of file max_size.hpp.

+ +
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+ +
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+template<typename T1 , typename T2 , typename T3 , typename T4 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
size_t stan::max_size (const T1 & x1,
const T2 & x2,
const T3 & x3,
const T4 & x4 
)
+
+ +

Definition at line 24 of file max_size.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + + + + + + + + + + + + + + +
size_t stan::max_size_mvt (const T1 & x1,
const T2 & x2 
)
+
+ +

Definition at line 10 of file max_size_mvt.hpp.

+ +
+
+ +
+
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+template<typename T1 , typename T2 , typename T3 >
+ + + + + + + + + + + + + + + + + + + + + + + + +
size_t stan::max_size_mvt (const T1 & x1,
const T2 & x2,
const T3 & x3 
)
+
+ +

Definition at line 17 of file max_size_mvt.hpp.

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+ +
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+template<typename T1 , typename T2 , typename T3 , typename T4 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
size_t stan::max_size_mvt (const T1 & x1,
const T2 & x2,
const T3 & x3,
const T4 & x4 
)
+
+ +

Definition at line 25 of file max_size_mvt.hpp.

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+template<typename T >
+ + + + + + + + +
size_t stan::size_of (const T & x)
+
+ +

Definition at line 24 of file size_of.hpp.

+ +
+
+
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+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/namespacestan_1_1math.html b/doc/api/html/namespacestan_1_1math.html new file mode 100644 index 00000000000..b0806a9d8ed --- /dev/null +++ b/doc/api/html/namespacestan_1_1math.html @@ -0,0 +1,58721 @@ + + + + + + +Stan Math Library: stan::math Namespace Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math Namespace Reference
+
+
+ +

Matrices and templated mathematical functions. +More...

+ + + + +

+Namespaces

 detail
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Classes

class  accumulator
 Class to accumulate values and eventually return their sum. More...
 
struct  apply_scalar_unary
 Base template class for vectorization of unary scalar functions defined by a template class F to a scalar, standard library vector, or Eigen dense matrix expression template. More...
 
struct  apply_scalar_unary< F, double >
 Template specialization for vectorized functions applying to double arguments. More...
 
struct  apply_scalar_unary< F, int >
 Template specialization for vectorized functions applying to integer arguments. More...
 
struct  apply_scalar_unary< F, stan::math::fvar< T > >
 Template specialization to fvar for vectorizing a unary scalar function. More...
 
struct  apply_scalar_unary< F, stan::math::var >
 Template specialization to var for vectorizing a unary scalar function. More...
 
struct  apply_scalar_unary< F, std::vector< T > >
 Template specialization for vectorized functions applying to standard vector containers. More...
 
struct  array_builder
 Structure for building up arrays in an expression (rather than in statements) using an argumentchaining add() method and a getter method array() to return the result. More...
 
struct  AutodiffStackStorage
 
class  chainable_alloc
 A chainable_alloc is an object which is constructed and destructed normally but the memory lifespan is managed along with the arena allocator for the gradient calculation. More...
 
struct  child_type
 Primary template class for metaprogram to compute child type of T. More...
 
struct  child_type< T_struct< T_child > >
 Specialization for template classes / structs. More...
 
class  cholesky_decompose_v_vari
 
struct  common_type
 
struct  common_type< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >
 
struct  common_type< std::vector< T1 >, std::vector< T2 > >
 
class  container_view
 Primary template class for container view of array y with same structure as T1 and size as x. More...
 
class  container_view< dummy, T2 >
 Dummy type specialization, used in conjunction with struct dummy as described above. More...
 
class  container_view< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >
 Template specialization for Eigen::Map view of array with scalar type T2 with size inferred from input Eigen::Matrix. More...
 
class  container_view< Eigen::Matrix< T1, R, C >, T2 >
 Template specialization for scalar view of array y with scalar type T2. More...
 
class  container_view< std::vector< Eigen::Matrix< T1, R, C > >, Eigen::Matrix< T2, R, C > >
 Template specialization for matrix view of array y with scalar type T2 with shape equal to x. More...
 
class  container_view< std::vector< T1 >, T2 >
 Template specialization for scalar view of array y with scalar type T2 with proper indexing inferred from input vector x of scalar type T1. More...
 
struct  coupled_ode_observer
 Observer for the coupled states. More...
 
struct  coupled_ode_system
 Base template class for a coupled ordinary differential equation system, which adds sensitivities to the base system. More...
 
class  coupled_ode_system< F, double, double >
 The coupled ode system for known initial values and known parameters. More...
 
struct  coupled_ode_system< F, double, stan::math::var >
 The coupled ODE system for known initial values and unknown parameters. More...
 
struct  coupled_ode_system< F, stan::math::var, double >
 The coupled ODE system for unknown initial values and known parameters. More...
 
struct  coupled_ode_system< F, stan::math::var, stan::math::var >
 The coupled ode system for unknown intial values and unknown parameters. More...
 
class  cvodes_ode_data
 CVODES ode data holder object which is used during CVODES integration for CVODES callbacks. More...
 
struct  dummy
 Empty struct for use in boost::condtional<is_constant_struct<T1>::value, T1, dummy>::type as false condtion for safe indexing. More...
 
struct  fvar
 
class  gevv_vvv_vari
 
struct  include_summand
 Template metaprogram to calculate whether a summand needs to be included in a proportional (log) probability calculation. More...
 
struct  index_type
 Primary template class for the metaprogram to compute the index type of a container. More...
 
struct  index_type< const T >
 Template class for metaprogram to compute the type of indexes used in a constant container type. More...
 
struct  index_type< Eigen::Matrix< T, R, C > >
 Template metaprogram defining typedef for the type of index for an Eigen matrix, vector, or row vector. More...
 
struct  index_type< std::vector< T > >
 Template metaprogram class to compute the type of index for a standard vector. More...
 
class  LDLT_alloc
 This object stores the actual (double typed) LDLT factorization of an Eigen::Matrix<var> along with pointers to its vari's which allow the *_ldlt functions to save memory. More...
 
class  LDLT_factor
 
class  LDLT_factor< stan::math::var, R, C >
 A template specialization of src/stan/math/matrix/LDLT_factor.hpp for stan::math::var which can be used with all the *_ldlt functions. More...
 
class  LDLT_factor< T, R, C >
 LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodiff of things like log determinants and solutions to linear systems. More...
 
class  ode_system
 Internal representation of an ODE model object which provides convenient Jacobian functions to obtain gradients wrt to states and parameters. More...
 
class  op_ddv_vari
 
class  op_dv_vari
 
class  op_dvd_vari
 
class  op_dvv_vari
 
class  op_matrix_vari
 
class  op_v_vari
 
class  op_vd_vari
 
class  op_vdd_vari
 
class  op_vdv_vari
 
class  op_vector_vari
 
class  op_vv_vari
 
class  op_vvd_vari
 
class  op_vvv_vari
 
struct  OperandsAndPartials
 This class builds partial derivatives with respect to a set of operands. More...
 
struct  OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
 This class builds partial derivatives with respect to a set of operands. More...
 
struct  OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >
 This class builds partial derivatives with respect to a set of operands. More...
 
struct  pass_type
 
struct  pass_type< double >
 
struct  pass_type< int >
 
class  precomp_v_vari
 
class  precomp_vv_vari
 
class  precomp_vvv_vari
 
class  precomputed_gradients_vari
 A variable implementation taking a sequence of operands and partial derivatives with respect to the operands. More...
 
struct  promote_scalar_struct
 General struct to hold static function for promoting underlying scalar types. More...
 
struct  promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > >
 Struct to hold static function for promoting underlying scalar types. More...
 
struct  promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > >
 Struct to hold static function for promoting underlying scalar types. More...
 
struct  promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > >
 Struct to hold static function for promoting underlying scalar types. More...
 
struct  promote_scalar_struct< T, std::vector< S > >
 Struct to hold static function for promoting underlying scalar types. More...
 
struct  promote_scalar_struct< T, T >
 Struct to hold static function for promoting underlying scalar types. More...
 
struct  promote_scalar_type
 Template metaprogram to calculate a type for converting a convertible type. More...
 
struct  promote_scalar_type< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >
 Template metaprogram to calculate a type for a row vector whose underlying scalar is converted from the second template parameter type to the first. More...
 
struct  promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >
 Template metaprogram to calculate a type for a matrix whose underlying scalar is converted from the second template parameter type to the first. More...
 
struct  promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >
 Template metaprogram to calculate a type for a vector whose underlying scalar is converted from the second template parameter type to the first. More...
 
struct  promote_scalar_type< T, std::vector< S > >
 Template metaprogram to calculate a type for a container whose underlying scalar is converted from the second template parameter type to the first. More...
 
struct  promoter
 
struct  promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > >
 
struct  promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > >
 
struct  promoter< std::vector< F >, std::vector< T > >
 
struct  promoter< std::vector< T >, std::vector< T > >
 
struct  promoter< T, T >
 
class  seq_view
 
class  seq_view< double, std::vector< int > >
 
class  seq_view< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >
 
class  seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >
 
class  seq_view< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >
 
class  seq_view< T, std::vector< S > >
 
class  seq_view< T, std::vector< std::vector< T > > >
 
class  seq_view< T, std::vector< T > >
 
class  stack_alloc
 An instance of this class provides a memory pool through which blocks of raw memory may be allocated and then collected simultaneously. More...
 
struct  store_type
 
struct  store_type< double >
 
struct  store_type< int >
 
class  stored_gradient_vari
 A var implementation that stores the daughter variable implementation pointers and the partial derivative with respect to the result explicitly in arrays constructed on the auto-diff memory stack. More...
 
class  sum_eigen_v_vari
 Class for representing sums with constructors for Eigen. More...
 
class  sum_v_vari
 Class for sums of variables constructed with standard vectors. More...
 
struct  value_type
 Primary template class for metaprogram to compute the type of values stored in a container. More...
 
struct  value_type< const T >
 Template class for metaprogram to compute the type of values stored in a constant container. More...
 
struct  value_type< Eigen::Matrix< T, R, C > >
 Template metaprogram defining the type of values stored in an Eigen matrix, vector, or row vector. More...
 
struct  value_type< std::vector< T > >
 Template metaprogram class to compute the type of values stored in a standard vector. More...
 
class  var
 Independent (input) and dependent (output) variables for gradients. More...
 
class  vari
 The variable implementation base class. More...
 
class  welford_covar_estimator
 
class  welford_var_estimator
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Typedefs

typedef Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
 Type for sizes and indexes in an Eigen matrix with double e. More...
 
typedef Eigen::Matrix< fvar< double >, Eigen::Dynamic, Eigen::Dynamic > matrix_fd
 
typedef Eigen::Matrix< fvar< fvar< double > >, Eigen::Dynamic, Eigen::Dynamic > matrix_ffd
 
typedef Eigen::Matrix< fvar< double >, Eigen::Dynamic, 1 > vector_fd
 
typedef Eigen::Matrix< fvar< fvar< double > >, Eigen::Dynamic, 1 > vector_ffd
 
typedef Eigen::Matrix< fvar< double >, 1, Eigen::Dynamic > row_vector_fd
 
typedef Eigen::Matrix< fvar< fvar< double > >, 1, Eigen::Dynamic > row_vector_ffd
 
typedef Eigen::Matrix< fvar< var >, Eigen::Dynamic, Eigen::Dynamic > matrix_fv
 
typedef Eigen::Matrix< fvar< fvar< var > >, Eigen::Dynamic, Eigen::Dynamic > matrix_ffv
 
typedef Eigen::Matrix< fvar< var >, Eigen::Dynamic, 1 > vector_fv
 
typedef Eigen::Matrix< fvar< fvar< var > >, Eigen::Dynamic, 1 > vector_ffv
 
typedef Eigen::Matrix< fvar< var >, 1, Eigen::Dynamic > row_vector_fv
 
typedef Eigen::Matrix< fvar< fvar< var > >, 1, Eigen::Dynamic > row_vector_ffv
 
typedef Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > matrix_d
 Type for matrix of double values. More...
 
typedef Eigen::Matrix< double, Eigen::Dynamic, 1 > vector_d
 Type for (column) vector of double values. More...
 
typedef Eigen::Matrix< double, 1, Eigen::Dynamic > row_vector_d
 Type for (row) vector of double values. More...
 
typedef AutodiffStackStorage< vari, chainable_allocChainableStack
 
typedef Eigen::Matrix< var, Eigen::Dynamic, Eigen::Dynamic > matrix_v
 The type of a matrix holding stan::math::var values. More...
 
typedef Eigen::Matrix< var, Eigen::Dynamic, 1 > vector_v
 The type of a (column) vector holding stan::math::var values. More...
 
typedef Eigen::Matrix< var, 1, Eigen::Dynamic > row_vector_v
 The type of a row vector holding stan::math::var values. More...
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T >
fvar< T > log_sum_exp (const std::vector< fvar< T > > &v)
 
template<typename T >
fvar< T > sum (const std::vector< fvar< T > > &m)
 Return the sum of the entries of the specified standard vector. More...
 
template<typename T >
std::vector< fvar< T > > to_fvar (const std::vector< T > &v)
 
template<typename T >
std::vector< fvar< T > > to_fvar (const std::vector< T > &v, const std::vector< T > &d)
 
template<typename T >
std::vector< fvar< T > > to_fvar (const std::vector< fvar< T > > &v)
 
template<typename T >
fvar< T > operator+ (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > operator+ (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > operator+ (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > operator/ (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > operator/ (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > operator/ (const double x1, const fvar< T > &x2)
 
template<typename T >
bool operator== (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool operator== (const fvar< T > &x, double y)
 
template<typename T >
bool operator== (double x, const fvar< T > &y)
 
template<typename T >
bool operator> (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool operator> (const fvar< T > &x, double y)
 
template<typename T >
bool operator> (double x, const fvar< T > &y)
 
template<typename T >
bool operator>= (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool operator>= (const fvar< T > &x, double y)
 
template<typename T >
bool operator>= (double x, const fvar< T > &y)
 
template<typename T >
bool operator< (const fvar< T > &x, double y)
 
template<typename T >
bool operator< (double x, const fvar< T > &y)
 
template<typename T >
bool operator< (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool operator<= (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool operator<= (const fvar< T > &x, double y)
 
template<typename T >
bool operator<= (double x, const fvar< T > &y)
 
template<typename T >
fvar< T > operator* (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > operator* (double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > operator* (const fvar< T > &x1, double x2)
 
template<typename T >
bool operator!= (const fvar< T > &x, const fvar< T > &y)
 
template<typename T >
bool operator!= (const fvar< T > &x, double y)
 
template<typename T >
bool operator!= (double x, const fvar< T > &y)
 
template<typename T >
fvar< T > operator- (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > operator- (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > operator- (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > operator- (const fvar< T > &x)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, 1, C1 > columns_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, 1, C1 > columns_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, 1, C1 > columns_dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, 1, C > columns_dot_self (const Eigen::Matrix< fvar< T >, R, C > &x)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, C, C > crossprod (const Eigen::Matrix< fvar< T >, R, C > &m)
 
template<typename T , int R, int C>
fvar< T > determinant (const Eigen::Matrix< fvar< T >, R, C > &m)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > divide (const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > divide (const Eigen::Matrix< fvar< T >, R, C > &v, const double c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > divide (const Eigen::Matrix< double, R, C > &v, const fvar< T > &c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > operator/ (const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > operator/ (const Eigen::Matrix< fvar< T >, R, C > &v, const double c)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > operator/ (const Eigen::Matrix< double, R, C > &v, const fvar< T > &c)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2, size_type &length)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2, size_type &length)
 
template<typename T , int R1, int C1, int R2, int C2>
fvar< T > dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2, size_type &length)
 
template<typename T >
fvar< T > dot_product (const std::vector< fvar< T > > &v1, const std::vector< fvar< T > > &v2)
 
template<typename T >
fvar< T > dot_product (const std::vector< double > &v1, const std::vector< fvar< T > > &v2)
 
template<typename T >
fvar< T > dot_product (const std::vector< fvar< T > > &v1, const std::vector< double > &v2)
 
template<typename T >
fvar< T > dot_product (const std::vector< fvar< T > > &v1, const std::vector< fvar< T > > &v2, size_type &length)
 
template<typename T >
fvar< T > dot_product (const std::vector< double > &v1, const std::vector< fvar< T > > &v2, size_type &length)
 
template<typename T >
fvar< T > dot_product (const std::vector< fvar< T > > &v1, const std::vector< double > &v2, size_type &length)
 
template<typename T , int R, int C>
fvar< T > dot_self (const Eigen::Matrix< fvar< T >, R, C > &v)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > inverse (const Eigen::Matrix< fvar< T >, R, C > &m)
 
template<typename T , int R, int C>
fvar< T > log_determinant (const Eigen::Matrix< fvar< T >, R, C > &m)
 
template<typename T >
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > log_softmax (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
 
template<typename T , int R, int C>
fvar< T > log_sum_exp (const Eigen::Matrix< fvar< T >, R, C > &v)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_left (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_left (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_left (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2, typename T2 >
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt (const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_left_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_left_tri_low (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_left_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_right (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_right (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_right (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_right_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_right_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_right_tri_low (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > multiply (const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
 
template<typename T , int R2, int C2>
Eigen::Matrix< fvar< T >, R2, C2 > multiply (const Eigen::Matrix< fvar< T >, R2, C2 > &m, const double c)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > multiply (const Eigen::Matrix< double, R1, C1 > &m, const fvar< T > &c)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > multiply (const fvar< T > &c, const Eigen::Matrix< fvar< T >, R1, C1 > &m)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > multiply (const double c, const Eigen::Matrix< fvar< T >, R1, C1 > &m)
 
template<typename T , int R1, int C1>
Eigen::Matrix< fvar< T >, R1, C1 > multiply (const fvar< T > &c, const Eigen::Matrix< double, R1, C1 > &m)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > multiply (const Eigen::Matrix< fvar< T >, R1, C1 > &m1, const Eigen::Matrix< fvar< T >, R2, C2 > &m2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > multiply (const Eigen::Matrix< fvar< T >, R1, C1 > &m1, const Eigen::Matrix< double, R2, C2 > &m2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, C2 > multiply (const Eigen::Matrix< double, R1, C1 > &m1, const Eigen::Matrix< fvar< T >, R2, C2 > &m2)
 
template<typename T , int C1, int R2>
fvar< T > multiply (const Eigen::Matrix< fvar< T >, 1, C1 > &rv, const Eigen::Matrix< fvar< T >, R2, 1 > &v)
 
template<typename T , int C1, int R2>
fvar< T > multiply (const Eigen::Matrix< fvar< T >, 1, C1 > &rv, const Eigen::Matrix< double, R2, 1 > &v)
 
template<typename T , int C1, int R2>
fvar< T > multiply (const Eigen::Matrix< double, 1, C1 > &rv, const Eigen::Matrix< fvar< T >, R2, 1 > &v)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose (const Eigen::Matrix< fvar< T >, R, C > &m)
 
template<typename T >
Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > qr_Q (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > &m)
 
template<typename T >
Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > qr_R (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > &m)
 
template<int RA, int CA, int RB, int CB, typename T >
Eigen::Matrix< fvar< T >, CB, CB > quad_form_sym (const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
 
template<int RA, int CA, int RB, typename T >
fvar< T > quad_form_sym (const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, 1 > &B)
 
template<int RA, int CA, int RB, int CB, typename T >
Eigen::Matrix< fvar< T >, CB, CB > quad_form_sym (const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
 
template<int RA, int CA, int RB, typename T >
fvar< T > quad_form_sym (const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, 1 > &B)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, 1 > rows_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, 1 > rows_dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< fvar< T >, R1, 1 > rows_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, 1 > rows_dot_self (const Eigen::Matrix< fvar< T >, R, C > &x)
 
template<typename T >
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > softmax (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
 
template<typename T >
std::vector< fvar< T > > sort_asc (std::vector< fvar< T > > xs)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > sort_asc (Eigen::Matrix< fvar< T >, R, C > xs)
 
template<typename T >
std::vector< fvar< T > > sort_desc (std::vector< fvar< T > > xs)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > sort_desc (Eigen::Matrix< fvar< T >, R, C > xs)
 
template<typename T , int R, int C>
fvar< T > sum (const Eigen::Matrix< fvar< T >, R, C > &m)
 Return the sum of the entries of the specified matrix. More...
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, R > tcrossprod (const Eigen::Matrix< fvar< T >, R, C > &m)
 
template<int R, int C, typename T >
Eigen::Matrix< T, R, C > to_fvar (const Eigen::Matrix< T, R, C > &m)
 
template<int R, int C>
Eigen::Matrix< fvar< double >, R, C > to_fvar (const Eigen::Matrix< double, R, C > &m)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > to_fvar (const Eigen::Matrix< T, R, C > &val, const Eigen::Matrix< T, R, C > &deriv)
 
template<int RD, int CD, int RA, int CA, int RB, int CB, typename T >
fvar< T > trace_gen_quad_form (const Eigen::Matrix< fvar< T >, RD, CD > &D, const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
 
template<int RA, int CA, int RB, int CB, typename T >
fvar< T > trace_quad_form (const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
 
template<int RA, int CA, int RB, int CB, typename T >
fvar< T > trace_quad_form (const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
 
template<int RA, int CA, int RB, int CB, typename T >
fvar< T > trace_quad_form (const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > unit_vector_constrain (const Eigen::Matrix< fvar< T >, R, C > &y)
 
template<typename T , int R, int C>
Eigen::Matrix< fvar< T >, R, C > unit_vector_constrain (const Eigen::Matrix< fvar< T >, R, C > &y, fvar< T > &lp)
 
template<typename T , typename F >
void gradient (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &fx, Eigen::Matrix< T, Eigen::Dynamic, 1 > &grad_fx)
 Calculate the value and the gradient of the specified function at the specified argument. More...
 
template<typename T , typename F >
void jacobian (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, Eigen::Matrix< T, Eigen::Dynamic, 1 > &fx, Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &J)
 
template<typename T >
fvar< T > abs (const fvar< T > &x)
 
template<typename T >
fvar< T > acos (const fvar< T > &x)
 
template<typename T >
fvar< T > acosh (const fvar< T > &x)
 
template<typename T >
fvar< T > asin (const fvar< T > &x)
 
template<typename T >
fvar< T > asinh (const fvar< T > &x)
 
template<typename T >
fvar< T > atan (const fvar< T > &x)
 
template<typename T >
fvar< T > atan2 (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > atan2 (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > atan2 (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > atanh (const fvar< T > &x)
 
template<typename T >
fvar< T > bessel_first_kind (int v, const fvar< T > &z)
 
template<typename T >
fvar< T > bessel_second_kind (int v, const fvar< T > &z)
 
template<typename T >
fvar< T > binary_log_loss (const int y, const fvar< T > &y_hat)
 
template<typename T >
fvar< T > binomial_coefficient_log (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > binomial_coefficient_log (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > binomial_coefficient_log (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > cbrt (const fvar< T > &x)
 
template<typename T >
fvar< T > ceil (const fvar< T > &x)
 
template<typename T >
fvar< T > cos (const fvar< T > &x)
 
template<typename T >
fvar< T > cosh (const fvar< T > &x)
 
template<typename T >
fvar< T > digamma (const fvar< T > &x)
 
template<typename T >
fvar< T > erf (const fvar< T > &x)
 
template<typename T >
fvar< T > erfc (const fvar< T > &x)
 
template<typename T >
fvar< T > exp (const fvar< T > &x)
 
template<typename T >
fvar< T > exp2 (const fvar< T > &x)
 
template<typename T >
fvar< T > expm1 (const fvar< T > &x)
 
template<typename T >
fvar< T > fabs (const fvar< T > &x)
 
template<typename T >
fvar< T > falling_factorial (const fvar< T > &x, const fvar< T > &n)
 
template<typename T >
fvar< T > falling_factorial (const fvar< T > &x, const double n)
 
template<typename T >
fvar< T > falling_factorial (const double x, const fvar< T > &n)
 
template<typename T >
fvar< T > fdim (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > fdim (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > fdim (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > floor (const fvar< T > &x)
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > fma (const fvar< T1 > &x1, const fvar< T2 > &x2, const fvar< T3 > &x3)
 The fused multiply-add operation (C99). More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > fma (const T1 &x1, const fvar< T2 > &x2, const fvar< T3 > &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > fma (const fvar< T1 > &x1, const T2 &x2, const fvar< T3 > &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > fma (const fvar< T1 > &x1, const fvar< T2 > &x2, const T3 &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > fma (const T1 &x1, const T2 &x2, const fvar< T3 > &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > fma (const fvar< T1 > &x1, const T2 &x2, const T3 &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T1 , typename T2 , typename T3 >
fvar< typename stan::return_type< T1, T2, T3 >::type > fma (const T1 &x1, const fvar< T2 > &x2, const T3 &x3)
 See all-var input signature for details on the function and derivatives. More...
 
template<typename T >
fvar< T > fmax (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > fmax (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > fmax (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > fmin (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > fmin (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > fmin (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > fmod (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > fmod (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > fmod (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > gamma_p (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > gamma_p (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > gamma_p (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > gamma_q (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > gamma_q (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > gamma_q (const double x1, const fvar< T > &x2)
 
template<typename T >
void grad_inc_beta (stan::math::fvar< T > &g1, stan::math::fvar< T > &g2, stan::math::fvar< T > a, stan::math::fvar< T > b, stan::math::fvar< T > z)
 
template<typename T >
fvar< T > hypot (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > hypot (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > hypot (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > inc_beta (const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
 
template<typename T >
fvar< T > inv (const fvar< T > &x)
 
template<typename T >
fvar< T > inv_cloglog (const fvar< T > &x)
 
template<typename T >
fvar< T > inv_logit (const fvar< T > &x)
 
template<typename T >
fvar< T > inv_Phi (const fvar< T > &p)
 
template<typename T >
fvar< T > inv_sqrt (const fvar< T > &x)
 
template<typename T >
fvar< T > inv_square (const fvar< T > &x)
 
template<typename T >
int is_inf (const fvar< T > &x)
 Returns 1 if the input's value is infinite and 0 otherwise. More...
 
template<typename T >
int is_nan (const fvar< T > &x)
 Returns 1 if the input's value is NaN and 0 otherwise. More...
 
template<typename T >
fvar< T > lbeta (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > lbeta (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > lbeta (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > lgamma (const fvar< T > &x)
 
template<typename T >
fvar< typename stan::return_type< T, int >::type > lmgamma (int x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > log (const fvar< T > &x)
 
template<typename T >
fvar< T > log10 (const fvar< T > &x)
 
template<typename T >
fvar< T > log1m (const fvar< T > &x)
 
template<typename T >
fvar< T > log1m_exp (const fvar< T > &x)
 
template<typename T >
fvar< T > log1m_inv_logit (const fvar< T > &x)
 
template<typename T >
fvar< T > log1p (const fvar< T > &x)
 
template<typename T >
fvar< T > log1p_exp (const fvar< T > &x)
 
template<typename T >
fvar< T > log2 (const fvar< T > &x)
 
template<typename T >
fvar< T > log_diff_exp (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T1 , typename T2 >
fvar< T2 > log_diff_exp (const T1 &x1, const fvar< T2 > &x2)
 
template<typename T1 , typename T2 >
fvar< T1 > log_diff_exp (const fvar< T1 > &x1, const T2 &x2)
 
template<typename T >
fvar< T > log_falling_factorial (const fvar< T > &x, const fvar< T > &n)
 
template<typename T >
fvar< T > log_falling_factorial (const double x, const fvar< T > &n)
 
template<typename T >
fvar< T > log_falling_factorial (const fvar< T > &x, const double n)
 
template<typename T >
fvar< T > log_inv_logit (const fvar< T > &x)
 
template<typename T_theta , typename T_lambda1 , typename T_lambda2 , int N>
void log_mix_partial_helper (const T_theta &theta, const T_lambda1 &lambda1, const T_lambda2 &lambda2, typename boost::math::tools::promote_args< T_theta, T_lambda1, T_lambda2 >::type(&partials_array)[N])
 
template<typename T >
fvar< T > log_mix (const fvar< T > &theta, const fvar< T > &lambda1, const fvar< T > &lambda2)
 Return the log mixture density with specified mixing proportion and log densities and its derivative at each. More...
 
template<typename T >
fvar< T > log_mix (const fvar< T > &theta, const fvar< T > &lambda1, const double lambda2)
 
template<typename T >
fvar< T > log_mix (const fvar< T > &theta, const double lambda1, const fvar< T > &lambda2)
 
template<typename T >
fvar< T > log_mix (const double theta, const fvar< T > &lambda1, const fvar< T > &lambda2)
 
template<typename T >
fvar< T > log_mix (const fvar< T > &theta, const double lambda1, const double lambda2)
 
template<typename T >
fvar< T > log_mix (const double theta, const fvar< T > &lambda1, const double lambda2)
 
template<typename T >
fvar< T > log_mix (const double theta, const double lambda1, const fvar< T > &lambda2)
 
template<typename T >
fvar< T > log_rising_factorial (const fvar< T > &x, const fvar< T > &n)
 
template<typename T >
fvar< T > log_rising_factorial (const fvar< T > &x, const double n)
 
template<typename T >
fvar< T > log_rising_factorial (const double x, const fvar< T > &n)
 
template<typename T >
fvar< T > log_sum_exp (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > log_sum_exp (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > log_sum_exp (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > logit (const fvar< T > &x)
 
template<typename T >
fvar< T > modified_bessel_first_kind (int v, const fvar< T > &z)
 
template<typename T >
fvar< T > modified_bessel_second_kind (int v, const fvar< T > &z)
 
template<typename T >
fvar< T > multiply_log (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > multiply_log (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > multiply_log (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > owens_t (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > owens_t (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > owens_t (const fvar< T > &x1, const double x2)
 
template<typename T >
fvar< T > Phi (const fvar< T > &x)
 
template<typename T >
fvar< T > pow (const fvar< T > &x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > pow (const double x1, const fvar< T > &x2)
 
template<typename T >
fvar< T > pow (const fvar< T > &x1, const double x2)
 
template<typename T >
double primitive_value (const fvar< T > &v)
 Return the primitive value of the specified forward-mode autodiff variable. More...
 
template<typename T >
fvar< T > rising_factorial (const fvar< T > &x, const fvar< T > &n)
 
template<typename T >
fvar< T > rising_factorial (const fvar< T > &x, const double n)
 
template<typename T >
fvar< T > rising_factorial (const double x, const fvar< T > &n)
 
template<typename T >
fvar< T > round (const fvar< T > &x)
 
template<typename T >
fvar< T > sin (const fvar< T > &x)
 
template<typename T >
fvar< T > sinh (const fvar< T > &x)
 
template<typename T >
fvar< T > sqrt (const fvar< T > &x)
 
template<typename T >
fvar< T > square (const fvar< T > &x)
 
template<typename T >
fvar< T > tan (const fvar< T > &x)
 
template<typename T >
fvar< T > tanh (const fvar< T > &x)
 
template<typename T >
fvar< T > tgamma (const fvar< T > &x)
 
template<typename T >
fvar< T > to_fvar (const T &x)
 
template<typename T >
fvar< T > to_fvar (const fvar< T > &x)
 
template<typename T >
fvar< T > trunc (const fvar< T > &x)
 
template<typename T >
value_of (const fvar< T > &v)
 Return the value of the specified variable. More...
 
template<typename T >
double value_of_rec (const fvar< T > &v)
 Return the value of the specified variable. More...
 
template<typename T >
bool is_aligned (T *ptr, unsigned int bytes_aligned)
 Return true if the specified pointer is aligned on the number of bytes. More...
 
template<typename T , typename F >
void derivative (const F &f, const T &x, T &fx, T &dfx_dx)
 Return the derivative of the specified univariate function at the specified argument. More...
 
template<typename F >
void finite_diff_grad_hessian (const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1,-1 > &hess, std::vector< Eigen::Matrix< double,-1,-1 > > &grad_hess_fx, const double epsilon=1e-04)
 Calculate the value and the gradient of the hessian of the specified function at the specified argument using second-order autodiff and first-order finite difference. More...
 
template<typename F >
void grad_hessian (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &H, std::vector< Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > > &grad_H)
 Calculate the value, the Hessian, and the gradient of the Hessian of the specified function at the specified argument. More...
 
template<typename F >
void grad_tr_mat_times_hessian (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &M, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad_tr_MH)
 
template<typename T1 , typename T2 , typename F >
void gradient_dot_vector (const F &f, const Eigen::Matrix< T1, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< T2, Eigen::Dynamic, 1 > &v, T1 &fx, T1 &grad_fx_dot_v)
 
template<typename F >
void hessian (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &H)
 Calculate the value, the gradient, and the Hessian, of the specified function at the specified argument in O(N^2) time and O(N^2) space. More...
 
template<typename T , typename F >
void hessian (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &fx, Eigen::Matrix< T, Eigen::Dynamic, 1 > &grad, Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &H)
 
template<typename F >
void hessian_times_vector (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &v, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &Hv)
 
template<typename T , typename F >
void hessian_times_vector (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, T &fx, Eigen::Matrix< T, Eigen::Dynamic, 1 > &Hv)
 
template<typename T , typename F >
void partial_derivative (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, int n, T &fx, T &dfx_dxn)
 Return the partial derivative of the specified multiivariate function at the specified argument. More...
 
template<typename T_y >
bool check_nonzero_size (const char *function, const char *name, const T_y &y)
 Return true if the specified matrix/vector is of non-zero size. More...
 
template<typename T_y >
bool check_ordered (const char *function, const char *name, const std::vector< T_y > &y)
 Return true if the specified vector is sorted into strictly increasing order. More...
 
double dist (const std::vector< double > &x, const std::vector< double > &y)
 
double dot (const std::vector< double > &x, const std::vector< double > &y)
 
double dot_self (const std::vector< double > &x)
 
template<typename T , typename S >
void fill (std::vector< T > &x, const S &y)
 Fill the specified container with the specified value. More...
 
double log_sum_exp (const std::vector< double > &x)
 Return the log of the sum of the exponentiated values of the specified sequence of values. More...
 
template<typename T >
std::vector< T > rep_array (const T &x, int n)
 
template<typename T >
std::vector< std::vector< T > > rep_array (const T &x, int m, int n)
 
template<typename T >
std::vector< std::vector< std::vector< T > > > rep_array (const T &x, int k, int m, int n)
 
void scaled_add (std::vector< double > &x, const std::vector< double > &y, const double lambda)
 
void sub (std::vector< double > &x, std::vector< double > &y, std::vector< double > &result)
 
template<typename T >
sum (const std::vector< T > &xs)
 Return the sum of the values in the specified standard vector. More...
 
template<typename T >
std::vector< typename child_type< T >::type > value_of (const std::vector< T > &x)
 Convert a std::vector of type T to a std::vector of child_type<T>::type. More...
 
template<>
std::vector< double > value_of (const std::vector< double > &x)
 Return the specified argument. More...
 
template<typename T >
std::vector< double > value_of_rec (const std::vector< T > &x)
 Convert a std::vector of type T to a std::vector of doubles. More...
 
template<>
std::vector< double > value_of_rec (const std::vector< double > &x)
 Return the specified argument. More...
 
template<typename F , typename T1 , typename T2 >
std::vector< std::vector< typename stan::return_type< T1, T2 >::type > > integrate_ode_rk45 (const F &f, const std::vector< T1 > y0, const double t0, const std::vector< double > &ts, const std::vector< T2 > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs=0, double relative_tolerance=1e-6, double absolute_tolerance=1e-6, int max_num_steps=1E6)
 Return the solutions for the specified system of ordinary differential equations given the specified initial state, initial times, times of desired solution, and parameters and data, writing error and warning messages to the specified stream. More...
 
template<typename T_y >
bool check_cholesky_factor (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a valid Cholesky factor. More...
 
template<typename T_y >
bool check_cholesky_factor_corr (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a valid Cholesky factor of a correlation matrix. More...
 
template<typename T_y , int R, int C>
bool check_column_index (const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
 Return true if the specified index is a valid column of the matrix. More...
 
template<typename T_y >
bool check_corr_matrix (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a valid correlation matrix. More...
 
template<typename T_y >
bool check_cov_matrix (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a valid covariance matrix. More...
 
template<typename T , int R, int C>
bool check_ldlt_factor (const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
 Return true if the argument is a valid stan::math::LDLT_factor. More...
 
template<typename T_y >
bool check_lower_triangular (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is lower triangular. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
bool check_matching_dims (const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
 Return true if the two matrices are of the same size. More...
 
template<typename T_y1 , typename T_y2 >
bool check_matching_sizes (const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
 Return true if two structures at the same size. More...
 
template<typename T1 , typename T2 >
bool check_multiplicable (const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
 Return true if the matrices can be multiplied. More...
 
template<typename T_y >
bool check_ordered (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, 1 > &y)
 Return true if the specified vector is sorted into strictly increasing order. More...
 
template<typename T_y >
bool check_pos_definite (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified square, symmetric matrix is positive definite. More...
 
template<typename Derived >
bool check_pos_definite (const char *function, const char *name, const Eigen::LDLT< Derived > &cholesky)
 Return true if the specified LDLT transform of a matrix is positive definite. More...
 
template<typename Derived >
bool check_pos_definite (const char *function, const char *name, const Eigen::LLT< Derived > &cholesky)
 Return true if the specified LLT transform of a matrix is positive definite. More...
 
template<typename T_y >
bool check_pos_semidefinite (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is positive definite. More...
 
template<typename T_y >
bool check_positive_ordered (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, 1 > &y)
 Return true if the specified vector contains non-negative values and is sorted into strictly increasing order. More...
 
bool check_range (const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
 Return true if specified index is within range. More...
 
bool check_range (const char *function, const char *name, const int max, const int index, const char *error_msg)
 Return true if specified index is within range. More...
 
bool check_range (const char *function, const char *name, const int max, const int index)
 Return true if specified index is within range. More...
 
template<typename T_y , int R, int C>
bool check_row_index (const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
 Return true if the specified index is a valid row of the matrix. More...
 
template<typename T_prob >
bool check_simplex (const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 Return true if the specified vector is simplex. More...
 
template<typename T_y >
bool check_spsd_matrix (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is a square, symmetric, and positive semi-definite. More...
 
template<typename T_y >
bool check_square (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is square. More...
 
template<typename T >
bool check_std_vector_index (const char *function, const char *name, const std::vector< T > &y, int i)
 Return true if the specified index is valid in std vector. More...
 
template<typename T_y >
bool check_symmetric (const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return true if the specified matrix is symmetric. More...
 
template<typename T_prob >
bool check_unit_vector (const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 Return true if the specified vector is unit vector. More...
 
template<typename T , int R, int C>
bool check_vector (const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
 Return true if the matrix is either a row vector or column vector. More...
 
void validate_non_negative_index (const char *var_name, const char *expr, int val)
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > add (const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
 Return the sum of the specified matrices. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > add (const Eigen::Matrix< T1, R, C > &m, const T2 &c)
 Return the sum of the specified matrix and specified scalar. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > add (const T1 &c, const Eigen::Matrix< T2, R, C > &m)
 Return the sum of the specified scalar and specified matrix. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > append_col (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &B)
 Return the result of appending the second argument matrix after the first argument matrix, that is, putting them side by side, with the first matrix followed by the second matrix. More...
 
template<typename T1 , typename T2 , int C1, int C2>
Eigen::Matrix< typename return_type< T1, T2 >::type, 1, Eigen::Dynamic > append_col (const Eigen::Matrix< T1, 1, C1 > &A, const Eigen::Matrix< T2, 1, C2 > &B)
 Return the result of concatenaing the first row vector followed by the second row vector side by side, with the result being a row vector. More...
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > append_col (const Eigen::Matrix< T, R1, C1 > &A, const Eigen::Matrix< T, R2, C2 > &B)
 Return the result of appending the second argument matrix after the first argument matrix, that is, putting them side by side, with the first matrix followed by the second matrix. More...
 
template<typename T , int C1, int C2>
Eigen::Matrix< T, 1, Eigen::Dynamic > append_col (const Eigen::Matrix< T, 1, C1 > &A, const Eigen::Matrix< T, 1, C2 > &B)
 Return the result of concatenaing the first row vector followed by the second row vector side by side, with the result being a row vector. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename return_type< T1, T2 >::type, 1, Eigen::Dynamic > append_col (const T1 &A, const Eigen::Matrix< T2, R, C > &B)
 Return the result of stacking an scalar on top of the a row vector, with the result being a row vector. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename return_type< T1, T2 >::type, 1, Eigen::Dynamic > append_col (const Eigen::Matrix< T1, R, C > &A, const T2 &B)
 Return the result of stacking a row vector on top of the an scalar, with the result being a row vector. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > append_row (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &B)
 Return the result of stacking the rows of the first argument matrix on top of the second argument matrix. More...
 
template<typename T1 , typename T2 , int R1, int R2>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, 1 > append_row (const Eigen::Matrix< T1, R1, 1 > &A, const Eigen::Matrix< T2, R2, 1 > &B)
 Return the result of stacking the first vector on top of the second vector, with the result being a vector. More...
 
template<typename T , int R1, int C1, int R2, int C2>
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > append_row (const Eigen::Matrix< T, R1, C1 > &A, const Eigen::Matrix< T, R2, C2 > &B)
 Return the result of stacking the rows of the first argument matrix on top of the second argument matrix. More...
 
template<typename T , int R1, int R2>
Eigen::Matrix< T, Eigen::Dynamic, 1 > append_row (const Eigen::Matrix< T, R1, 1 > &A, const Eigen::Matrix< T, R2, 1 > &B)
 Return the result of stacking the first vector on top of the second vector, with the result being a vector. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, 1 > append_row (const T1 &A, const Eigen::Matrix< T2, R, C > &B)
 Return the result of stacking an scalar on top of the a vector, with the result being a vector. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename return_type< T1, T2 >::type, Eigen::Dynamic, 1 > append_row (const Eigen::Matrix< T1, R, C > &A, const T2 &B)
 Return the result of stacking a vector on top of the an scalar, with the result being a vector. More...
 
void print_mat_size (int n, std::ostream &o)
 Helper function to return the matrix size as either "dynamic" or "1". More...
 
template<typename LHS , typename RHS >
void assign (LHS &lhs, const RHS &rhs)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename LHS , typename RHS , int R1, int C1, int R2, int C2>
void assign (Eigen::Matrix< LHS, R1, C1 > &x, const Eigen::Matrix< RHS, R2, C2 > &y)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename LHS , typename RHS , int R, int C>
void assign (Eigen::Matrix< LHS, R, C > &x, const Eigen::Matrix< RHS, R, C > &y)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename LHS , typename RHS , int R, int C>
void assign (Eigen::Block< LHS > x, const Eigen::Matrix< RHS, R, C > &y)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename LHS , typename RHS >
void assign (std::vector< LHS > &x, const std::vector< RHS > &y)
 Copy the right-hand side's value to the left-hand side variable. More...
 
template<typename T >
void autocorrelation (const std::vector< T > &y, std::vector< T > &ac, Eigen::FFT< T > &fft)
 Write autocorrelation estimates for every lag for the specified input sequence into the specified result using the specified FFT engine. More...
 
template<typename T >
void autocorrelation (const std::vector< T > &y, std::vector< T > &ac)
 Write autocorrelation estimates for every lag for the specified input sequence into the specified result. More...
 
template<typename T >
void autocovariance (const std::vector< T > &y, std::vector< T > &acov, Eigen::FFT< T > &fft)
 Write autocovariance estimates for every lag for the specified input sequence into the specified result using the specified FFT engine. More...
 
template<typename T >
void autocovariance (const std::vector< T > &y, std::vector< T > &acov)
 Write autocovariance estimates for every lag for the specified input sequence into the specified result. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > block (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t nrows, size_t ncols)
 Return a nrows x ncols submatrix starting at (i-1, j-1). More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_corr_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y, int K)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_corr_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y, int K, T &lp)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > cholesky_corr_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_decompose (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Return the lower-triangular Cholesky factor (i.e., matrix square root) of the specified square, symmetric matrix. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_factor_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, int M, int N)
 Return the Cholesky factor of the specified size read from the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_factor_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, int M, int N, T &lp)
 Return the Cholesky factor of the specified size read from the specified vector and increment the specified log probability reference with the log Jacobian adjustment of the transform. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > cholesky_factor_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return the unconstrained vector of parameters correspdonding to the specified Cholesky factor. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > col (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t j)
 Return the specified column of the specified matrix using start-at-1 indexing. More...
 
template<typename T , int R, int C>
int cols (const Eigen::Matrix< T, R, C > &m)
 Return the number of columns in the specified matrix, vector, or row vector. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< double, 1, C1 > columns_dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 Returns the dot product of the specified vectors. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, 1, C > columns_dot_self (const Eigen::Matrix< T, R, C > &x)
 Returns the dot product of each column of a matrix with itself. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > corr_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type k)
 Return the correlation matrix of the specified dimensionality derived from the specified vector of unconstrained values. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > corr_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type k, T &lp)
 Return the correlation matrix of the specified dimensionality derived from the specified vector of unconstrained values. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > corr_matrix_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return the vector of unconstrained partial correlations that define the specified correlation matrix when transformed. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cov_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type K)
 Return the symmetric, positive-definite matrix of dimensions K by K resulting from transforming the specified finite vector of size K plus (K choose 2). More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cov_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >::type K, T &lp)
 Return the symmetric, positive-definite matrix of dimensions K by K resulting from transforming the specified finite vector of size K plus (K choose 2). More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cov_matrix_constrain_lkj (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t k)
 Return the covariance matrix of the specified dimensionality derived from constraining the specified vector of unconstrained values. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cov_matrix_constrain_lkj (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t k, T &lp)
 Return the covariance matrix of the specified dimensionality derived from constraining the specified vector of unconstrained values and increment the specified log probability reference with the log absolute Jacobian determinant. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > cov_matrix_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
 The covariance matrix derived from the symmetric view of the lower-triangular view of the K by K specified matrix is freed to return a vector of size K + (K choose 2). More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > cov_matrix_free_lkj (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &y)
 Return the vector of unconstrained partial correlations and deviations that transform to the specified covariance matrix. More...
 
matrix_d crossprod (const matrix_d &M)
 Returns the result of pre-multiplying a matrix by its own transpose. More...
 
template<typename T >
const std::vector< int > csr_extract_u (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 Extract the NZE index for each entry from a sparse matrix. More...
 
template<typename T , int R, int C>
const std::vector< int > csr_extract_u (const Eigen::Matrix< T, R, C > &A)
 Extract the NZE index for each entry from a sparse matrix. More...
 
template<typename T >
const std::vector< int > csr_extract_v (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 Extract the column indexes for non-zero value from a sparse matrix. More...
 
template<typename T , int R, int C>
const std::vector< int > csr_extract_v (const Eigen::Matrix< T, R, C > &A)
 Extract the column indexes for non-zero values from a dense matrix by converting to sparse and calling the sparse matrix extractor. More...
 
template<typename T >
const Eigen::Matrix< T, Eigen::Dynamic, 1 > csr_extract_w (const Eigen::SparseMatrix< T, Eigen::RowMajor > &A)
 
template<typename T , int R, int C>
const Eigen::Matrix< T, Eigen::Dynamic, 1 > csr_extract_w (const Eigen::Matrix< T, R, C > &A)
 
template<typename T1 , typename T2 >
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, Eigen::Dynamic, 1 > csr_matrix_times_vector (const int &m, const int &n, const Eigen::Matrix< T1, Eigen::Dynamic, 1 > &w, const std::vector< int > &v, const std::vector< int > &u, const Eigen::Matrix< T2, Eigen::Dynamic, 1 > &b)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > csr_to_dense_matrix (const int &m, const int &n, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &w, const std::vector< int > &v, const std::vector< int > &u)
 Construct a dense Eigen matrix from the CSR format components. More...
 
int csr_u_to_z (const std::vector< int > &u, int i)
 Return the z vector computed from the specified u vector at the index for the z vector. More...
 
template<typename T >
std::vector< T > cumulative_sum (const std::vector< T > &x)
 Return the cumulative sum of the specified vector. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > cumulative_sum (const Eigen::Matrix< T, R, C > &m)
 Return the cumulative sum of the specified matrix. More...
 
template<typename T , int R, int C>
determinant (const Eigen::Matrix< T, R, C > &m)
 Returns the determinant of the specified square matrix. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > diag_matrix (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v)
 Return a square diagonal matrix with the specified vector of coefficients as the diagonal values. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C1 > diag_post_multiply (const Eigen::Matrix< T1, R1, C1 > &m1, const Eigen::Matrix< T2, R2, C2 > &m2)
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R2, C2 > diag_pre_multiply (const Eigen::Matrix< T1, R1, C1 > &m1, const Eigen::Matrix< T2, R2, C2 > &m2)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > diagonal (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Return a column vector of the diagonal elements of the specified matrix. More...
 
template<typename T >
void dims (const T &x, std::vector< int > &result)
 
template<typename T , int R, int C>
void dims (const Eigen::Matrix< T, R, C > &x, std::vector< int > &result)
 
template<typename T >
void dims (const std::vector< T > &x, std::vector< int > &result)
 
template<typename T >
std::vector< int > dims (const T &x)
 
template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::math::tools::promote_args< T1, T2 >::type distance (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 Returns the distance between the specified vectors. More...
 
template<int R, int C, typename T >
boost::enable_if_c< boost::is_arithmetic< T >::value, Eigen::Matrix< double, R, C > >::type divide (const Eigen::Matrix< double, R, C > &m, T c)
 Return specified matrix divided by specified scalar. More...
 
template<int R1, int C1, int R2, int C2>
double dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 Returns the dot product of the specified vectors. More...
 
double dot_product (const double *v1, const double *v2, size_t length)
 Returns the dot product of the specified arrays of doubles. More...
 
double dot_product (const std::vector< double > &v1, const std::vector< double > &v2)
 Returns the dot product of the specified arrays of doubles. More...
 
template<int R, int C>
double dot_self (const Eigen::Matrix< double, R, C > &v)
 Returns the dot product of the specified vector with itself. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > eigenvalues_sym (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Return the eigenvalues of the specified symmetric matrix in descending order of magnitude. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > eigenvectors_sym (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > elt_divide (const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
 Return the elementwise division of the specified matrices. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > elt_divide (const Eigen::Matrix< T1, R, C > &m, T2 s)
 Return the elementwise division of the specified matrix by the specified scalar. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > elt_divide (T1 s, const Eigen::Matrix< T2, R, C > &m)
 Return the elementwise division of the specified scalar by the specified matrix. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > elt_multiply (const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
 Return the elementwise multiplication of the specified matrices. More...
 
template<typename T , int Rows, int Cols>
Eigen::Matrix< T, Rows, Cols > exp (const Eigen::Matrix< T, Rows, Cols > &m)
 Return the element-wise exponentiation of the matrix or vector. More...
 
template<int Rows, int Cols>
Eigen::Matrix< double, Rows, Cols > exp (const Eigen::Matrix< double, Rows, Cols > &m)
 
template<typename T >
bool factor_cov_matrix (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &Sigma, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, Eigen::Array< T, Eigen::Dynamic, 1 > &sds)
 This function is intended to make starting values, given a covariance matrix Sigma. More...
 
template<typename T >
void factor_U (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &U, Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs)
 This function is intended to make starting values, given a unit upper-triangular matrix U such that U'DU is a correlation matrix. More...
 
template<typename T , int R, int C, typename S >
void fill (Eigen::Matrix< T, R, C > &x, const S &y)
 Fill the specified container with the specified value. More...
 
template<typename T >
const T & get_base1 (const std::vector< T > &x, size_t i, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one index. More...
 
template<typename T >
const T & get_base1 (const std::vector< std::vector< T > > &x, size_t i1, size_t i2, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & get_base1 (const std::vector< std::vector< std::vector< T > > > &x, size_t i1, size_t i2, size_t i3, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & get_base1 (const std::vector< std::vector< std::vector< std::vector< T > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, size_t i7, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
const T & get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, size_t i7, size_t i8, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x, size_t m, const char *error_msg, size_t idx)
 Return a copy of the row of the specified vector at the specified base-one row index. More...
 
template<typename T >
const T & get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x, size_t m, size_t n, const char *error_msg, size_t idx)
 Return a reference to the value of the specified matrix at the specified base-one row and column indexes. More...
 
template<typename T >
const T & get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t m, const char *error_msg, size_t idx)
 Return a reference to the value of the specified column vector at the specified base-one index. More...
 
template<typename T >
const T & get_base1 (const Eigen::Matrix< T, 1, Eigen::Dynamic > &x, size_t n, const char *error_msg, size_t idx)
 Return a reference to the value of the specified row vector at the specified base-one index. More...
 
template<typename T >
T & get_base1_lhs (std::vector< T > &x, size_t i, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one index. More...
 
template<typename T >
T & get_base1_lhs (std::vector< std::vector< T > > &x, size_t i1, size_t i2, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & get_base1_lhs (std::vector< std::vector< std::vector< T > > > &x, size_t i1, size_t i2, size_t i3, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & get_base1_lhs (std::vector< std::vector< std::vector< std::vector< T > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, size_t i7, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
T & get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > > &x, size_t i1, size_t i2, size_t i3, size_t i4, size_t i5, size_t i6, size_t i7, size_t i8, const char *error_msg, size_t idx)
 Return a reference to the value of the specified vector at the specified base-one indexes. More...
 
template<typename T >
Eigen::Block< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > > get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x, size_t m, const char *error_msg, size_t idx)
 Return a copy of the row of the specified vector at the specified base-one row index. More...
 
template<typename T >
T & get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x, size_t m, size_t n, const char *error_msg, size_t idx)
 Return a reference to the value of the specified matrix at the specified base-one row and column indexes. More...
 
template<typename T >
T & get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, size_t m, const char *error_msg, size_t idx)
 Return a reference to the value of the specified column vector at the specified base-one index. More...
 
template<typename T >
T & get_base1_lhs (Eigen::Matrix< T, 1, Eigen::Dynamic > &x, size_t n, const char *error_msg, size_t idx)
 Return a reference to the value of the specified row vector at the specified base-one index. More...
 
template<typename T_lp , typename T_lp_accum >
boost::math::tools::promote_args< T_lp, T_lp_accum >::type get_lp (const T_lp &lp, const stan::math::accumulator< T_lp_accum > &lp_accum)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > head (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t n)
 Return the specified number of elements as a vector from the front of the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > head (const Eigen::Matrix< T, 1, Eigen::Dynamic > &rv, size_t n)
 Return the specified number of elements as a row vector from the front of the specified row vector. More...
 
template<typename T >
std::vector< T > head (const std::vector< T > &sv, size_t n)
 Return the specified number of elements as a standard vector from the front of the specified standard vector. More...
 
template<typename T >
void initialize (T &x, const T &v)
 
template<typename T , typename V >
boost::enable_if_c< boost::is_arithmetic< V >::value, void >::type initialize (T &x, V v)
 
template<typename T , int R, int C, typename V >
void initialize (Eigen::Matrix< T, R, C > &x, const V &v)
 
template<typename T , typename V >
void initialize (std::vector< T > &x, const V &v)
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > inverse (const Eigen::Matrix< T, R, C > &m)
 Returns the inverse of the specified matrix. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > inverse_spd (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Returns the inverse of the specified symmetric, pos/neg-definite matrix. More...
 
template<typename T , int Rows, int Cols>
Eigen::Matrix< T, Rows, Cols > log (const Eigen::Matrix< T, Rows, Cols > &m)
 Return the element-wise logarithm of the matrix or vector. More...
 
template<typename T , int R, int C>
log_determinant (const Eigen::Matrix< T, R, C > &m)
 Returns the log absolute determinant of the specified square matrix. More...
 
template<int R, int C, typename T >
log_determinant_ldlt (stan::math::LDLT_factor< T, R, C > &A)
 
template<typename T , int R, int C>
log_determinant_spd (const Eigen::Matrix< T, R, C > &m)
 Returns the log absolute determinant of the specified square matrix. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > log_softmax (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v)
 Return the natural logarithm of the softmax of the specified vector. More...
 
template<int R, int C>
double log_sum_exp (const Eigen::Matrix< double, R, C > &x)
 Return the log of the sum of the exponentiated values of the specified matrix of values. More...
 
template<typename T >
const Eigen::Array< T, Eigen::Dynamic, 1 > make_nu (const T eta, const size_t K)
 This function calculates the degrees of freedom for the t distribution that corresponds to the shape parameter in the Lewandowski et. More...
 
int max (const std::vector< int > &x)
 Returns the maximum coefficient in the specified column vector. More...
 
template<typename T >
max (const std::vector< T > &x)
 Returns the maximum coefficient in the specified column vector. More...
 
template<typename T , int R, int C>
max (const Eigen::Matrix< T, R, C > &m)
 Returns the maximum coefficient in the specified vector, row vector, or matrix. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 Returns the solution of the system Ax=b. More...
 
template<int R1, int C1, int R2, int C2, typename T1 , typename T2 >
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_ldlt (const stan::math::LDLT_factor< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_spd (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 Returns the solution of the system Ax=b where A is symmetric positive definite. More...
 
template<int TriView, typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_tri (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 Returns the solution of the system Ax=b when A is triangular. More...
 
template<int TriView, typename T , int R1, int C1>
Eigen::Matrix< T, R1, C1 > mdivide_left_tri (const Eigen::Matrix< T, R1, C1 > &A)
 Returns the solution of the system Ax=b when A is triangular and b=I. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_tri_low (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 
template<typename T , int R1, int C1>
Eigen::Matrix< T, R1, C1 > mdivide_left_tri_low (const Eigen::Matrix< T, R1, C1 > &A)
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_right (const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
 Returns the solution of the system Ax=b. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_right_ldlt (const Eigen::Matrix< T1, R1, C1 > &b, const stan::math::LDLT_factor< T2, R2, C2 > &A)
 Returns the solution of the system xA=b given an LDLT_factor of A. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< double, R1, C2 > mdivide_right_ldlt (const Eigen::Matrix< double, R1, C1 > &b, const stan::math::LDLT_factor< double, R2, C2 > &A)
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_right_spd (const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
 Returns the solution of the system Ax=b where A is symmetric positive definite. More...
 
template<int TriView, typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_right_tri (const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
 Returns the solution of the system Ax=b when A is triangular. More...
 
template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_right_tri_low (const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
 Returns the solution of the system tri(A)x=b when tri(A) is a lower triangular view of the matrix A. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type mean (const std::vector< T > &v)
 Returns the sample mean (i.e., average) of the coefficients in the specified standard vector. More...
 
template<typename T , int R, int C>
boost::math::tools::promote_args< T >::type mean (const Eigen::Matrix< T, R, C > &m)
 Returns the sample mean (i.e., average) of the coefficients in the specified vector, row vector, or matrix. More...
 
int min (const std::vector< int > &x)
 Returns the minimum coefficient in the specified column vector. More...
 
template<typename T >
min (const std::vector< T > &x)
 Returns the minimum coefficient in the specified column vector. More...
 
template<typename T , int R, int C>
min (const Eigen::Matrix< T, R, C > &m)
 Returns the minimum coefficient in the specified matrix, vector, or row vector. More...
 
template<typename T >
minus (const T &x)
 Returns the negation of the specified scalar or matrix. More...
 
template<int R, int C, typename T >
boost::enable_if_c< boost::is_arithmetic< T >::value, Eigen::Matrix< double, R, C > >::type multiply (const Eigen::Matrix< double, R, C > &m, T c)
 Return specified matrix multiplied by specified scalar. More...
 
template<int R, int C, typename T >
boost::enable_if_c< boost::is_arithmetic< T >::value, Eigen::Matrix< double, R, C > >::type multiply (T c, const Eigen::Matrix< double, R, C > &m)
 Return specified scalar multiplied by specified matrix. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< double, R1, C2 > multiply (const Eigen::Matrix< double, R1, C1 > &m1, const Eigen::Matrix< double, R2, C2 > &m2)
 Return the product of the specified matrices. More...
 
template<int C1, int R2>
double multiply (const Eigen::Matrix< double, 1, C1 > &rv, const Eigen::Matrix< double, R2, 1 > &v)
 Return the scalar product of the specified row vector and specified column vector. More...
 
matrix_d multiply_lower_tri_self_transpose (const matrix_d &L)
 Returns the result of multiplying the lower triangular portion of the input matrix by its own transpose. More...
 
template<typename T >
int num_elements (const T &x)
 Returns 1, the number of elements in a primitive type. More...
 
template<typename T , int R, int C>
int num_elements (const Eigen::Matrix< T, R, C > &m)
 Returns the size of the specified matrix. More...
 
template<typename T >
int num_elements (const std::vector< T > &v)
 Returns the number of elements in the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 Return an increasing ordered vector derived from the specified free vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &lp)
 Return a positive valued, increasing ordered vector derived from the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > ordered_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
 Return the vector of unconstrained scalars that transform to the specified positive ordered vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > positive_ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 Return an increasing positive ordered vector derived from the specified free vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > positive_ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &lp)
 Return a positive valued, increasing positive ordered vector derived from the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > positive_ordered_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
 Return the vector of unconstrained scalars that transform to the specified positive ordered vector. More...
 
template<typename T >
prod (const std::vector< T > &v)
 Returns the product of the coefficients of the specified standard vector. More...
 
template<typename T , int R, int C>
prod (const Eigen::Matrix< T, R, C > &v)
 Returns the product of the coefficients of the specified column vector. More...
 
template<typename T1 , typename T2 , typename F >
common_type< T1, T2 >::type promote_common (const F &u)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > qr_Q (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > qr_R (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 
template<int RA, int CA, int RB, int CB, typename T >
Eigen::Matrix< T, CB, CB > quad_form (const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, CB > &B)
 Compute B^T A B. More...
 
template<int RA, int CA, int RB, typename T >
quad_form (const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, 1 > &B)
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > quad_form_diag (const Eigen::Matrix< T1, Eigen::Dynamic, Eigen::Dynamic > &mat, const Eigen::Matrix< T2, R, C > &vec)
 
template<int RA, int CA, int RB, int CB, typename T >
Eigen::Matrix< T, CB, CB > quad_form_sym (const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, CB > &B)
 
template<int RA, int CA, int RB, typename T >
quad_form_sym (const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, 1 > &B)
 
template<typename T >
int rank (const std::vector< T > &v, int s)
 Return the number of components of v less than v[s]. More...
 
template<typename T , int R, int C>
int rank (const Eigen::Matrix< T, R, C > &v, int s)
 Return the number of components of v less than v[s]. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_L (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
 Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_L (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K, T &log_prob)
 Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations, incrementing the specified scalar reference with the log absolute determinant of the Jacobian of the transformation. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
 Return the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K, T &log_prob)
 Return the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations, incrementing the specified scalar reference with the log absolute determinant of the Jacobian of the transformation. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_cov_L (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds, T &log_prob)
 This is the function that should be called prior to evaluating the density of any elliptical distribution. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_cov_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds, T &log_prob)
 A generally worse alternative to call prior to evaluating the density of an elliptical distribution. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_cov_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds)
 Builds a covariance matrix from CPCs and standard deviations. More...
 
template<typename T >
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, Eigen::Dynamic, Eigen::Dynamic > rep_matrix (const T &x, int m, int n)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > rep_matrix (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, int n)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > rep_matrix (const Eigen::Matrix< T, 1, Eigen::Dynamic > &rv, int m)
 
template<typename T >
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, 1, Eigen::Dynamic > rep_row_vector (const T &x, int m)
 
template<typename T >
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, Eigen::Dynamic, 1 > rep_vector (const T &x, int n)
 
template<typename T >
void resize (T &x, std::vector< size_t > dims)
 Recursively resize the specified vector of vectors, which must bottom out at scalar values, Eigen vectors or Eigen matrices. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > row (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i)
 Return the specified row of the specified matrix, using start-at-1 indexing. More...
 
template<typename T , int R, int C>
int rows (const Eigen::Matrix< T, R, C > &m)
 Return the number of rows in the specified matrix, vector, or row vector. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< double, R1, 1 > rows_dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 Returns the dot product of the specified vectors. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, 1 > rows_dot_self (const Eigen::Matrix< T, R, C > &x)
 Returns the dot product of each row of a matrix with itself. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type sd (const std::vector< T > &v)
 Returns the unbiased sample standard deviation of the coefficients in the specified column vector. More...
 
template<typename T , int R, int C>
boost::math::tools::promote_args< T >::type sd (const Eigen::Matrix< T, R, C > &m)
 Returns the unbiased sample standard deviation of the coefficients in the specified vector, row vector, or matrix. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > segment (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t i, size_t n)
 Return the specified number of elements as a vector starting from the specified element - 1 of the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > segment (const Eigen::Matrix< T, 1, Eigen::Dynamic > &v, size_t i, size_t n)
 
template<typename T >
std::vector< T > segment (const std::vector< T > &sv, size_t i, size_t n)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > simplex_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
 Return the simplex corresponding to the specified free vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > simplex_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y, T &lp)
 Return the simplex corresponding to the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > simplex_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 Return an unconstrained vector that when transformed produces the specified simplex. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > singular_values (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Return the vector of the singular values of the specified matrix in decreasing order of magnitude. More...
 
template<typename T >
int size (const std::vector< T > &x)
 Return the size of the specified standard vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > softmax (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v)
 Return the softmax of the specified vector. More...
 
template<typename T >
std::vector< T > sort_asc (std::vector< T > xs)
 Return the specified standard vector in ascending order. More...
 
template<typename T >
std::vector< T > sort_desc (std::vector< T > xs)
 Return the specified standard vector in descending order. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > sort_asc (Eigen::Matrix< T, R, C > xs)
 Return the specified eigen vector in ascending order. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > sort_desc (Eigen::Matrix< T, R, C > xs)
 Return the specified eigen vector in descending order. More...
 
template<typename C >
std::vector< int > sort_indices_asc (const C &xs)
 Return a sorted copy of the argument container in ascending order. More...
 
template<typename C >
std::vector< int > sort_indices_desc (const C &xs)
 Return a sorted copy of the argument container in ascending order. More...
 
template<int R1, int C1, int R2, int C2, typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type squared_distance (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 Returns the squared distance between the specified vectors. More...
 
template<typename T >
void stan_print (std::ostream *o, const T &x)
 
template<typename T >
void stan_print (std::ostream *o, const std::vector< T > &x)
 
template<typename T >
void stan_print (std::ostream *o, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 
template<typename T >
void stan_print (std::ostream *o, const Eigen::Matrix< T, 1, Eigen::Dynamic > &x)
 
template<typename T >
void stan_print (std::ostream *o, const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > sub_col (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t nrows)
 Return a nrows x 1 subcolumn starting at (i-1, j-1). More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > sub_row (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t ncols)
 Return a 1 x nrows subrow starting at (i-1, j-1). More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract (const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
 Return the result of subtracting the second specified matrix from the first specified matrix. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract (const T1 &c, const Eigen::Matrix< T2, R, C > &m)
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract (const Eigen::Matrix< T1, R, C > &m, const T2 &c)
 
template<typename T , int R, int C>
double sum (const Eigen::Matrix< T, R, C > &v)
 Returns the sum of the coefficients of the specified column vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > tail (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t n)
 Return the specified number of elements as a vector from the back of the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > tail (const Eigen::Matrix< T, 1, Eigen::Dynamic > &rv, size_t n)
 Return the specified number of elements as a row vector from the back of the specified row vector. More...
 
template<typename T >
std::vector< T > tail (const std::vector< T > &sv, size_t n)
 
matrix_d tcrossprod (const matrix_d &M)
 Returns the result of post-multiplying a matrix by its own transpose. More...
 
template<typename T , int R, int C>
std::vector< T > to_array_1d (const Eigen::Matrix< T, R, C > &matrix)
 
template<typename T >
std::vector< T > to_array_1d (const std::vector< T > &x)
 
template<typename T >
std::vector< typename scalar_type< T >::type > to_array_1d (const std::vector< std::vector< T > > &x)
 
template<typename T >
std::vector< std::vector< T > > to_array_2d (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &matrix)
 
template<typename T , int R, int C>
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > to_matrix (Eigen::Matrix< T, R, C > matrix)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > to_matrix (const std::vector< std::vector< T > > &vec)
 
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > to_matrix (const std::vector< std::vector< int > > &vec)
 
template<typename T , int R, int C>
Eigen::Matrix< T, 1, Eigen::Dynamic > to_row_vector (const Eigen::Matrix< T, R, C > &matrix)
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > to_row_vector (const std::vector< T > &vec)
 
Eigen::Matrix< double, 1, Eigen::Dynamic > to_row_vector (const std::vector< int > &vec)
 
template<typename T , int R, int C>
Eigen::Matrix< T, Eigen::Dynamic, 1 > to_vector (const Eigen::Matrix< T, R, C > &matrix)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > to_vector (const std::vector< T > &vec)
 
Eigen::Matrix< double, Eigen::Dynamic, 1 > to_vector (const std::vector< int > &vec)
 
template<typename T >
trace (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Returns the trace of the specified matrix. More...
 
template<typename T >
trace (const T &m)
 
template<typename T1 , typename T2 , typename T3 , int R1, int C1, int R2, int C2, int R3, int C3>
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value &&!stan::is_var< T3 >::value, typename boost::math::tools::promote_args< T1, T2, T3 >::type >::type trace_gen_inv_quad_form_ldlt (const Eigen::Matrix< T1, R1, C1 > &D, const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
 
template<int RD, int CD, int RA, int CA, int RB, int CB>
double trace_gen_quad_form (const Eigen::Matrix< double, RD, CD > &D, const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
 Compute trace(D B^T A B). More...
 
template<typename T1 , typename T2 , int R2, int C2, int R3, int C3>
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value, typename boost::math::tools::promote_args< T1, T2 >::type >::type trace_inv_quad_form_ldlt (const stan::math::LDLT_factor< T1, R2, C2 > &A, const Eigen::Matrix< T2, R3, C3 > &B)
 
template<int RA, int CA, int RB, int CB>
double trace_quad_form (const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
 Compute trace(B^T A B). More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, C, R > transpose (const Eigen::Matrix< T, R, C > &m)
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > unit_vector_constrain (const Eigen::Matrix< T, R, C > &y)
 Return the unit length vector corresponding to the free vector y. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > unit_vector_constrain (const Eigen::Matrix< T, R, C > &y, T &lp)
 Return the unit length vector corresponding to the free vector y. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > unit_vector_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 Transformation of a unit length vector to a "free" vector However, we are just fixing the unidentified radius to 1. More...
 
template<typename T , int R, int C>
Eigen::Matrix< typename child_type< T >::type, R, C > value_of (const Eigen::Matrix< T, R, C > &M)
 Convert a matrix of type T to a matrix of doubles. More...
 
template<int R, int C>
Eigen::Matrix< double, R, C > value_of (const Eigen::Matrix< double, R, C > &x)
 Return the specified argument. More...
 
template<typename T , int R, int C>
Eigen::Matrix< double, R, C > value_of_rec (const Eigen::Matrix< T, R, C > &M)
 Convert a matrix of type T to a matrix of doubles. More...
 
template<int R, int C>
Eigen::Matrix< double, R, C > value_of_rec (const Eigen::Matrix< double, R, C > &x)
 Return the specified argument. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type variance (const std::vector< T > &v)
 Returns the sample variance (divide by length - 1) of the coefficients in the specified standard vector. More...
 
template<typename T , int R, int C>
boost::math::tools::promote_args< T >::type variance (const Eigen::Matrix< T, R, C > &m)
 Returns the sample variance (divide by length - 1) of the coefficients in the specified column vector. More...
 
template<typename F >
void finite_diff_gradient (const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1, 1 > &grad_fx, const double epsilon=1e-03)
 Calculate the value and the gradient of the specified function at the specified argument using finite difference. More...
 
template<typename F >
double finite_diff_hess_helper (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const int lambda, const double epsilon=1e-03)
 
template<typename F >
void finite_diff_hessian (const F &f, const Eigen::Matrix< double,-1, 1 > &x, double &fx, Eigen::Matrix< double,-1, 1 > &grad_fx, Eigen::Matrix< double,-1,-1 > &hess_fx, const double epsilon=1e-03)
 Calculate the value and the Hessian of the specified function at the specified argument using second-order finite difference. More...
 
template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type categorical_log (int n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type categorical_log (const typename math::index_type< Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > >::type n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type categorical_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type categorical_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type categorical_logit_log (int n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type categorical_logit_log (int n, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
 
template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type categorical_logit_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type categorical_logit_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &beta)
 
template<class RNG >
int categorical_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &theta, RNG &rng)
 
template<bool propto, typename T_prob , typename T_prior_sample_size >
boost::math::tools::promote_args< T_prob, T_prior_sample_size >::type dirichlet_log (const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta, const Eigen::Matrix< T_prior_sample_size, Eigen::Dynamic, 1 > &alpha)
 The log of the Dirichlet density for the given theta and a vector of prior sample sizes, alpha. More...
 
template<typename T_prob , typename T_prior_sample_size >
boost::math::tools::promote_args< T_prob, T_prior_sample_size >::type dirichlet_log (const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta, const Eigen::Matrix< T_prior_sample_size, Eigen::Dynamic, 1 > &alpha)
 
template<class RNG >
Eigen::VectorXd dirichlet_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &alpha, RNG &rng)
 Return a draw from a Dirichlet distribution with specified parameters and pseudo-random number generator. More...
 
template<bool propto, typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, Eigen::Dynamic > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
 The log of a Gaussian dynamic linear model (GDLM). More...
 
template<typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, Eigen::Dynamic > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
 
template<bool propto, typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, 1 > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
 The log of a Gaussian dynamic linear model (GDLM) with uncorrelated observation disturbances. More...
 
template<typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
return_type< T_y, typename return_type< T_F, T_G, T_V, T_W, T_m0, T_C0 >::type >::type gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > &F, const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > &G, const Eigen::Matrix< T_V, Eigen::Dynamic, 1 > &V, const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > &W, const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > &m0, const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > &C0)
 
template<bool propto, typename T_y , typename T_dof , typename T_scale >
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type inv_wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
 The log of the Inverse-Wishart density for the given W, degrees of freedom, and scale matrix. More...
 
template<typename T_y , typename T_dof , typename T_scale >
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type inv_wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
 
template<class RNG >
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > inv_wishart_rng (const double nu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
 
template<bool propto, typename T_covar , typename T_shape >
boost::math::tools::promote_args< T_covar, T_shape >::type lkj_corr_cholesky_log (const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const T_shape &eta)
 
template<typename T_covar , typename T_shape >
boost::math::tools::promote_args< T_covar, T_shape >::type lkj_corr_cholesky_log (const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const T_shape &eta)
 
template<class RNG >
Eigen::MatrixXd lkj_corr_cholesky_rng (const size_t K, const double eta, RNG &rng)
 
template<typename T_shape >
T_shape do_lkj_constant (const T_shape &eta, const unsigned int &K)
 
template<bool propto, typename T_y , typename T_shape >
boost::math::tools::promote_args< T_y, T_shape >::type lkj_corr_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_shape &eta)
 
template<typename T_y , typename T_shape >
boost::math::tools::promote_args< T_y, T_shape >::type lkj_corr_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_shape &eta)
 
template<class RNG >
Eigen::MatrixXd lkj_corr_rng (const size_t K, const double eta, RNG &rng)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_loc, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< T_scale, Eigen::Dynamic, 1 > &sigma, const T_shape &eta)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_loc, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< T_scale, Eigen::Dynamic, 1 > &sigma, const T_shape &eta)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_loc &mu, const T_scale &sigma, const T_shape &eta)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
boost::math::tools::promote_args< T_y, T_loc, T_scale, T_shape >::type lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const T_loc &mu, const T_scale &sigma, const T_shape &eta)
 
template<bool propto, typename T_y , typename T_Mu , typename T_Sigma , typename T_D >
boost::math::tools::promote_args< T_y, T_Mu, T_Sigma, T_D >::type matrix_normal_prec_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_Mu, Eigen::Dynamic, Eigen::Dynamic > &Mu, const Eigen::Matrix< T_Sigma, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_D, Eigen::Dynamic, Eigen::Dynamic > &D)
 The log of the matrix normal density for the given y, mu, Sigma and D where Sigma and D are given as precision matrices, not covariance matrices. More...
 
template<typename T_y , typename T_Mu , typename T_Sigma , typename T_D >
boost::math::tools::promote_args< T_y, T_Mu, T_Sigma, T_D >::type matrix_normal_prec_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_Mu, Eigen::Dynamic, Eigen::Dynamic > &Mu, const Eigen::Matrix< T_Sigma, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_D, Eigen::Dynamic, Eigen::Dynamic > &D)
 
template<bool propto, typename T_y , typename T_covar , typename T_w >
boost::math::tools::promote_args< T_y, T_covar, T_w >::type multi_gp_cholesky_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
 The log of a multivariate Gaussian Process for the given y, w, and a Cholesky factor L of the kernel matrix Sigma. More...
 
template<typename T_y , typename T_covar , typename T_w >
boost::math::tools::promote_args< T_y, T_covar, T_w >::type multi_gp_cholesky_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &L, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
 
template<bool propto, typename T_y , typename T_covar , typename T_w >
boost::math::tools::promote_args< T_y, T_covar, T_w >::type multi_gp_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
 The log of a multivariate Gaussian Process for the given y, Sigma, and w. More...
 
template<typename T_y , typename T_covar , typename T_w >
boost::math::tools::promote_args< T_y, T_covar, T_w >::type multi_gp_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y, const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > &Sigma, const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > &w)
 
template<bool propto, typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type multi_normal_cholesky_log (const T_y &y, const T_loc &mu, const T_covar &L)
 The log of the multivariate normal density for the given y, mu, and a Cholesky factor L of the variance matrix. More...
 
template<typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type multi_normal_cholesky_log (const T_y &y, const T_loc &mu, const T_covar &L)
 
template<class RNG >
Eigen::VectorXd multi_normal_cholesky_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
 
template<bool propto, typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type multi_normal_log (const T_y &y, const T_loc &mu, const T_covar &Sigma)
 
template<typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type multi_normal_log (const T_y &y, const T_loc &mu, const T_covar &Sigma)
 
template<bool propto, typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type multi_normal_prec_log (const T_y &y, const T_loc &mu, const T_covar &Sigma)
 
template<typename T_y , typename T_loc , typename T_covar >
return_type< T_y, T_loc, T_covar >::type multi_normal_prec_log (const T_y &y, const T_loc &mu, const T_covar &Sigma)
 
template<class RNG >
Eigen::VectorXd multi_normal_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
 
template<bool propto, typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type multi_student_t_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &Sigma)
 Return the log of the multivariate Student t distribution at the specified arguments. More...
 
template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type multi_student_t_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &Sigma)
 
template<class RNG >
Eigen::VectorXd multi_student_t_rng (const double nu, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &s, RNG &rng)
 
template<bool propto, typename T_prob >
boost::math::tools::promote_args< T_prob >::type multinomial_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<typename T_prob >
boost::math::tools::promote_args< T_prob >::type multinomial_log (const std::vector< int > &ns, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
 
template<class RNG >
std::vector< int > multinomial_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &theta, const int N, RNG &rng)
 
template<typename T >
log_inv_logit_diff (const T &alpha, const T &beta)
 
template<bool propto, typename T_lambda , typename T_cut >
boost::math::tools::promote_args< T_lambda, T_cut >::type ordered_logistic_log (int y, const T_lambda &lambda, const Eigen::Matrix< T_cut, Eigen::Dynamic, 1 > &c)
 Returns the (natural) log probability of the specified integer outcome given the continuous location and specified cutpoints in an ordered logistic model. More...
 
template<typename T_lambda , typename T_cut >
boost::math::tools::promote_args< T_lambda, T_cut >::type ordered_logistic_log (int y, const T_lambda &lambda, const Eigen::Matrix< T_cut, Eigen::Dynamic, 1 > &c)
 
template<class RNG >
int ordered_logistic_rng (const double eta, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &c, RNG &rng)
 
template<bool propto, typename T_y , typename T_dof , typename T_scale >
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
 The log of the Wishart density for the given W, degrees of freedom, and scale matrix. More...
 
template<typename T_y , typename T_dof , typename T_scale >
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
 
template<class RNG >
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > wishart_rng (const double nu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
 
template<typename T_y , typename T_low , typename T_high >
bool check_bounded (const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
 Return true if the value is between the low and high values, inclusively. More...
 
template<typename T >
bool check_consistent_size (const char *function, const char *name, const T &x, size_t expected_size)
 Return true if the dimension of x is consistent, which is defined to be expected_size if x is a vector or 1 if x is not a vector. More...
 
template<typename T1 , typename T2 >
bool check_consistent_sizes (const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
 Return true if the dimension of x1 is consistent with x2. More...
 
template<typename T1 , typename T2 , typename T3 >
bool check_consistent_sizes (const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2, const char *name3, const T3 &x3)
 Return true if the dimension of x1, x2, and x3 are consistent. More...
 
template<typename T1 , typename T2 , typename T3 , typename T4 >
bool check_consistent_sizes (const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2, const char *name3, const T3 &x3, const char *name4, const T4 &x4)
 Return true if the dimension of x1, x2, x3, and x4 are consistent. More...
 
template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 >
bool check_consistent_sizes (const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2, const char *name3, const T3 &x3, const char *name4, const T4 &x4, const char *name5, const T5 &x5)
 
template<typename T_y , typename T_eq >
bool check_equal (const char *function, const char *name, const T_y &y, const T_eq &eq)
 Return true if y is equal to eq. More...
 
template<typename T_y >
bool check_finite (const char *function, const char *name, const T_y &y)
 Return true if y is finite. More...
 
template<typename T_y , typename T_low >
bool check_greater (const char *function, const char *name, const T_y &y, const T_low &low)
 Return true if y is strictly greater than low. More...
 
template<typename T_y , typename T_low >
bool check_greater_or_equal (const char *function, const char *name, const T_y &y, const T_low &low)
 Return true if y is greater or equal than low. More...
 
template<typename T_y , typename T_high >
bool check_less (const char *function, const char *name, const T_y &y, const T_high &high)
 Return true if y is strictly less than high. More...
 
template<typename T_y , typename T_high >
bool check_less_or_equal (const char *function, const char *name, const T_y &y, const T_high &high)
 Return true if y is less or equal to high. More...
 
template<typename T_y >
bool check_nonnegative (const char *function, const char *name, const T_y &y)
 Return true if y is non-negative. More...
 
template<typename T_y >
bool check_not_nan (const char *function, const char *name, const T_y &y)
 Return true if y is not NaN. More...
 
template<typename T_y >
bool check_positive (const char *function, const char *name, const T_y &y)
 Return true if y is positive. More...
 
template<typename T_y >
bool check_positive_finite (const char *function, const char *name, const T_y &y)
 Return true if y is positive and finite. More...
 
bool check_positive_size (const char *function, const char *name, const char *expr, const int size)
 Return true if size is positive. More...
 
template<typename T_size1 , typename T_size2 >
bool check_size_match (const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
 Return true if the provided sizes match. More...
 
template<typename T_size1 , typename T_size2 >
bool check_size_match (const char *function, const char *expr_i, const char *name_i, T_size1 i, const char *expr_j, const char *name_j, T_size2 j)
 Return true if the provided sizes match. More...
 
template<typename T >
void domain_error (const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
 Throw a domain error with a consistently formatted message. More...
 
template<typename T >
void domain_error (const char *function, const char *name, const T &y, const char *msg1)
 Throw a domain error with a consistently formatted message. More...
 
template<typename T >
void domain_error_vec (const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
 Throw a domain error with a consistently formatted message. More...
 
template<typename T >
void domain_error_vec (const char *function, const char *name, const T &y, const size_t i, const char *msg)
 Throw a domain error with a consistently formatted message. More...
 
template<typename T >
void invalid_argument (const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
 Throw an invalid_argument exception with a consistently formatted message. More...
 
template<typename T >
void invalid_argument (const char *function, const char *name, const T &y, const char *msg1)
 Throw an invalid_argument exception with a consistently formatted message. More...
 
template<typename T >
void invalid_argument_vec (const char *function, const char *name, const T &y, const size_t i, const char *msg1, const char *msg2)
 Throw an invalid argument exception with a consistently formatted message. More...
 
template<typename T >
void invalid_argument_vec (const char *function, const char *name, const T &y, const size_t i, const char *msg)
 Throw an invalid argument exception with a consistently formatted message. More...
 
void out_of_range (const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
 Throw an out_of_range exception with a consistently formatted message. More...
 
double abs (double x)
 Return floating-point absolute value. More...
 
template<typename T >
bool as_bool (const T x)
 Return 1 if the argument is unequal to zero and 0 otherwise. More...
 
template<typename T2 >
T2 bessel_first_kind (const int v, const T2 z)
 

+\[ \mbox{bessel\_first\_kind}(v, x) = \begin{cases} J_v(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{error} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T2 >
T2 bessel_second_kind (const int v, const T2 z)
 

+\[ \mbox{bessel\_second\_kind}(v, x) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0 \\ Y_v(x) & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T >
boost::math::tools::promote_args< T >::type binary_log_loss (const int y, const T y_hat)
 Returns the log loss function for binary classification with specified reference and response values. More...
 
template<typename T_N , typename T_n >
boost::math::tools::promote_args< T_N, T_n >::type binomial_coefficient_log (const T_N N, const T_n n)
 Return the log of the binomial coefficient for the specified arguments. More...
 
double pi ()
 Return the value of pi. More...
 
double e ()
 Return the base of the natural logarithm. More...
 
double sqrt2 ()
 Return the square root of two. More...
 
double log10 ()
 Return natural logarithm of ten. More...
 
double positive_infinity ()
 Return positive infinity. More...
 
double negative_infinity ()
 Return negative infinity. More...
 
double not_a_number ()
 Return (quiet) not-a-number. More...
 
double machine_precision ()
 Returns the difference between 1.0 and the next value representable. More...
 
template<typename T >
corr_constrain (const T x)
 Return the result of transforming the specified scalar to have a valid correlation value between -1 and 1 (inclusive). More...
 
template<typename T >
corr_constrain (const T x, T &lp)
 Return the result of transforming the specified scalar to have a valid correlation value between -1 and 1 (inclusive). More...
 
template<typename T >
corr_free (const T y)
 Return the unconstrained scalar that when transformed to a valid correlation produces the specified value. More...
 
double digamma (double x)
 

+\[ \mbox{digamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T1 , typename T2 >
stan::return_type< T1, T2 >::type divide (const T1 &x, const T2 &y)
 Return the division of the first scalar by the second scalar. More...
 
int divide (const int x, const int y)
 
template<typename T >
boost::math::tools::promote_args< T >::type exp2 (const T y)
 Return the exponent base 2 of the specified argument (C99). More...
 
template<typename T >
F32 (T a, T b, T c, T d, T e, T z, T precision=1e-6)
 
template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type falling_factorial (const T1 x, const T2 n)
 

+\[ \mbox{falling\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ (x)_n & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type fdim (T1 a, T2 b)
 The positive difference function (C99). More...
 
template<typename T , typename S >
void fill (T &x, const S &y)
 Fill the specified container with the specified value. More...
 
double gamma_p (double x, double a)
 

+\[ \mbox{gamma\_p}(a, z) = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ P(a, z) & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

+ More...
 
double gamma_q (double x, double a)
 

+\[ \mbox{gamma\_q}(a, z) = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ Q(a, z) & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T >
void grad_2F1 (T &gradA, T &gradC, T a, T b, T c, T z, T precision=1e-6)
 
template<typename T >
void grad_F32 (T *g, T a, T b, T c, T d, T e, T z, T precision=1e-6)
 
void grad_inc_beta (double &g1, double &g2, double a, double b, double z)
 
template<typename T >
void grad_reg_inc_beta (T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
 
template<typename T >
grad_reg_inc_gamma (T a, T z, T g, T dig, T precision=1e-6)
 
double ibeta (const double a, const double b, const double x)
 The normalized incomplete beta function of a, b, and x. More...
 
template<typename T >
identity_constrain (T x)
 Returns the result of applying the identity constraint transform to the input. More...
 
template<typename T >
identity_constrain (const T x, T &)
 Returns the result of applying the identity constraint transform to the input and increments the log probability reference with the log absolute Jacobian determinant. More...
 
template<typename T >
identity_free (const T y)
 Returns the result of applying the inverse of the identity constraint transform to the input. More...
 
template<typename T_true , typename T_false >
boost::math::tools::promote_args< T_true, T_false >::type if_else (const bool c, const T_true y_true, const T_false y_false)
 Return the second argument if the first argument is true and otherwise return the second argument. More...
 
double inc_beta (const double &a, const double &b, const double &x)
 
template<typename T >
inc_beta_ddb (T a, T b, T z, T digamma_b, T digamma_ab)
 Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to b. More...
 
template<typename T >
inc_beta_dda (T a, T b, T z, T digamma_a, T digamma_ab)
 Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a. More...
 
template<typename T >
inc_beta_ddz (T a, T b, T z)
 Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to z. More...
 
template<>
double inc_beta_ddz (double a, double b, double z)
 
template<typename T >
unsigned int int_step (const T y)
 The integer step, or Heaviside, function. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type inv (const T x)
 
template<typename T >
boost::math::tools::promote_args< T >::type inv_cloglog (T x)
 The inverse complementary log-log function. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type inv_logit (const T a)
 Returns the inverse logit function applied to the argument. More...
 
double inv_Phi (double p)
 The inverse of the unit normal cumulative distribution function. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type inv_sqrt (const T x)
 
template<typename T >
boost::math::tools::promote_args< T >::type inv_square (const T x)
 
template<typename Vector >
void inverse_softmax (const Vector &simplex, Vector &y)
 Writes the inverse softmax of the simplex argument into the second argument. More...
 
int is_inf (const double x)
 Returns 1 if the input is infinite and 0 otherwise. More...
 
bool is_nan (double x)
 Returns 1 if the input is NaN and 0 otherwise. More...
 
template<typename T >
bool is_uninitialized (T x)
 Returns true if the specified variable is uninitialized. More...
 
template<typename T , typename TL >
lb_constrain (const T x, const TL lb)
 Return the lower-bounded value for the specified unconstrained input and specified lower bound. More...
 
template<typename T , typename TL >
boost::math::tools::promote_args< T, TL >::type lb_constrain (const T x, const TL lb, T &lp)
 Return the lower-bounded value for the speicifed unconstrained input and specified lower bound, incrementing the specified reference with the log absolute Jacobian determinant of the transform. More...
 
template<typename T , typename TL >
boost::math::tools::promote_args< T, TL >::type lb_free (const T y, const TL lb)
 Return the unconstrained value that produces the specified lower-bound constrained value. More...
 
template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type lbeta (const T1 a, const T2 b)
 Return the log of the beta function applied to the specified arguments. More...
 
double lgamma (double x)
 

+\[ \mbox{lgamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \ln\Gamma(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T >
boost::math::tools::promote_args< T >::type lmgamma (const int k, T x)
 Return the natural logarithm of the multivariate gamma function with the speciifed dimensions and argument. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type log1m (T x)
 Return the natural logarithm of one minus the specified value. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type log1m_exp (const T a)
 Calculates the log of 1 minus the exponential of the specified value without overflow log1m_exp(x) = log(1-exp(x)). More...
 
template<typename T >
boost::math::tools::promote_args< T >::type log1m_inv_logit (const T u)
 Returns the natural logarithm of 1 minus the inverse logit of the specified argument. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type log1p (const T x)
 Return the natural logarithm of one plus the specified value. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type log1p_exp (const T a)
 Calculates the log of 1 plus the exponential of the specified value without overflow. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type log2 (const T a)
 Returns the base 2 logarithm of the argument (C99). More...
 
double log2 ()
 Return natural logarithm of two. More...
 
template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type log_diff_exp (const T1 x, const T2 y)
 The natural logarithm of the difference of the natural exponentiation of x1 and the natural exponentiation of x2. More...
 
template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type log_falling_factorial (const T1 x, const T2 n)
 

+\[ \mbox{log\_falling\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \ln (x)_n & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T >
boost::math::tools::promote_args< T >::type log_inv_logit (const T &u)
 Returns the natural logarithm of the inverse logit of the specified argument. More...
 
double log_mix (double theta, double lambda1, double lambda2)
 Return the log mixture density with specified mixing proportion and log densities. More...
 
template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type log_rising_factorial (const T1 x, const T2 n)
 

+\[ \mbox{log\_rising\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \ln x^{(n)} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type log_sum_exp (const T2 &a, const T1 &b)
 Calculates the log sum of exponetials without overflow. More...
 
template<typename T1 , typename T2 >
int logical_and (const T1 x1, const T2 x2)
 The logical and function which returns 1 if both arguments are unequal to zero and 0 otherwise. More...
 
template<typename T1 , typename T2 >
int logical_eq (const T1 x1, const T2 x2)
 Return 1 if the first argument is equal to the second. More...
 
template<typename T1 , typename T2 >
int logical_gt (const T1 x1, const T2 x2)
 Return 1 if the first argument is strictly greater than the second. More...
 
template<typename T1 , typename T2 >
int logical_gte (const T1 x1, const T2 x2)
 Return 1 if the first argument is greater than or equal to the second. More...
 
template<typename T1 , typename T2 >
int logical_lt (T1 x1, T2 x2)
 Return 1 if the first argument is strictly less than the second. More...
 
template<typename T1 , typename T2 >
int logical_lte (const T1 x1, const T2 x2)
 Return 1 if the first argument is less than or equal to the second. More...
 
template<typename T >
int logical_negation (const T x)
 The logical negation function which returns 1 if the input is equal to zero and 0 otherwise. More...
 
template<typename T1 , typename T2 >
int logical_neq (const T1 x1, const T2 x2)
 Return 1 if the first argument is unequal to the second. More...
 
template<typename T1 , typename T2 >
int logical_or (T1 x1, T2 x2)
 The logical or function which returns 1 if either argument is unequal to zero and 0 otherwise. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type logit (const T a)
 Returns the logit function applied to the argument. More...
 
template<typename T , typename TL , typename TU >
boost::math::tools::promote_args< T, TL, TU >::type lub_constrain (const T x, TL lb, TU ub)
 Return the lower- and upper-bounded scalar derived by transforming the specified free scalar given the specified lower and upper bounds. More...
 
template<typename T , typename TL , typename TU >
boost::math::tools::promote_args< T, TL, TU >::type lub_constrain (const T x, const TL lb, const TU ub, T &lp)
 Return the lower- and upper-bounded scalar derived by transforming the specified free scalar given the specified lower and upper bounds and increment the specified log probability with the log absolute Jacobian determinant. More...
 
template<typename T , typename TL , typename TU >
boost::math::tools::promote_args< T, TL, TU >::type lub_free (const T y, TL lb, TU ub)
 Return the unconstrained scalar that transforms to the specified lower- and upper-bounded scalar given the specified bounds. More...
 
template<typename T2 >
T2 modified_bessel_first_kind (const int v, const T2 z)
 

+\[ \mbox{modified\_bessel\_first\_kind}(v, z) = \begin{cases} I_v(z) & \mbox{if } -\infty\leq z \leq \infty \\[6pt] \textrm{error} & \mbox{if } z = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T2 >
T2 modified_bessel_second_kind (const int v, const T2 z)
 

+\[ \mbox{modified\_bessel\_second\_kind}(v, z) = \begin{cases} \textrm{error} & \mbox{if } z \leq 0 \\ K_v(z) & \mbox{if } z > 0 \\[6pt] \textrm{NaN} & \mbox{if } z = \textrm{NaN} \end{cases} \] +

+ More...
 
int modulus (const int x, const int y)
 
template<typename T_a , typename T_b >
boost::math::tools::promote_args< T_a, T_b >::type multiply_log (const T_a a, const T_b b)
 Calculated the value of the first argument times log of the second argument while behaving properly with 0 inputs. More...
 
double owens_t (const double h, const double a)
 The Owen's T function of h and a. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type Phi (const T x)
 The unit normal cumulative distribution function. More...
 
template<typename T >
boost::math::tools::promote_args< T >::type Phi_approx (T x)
 Approximation of the unit normal CDF. More...
 
template<typename T >
positive_constrain (const T x)
 Return the positive value for the specified unconstrained input. More...
 
template<typename T >
positive_constrain (const T x, T &lp)
 Return the positive value for the specified unconstrained input, incrementing the scalar reference with the log absolute Jacobian determinant. More...
 
template<typename T >
positive_free (const T y)
 Return the unconstrained value corresponding to the specified positive-constrained value. More...
 
template<typename T >
boost::enable_if< boost::is_arithmetic< T >, T >::type primitive_value (T x)
 Return the value of the specified arithmetic argument unmodified with its own declared type. More...
 
template<typename T >
boost::disable_if< boost::is_arithmetic< T >, double >::type primitive_value (const T &x)
 Return the primitive value of the specified argument. More...
 
template<typename T >
prob_constrain (const T x)
 Return a probability value constrained to fall between 0 and 1 (inclusive) for the specified free scalar. More...
 
template<typename T >
prob_constrain (const T x, T &lp)
 Return a probability value constrained to fall between 0 and 1 (inclusive) for the specified free scalar and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
template<typename T >
prob_free (const T y)
 Return the free scalar that when transformed to a probability produces the specified scalar. More...
 
template<typename T , typename S >
promote_scalar_type< T, S >::type promote_scalar (const S &x)
 This is the top-level function to call to promote the scalar types of an input of type S to type T. More...
 
template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type rising_factorial (const T1 x, const T2 n)
 

+\[ \mbox{rising\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ x^{(n)} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T >
int sign (const T &z)
 
template<typename T >
square (const T x)
 Return the square of the specified argument. More...
 
template<typename T >
int step (const T y)
 The step, or Heaviside, function. More...
 
template<typename T >
trigamma (T x)
 

+\[ \mbox{trigamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi_1(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
template<typename T , typename TU >
boost::math::tools::promote_args< T, TU >::type ub_constrain (const T x, const TU ub)
 Return the upper-bounded value for the specified unconstrained scalar and upper bound. More...
 
template<typename T , typename TU >
boost::math::tools::promote_args< T, TU >::type ub_constrain (const T x, const TU ub, T &lp)
 Return the upper-bounded value for the specified unconstrained scalar and upper bound and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
template<typename T , typename TU >
boost::math::tools::promote_args< T, TU >::type ub_free (const T y, const TU ub)
 Return the free scalar that corresponds to the specified upper-bounded value with respect to the specified upper bound. More...
 
template<typename T >
double value_of (const T x)
 Return the value of the specified scalar argument converted to a double value. More...
 
template<>
double value_of< double > (const double x)
 Return the specified argument. More...
 
template<typename T >
double value_of_rec (const T x)
 Return the value of the specified scalar argument converted to a double value. More...
 
template<>
double value_of_rec< double > (const double x)
 Return the specified argument. More...
 
template<typename T_n , typename T_prob >
return_type< T_prob >::type bernoulli_ccdf_log (const T_n &n, const T_prob &theta)
 
template<typename T_n , typename T_prob >
return_type< T_prob >::type bernoulli_cdf (const T_n &n, const T_prob &theta)
 
template<typename T_n , typename T_prob >
return_type< T_prob >::type bernoulli_cdf_log (const T_n &n, const T_prob &theta)
 
template<bool propto, typename T_n , typename T_prob >
return_type< T_prob >::type bernoulli_log (const T_n &n, const T_prob &theta)
 
template<typename T_y , typename T_prob >
return_type< T_prob >::type bernoulli_log (const T_y &n, const T_prob &theta)
 
template<bool propto, typename T_n , typename T_prob >
return_type< T_prob >::type bernoulli_logit_log (const T_n &n, const T_prob &theta)
 
template<typename T_n , typename T_prob >
return_type< T_prob >::type bernoulli_logit_log (const T_n &n, const T_prob &theta)
 
template<class RNG >
int bernoulli_rng (const double theta, RNG &rng)
 
template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type beta_binomial_ccdf_log (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type beta_binomial_cdf (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type beta_binomial_cdf_log (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
template<bool propto, typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type beta_binomial_log (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
return_type< T_size1, T_size2 >::type beta_binomial_log (const T_n &n, const T_N &N, const T_size1 &alpha, const T_size2 &beta)
 
template<class RNG >
int beta_binomial_rng (const int N, const double alpha, const double beta, RNG &rng)
 
template<typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_ccdf_log (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 
template<typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_cdf (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 Calculates the beta cumulative distribution function for the given variate and scale variables. More...
 
template<typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_cdf_log (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 
template<bool propto, typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_log (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 The log of the beta density for the specified scalar(s) given the specified sample size(s). More...
 
template<typename T_y , typename T_scale_succ , typename T_scale_fail >
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_log (const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
 
template<class RNG >
double beta_rng (const double alpha, const double beta, RNG &rng)
 
template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type binomial_ccdf_log (const T_n &n, const T_N &N, const T_prob &theta)
 
template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type binomial_cdf (const T_n &n, const T_N &N, const T_prob &theta)
 
template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type binomial_cdf_log (const T_n &n, const T_N &N, const T_prob &theta)
 
template<bool propto, typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type binomial_log (const T_n &n, const T_N &N, const T_prob &theta)
 
template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type binomial_log (const T_n &n, const T_N &N, const T_prob &theta)
 
template<bool propto, typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type binomial_logit_log (const T_n &n, const T_N &N, const T_prob &alpha)
 
template<typename T_n , typename T_N , typename T_prob >
return_type< T_prob >::type binomial_logit_log (const T_n &n, const T_N &N, const T_prob &alpha)
 
template<class RNG >
int binomial_rng (const int N, const double theta, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type cauchy_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type cauchy_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 Calculates the cauchy cumulative distribution function for the given variate, location, and scale. More...
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type cauchy_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type cauchy_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 The log of the Cauchy density for the specified scalar(s) given the specified location parameter(s) and scale parameter(s). More...
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type cauchy_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<class RNG >
double cauchy_rng (const double mu, const double sigma, RNG &rng)
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type chi_square_ccdf_log (const T_y &y, const T_dof &nu)
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type chi_square_cdf (const T_y &y, const T_dof &nu)
 Calculates the chi square cumulative distribution function for the given variate and degrees of freedom. More...
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type chi_square_cdf_log (const T_y &y, const T_dof &nu)
 
template<bool propto, typename T_y , typename T_dof >
return_type< T_y, T_dof >::type chi_square_log (const T_y &y, const T_dof &nu)
 The log of a chi-squared density for y with the specified degrees of freedom parameter. More...
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type chi_square_log (const T_y &y, const T_dof &nu)
 
template<class RNG >
double chi_square_rng (const double nu, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type double_exponential_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type double_exponential_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 Calculates the double exponential cumulative density function. More...
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type double_exponential_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type double_exponential_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type double_exponential_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<class RNG >
double double_exponential_rng (const double mu, const double sigma, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
return_type< T_y, T_loc, T_scale, T_inv_scale >::type exp_mod_normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_inv_scale &lambda)
 
template<class RNG >
double exp_mod_normal_rng (const double mu, const double sigma, const double lambda, RNG &rng)
 
template<typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type exponential_ccdf_log (const T_y &y, const T_inv_scale &beta)
 
template<typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type exponential_cdf (const T_y &y, const T_inv_scale &beta)
 Calculates the exponential cumulative distribution function for the given y and beta. More...
 
template<typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type exponential_cdf_log (const T_y &y, const T_inv_scale &beta)
 
template<bool propto, typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type exponential_log (const T_y &y, const T_inv_scale &beta)
 The log of an exponential density for y with the specified inverse scale parameter. More...
 
template<typename T_y , typename T_inv_scale >
return_type< T_y, T_inv_scale >::type exponential_log (const T_y &y, const T_inv_scale &beta)
 
template<class RNG >
double exponential_rng (const double beta, RNG &rng)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type frechet_ccdf_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type frechet_cdf (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type frechet_cdf_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type frechet_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type frechet_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<class RNG >
double frechet_rng (const double alpha, const double sigma, RNG &rng)
 
template<typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type gamma_ccdf_log (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 
template<typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type gamma_cdf (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 The cumulative density function for a gamma distribution for y with the specified shape and inverse scale parameters. More...
 
template<typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type gamma_cdf_log (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 
template<bool propto, typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type gamma_log (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 The log of a gamma density for y with the specified shape and inverse scale parameters. More...
 
template<typename T_y , typename T_shape , typename T_inv_scale >
return_type< T_y, T_shape, T_inv_scale >::type gamma_log (const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
 
template<class RNG >
double gamma_rng (const double alpha, const double beta, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type gumbel_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &beta)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type gumbel_cdf (const T_y &y, const T_loc &mu, const T_scale &beta)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type gumbel_cdf_log (const T_y &y, const T_loc &mu, const T_scale &beta)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type gumbel_log (const T_y &y, const T_loc &mu, const T_scale &beta)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type gumbel_log (const T_y &y, const T_loc &mu, const T_scale &beta)
 
template<class RNG >
double gumbel_rng (const double mu, const double beta, RNG &rng)
 
template<bool propto, typename T_n , typename T_N , typename T_a , typename T_b >
double hypergeometric_log (const T_n &n, const T_N &N, const T_a &a, const T_b &b)
 
template<typename T_n , typename T_N , typename T_a , typename T_b >
double hypergeometric_log (const T_n &n, const T_N &N, const T_a &a, const T_b &b)
 
template<class RNG >
int hypergeometric_rng (int N, int a, int b, RNG &rng)
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type inv_chi_square_ccdf_log (const T_y &y, const T_dof &nu)
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type inv_chi_square_cdf (const T_y &y, const T_dof &nu)
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type inv_chi_square_cdf_log (const T_y &y, const T_dof &nu)
 
template<bool propto, typename T_y , typename T_dof >
return_type< T_y, T_dof >::type inv_chi_square_log (const T_y &y, const T_dof &nu)
 The log of an inverse chi-squared density for y with the specified degrees of freedom parameter. More...
 
template<typename T_y , typename T_dof >
return_type< T_y, T_dof >::type inv_chi_square_log (const T_y &y, const T_dof &nu)
 
template<class RNG >
double inv_chi_square_rng (const double nu, RNG &rng)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type inv_gamma_ccdf_log (const T_y &y, const T_shape &alpha, const T_scale &beta)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type inv_gamma_cdf (const T_y &y, const T_shape &alpha, const T_scale &beta)
 The CDF of an inverse gamma density for y with the specified shape and scale parameters. More...
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type inv_gamma_cdf_log (const T_y &y, const T_shape &alpha, const T_scale &beta)
 
template<bool propto, typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type inv_gamma_log (const T_y &y, const T_shape &alpha, const T_scale &beta)
 The log of an inverse gamma density for y with the specified shape and scale parameters. More...
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type inv_gamma_log (const T_y &y, const T_shape &alpha, const T_scale &beta)
 
template<class RNG >
double inv_gamma_rng (const double alpha, const double beta, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type logistic_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type logistic_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type logistic_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type logistic_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type logistic_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<class RNG >
double logistic_rng (const double mu, const double sigma, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type lognormal_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type lognormal_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type lognormal_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type lognormal_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type lognormal_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<class RNG >
double lognormal_rng (const double mu, const double sigma, RNG &rng)
 
template<typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type neg_binomial_2_ccdf_log (const T_n &n, const T_location &mu, const T_precision &phi)
 
template<typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type neg_binomial_2_cdf (const T_n &n, const T_location &mu, const T_precision &phi)
 
template<typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type neg_binomial_2_cdf_log (const T_n &n, const T_location &mu, const T_precision &phi)
 
template<bool propto, typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type neg_binomial_2_log (const T_n &n, const T_location &mu, const T_precision &phi)
 
template<typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type neg_binomial_2_log (const T_n &n, const T_location &mu, const T_precision &phi)
 
template<bool propto, typename T_n , typename T_log_location , typename T_precision >
return_type< T_log_location, T_precision >::type neg_binomial_2_log_log (const T_n &n, const T_log_location &eta, const T_precision &phi)
 
template<typename T_n , typename T_log_location , typename T_precision >
return_type< T_log_location, T_precision >::type neg_binomial_2_log_log (const T_n &n, const T_log_location &eta, const T_precision &phi)
 
template<class RNG >
int neg_binomial_2_log_rng (const double eta, const double phi, RNG &rng)
 
template<class RNG >
int neg_binomial_2_rng (const double mu, const double phi, RNG &rng)
 
template<typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type neg_binomial_ccdf_log (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
template<typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type neg_binomial_cdf (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
template<typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type neg_binomial_cdf_log (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
template<bool propto, typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type neg_binomial_log (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
template<typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type neg_binomial_log (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
template<class RNG >
int neg_binomial_rng (const double alpha, const double beta, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type normal_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type normal_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 Calculates the normal cumulative distribution function for the given variate, location, and scale. More...
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type normal_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 The log of the normal density for the specified scalar(s) given the specified mean(s) and deviation(s). More...
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
template<class RNG >
double normal_rng (const double mu, const double sigma, RNG &rng)
 
template<typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type pareto_ccdf_log (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
template<typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type pareto_cdf (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
template<typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type pareto_cdf_log (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
template<bool propto, typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type pareto_log (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
template<typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type pareto_log (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
template<class RNG >
double pareto_rng (const double y_min, const double alpha, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_cdf (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_cdf_log (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_log (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_log (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
template<class RNG >
double pareto_type_2_rng (const double mu, const double lambda, const double alpha, RNG &rng)
 
template<typename T_n , typename T_rate >
return_type< T_rate >::type poisson_ccdf_log (const T_n &n, const T_rate &lambda)
 
template<typename T_n , typename T_rate >
return_type< T_rate >::type poisson_cdf (const T_n &n, const T_rate &lambda)
 
template<typename T_n , typename T_rate >
return_type< T_rate >::type poisson_cdf_log (const T_n &n, const T_rate &lambda)
 
template<bool propto, typename T_n , typename T_rate >
return_type< T_rate >::type poisson_log (const T_n &n, const T_rate &lambda)
 
template<typename T_n , typename T_rate >
return_type< T_rate >::type poisson_log (const T_n &n, const T_rate &lambda)
 
template<bool propto, typename T_n , typename T_log_rate >
return_type< T_log_rate >::type poisson_log_log (const T_n &n, const T_log_rate &alpha)
 
template<typename T_n , typename T_log_rate >
return_type< T_log_rate >::type poisson_log_log (const T_n &n, const T_log_rate &alpha)
 
template<class RNG >
int poisson_log_rng (const double alpha, RNG &rng)
 
template<class RNG >
int poisson_rng (const double lambda, RNG &rng)
 
template<typename T_y , typename T_scale >
return_type< T_y, T_scale >::type rayleigh_ccdf_log (const T_y &y, const T_scale &sigma)
 
template<typename T_y , typename T_scale >
return_type< T_y, T_scale >::type rayleigh_cdf (const T_y &y, const T_scale &sigma)
 
template<typename T_y , typename T_scale >
return_type< T_y, T_scale >::type rayleigh_cdf_log (const T_y &y, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_scale >
return_type< T_y, T_scale >::type rayleigh_log (const T_y &y, const T_scale &sigma)
 
template<typename T_y , typename T_scale >
return_type< T_y, T_scale >::type rayleigh_log (const T_y &y, const T_scale &sigma)
 
template<class RNG >
double rayleigh_rng (const double sigma, RNG &rng)
 
template<typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_ccdf_log (const T_y &y, const T_dof &nu, const T_scale &s)
 
template<typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_cdf (const T_y &y, const T_dof &nu, const T_scale &s)
 The CDF of a scaled inverse chi-squared density for y with the specified degrees of freedom parameter and scale parameter. More...
 
template<typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_cdf_log (const T_y &y, const T_dof &nu, const T_scale &s)
 
template<bool propto, typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_log (const T_y &y, const T_dof &nu, const T_scale &s)
 The log of a scaled inverse chi-squared density for y with the specified degrees of freedom parameter and scale parameter. More...
 
template<typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_log (const T_y &y, const T_dof &nu, const T_scale &s)
 
template<class RNG >
double scaled_inv_chi_square_rng (const double nu, const double s, RNG &rng)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
template<class RNG >
double skew_normal_rng (const double mu, const double sigma, const double alpha, RNG &rng)
 
template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_ccdf_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_cdf (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 
template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_cdf_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 The log of the Student-t density for the given y, nu, mean, and scale parameter. More...
 
template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 
template<class RNG >
double student_t_rng (const double nu, const double mu, const double sigma, RNG &rng)
 
template<typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type uniform_ccdf_log (const T_y &y, const T_low &alpha, const T_high &beta)
 
template<typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type uniform_cdf (const T_y &y, const T_low &alpha, const T_high &beta)
 
template<typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type uniform_cdf_log (const T_y &y, const T_low &alpha, const T_high &beta)
 
template<bool propto, typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type uniform_log (const T_y &y, const T_low &alpha, const T_high &beta)
 The log of a uniform density for the given y, lower, and upper bound. More...
 
template<typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type uniform_log (const T_y &y, const T_low &alpha, const T_high &beta)
 
template<class RNG >
double uniform_rng (const double alpha, const double beta, RNG &rng)
 
template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type von_mises_log (T_y const &y, T_loc const &mu, T_scale const &kappa)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type von_mises_log (T_y const &y, T_loc const &mu, T_scale const &kappa)
 
template<class RNG >
double von_mises_rng (const double mu, const double kappa, RNG &rng)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type weibull_ccdf_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type weibull_cdf (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type weibull_cdf_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<bool propto, typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type weibull_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type weibull_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<class RNG >
double weibull_rng (const double alpha, const double sigma, RNG &rng)
 
template<bool propto, typename T_y , typename T_alpha , typename T_tau , typename T_beta , typename T_delta >
return_type< T_y, T_alpha, T_tau, T_beta, T_delta >::type wiener_log (const T_y &y, const T_alpha &alpha, const T_tau &tau, const T_beta &beta, const T_delta &delta)
 The log of the first passage time density function for a (Wiener) drift diffusion model for the given $y$, boundary separation $\alpha$, nondecision time $\tau$, relative bias $\beta$, and drift rate $\delta$. More...
 
template<typename T_y , typename T_alpha , typename T_tau , typename T_beta , typename T_delta >
return_type< T_y, T_alpha, T_tau, T_beta, T_delta >::type wiener_log (const T_y &y, const T_alpha &alpha, const T_tau &tau, const T_beta &beta, const T_delta &delta)
 
template<typename T_initial , typename T_param >
std::vector< std::vector< typename stan::return_type< T_initial, T_param >::type > > decouple_ode_states (const std::vector< std::vector< double > > &y, const std::vector< T_initial > &y0, const std::vector< T_param > &theta)
 Takes sensitivity output from integrators and returns results in precomputed_gradients format. More...
 
template<>
std::vector< std::vector< double > > decouple_ode_states (const std::vector< std::vector< double > > &y, const std::vector< double > &y0, const std::vector< double > &theta)
 The decouple ODE states operation for the case of no sensitivities is equal to the indentity operation. More...
 
var log_sum_exp (const std::vector< var > &x)
 Returns the log sum of exponentials. More...
 
var sum (const std::vector< var > &m)
 Returns the sum of the entries of the specified vector. More...
 
std::vector< varto_var (const std::vector< double > &v)
 Converts argument to an automatic differentiation variable. More...
 
std::vector< varto_var (const std::vector< var > &v)
 Converts argument to an automatic differentiation variable. More...
 
void add_initial_values (const std::vector< stan::math::var > &y0, std::vector< std::vector< stan::math::var > > &y)
 Increment the state derived from the coupled system in the with the original initial state. More...
 
static bool empty_nested ()
 Return true if there is no nested autodiff being executed. More...
 
static void grad (vari *vi)
 Compute the gradient for all variables starting from the specified root variable implementation. More...
 
static size_t nested_size ()
 
var operator+ (const var &a, const var &b)
 Addition operator for variables (C++). More...
 
var operator+ (const var &a, const double b)
 Addition operator for variable and scalar (C++). More...
 
var operator+ (const double a, const var &b)
 Addition operator for scalar and variable (C++). More...
 
var operator/ (const var &a, const var &b)
 Division operator for two variables (C++). More...
 
var operator/ (const var &a, const double b)
 Division operator for dividing a variable by a scalar (C++). More...
 
var operator/ (const double a, const var &b)
 Division operator for dividing a scalar by a variable (C++). More...
 
bool operator== (const var &a, const var &b)
 Equality operator comparing two variables' values (C++). More...
 
bool operator== (const var &a, const double b)
 Equality operator comparing a variable's value and a double (C++). More...
 
bool operator== (const double a, const var &b)
 Equality operator comparing a scalar and a variable's value (C++). More...
 
bool operator> (const var &a, const var &b)
 Greater than operator comparing variables' values (C++). More...
 
bool operator> (const var &a, const double b)
 Greater than operator comparing variable's value and double (C++). More...
 
bool operator> (const double a, const var &b)
 Greater than operator comparing a double and a variable's value (C++). More...
 
bool operator>= (const var &a, const var &b)
 Greater than or equal operator comparing two variables' values (C++). More...
 
bool operator>= (const var &a, const double b)
 Greater than or equal operator comparing variable's value and double (C++). More...
 
bool operator>= (const double a, const var &b)
 Greater than or equal operator comparing double and variable's value (C++). More...
 
bool operator< (const var &a, const var &b)
 Less than operator comparing variables' values (C++). More...
 
bool operator< (const var &a, const double b)
 Less than operator comparing variable's value and a double (C++). More...
 
bool operator< (const double a, const var &b)
 Less than operator comparing a double and variable's value (C++). More...
 
bool operator<= (const var &a, const var &b)
 Less than or equal operator comparing two variables' values (C++). More...
 
bool operator<= (const var &a, const double b)
 Less than or equal operator comparing a variable's value and a scalar (C++). More...
 
bool operator<= (const double a, const var &b)
 Less than or equal operator comparing a double and variable's value (C++). More...
 
var operator* (const var &a, const var &b)
 Multiplication operator for two variables (C++). More...
 
var operator* (const var &a, const double b)
 Multiplication operator for a variable and a scalar (C++). More...
 
var operator* (const double a, const var &b)
 Multiplication operator for a scalar and a variable (C++). More...
 
bool operator!= (const var &a, const var &b)
 Inequality operator comparing two variables' values (C++). More...
 
bool operator!= (const var &a, const double b)
 Inequality operator comparing a variable's value and a double (C++). More...
 
bool operator!= (const double a, const var &b)
 Inequality operator comparing a double and a variable's value (C++). More...
 
var operator- (const var &a, const var &b)
 Subtraction operator for variables (C++). More...
 
var operator- (const var &a, const double b)
 Subtraction operator for variable and scalar (C++). More...
 
var operator- (const double a, const var &b)
 Subtraction operator for scalar and variable (C++). More...
 
varoperator-- (var &a)
 Prefix decrement operator for variables (C++). More...
 
var operator-- (var &a, int)
 Postfix decrement operator for variables (C++). More...
 
varoperator++ (var &a)
 Prefix increment operator for variables (C++). More...
 
var operator++ (var &a, int)
 Postfix increment operator for variables (C++). More...
 
var operator- (const var &a)
 Unary negation operator for variables (C++). More...
 
bool operator! (const var &a)
 Prefix logical negation for the value of variables (C++). More...
 
var operator+ (const var &a)
 Unary plus operator for variables (C++). More...
 
var precomputed_gradients (const double value, const std::vector< var > &operands, const std::vector< double > &gradients)
 This function returns a var for an expression that has the specified value, vector of operands, and vector of partial derivatives of value with respect to the operands. More...
 
void print_stack (std::ostream &o)
 Prints the auto-dif variable stack. More...
 
static void recover_memory ()
 Recover memory used for all variables for reuse. More...
 
static void recover_memory_nested ()
 Recover only the memory used for the top nested call. More...
 
static void set_zero_all_adjoints ()
 Reset all adjoint values in the stack to zero. More...
 
static void set_zero_all_adjoints_nested ()
 Reset all adjoint values in the top nested portion of the stack to zero. More...
 
static void start_nested ()
 Record the current position so that recover_memory_nested() can find it. More...
 
static void grad (vari *vi)
 
Eigen::Matrix< var,-1,-1 > cholesky_decompose (const Eigen::Matrix< var,-1,-1 > &A)
 
template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, Eigen::Matrix< var, 1, C1 > >::type columns_dot_product (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 
template<int R, int C>
Eigen::Matrix< var, 1, C > columns_dot_self (const Eigen::Matrix< var, R, C > &x)
 Returns the dot product of each column of a matrix with itself. More...
 
matrix_v crossprod (const matrix_v &M)
 Returns the result of pre-multiplying a matrix by its own transpose. More...
 
template<int R, int C>
var determinant (const Eigen::Matrix< var, R, C > &m)
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< var, R, C > divide (const Eigen::Matrix< T1, R, C > &v, const T2 &c)
 Return the division of the specified column vector by the specified scalar. More...
 
template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, var >::type dot_product (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 Returns the dot product. More...
 
template<typename T1 , typename T2 >
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, var >::type dot_product (const T1 *v1, const T2 *v2, size_t length)
 Returns the dot product. More...
 
template<typename T1 , typename T2 >
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, var >::type dot_product (const std::vector< T1 > &v1, const std::vector< T2 > &v2)
 Returns the dot product. More...
 
template<int R, int C>
var dot_self (const Eigen::Matrix< var, R, C > &v)
 Returns the dot product of a vector with itself. More...
 
void grad (var &v, Eigen::Matrix< var, Eigen::Dynamic, 1 > &x, Eigen::VectorXd &g)
 Propagate chain rule to calculate gradients starting from the specified variable. More...
 
void initialize_variable (var &variable, const var &value)
 Initialize variable to value. More...
 
template<int R, int C>
void initialize_variable (Eigen::Matrix< var, R, C > &matrix, const var &value)
 Initialize every cell in the matrix to the specified value. More...
 
template<typename T >
void initialize_variable (std::vector< T > &variables, const var &value)
 Initialize the variables in the standard vector recursively. More...
 
template<int R, int C>
var log_determinant (const Eigen::Matrix< var, R, C > &m)
 
template<int R, int C>
var log_determinant_ldlt (stan::math::LDLT_factor< var, R, C > &A)
 
template<int R, int C>
var log_determinant_spd (const Eigen::Matrix< var, R, C > &m)
 
Eigen::Matrix< var, Eigen::Dynamic, 1 > log_softmax (const Eigen::Matrix< var, Eigen::Dynamic, 1 > &alpha)
 Return the softmax of the specified Eigen vector. More...
 
template<int R, int C>
var log_sum_exp (const Eigen::Matrix< var, R, C > &x)
 Returns the log sum of exponentials. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_ldlt (const stan::math::LDLT_factor< var, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_ldlt (const stan::math::LDLT_factor< var, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_ldlt (const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_spd (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_spd (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_spd (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int TriView, int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_tri (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int TriView, int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_tri (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int TriView, int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > mdivide_left_tri (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<typename T1 , typename T2 >
boost::enable_if_c< (boost::is_scalar< T1 >::value||boost::is_same< T1, var >::value)&&(boost::is_scalar< T2 >::value||boost::is_same< T2, var >::value), typename boost::math::tools::promote_args< T1, T2 >::type >::type multiply (const T1 &v, const T2 &c)
 Return the product of two scalars. More...
 
template<typename T1 , typename T2 , int R2, int C2>
Eigen::Matrix< var, R2, C2 > multiply (const T1 &c, const Eigen::Matrix< T2, R2, C2 > &m)
 Return the product of scalar and matrix. More...
 
template<typename T1 , int R1, int C1, typename T2 >
Eigen::Matrix< var, R1, C1 > multiply (const Eigen::Matrix< T1, R1, C1 > &m, const T2 &c)
 Return the product of scalar and matrix. More...
 
template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, Eigen::Matrix< var, R1, C2 > >::type multiply (const Eigen::Matrix< T1, R1, C1 > &m1, const Eigen::Matrix< T2, R2, C2 > &m2)
 Return the product of the specified matrices. More...
 
template<typename T1 , int C1, typename T2 , int R2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, var >::type multiply (const Eigen::Matrix< T1, 1, C1 > &rv, const Eigen::Matrix< T2, R2, 1 > &v)
 Return the scalar product of the specified row vector and specified column vector. More...
 
matrix_v multiply_lower_tri_self_transpose (const matrix_v &L)
 
template<typename TA , int RA, int CA, typename TB , int RB, int CB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, Eigen::Matrix< var, CB, CB > >::type quad_form (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, CB > &B)
 
template<typename TA , int RA, int CA, typename TB , int RB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, var >::type quad_form (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, 1 > &B)
 
template<typename TA , int RA, int CA, typename TB , int RB, int CB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, Eigen::Matrix< var, CB, CB > >::type quad_form_sym (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, CB > &B)
 
template<typename TA , int RA, int CA, typename TB , int RB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, var >::type quad_form_sym (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, 1 > &B)
 
template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, Eigen::Matrix< var, R1, 1 > >::type rows_dot_product (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 
var sd (const std::vector< var > &v)
 Return the sample standard deviation of the specified standard vector. More...
 
template<int R, int C>
var sd (const Eigen::Matrix< var, R, C > &m)
 
Eigen::Matrix< var, Eigen::Dynamic, 1 > softmax (const Eigen::Matrix< var, Eigen::Dynamic, 1 > &alpha)
 Return the softmax of the specified Eigen vector. More...
 
std::vector< varsort_asc (std::vector< var > xs)
 Return the specified standard vector in ascending order with gradients kept. More...
 
template<int R, int C>
Eigen::Matrix< var, R, C > sort_asc (Eigen::Matrix< var, R, C > xs)
 Return the specified eigen vector in ascending order with gradients kept. More...
 
std::vector< varsort_desc (std::vector< var > xs)
 Return the specified standard vector in descending order with gradients kept. More...
 
template<int R, int C>
Eigen::Matrix< var, R, C > sort_desc (Eigen::Matrix< var, R, C > xs)
 Return the specified eigen vector in descending order with gradients kept. More...
 
template<int R1, int C1, int R2, int C2>
var squared_distance (const Eigen::Matrix< var, R1, C1 > &v1, const Eigen::Matrix< var, R2, C2 > &v2)
 
template<int R1, int C1, int R2, int C2>
var squared_distance (const Eigen::Matrix< var, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 
template<int R1, int C1, int R2, int C2>
var squared_distance (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< var, R2, C2 > &v2)
 
void stan_print (std::ostream *o, const var &x)
 
template<int R, int C>
var sum (const Eigen::Matrix< var, R, C > &m)
 Returns the sum of the coefficients of the specified matrix, column vector or row vector. More...
 
matrix_v tcrossprod (const matrix_v &M)
 Returns the result of post-multiplying a matrix by its own transpose. More...
 
matrix_v to_var (const stan::math::matrix_d &m)
 Converts argument to an automatic differentiation variable. More...
 
matrix_v to_var (const matrix_v &m)
 Converts argument to an automatic differentiation variable. More...
 
vector_v to_var (const stan::math::vector_d &v)
 Converts argument to an automatic differentiation variable. More...
 
vector_v to_var (const vector_v &v)
 Converts argument to an automatic differentiation variable. More...
 
row_vector_v to_var (const stan::math::row_vector_d &rv)
 Converts argument to an automatic differentiation variable. More...
 
row_vector_v to_var (const row_vector_v &rv)
 Converts argument to an automatic differentiation variable. More...
 
template<typename T1 , int R1, int C1, typename T2 , int R2, int C2, typename T3 , int R3, int C3>
boost::enable_if_c< stan::is_var< T1 >::value||stan::is_var< T2 >::value||stan::is_var< T3 >::value, var >::type trace_gen_inv_quad_form_ldlt (const Eigen::Matrix< T1, R1, C1 > &D, const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
 Compute the trace of an inverse quadratic form. More...
 
template<typename TD , int RD, int CD, typename TA , int RA, int CA, typename TB , int RB, int CB>
boost::enable_if_c< boost::is_same< TD, var >::value||boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, var >::type trace_gen_quad_form (const Eigen::Matrix< TD, RD, CD > &D, const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, CB > &B)
 
template<typename T2 , int R2, int C2, typename T3 , int R3, int C3>
boost::enable_if_c< stan::is_var< T2 >::value||stan::is_var< T3 >::value, var >::type trace_inv_quad_form_ldlt (const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
 Compute the trace of an inverse quadratic form. More...
 
template<typename TA , int RA, int CA, typename TB , int RB, int CB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, var >::type trace_quad_form (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, CB > &B)
 
template<int R, int C>
Eigen::Matrix< var, R, C > unit_vector_constrain (const Eigen::Matrix< var, R, C > &y)
 Return the unit length vector corresponding to the free vector y. More...
 
template<int R, int C>
Eigen::Matrix< var, R, C > unit_vector_constrain (const Eigen::Matrix< var, R, C > &y, var &lp)
 Return the unit length vector corresponding to the free vector y. More...
 
var variance (const std::vector< var > &v)
 Return the sample variance of the specified standard vector. More...
 
template<int R, int C>
var variance (const Eigen::Matrix< var, R, C > &m)
 
void cvodes_silent_err_handler (int error_code, const char *module, const char *function, char *msg, void *eh_data)
 
void cvodes_check_flag (int flag, const std::string &func_name)
 
void cvodes_set_options (void *cvodes_mem, double rel_tol, double abs_tol, long int max_num_steps)
 
template<typename F >
void gradient (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad_fx)
 Calculate the value and the gradient of the specified function at the specified argument. More...
 
void free_cvodes_memory (N_Vector &cvodes_state, N_Vector *cvodes_state_sens, void *cvodes_mem, size_t S)
 Free memory allocated for CVODES state, sensitivity, and general memory. More...
 
template<typename F , typename T_initial , typename T_param >
std::vector< std::vector< typename stan::return_type< T_initial, T_param >::type > > integrate_ode_bdf (const F &f, const std::vector< T_initial > &y0, const double t0, const std::vector< double > &ts, const std::vector< T_param > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs=0, double relative_tolerance=1e-10, double absolute_tolerance=1e-10, long int max_num_steps=1e8)
 Return the solutions for the specified system of ordinary differential equations given the specified initial state, initial times, times of desired solution, and parameters and data, writing error and warning messages to the specified stream. More...
 
template<typename F >
void jacobian (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, Eigen::Matrix< double, Eigen::Dynamic, 1 > &fx, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &J)
 
var abs (const var &a)
 Return the absolute value of the variable (std). More...
 
var acos (const var &a)
 Return the principal value of the arc cosine of a variable, in radians (cmath). More...
 
var acosh (const var &a)
 The inverse hyperbolic cosine function for variables (C99). More...
 
int as_bool (const var &v)
 Return 1 if the argument is unequal to zero and 0 otherwise. More...
 
var asin (const var &a)
 Return the principal value of the arc sine, in radians, of the specified variable (cmath). More...
 
var asinh (const var &a)
 The inverse hyperbolic sine function for variables (C99). More...
 
var atan (const var &a)
 Return the principal value of the arc tangent, in radians, of the specified variable (cmath). More...
 
var atan2 (const var &a, const var &b)
 Return the principal value of the arc tangent, in radians, of the first variable divided by the second (cmath). More...
 
var atan2 (const var &a, const double b)
 Return the principal value of the arc tangent, in radians, of the first variable divided by the second scalar (cmath). More...
 
var atan2 (const double a, const var &b)
 Return the principal value of the arc tangent, in radians, of the first scalar divided by the second variable (cmath). More...
 
var atanh (const var &a)
 The inverse hyperbolic tangent function for variables (C99). More...
 
var bessel_first_kind (const int &v, const var &a)
 
var bessel_second_kind (const int &v, const var &a)
 
var binary_log_loss (const int y, const stan::math::var &y_hat)
 The log loss function for variables (stan). More...
 
double calculate_chain (const double &x, const double &val)
 
var cbrt (const var &a)
 Returns the cube root of the specified variable (C99). More...
 
var ceil (const var &a)
 Return the ceiling of the specified variable (cmath). More...
 
var cos (const var &a)
 Return the cosine of a radian-scaled variable (cmath). More...
 
var cosh (const var &a)
 Return the hyperbolic cosine of the specified variable (cmath). More...
 
var digamma (const stan::math::var &a)
 
var erf (const var &a)
 The error function for variables (C99). More...
 
var erfc (const var &a)
 The complementary error function for variables (C99). More...
 
var exp (const var &a)
 Return the exponentiation of the specified variable (cmath). More...
 
var exp2 (const var &a)
 Exponentiation base 2 function for variables (C99). More...
 
var expm1 (const stan::math::var &a)
 The exponentiation of the specified variable minus 1 (C99). More...
 
var fabs (const var &a)
 Return the absolute value of the variable (cmath). More...
 
var falling_factorial (const var &a, const double &b)
 
var falling_factorial (const var &a, const var &b)
 
var falling_factorial (const double &a, const var &b)
 
var fdim (const stan::math::var &a, const stan::math::var &b)
 Return the positive difference between the first variable's the value and the second's (C99). More...
 
var fdim (const double &a, const stan::math::var &b)
 Return the positive difference between the first value and the value of the second variable (C99). More...
 
var fdim (const stan::math::var &a, const double &b)
 Return the positive difference between the first variable's value and the second value (C99). More...
 
var floor (const var &a)
 Return the floor of the specified variable (cmath). More...
 
var fma (const stan::math::var &a, const stan::math::var &b, const stan::math::var &c)
 The fused multiply-add function for three variables (C99). More...
 
var fma (const stan::math::var &a, const stan::math::var &b, const double &c)
 The fused multiply-add function for two variables and a value (C99). More...
 
var fma (const stan::math::var &a, const double &b, const stan::math::var &c)
 The fused multiply-add function for a variable, value, and variable (C99). More...
 
var fma (const stan::math::var &a, const double &b, const double &c)
 The fused multiply-add function for a variable and two values (C99). More...
 
var fma (const double &a, const stan::math::var &b, const double &c)
 The fused multiply-add function for a value, variable, and value (C99). More...
 
var fma (const double &a, const double &b, const stan::math::var &c)
 The fused multiply-add function for two values and a variable, and value (C99). More...
 
var fma (const double &a, const stan::math::var &b, const stan::math::var &c)
 The fused multiply-add function for a value and two variables (C99). More...
 
var fmax (const stan::math::var &a, const stan::math::var &b)
 Returns the maximum of the two variable arguments (C99). More...
 
var fmax (const stan::math::var &a, const double &b)
 Returns the maximum of the variable and scalar, promoting the scalar to a variable if it is larger (C99). More...
 
var fmax (const double &a, const stan::math::var &b)
 Returns the maximum of a scalar and variable, promoting the scalar to a variable if it is larger (C99). More...
 
var fmin (const stan::math::var &a, const stan::math::var &b)
 Returns the minimum of the two variable arguments (C99). More...
 
var fmin (const stan::math::var &a, double b)
 Returns the minimum of the variable and scalar, promoting the scalar to a variable if it is larger (C99). More...
 
var fmin (double a, const stan::math::var &b)
 Returns the minimum of a scalar and variable, promoting the scalar to a variable if it is larger (C99). More...
 
var fmod (const var &a, const var &b)
 Return the floating point remainder after dividing the first variable by the second (cmath). More...
 
var fmod (const var &a, const double b)
 Return the floating point remainder after dividing the the first variable by the second scalar (cmath). More...
 
var fmod (const double a, const var &b)
 Return the floating point remainder after dividing the first scalar by the second variable (cmath). More...
 
var gamma_p (const stan::math::var &a, const stan::math::var &b)
 
var gamma_p (const stan::math::var &a, const double &b)
 
var gamma_p (const double &a, const stan::math::var &b)
 
var gamma_q (const stan::math::var &a, const stan::math::var &b)
 
var gamma_q (const stan::math::var &a, const double &b)
 
var gamma_q (const double &a, const stan::math::var &b)
 
void grad_inc_beta (var &g1, var &g2, const var &a, const var &b, const var &z)
 
var hypot (const var &a, const var &b)
 Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99). More...
 
var hypot (const var &a, double b)
 Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99). More...
 
var hypot (double a, const var &b)
 Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99). More...
 
var ibeta (const var &a, const var &b, const var &x)
 The normalized incomplete beta function of a, b, and x. More...
 
var if_else (bool c, const var &y_true, const var &y_false)
 If the specified condition is true, return the first variable, otherwise return the second variable. More...
 
var if_else (bool c, double y_true, const var &y_false)
 If the specified condition is true, return a new variable constructed from the first scalar, otherwise return the second variable. More...
 
var if_else (bool c, const var &y_true, const double y_false)
 If the specified condition is true, return the first variable, otherwise return a new variable constructed from the second scalar. More...
 
var inc_beta (const stan::math::var &a, const stan::math::var &b, const stan::math::var &c)
 
var inv (const var &a)
 

+\[ \mbox{inv}(x) = \begin{cases} \frac{1}{x} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
var inv_cloglog (const stan::math::var &a)
 Return the inverse complementary log-log function applied specified variable (stan). More...
 
var inv_logit (const stan::math::var &a)
 The inverse logit function for variables (stan). More...
 
var inv_Phi (const stan::math::var &p)
 The inverse of unit normal cumulative density function. More...
 
var inv_sqrt (const var &a)
 

+\[ \mbox{inv\_sqrt}(x) = \begin{cases} \frac{1}{\sqrt{x}} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
var inv_square (const var &a)
 

+\[ \mbox{inv\_square}(x) = \begin{cases} \frac{1}{x^2} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
int is_inf (const var &v)
 Returns 1 if the input's value is infinite and 0 otherwise. More...
 
bool is_nan (const var &v)
 Returns 1 if the input's value is NaN and 0 otherwise. More...
 
bool is_uninitialized (var x)
 Returns true if the specified variable is uninitialized. More...
 
var lgamma (const stan::math::var &a)
 The log gamma function for variables (C99). More...
 
var lmgamma (int a, const stan::math::var &b)
 
var log (const var &a)
 Return the natural log of the specified variable (cmath). More...
 
var log10 (const var &a)
 Return the base 10 log of the specified variable (cmath). More...
 
var log1m (const stan::math::var &a)
 The log (1 - x) function for variables. More...
 
var log1m_exp (const stan::math::var &a)
 Return the log of 1 minus the exponential of the specified variable. More...
 
var log1p (const stan::math::var &a)
 The log (1 + x) function for variables (C99). More...
 
var log1p_exp (const stan::math::var &a)
 Return the log of 1 plus the exponential of the specified variable. More...
 
var log2 (const stan::math::var &a)
 Returns the base 2 logarithm of the specified variable (C99). More...
 
var log_diff_exp (const stan::math::var &a, const stan::math::var &b)
 Returns the log sum of exponentials. More...
 
var log_diff_exp (const stan::math::var &a, const double &b)
 Returns the log sum of exponentials. More...
 
var log_diff_exp (const double &a, const stan::math::var &b)
 Returns the log sum of exponentials. More...
 
var log_falling_factorial (const var &a, const double &b)
 
var log_falling_factorial (const var &a, const var &b)
 
var log_falling_factorial (const double &a, const var &b)
 
void log_mix_partial_helper (const double &theta_val, const double &lambda1_val, const double &lambda2_val, double &one_m_exp_lam2_m_lam1, double &one_m_t_prod_exp_lam2_m_lam1, double &one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1)
 
template<typename T_theta , typename T_lambda1 , typename T_lambda2 >
return_type< T_theta, T_lambda1, T_lambda2 >::type log_mix (const T_theta &theta, const T_lambda1 &lambda1, const T_lambda2 &lambda2)
 Return the log mixture density with specified mixing proportion and log densities and its derivative at each. More...
 
var log_rising_factorial (const var &a, const double &b)
 
var log_rising_factorial (const var &a, const var &b)
 
var log_rising_factorial (const double &a, const var &b)
 
var log_sum_exp (const stan::math::var &a, const stan::math::var &b)
 Returns the log sum of exponentials. More...
 
var log_sum_exp (const stan::math::var &a, const double &b)
 Returns the log sum of exponentials. More...
 
var log_sum_exp (const double &a, const stan::math::var &b)
 Returns the log sum of exponentials. More...
 
var modified_bessel_first_kind (const int &v, const var &a)
 
var modified_bessel_second_kind (const int &v, const var &a)
 
var multiply_log (const var &a, const var &b)
 Return the value of a*log(b). More...
 
var multiply_log (const var &a, const double b)
 Return the value of a*log(b). More...
 
var multiply_log (const double a, const var &b)
 Return the value of a*log(b). More...
 
var owens_t (const var &h, const var &a)
 The Owen's T function of h and a. More...
 
var owens_t (const var &h, double a)
 The Owen's T function of h and a. More...
 
var owens_t (double h, const var &a)
 The Owen's T function of h and a. More...
 
var Phi (const stan::math::var &a)
 The unit normal cumulative density function for variables (stan). More...
 
var Phi_approx (const stan::math::var &a)
 Approximation of the unit normal CDF for variables (stan). More...
 
var pow (const var &base, const var &exponent)
 Return the base raised to the power of the exponent (cmath). More...
 
var pow (const var &base, const double exponent)
 Return the base variable raised to the power of the exponent scalar (cmath). More...
 
var pow (const double base, const var &exponent)
 Return the base scalar raised to the power of the exponent variable (cmath). More...
 
double primitive_value (const var &v)
 Return the primitive double value for the specified auto-diff variable. More...
 
var rising_factorial (const var &a, const double &b)
 
var rising_factorial (const var &a, const var &b)
 
var rising_factorial (const double &a, const var &b)
 
var round (const var &a)
 Returns the rounded form of the specified variable (C99). More...
 
var sin (const var &a)
 Return the sine of a radian-scaled variable (cmath). More...
 
var sinh (const var &a)
 Return the hyperbolic sine of the specified variable (cmath). More...
 
var sqrt (const var &a)
 Return the square root of the specified variable (cmath). More...
 
var square (const var &x)
 Return the square of the input variable. More...
 
var step (const stan::math::var &a)
 Return the step, or heaviside, function applied to the specified variable (stan). More...
 
var tan (const var &a)
 Return the tangent of a radian-scaled variable (cmath). More...
 
var tanh (const var &a)
 Return the hyperbolic tangent of the specified variable (cmath). More...
 
var tgamma (const stan::math::var &a)
 Return the Gamma function applied to the specified variable (C99). More...
 
var to_var (const double &x)
 Converts argument to an automatic differentiation variable. More...
 
var to_var (const var &x)
 Converts argument to an automatic differentiation variable. More...
 
var trunc (const var &a)
 Returns the truncatation of the specified variable (C99). More...
 
double value_of (const var &v)
 Return the value of the specified variable. More...
 
double value_of_rec (const var &v)
 Return the value of the specified variable. More...
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Variables

const double CONSTRAINT_TOLERANCE = 1E-8
 The tolerance for checking arithmetic bounds In rank and in simplexes. More...
 
const double E = boost::math::constants::e<double>()
 The base of the natural logarithm, $ e $. More...
 
const double SQRT_2 = std::sqrt(2.0)
 The value of the square root of 2, $ \sqrt{2} $. More...
 
const double INV_SQRT_2 = 1.0 / SQRT_2
 The value of 1 over the square root of 2, $ 1 / \sqrt{2} $. More...
 
const double LOG_2 = std::log(2.0)
 The natural logarithm of 2, $ \log 2 $. More...
 
const double LOG_10 = std::log(10.0)
 The natural logarithm of 10, $ \log 10 $. More...
 
const double INFTY = std::numeric_limits<double>::infinity()
 Positive infinity. More...
 
const double NEGATIVE_INFTY = - std::numeric_limits<double>::infinity()
 Negative infinity. More...
 
const double NOT_A_NUMBER = std::numeric_limits<double>::quiet_NaN()
 (Quiet) not-a-number value. More...
 
const double EPSILON = std::numeric_limits<double>::epsilon()
 Smallest positive value. More...
 
const double NEGATIVE_EPSILON = - std::numeric_limits<double>::epsilon()
 Largest negative value (i.e., smallest absolute value). More...
 
const double POISSON_MAX_RATE = std::pow(2.0, 30)
 Largest rate parameter allowed in Poisson RNG. More...
 
const double LOG_PI_OVER_FOUR = std::log(boost::math::constants::pi<double>()) / 4.0
 Log pi divided by 4 $ \log \pi / 4 $. More...
 
const double SQRT_PI = std::sqrt(boost::math::constants::pi<double>())
 
const double SQRT_2_TIMES_SQRT_PI = SQRT_2 * SQRT_PI
 
const double TWO_OVER_SQRT_PI = 2.0 / SQRT_PI
 
const double NEG_TWO_OVER_SQRT_PI = -TWO_OVER_SQRT_PI
 
const double INV_SQRT_TWO_PI = 1.0 / std::sqrt(2.0 * boost::math::constants::pi<double>())
 
const double LOG_PI = std::log(boost::math::constants::pi<double>())
 
const double LOG_SQRT_PI = std::log(SQRT_PI)
 
const double LOG_ZERO = std::log(0.0)
 
const double LOG_TWO = std::log(2.0)
 
const double LOG_HALF = std::log(0.5)
 
const double NEG_LOG_TWO = - LOG_TWO
 
const double NEG_LOG_SQRT_TWO_PI = - std::log(std::sqrt(2.0 * boost::math::constants::pi<double>()))
 
const double NEG_LOG_PI = - LOG_PI
 
const double NEG_LOG_SQRT_PI = -std::log(std::sqrt(boost::math::constants::pi<double>()))
 
const double NEG_LOG_TWO_OVER_TWO = - LOG_TWO / 2.0
 
const double LOG_TWO_PI = LOG_TWO + LOG_PI
 
const double NEG_LOG_TWO_PI = - LOG_TWO_PI
 
const std::string MAJOR_VERSION = STAN_STRING(STAN_MATH_MAJOR)
 Major version number for Stan math library. More...
 
const std::string MINOR_VERSION = STAN_STRING(STAN_MATH_MINOR)
 Minor version number for Stan math library. More...
 
const std::string PATCH_VERSION = STAN_STRING(STAN_MATH_PATCH)
 Patch version for Stan math library. More...
 
+

Detailed Description

+

Matrices and templated mathematical functions.

+

Templated probability distributions. All paramaterizations are based on Bayesian Data Analysis. Function gradients via reverse-mode automatic differentiation.

+

Typedef Documentation

+ +
+
+ +

Definition at line 10 of file chainablestack.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> stan::math::matrix_d
+
+ +

Type for matrix of double values.

+ +

Definition at line 23 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<double>, Eigen::Dynamic, Eigen::Dynamic> stan::math::matrix_fd
+
+ +

Definition at line 17 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<fvar<double> >, Eigen::Dynamic, Eigen::Dynamic> stan::math::matrix_ffd
+
+ +

Definition at line 21 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<fvar<var> >, Eigen::Dynamic, Eigen::Dynamic> stan::math::matrix_ffv
+
+ +

Definition at line 18 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<var>, Eigen::Dynamic, Eigen::Dynamic> stan::math::matrix_fv
+
+ +

Definition at line 14 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<var, Eigen::Dynamic, Eigen::Dynamic> stan::math::matrix_v
+
+ +

The type of a matrix holding stan::math::var values.

+ +

Definition at line 21 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<double, 1, Eigen::Dynamic> stan::math::row_vector_d
+
+ +

Type for (row) vector of double values.

+ +

Definition at line 37 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<double>, 1, Eigen::Dynamic> stan::math::row_vector_fd
+
+ +

Definition at line 33 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<fvar<double> >, 1, Eigen::Dynamic> stan::math::row_vector_ffd
+
+ +

Definition at line 37 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<fvar<var> >, 1, Eigen::Dynamic> stan::math::row_vector_ffv
+
+ +

Definition at line 34 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<var>, 1, Eigen::Dynamic> stan::math::row_vector_fv
+
+ +

Definition at line 30 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<var, 1, Eigen::Dynamic> stan::math::row_vector_v
+
+ +

The type of a row vector holding stan::math::var values.

+ +

Definition at line 37 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index stan::math::size_type
+
+ +

Type for sizes and indexes in an Eigen matrix with double e.

+ +

Definition at line 13 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<double, Eigen::Dynamic, 1> stan::math::vector_d
+
+ +

Type for (column) vector of double values.

+ +

Definition at line 30 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<double>, Eigen::Dynamic, 1> stan::math::vector_fd
+
+ +

Definition at line 25 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<fvar<double> >, Eigen::Dynamic, 1> stan::math::vector_ffd
+
+ +

Definition at line 29 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<fvar<var> >, Eigen::Dynamic, 1> stan::math::vector_ffv
+
+ +

Definition at line 26 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<fvar<var>, Eigen::Dynamic, 1> stan::math::vector_fv
+
+ +

Definition at line 22 of file typedefs.hpp.

+ +
+
+ +
+
+ + + + +
typedef Eigen::Matrix<var, Eigen::Dynamic, 1> stan::math::vector_v
+
+ +

The type of a (column) vector holding stan::math::var values.

+ +

Definition at line 29 of file typedefs.hpp.

+ +
+
+

Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::abs (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file abs.hpp.

+ +
+
+ +
+
+ + + + + + + + +
double stan::math::abs (double x)
+
+ +

Return floating-point absolute value.

+

Delegates to fabs(double) rather than std::abs(int).

+
Parameters
+ + +
xscalar
+
+
+
Returns
absolute value of scalar
+ +

Definition at line 19 of file abs.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::abs (const vara)
+
+inline
+
+ +

Return the absolute value of the variable (std).

+

Delegates to fabs() (see for doc).

+

+\[ \mbox{abs}(x) = \begin{cases} |x| & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{abs}(x)}{\partial x} = \begin{cases} -1 & \mbox{if } x < 0 \\ 0 & \mbox{if } x = 0 \\ 1 & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable input.
+
+
+
Returns
Absolute value of variable.
+ +

Definition at line 35 of file abs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::acos (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file acos.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::acos (const vara)
+
+inline
+
+ +

Return the principal value of the arc cosine of a variable, in radians (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \arccos x = \frac{-1}{\sqrt{1 - x^2}}$.

+

+\[ \mbox{acos}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \arccos(x) & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{acos}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \frac{\partial\, \arccos(x)}{\partial x} & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x < -1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial \, \arccos(x)}{\partial x} = -\frac{1}{\sqrt{1-x^2}} \] +

+
Parameters
+ + +
aVariable in range [-1, 1].
+
+
+
Returns
Arc cosine of variable, in radians.
+ +

Definition at line 59 of file acos.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::acosh (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file acosh.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::acosh (const vara)
+
+inline
+
+ +

The inverse hyperbolic cosine function for variables (C99).

+

For non-variable function, see acosh().

+

The derivative is defined by

+

$\frac{d}{dx} \mbox{acosh}(x) = \frac{x}{x^2 - 1}$.

+

+\[ \mbox{acosh}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < 1 \\ \cosh^{-1}(x) & \mbox{if } x \geq 1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{acosh}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 1 \\ \frac{\partial\, \cosh^{-1}(x)}{\partial x} & \mbox{if } x \geq 1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \cosh^{-1}(x)=\ln\left(x+\sqrt{x^2-1}\right) \] +

+

+\[ \frac{\partial \, \cosh^{-1}(x)}{\partial x} = \frac{1}{\sqrt{x^2-1}} \] +

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
Inverse hyperbolic cosine of the variable.
+ +

Definition at line 68 of file acosh.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::add (const Eigen::Matrix< T1, R, C > & m1,
const Eigen::Matrix< T2, R, C > & m2 
)
+
+inline
+
+ +

Return the sum of the specified matrices.

+

The two matrices must have the same dimensions.

Template Parameters
+ + + + + +
T1Scalar type of first matrix.
T2Scalar type of second matrix.
RRow type of matrices.
CColumn type of matrices.
+
+
+
Parameters
+ + + +
m1First matrix.
m2Second matrix.
+
+
+
Returns
Sum of the matrices.
+
Exceptions
+ + +
std::invalid_argumentif m1 and m2 do not have the same dimensions.
+
+
+ +

Definition at line 27 of file add.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::add (const Eigen::Matrix< T1, R, C > & m,
const T2 & c 
)
+
+inline
+
+ +

Return the sum of the specified matrix and specified scalar.

+
Template Parameters
+ + + +
T1Scalar type of matrix.
T2Type of scalar.
+
+
+
Parameters
+ + + +
mMatrix.
cScalar.
+
+
+
Returns
The matrix plus the scalar.
+ +

Definition at line 52 of file add.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::add (const T1 & c,
const Eigen::Matrix< T2, R, C > & m 
)
+
+inline
+
+ +

Return the sum of the specified scalar and specified matrix.

+
Template Parameters
+ + + +
T1Type of scalar.
T2Scalar type of matrix.
+
+
+
Parameters
+ + + +
cScalar.
mMatrix.
+
+
+
Returns
The scalar plus the matrix.
+ +

Definition at line 74 of file add.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + +
void stan::math::add_initial_values (const std::vector< stan::math::var > & y0,
std::vector< std::vector< stan::math::var > > & y 
)
+
+ +

Increment the state derived from the coupled system in the with the original initial state.

+

This is necessary because the coupled system subtracts out the initial state in its representation when the initial state is unknown.

+
Parameters
+ + + +
[in]y0original initial values to add back into the coupled system.
[in,out]ystate of the coupled system on input, incremented with initial values on output.
+
+
+ +

Definition at line 34 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename return_type<T1, T2>::type, Eigen::Dynamic, Eigen::Dynamic> stan::math::append_col (const Eigen::Matrix< T1, R1, C1 > & A,
const Eigen::Matrix< T2, R2, C2 > & B 
)
+
+inline
+
+ +

Return the result of appending the second argument matrix after the first argument matrix, that is, putting them side by side, with the first matrix followed by the second matrix.

+

The inputs can be (matrix, matrix), (matrix, vector), (vector, matrix), or (vector, vector) and the output is always a matrix.

+
Template Parameters
+ + + + + + + +
T1Scalar type of first matrix.
T2Scalar type of second matrix.
R1Row specification of first matrix.
C1Column specification of first matrix.
R2Row specification of second matrix.
C2Column specification of second matrix.
+
+
+
Parameters
+ + + +
AFirst matrix.
BSecond matrix.
+
+
+
Returns
Result of appending the first matrix followed by the second matrix side by side.
+ +

Definition at line 39 of file append_col.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int C1, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename return_type<T1, T2>::type, 1, Eigen::Dynamic> stan::math::append_col (const Eigen::Matrix< T1, 1, C1 > & A,
const Eigen::Matrix< T2, 1, C2 > & B 
)
+
+inline
+
+ +

Return the result of concatenaing the first row vector followed by the second row vector side by side, with the result being a row vector.

+

This function applies to (row_vector, row_vector) and returns a row_vector.

+
Template Parameters
+ + + + + +
T1Scalar type of first row vector.
T2Scalar type of second row vector.
C1Column specification of first row vector.
C2Column specification of second row vector.
+
+
+
Parameters
+ + + +
AFirst vector.
BSecond vector
+
+
+
Returns
Result of appending the second row vector to the right of the first row vector.
+ +

Definition at line 85 of file append_col.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::append_col (const Eigen::Matrix< T, R1, C1 > & A,
const Eigen::Matrix< T, R2, C2 > & B 
)
+
+inline
+
+ +

Return the result of appending the second argument matrix after the first argument matrix, that is, putting them side by side, with the first matrix followed by the second matrix.

+

This is an overloaded template function for the case when both matrices have the same type.

+

The inputs can be (matrix, matrix), (matrix, vector), (vector, matrix), or (vector, vector), and the output is always a matrix.

+
Template Parameters
+ + + + + + +
TScalar type of both matrices.
R1Row specification of first matrix.
C1Column specification of first matrix.
R2Row specification of second matrix.
C2Column specification of second matrix.
+
+
+
Parameters
+ + + +
AFirst matrix.
BSecond matrix.
+
+
+
Returns
Result of appending the first matrix followed by the second matrix side by side.
+ +

Definition at line 128 of file append_col.hpp.

+ +
+
+ +
+
+
+template<typename T , int C1, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::append_col (const Eigen::Matrix< T, 1, C1 > & A,
const Eigen::Matrix< T, 1, C2 > & B 
)
+
+inline
+
+ +

Return the result of concatenaing the first row vector followed by the second row vector side by side, with the result being a row vector.

+

This function applies to (row_vector, row_vector) and returns a row_vector.

+
Template Parameters
+ + + + +
TScalar type of both vectors.
C1Column specification of first row vector.
C2Column specification of second row vector.
+
+
+
Parameters
+ + + +
AFirst vector.
BSecond vector
+
+
+
Returns
Result of appending the second row vector to the right of the first row vector.
+ +

Definition at line 160 of file append_col.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename return_type<T1, T2>::type, 1, Eigen::Dynamic> stan::math::append_col (const T1 & A,
const Eigen::Matrix< T2, R, C > & B 
)
+
+inline
+
+ +

Return the result of stacking an scalar on top of the a row vector, with the result being a row vector.

+

This function applies to (scalar, row vector) and returns a row vector.

+
Template Parameters
+ + + + +
T1Scalar type of the scalar
T2Scalar type of the row vector.
RRow specification of the row vector.
+
+
+
Parameters
+ + + +
Ascalar.
Brow vector.
+
+
+
Returns
Result of stacking the scalar on top of the row vector.
+ +

Definition at line 188 of file append_col.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename return_type<T1, T2>::type, 1, Eigen::Dynamic> stan::math::append_col (const Eigen::Matrix< T1, R, C > & A,
const T2 & B 
)
+
+inline
+
+ +

Return the result of stacking a row vector on top of the an scalar, with the result being a row vector.

+

This function applies to (row vector, scalar) and returns a row vector.

+
Template Parameters
+ + + + +
T1Scalar type of the row vector.
T2Scalar type of the scalar
RRow specification of the row vector.
+
+
+
Parameters
+ + + +
Arow vector.
Bscalar.
+
+
+
Returns
Result of stacking the row vector on top of the scalar.
+ +

Definition at line 218 of file append_col.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename return_type<T1, T2>::type, Eigen::Dynamic, Eigen::Dynamic> stan::math::append_row (const Eigen::Matrix< T1, R1, C1 > & A,
const Eigen::Matrix< T2, R2, C2 > & B 
)
+
+inline
+
+ +

Return the result of stacking the rows of the first argument matrix on top of the second argument matrix.

+

The inputs can be (matrix, matrix), (matrix, row_vector), (row_vector, matrix), or (row_vector, row_vector), and the output is always a matrix.

+
Template Parameters
+ + + + + + + +
T1Scalar type of first matrix.
T2Scalar type of second matrix.
R1Row specification of first matrix.
C1Column specification of first matrix.
R2Row specification of second matrix.
C2Column specification of second matrix.
+
+
+
Parameters
+ + + +
AFirst matrix.
BSecond matrix.
+
+
+
Returns
Result of stacking first matrix on top of second.
+ +

Definition at line 37 of file append_row.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int R2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename return_type<T1, T2>::type, Eigen::Dynamic, 1> stan::math::append_row (const Eigen::Matrix< T1, R1, 1 > & A,
const Eigen::Matrix< T2, R2, 1 > & B 
)
+
+inline
+
+ +

Return the result of stacking the first vector on top of the second vector, with the result being a vector.

+

This function applies to (vector, vector) and returns a vector.

+
Template Parameters
+ + + + + +
T1Scalar type of first vector.
T2Scalar type of second vector.
R1Row specification of first vector.
R2Row specification of second vector.
+
+
+
Parameters
+ + + +
AFirst vector.
BSecond vector.
+
+
+
Returns
Result of stacking first vector on top of the second vector.
+ +

Definition at line 80 of file append_row.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::append_row (const Eigen::Matrix< T, R1, C1 > & A,
const Eigen::Matrix< T, R2, C2 > & B 
)
+
+inline
+
+ +

Return the result of stacking the rows of the first argument matrix on top of the second argument matrix.

+

This is an overload for the case when the scalar types of the two input matrix are the same.

+

The inputs can be (matrix, matrix), (matrix, row_vector), (row_vector, matrix), or (row_vector, row_vector), and the output is always a matrix.

+
Template Parameters
+ + + + + + +
TScalar type of both matrices.
R1Row specification of first matrix.
C1Column specification of first matrix.
R2Row specification of second matrix.
C2Column specification of second matrix.
+
+
+
Parameters
+ + + +
AFirst matrix.
BSecond matrix.
+
+
+
Returns
Result of stacking first matrix on top of second.
+ +

Definition at line 121 of file append_row.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int R2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::append_row (const Eigen::Matrix< T, R1, 1 > & A,
const Eigen::Matrix< T, R2, 1 > & B 
)
+
+inline
+
+ +

Return the result of stacking the first vector on top of the second vector, with the result being a vector.

+

This is an overloaded template function for the case where both inputs have the same scalar type.

+

This function applies to (vector, vector) and returns a vector.

+
Template Parameters
+ + + + +
TScalar type of both vectors.
R1Row specification of first vector.
R2Row specification of second vector.
+
+
+
Parameters
+ + + +
AFirst vector.
BSecond vector.
+
+
+
Returns
Result of stacking first vector on top of the second vector.
+ +

Definition at line 155 of file append_row.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename return_type<T1, T2>::type, Eigen::Dynamic, 1> stan::math::append_row (const T1 & A,
const Eigen::Matrix< T2, R, C > & B 
)
+
+inline
+
+ +

Return the result of stacking an scalar on top of the a vector, with the result being a vector.

+

This function applies to (scalar, vector) and returns a vector.

+
Template Parameters
+ + + + +
T1Scalar type of the scalar
T2Scalar type of the vector.
RRow specification of the vector.
+
+
+
Parameters
+ + + +
Ascalar.
Bvector.
+
+
+
Returns
Result of stacking the scalar on top of the vector.
+ +

Definition at line 182 of file append_row.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename return_type<T1, T2>::type, Eigen::Dynamic, 1> stan::math::append_row (const Eigen::Matrix< T1, R, C > & A,
const T2 & B 
)
+
+inline
+
+ +

Return the result of stacking a vector on top of the an scalar, with the result being a vector.

+

This function applies to (vector, scalar) and returns a vector.

+
Template Parameters
+ + + + +
T1Scalar type of the vector.
T2Scalar type of the scalar
RRow specification of the vector.
+
+
+
Parameters
+ + + +
Avector.
Bscalar.
+
+
+
Returns
Result of stacking the vector on top of the scalar.
+ +

Definition at line 211 of file append_row.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
bool stan::math::as_bool (const T x)
+
+inline
+
+ +

Return 1 if the argument is unequal to zero and 0 otherwise.

+
Parameters
+ + +
xValue.
+
+
+
Returns
1 if argument is equal to zero (or NaN) and 0 otherwise.
+ +

Definition at line 14 of file as_bool.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
int stan::math::as_bool (const varv)
+
+inline
+
+ +

Return 1 if the argument is unequal to zero and 0 otherwise.

+
Parameters
+ + +
vValue.
+
+
+
Returns
1 if argument is equal to zero (or NaN) and 0 otherwise.
+ +

Definition at line 15 of file as_bool.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::asin (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 12 of file asin.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::asin (const vara)
+
+inline
+
+ +

Return the principal value of the arc sine, in radians, of the specified variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \arcsin x = \frac{1}{\sqrt{1 - x^2}}$.

+

+\[ \mbox{asin}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \arcsin(x) & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{asin}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \frac{\partial\, \arcsin(x)}{\partial x} & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x < -1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial \, \arcsin(x)}{\partial x} = \frac{1}{\sqrt{1-x^2}} \] +

+
Parameters
+ + +
aVariable in range [-1, 1].
+
+
+
Returns
Arc sine of variable, in radians.
+ +

Definition at line 58 of file asin.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::asinh (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 13 of file asinh.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::asinh (const vara)
+
+inline
+
+ +

The inverse hyperbolic sine function for variables (C99).

+

For non-variable function, see asinh().

+

The derivative is defined by

+

$\frac{d}{dx} \mbox{asinh}(x) = \frac{x}{x^2 + 1}$.

+

+\[ \mbox{asinh}(x) = \begin{cases} \sinh^{-1}(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{asinh}(x)}{\partial x} = \begin{cases} \frac{\partial\, \sinh^{-1}(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \sinh^{-1}(x)=\ln\left(x+\sqrt{x^2+1}\right) \] +

+

+\[ \frac{\partial \, \sinh^{-1}(x)}{\partial x} = \frac{1}{\sqrt{x^2+1}} \] +

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
Inverse hyperbolic sine of the variable.
+ +

Definition at line 67 of file asinh.hpp.

+ +
+
+ +
+
+
+template<typename LHS , typename RHS >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::assign (LHS & lhs,
const RHS & rhs 
)
+
+inline
+
+ +

Copy the right-hand side's value to the left-hand side variable.

+

The assign() function is overloaded. This instance will match arguments where the right-hand side is assignable to the left and they are not both std::vector or Eigen::Matrix types.

+
Template Parameters
+ + + +
LHSType of left-hand side.
RHSType of right-hand side.
+
+
+
Parameters
+ + + +
lhsLeft-hand side.
rhsRight-hand side.
+
+
+ +

Definition at line 51 of file assign.hpp.

+ +
+
+ +
+
+
+template<typename LHS , typename RHS , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::assign (Eigen::Matrix< LHS, R1, C1 > & x,
const Eigen::Matrix< RHS, R2, C2 > & y 
)
+
+inline
+
+ +

Copy the right-hand side's value to the left-hand side variable.

+

The assign() function is overloaded. This instance will be called for arguments that are both Eigen::Matrix types, but whose shapes are not compatible. The shapes are specified in the row and column template parameters.

+
Template Parameters
+ + + + + + + +
LHSType of left-hand side matrix elements.
RHSType of right-hand side matrix elements.
R1Row shape of left-hand side matrix.
C1Column shape of left-hand side matrix.
R2Row shape of right-hand side matrix.
C2Column shape of right-hand side matrix.
+
+
+
Parameters
+ + + +
xLeft-hand side matrix.
yRight-hand side matrix.
+
+
+
Exceptions
+ + +
std::invalid_argument
+
+
+ +

Definition at line 77 of file assign.hpp.

+ +
+
+ +
+
+
+template<typename LHS , typename RHS , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::assign (Eigen::Matrix< LHS, R, C > & x,
const Eigen::Matrix< RHS, R, C > & y 
)
+
+inline
+
+ +

Copy the right-hand side's value to the left-hand side variable.

+

The assign() function is overloaded. This instance will be called for arguments that are both Eigen::Matrix types and whose shapes match. The shapes are specified in the row and column template parameters.

+
Template Parameters
+ + + + + +
LHSType of left-hand side matrix elements.
RHSType of right-hand side matrix elements.
RRow shape of both matrices.
CColumn shape of both mtarices.
+
+
+
Parameters
+ + + +
xLeft-hand side matrix.
yRight-hand side matrix.
+
+
+
Exceptions
+ + +
std::invalid_argumentif sizes do not match.
+
+
+ +

Definition at line 113 of file assign.hpp.

+ +
+
+ +
+
+
+template<typename LHS , typename RHS , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::assign (Eigen::Block< LHS > x,
const Eigen::Matrix< RHS, R, C > & y 
)
+
+inline
+
+ +

Copy the right-hand side's value to the left-hand side variable.

+

The assign() function is overloaded. This instance will be called for arguments that are both Eigen::Matrix types and whose shapes match. The shape of the right-hand side matrix is specified in the row and column shape template parameters.

+
Template Parameters
+ + + + + +
LHSType of matrix block elements.
RHSType of right-hand side matrix elements.
RRow shape for right-hand side matrix.
CColumn shape for right-hand side matrix.
+
+
+
Parameters
+ + + +
xLeft-hand side block view of matrix.
yRight-hand side matrix.
+
+
+
Exceptions
+ + +
std::invalid_argumentif sizes do not match.
+
+
+ +

Definition at line 142 of file assign.hpp.

+ +
+
+ +
+
+
+template<typename LHS , typename RHS >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::assign (std::vector< LHS > & x,
const std::vector< RHS > & y 
)
+
+inline
+
+ +

Copy the right-hand side's value to the left-hand side variable.

+

The assign() function is overloaded. This instance will be called for arguments that are both std::vector, and will call assign() element-by element.

+

For example, a std::vector<int> can be assigned to a std::vector<double> using this function.

+
Template Parameters
+ + + +
LHSType of left-hand side vector elements.
RHSType of right-hand side vector elements.
+
+
+
Parameters
+ + + +
xLeft-hand side vector.
yRight-hand side vector.
+
+
+
Exceptions
+ + +
std::invalid_argumentif sizes do not match.
+
+
+ +

Definition at line 177 of file assign.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::atan (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 12 of file atan.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::atan (const vara)
+
+inline
+
+ +

Return the principal value of the arc tangent, in radians, of the specified variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \arctan x = \frac{1}{1 + x^2}$.

+

+\[ \mbox{atan}(x) = \begin{cases} \arctan(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{atan}(x)}{\partial x} = \begin{cases} \frac{\partial\, \arctan(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial \, \arctan(x)}{\partial x} = \frac{1}{x^2+1} \] +

+
Parameters
+ + +
aVariable in range [-1, 1].
+
+
+
Returns
Arc tangent of variable, in radians.
+ +

Definition at line 55 of file atan.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::atan2 (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 12 of file atan2.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::atan2 (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 21 of file atan2.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::atan2 (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 29 of file atan2.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::atan2 (const vara,
const varb 
)
+
+inline
+
+ +

Return the principal value of the arc tangent, in radians, of the first variable divided by the second (cmath).

+

The partial derivatives are defined by

+

$ \frac{\partial}{\partial x} \arctan \frac{x}{y} = \frac{y}{x^2 + y^2}$, and

+

$ \frac{\partial}{\partial y} \arctan \frac{x}{y} = \frac{-x}{x^2 + y^2}$.

+
Parameters
+ + + +
aNumerator variable.
bDenominator variable.
+
+
+
Returns
The arc tangent of the fraction, in radians.
+ +

Definition at line 62 of file atan2.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::atan2 (const vara,
const double b 
)
+
+inline
+
+ +

Return the principal value of the arc tangent, in radians, of the first variable divided by the second scalar (cmath).

+

The derivative with respect to the variable is

+

$ \frac{d}{d x} \arctan \frac{x}{c} = \frac{c}{x^2 + c^2}$.

+
Parameters
+ + + +
aNumerator variable.
bDenominator scalar.
+
+
+
Returns
The arc tangent of the fraction, in radians.
+ +

Definition at line 78 of file atan2.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::atan2 (const double a,
const varb 
)
+
+inline
+
+ +

Return the principal value of the arc tangent, in radians, of the first scalar divided by the second variable (cmath).

+

The derivative with respect to the variable is

+

$ \frac{\partial}{\partial y} \arctan \frac{c}{y} = \frac{-c}{c^2 + y^2}$.

+

+\[ \mbox{atan2}(x, y) = \begin{cases} \arctan\left(\frac{x}{y}\right) & \mbox{if } -\infty\leq x \leq \infty, -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{atan2}(x, y)}{\partial x} = \begin{cases} \frac{y}{x^2+y^2} & \mbox{if } -\infty\leq x\leq \infty, -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{atan2}(x, y)}{\partial y} = \begin{cases} -\frac{x}{x^2+y^2} & \mbox{if } -\infty\leq x\leq \infty, -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aNumerator scalar.
bDenominator variable.
+
+
+
Returns
The arc tangent of the fraction, in radians.
+ +

Definition at line 119 of file atan2.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::atanh (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 13 of file atanh.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::atanh (const vara)
+
+inline
+
+ +

The inverse hyperbolic tangent function for variables (C99).

+

For non-variable function, see atanh().

+

The derivative is defined by

+

$\frac{d}{dx} \mbox{atanh}(x) = \frac{1}{1 - x^2}$.

+

+\[ \mbox{atanh}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \tanh^{-1}(x) & \mbox{if } -1\leq x \leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{atanh}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \frac{\partial\, \tanh^{-1}(x)}{\partial x} & \mbox{if } -1\leq x\leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \tanh^{-1}(x)=\frac{1}{2}\ln\left(\frac{1+x}{1-x}\right) \] +

+

+\[ \frac{\partial \, \tanh^{-1}(x)}{\partial x} = \frac{1}{1-x^2} \] +

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
Inverse hyperbolic tangent of the variable.
+ +

Definition at line 70 of file atanh.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::autocorrelation (const std::vector< T > & y,
std::vector< T > & ac,
Eigen::FFT< T > & fft 
)
+
+ +

Write autocorrelation estimates for every lag for the specified input sequence into the specified result using the specified FFT engine.

+

The return vector be resized to the same length as the input sequence with lags given by array index.

+

The implementation involves a fast Fourier transform, followed by a normalization, followed by an inverse transform.

+

An FFT engine can be created for reuse for type double with:

+
+    Eigen::FFT<double> fft;
+
Template Parameters
+ + +
TScalar type.
+
+
+
Parameters
+ + + + +
yInput sequence.
acAutocorrelations.
fftFFT engine instance.
+
+
+ +

Definition at line 54 of file autocorrelation.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
void stan::math::autocorrelation (const std::vector< T > & y,
std::vector< T > & ac 
)
+
+ +

Write autocorrelation estimates for every lag for the specified input sequence into the specified result.

+

The return vector be resized to the same length as the input sequence with lags given by array index.

+

The implementation involves a fast Fourier transform, followed by a normalization, followed by an inverse transform.

+

This method is just a light wrapper around the three-argument autocorrelation function

+
Template Parameters
+ + +
TScalar type.
+
+
+
Parameters
+ + + +
yInput sequence.
acAutocorrelations.
+
+
+ +

Definition at line 123 of file autocorrelation.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::autocovariance (const std::vector< T > & y,
std::vector< T > & acov,
Eigen::FFT< T > & fft 
)
+
+ +

Write autocovariance estimates for every lag for the specified input sequence into the specified result using the specified FFT engine.

+

The return vector be resized to the same length as the input sequence with lags given by array index.

+

The implementation involves a fast Fourier transform, followed by a normalization, followed by an inverse transform.

+

An FFT engine can be created for reuse for type double with:

+
+    Eigen::FFT<double> fft;
+
Template Parameters
+ + +
TScalar type.
+
+
+
Parameters
+ + + + +
yInput sequence.
acovAutocovariance.
fftFFT engine instance.
+
+
+ +

Definition at line 34 of file autocovariance.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
void stan::math::autocovariance (const std::vector< T > & y,
std::vector< T > & acov 
)
+
+ +

Write autocovariance estimates for every lag for the specified input sequence into the specified result.

+

The return vector be resized to the same length as the input sequence with lags given by array index.

+

The implementation involves a fast Fourier transform, followed by a normalization, followed by an inverse transform.

+

This method is just a light wrapper around the three-argument autocovariance function

+
Template Parameters
+ + +
TScalar type.
+
+
+
Parameters
+ + + +
yInput sequence.
acovAutocovariances.
+
+
+ +

Definition at line 62 of file autocovariance.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_prob >
+ + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::bernoulli_ccdf_log (const T_n & n,
const T_prob & theta 
)
+
+ +

Definition at line 26 of file bernoulli_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_prob >
+ + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::bernoulli_cdf (const T_n & n,
const T_prob & theta 
)
+
+ +

Definition at line 26 of file bernoulli_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_prob >
+ + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::bernoulli_cdf_log (const T_n & n,
const T_prob & theta 
)
+
+ +

Definition at line 26 of file bernoulli_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_prob >
+ + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::bernoulli_log (const T_n & n,
const T_prob & theta 
)
+
+ +

Definition at line 28 of file bernoulli_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_prob >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::bernoulli_log (const T_y & n,
const T_prob & theta 
)
+
+inline
+
+ +

Definition at line 122 of file bernoulli_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_prob >
+ + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::bernoulli_logit_log (const T_n & n,
const T_prob & theta 
)
+
+ +

Definition at line 28 of file bernoulli_logit_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_prob >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::bernoulli_logit_log (const T_n & n,
const T_prob & theta 
)
+
+inline
+
+ +

Definition at line 106 of file bernoulli_logit_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::bernoulli_rng (const double theta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 22 of file bernoulli_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::bessel_first_kind (int v,
const fvar< T > & z 
)
+
+inline
+
+ +

Definition at line 15 of file bessel_first_kind.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::bessel_first_kind (const int & v,
const vara 
)
+
+inline
+
+ +

Definition at line 27 of file bessel_first_kind.hpp.

+ +
+
+ +
+
+
+template<typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T2 stan::math::bessel_first_kind (const int v,
const T2 z 
)
+
+inline
+
+ +

+\[ \mbox{bessel\_first\_kind}(v, x) = \begin{cases} J_v(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{error} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{bessel\_first\_kind}(v, x)}{\partial x} = \begin{cases} \frac{\partial\, J_v(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{error} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ J_v(x)=\left(\frac{1}{2}x\right)^v \sum_{k=0}^\infty \frac{\left(-\frac{1}{4}x^2\right)^k}{k!\, \Gamma(v+k+1)} \] +

+

+\[ \frac{\partial \, J_v(x)}{\partial x} = \frac{v}{x}J_v(x)-J_{v+1}(x) \] +

+ +

Definition at line 40 of file bessel_first_kind.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::bessel_second_kind (int v,
const fvar< T > & z 
)
+
+inline
+
+ +

Definition at line 15 of file bessel_second_kind.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::bessel_second_kind (const int & v,
const vara 
)
+
+inline
+
+ +

Definition at line 27 of file bessel_second_kind.hpp.

+ +
+
+ +
+
+
+template<typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T2 stan::math::bessel_second_kind (const int v,
const T2 z 
)
+
+inline
+
+ +

+\[ \mbox{bessel\_second\_kind}(v, x) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0 \\ Y_v(x) & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{bessel\_second\_kind}(v, x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0 \\ \frac{\partial\, Y_v(x)}{\partial x} & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ Y_v(x)=\frac{J_v(x)\cos(v\pi)-J_{-v}(x)}{\sin(v\pi)} \] +

+

+\[ \frac{\partial \, Y_v(x)}{\partial x} = \frac{v}{x}Y_v(x)-Y_{v+1}(x) \] +

+ +

Definition at line 40 of file bessel_second_kind.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_size1, T_size2>::type stan::math::beta_binomial_ccdf_log (const T_n & n,
const T_N & N,
const T_size1 & alpha,
const T_size2 & beta 
)
+
+ +

Definition at line 30 of file beta_binomial_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_size1, T_size2>::type stan::math::beta_binomial_cdf (const T_n & n,
const T_N & N,
const T_size1 & alpha,
const T_size2 & beta 
)
+
+ +

Definition at line 31 of file beta_binomial_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_size1, T_size2>::type stan::math::beta_binomial_cdf_log (const T_n & n,
const T_N & N,
const T_size1 & alpha,
const T_size2 & beta 
)
+
+ +

Definition at line 30 of file beta_binomial_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_N , typename T_size1 , typename T_size2 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_size1, T_size2>::type stan::math::beta_binomial_log (const T_n & n,
const T_N & N,
const T_size1 & alpha,
const T_size2 & beta 
)
+
+ +

Definition at line 32 of file beta_binomial_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_size1 , typename T_size2 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_size1, T_size2>::type stan::math::beta_binomial_log (const T_n & n,
const T_N & N,
const T_size1 & alpha,
const T_size2 & beta 
)
+
+ +

Definition at line 177 of file beta_binomial_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
int stan::math::beta_binomial_rng (const int N,
const double alpha,
const double beta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 25 of file beta_binomial_rng.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale_succ , typename T_scale_fail >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale_succ, T_scale_fail>::type stan::math::beta_ccdf_log (const T_y & y,
const T_scale_succ & alpha,
const T_scale_fail & beta 
)
+
+ +

Definition at line 36 of file beta_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale_succ , typename T_scale_fail >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale_succ, T_scale_fail>::type stan::math::beta_cdf (const T_y & y,
const T_scale_succ & alpha,
const T_scale_fail & beta 
)
+
+ +

Calculates the beta cumulative distribution function for the given variate and scale variables.

+
Parameters
+ + + + +
yA scalar variate.
alphaPrior sample size.
betaPrior sample size.
+
+
+
Returns
The beta cdf evaluated at the specified arguments.
+
Template Parameters
+ + + + +
T_yType of y.
T_scale_succType of alpha.
T_scale_failType of beta.
+
+
+ +

Definition at line 49 of file beta_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale_succ , typename T_scale_fail >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale_succ, T_scale_fail>::type stan::math::beta_cdf_log (const T_y & y,
const T_scale_succ & alpha,
const T_scale_fail & beta 
)
+
+ +

Definition at line 35 of file beta_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_scale_succ , typename T_scale_fail >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale_succ, T_scale_fail>::type stan::math::beta_log (const T_y & y,
const T_scale_succ & alpha,
const T_scale_fail & beta 
)
+
+ +

The log of the beta density for the specified scalar(s) given the specified sample size(s).

+

y, alpha, or beta can each either be scalar or a vector. Any vector inputs must be the same length.

+

The result log probability is defined to be the sum of the log probabilities for each observation/alpha/beta triple.

+

Prior sample sizes, alpha and beta, must be greater than 0.

+
Parameters
+ + + + +
y(Sequence of) scalar(s).
alpha(Sequence of) prior sample size(s).
beta(Sequence of) prior sample size(s).
+
+
+
Returns
The log of the product of densities.
+
Template Parameters
+ + + + +
T_yType of scalar outcome.
T_scale_succType of prior scale for successes.
T_scale_failType of prior scale for failures.
+
+
+ +

Definition at line 54 of file beta_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale_succ , typename T_scale_fail >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale_succ, T_scale_fail>::type stan::math::beta_log (const T_y & y,
const T_scale_succ & alpha,
const T_scale_fail & beta 
)
+
+inline
+
+ +

Definition at line 211 of file beta_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::beta_rng (const double alpha,
const double beta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 29 of file beta_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::binary_log_loss (const int y,
const fvar< T > & y_hat 
)
+
+inline
+
+ +

Definition at line 15 of file binary_log_loss.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::binary_log_loss (const int y,
const T y_hat 
)
+
+inline
+
+ +

Returns the log loss function for binary classification with specified reference and response values.

+

The log loss function for prediction $\hat{y} \in [0, 1]$ given outcome $y \in \{ 0, 1 \}$ is

+

$\mbox{logloss}(1, \hat{y}) = -\log \hat{y} $, and

+

$\mbox{logloss}(0, \hat{y}) = -\log (1 - \hat{y}) $.

+
Parameters
+ + + +
yReference value in { 0 , 1 }.
y_hatResponse value in [0, 1].
+
+
+
Returns
Log loss for response given reference value.
+ +

Definition at line 26 of file binary_log_loss.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::binary_log_loss (const int y,
const stan::math::vary_hat 
)
+
+inline
+
+ +

The log loss function for variables (stan).

+

See stan::math::binary_log_loss() for the double-based version.

+

The derivative with respect to the variable $\hat{y}$ is

+

$\frac{d}{d\hat{y}} \mbox{logloss}(1, \hat{y}) = - \frac{1}{\hat{y}}$, and

+

$\frac{d}{d\hat{y}} \mbox{logloss}(0, \hat{y}) = \frac{1}{1 - \hat{y}}$.

+

+\[ \mbox{binary\_log\_loss}(y, \hat{y}) = \begin{cases} y \log \hat{y} + (1 - y) \log (1 - \hat{y}) & \mbox{if } 0\leq \hat{y}\leq 1, y\in\{ 0, 1 \}\\[6pt] \textrm{NaN} & \mbox{if } \hat{y} = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{binary\_log\_loss}(y, \hat{y})}{\partial \hat{y}} = \begin{cases} \frac{y}{\hat{y}}-\frac{1-y}{1-\hat{y}} & \mbox{if } 0\leq \hat{y}\leq 1, y\in\{ 0, 1 \}\\[6pt] \textrm{NaN} & \mbox{if } \hat{y} = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
yReference value.
y_hatResponse variable.
+
+
+
Returns
Log loss of response versus reference value.
+ +

Definition at line 68 of file binary_log_loss.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_prob >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::binomial_ccdf_log (const T_n & n,
const T_N & N,
const T_prob & theta 
)
+
+ +

Definition at line 33 of file binomial_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_prob >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::binomial_cdf (const T_n & n,
const T_N & N,
const T_prob & theta 
)
+
+ +

Definition at line 34 of file binomial_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_prob >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::binomial_cdf_log (const T_n & n,
const T_N & N,
const T_prob & theta 
)
+
+ +

Definition at line 33 of file binomial_cdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::binomial_coefficient_log (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 16 of file binomial_coefficient_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::binomial_coefficient_log (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 46 of file binomial_coefficient_log.hpp.

+ +
+
+ +
+
+
+template<typename T_N , typename T_n >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_N, T_n>::type stan::math::binomial_coefficient_log (const T_N N,
const T_n n 
)
+
+inline
+
+ +

Return the log of the binomial coefficient for the specified arguments.

+

The binomial coefficient, ${N \choose n}$, read "N choose n", is defined for $0 \leq n \leq N$ by

+

${N \choose n} = \frac{N!}{n! (N-n)!}$.

+

This function uses Gamma functions to define the log and generalize the arguments to continuous N and n.

+

$ \log {N \choose n} = \log \ \Gamma(N+1) - \log \Gamma(n+1) - \log \Gamma(N-n+1)$.

+

+\[ \mbox{binomial\_coefficient\_log}(x, y) = \begin{cases} \textrm{error} & \mbox{if } y > x \textrm{ or } y < 0\\ \ln\Gamma(x+1) & \mbox{if } 0\leq y \leq x \\ \quad -\ln\Gamma(y+1)& \\ \quad -\ln\Gamma(x-y+1)& \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{binomial\_coefficient\_log}(x, y)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } y > x \textrm{ or } y < 0\\ \Psi(x+1) & \mbox{if } 0\leq y \leq x \\ \quad -\Psi(x-y+1)& \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{binomial\_coefficient\_log}(x, y)}{\partial y} = \begin{cases} \textrm{error} & \mbox{if } y > x \textrm{ or } y < 0\\ -\Psi(y+1) & \mbox{if } 0\leq y \leq x \\ \quad +\Psi(x-y+1)& \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
Ntotal number of objects.
nnumber of objects chosen.
+
+
+
Returns
log (N choose n).
+ +

Definition at line 62 of file binomial_coefficient_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::binomial_coefficient_log (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 70 of file binomial_coefficient_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_N , typename T_prob >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::binomial_log (const T_n & n,
const T_N & N,
const T_prob & theta 
)
+
+ +

Definition at line 38 of file binomial_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_prob >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::binomial_log (const T_n & n,
const T_N & N,
const T_prob & theta 
)
+
+inline
+
+ +

Definition at line 129 of file binomial_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_N , typename T_prob >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::binomial_logit_log (const T_n & n,
const T_N & N,
const T_prob & alpha 
)
+
+ +

Definition at line 39 of file binomial_logit_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_prob >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_prob>::type stan::math::binomial_logit_log (const T_n & n,
const T_N & N,
const T_prob & alpha 
)
+
+inline
+
+ +

Definition at line 133 of file binomial_logit_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
int stan::math::binomial_rng (const int N,
const double theta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 30 of file binomial_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::block (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m,
size_t i,
size_t j,
size_t nrows,
size_t ncols 
)
+
+inline
+
+ +

Return a nrows x ncols submatrix starting at (i-1, j-1).

+
Parameters
+ + + + + + +
mMatrix
iStarting row
jStarting column
nrowsNumber of rows in block
ncolsNumber of columns in block
+
+
+ +

Definition at line 23 of file block.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::calculate_chain (const double & x,
const double & val 
)
+
+inline
+
+ +

Definition at line 8 of file calculate_chain.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_prob >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::categorical_log (int n,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta 
)
+
+ +

Definition at line 25 of file categorical_log.hpp.

+ +
+
+ +
+
+
+template<typename T_prob >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::categorical_log (const typename math::index_type< Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > >::type n,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta 
)
+
+inline
+
+ +

Definition at line 56 of file categorical_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_prob >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::categorical_log (const std::vector< int > & ns,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta 
)
+
+ +

Definition at line 68 of file categorical_log.hpp.

+ +
+
+ +
+
+
+template<typename T_prob >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::categorical_log (const std::vector< int > & ns,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta 
)
+
+inline
+
+ +

Definition at line 116 of file categorical_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_prob >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::categorical_logit_log (int n,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & beta 
)
+
+ +

Definition at line 22 of file categorical_logit_log.hpp.

+ +
+
+ +
+
+
+template<typename T_prob >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::categorical_logit_log (int n,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & beta 
)
+
+inline
+
+ +

Definition at line 45 of file categorical_logit_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_prob >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::categorical_logit_log (const std::vector< int > & ns,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & beta 
)
+
+ +

Definition at line 54 of file categorical_logit_log.hpp.

+ +
+
+ +
+
+
+template<typename T_prob >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::categorical_logit_log (const std::vector< int > & ns,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & beta 
)
+
+inline
+
+ +

Definition at line 89 of file categorical_logit_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::categorical_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > & theta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 20 of file categorical_rng.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::cauchy_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 26 of file cauchy_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::cauchy_cdf (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Calculates the cauchy cumulative distribution function for the given variate, location, and scale.

+

$\frac{1}{\pi}\arctan\left(\frac{y-\mu}{\sigma}\right) + \frac{1}{2}$

+
Parameters
+ + + + +
yA scalar variate.
muThe location parameter.
sigmaThe scale parameter.
+
+
+
Returns
+ +

Definition at line 38 of file cauchy_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::cauchy_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 26 of file cauchy_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::cauchy_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

The log of the Cauchy density for the specified scalar(s) given the specified location parameter(s) and scale parameter(s).

+

y, mu, or sigma can each either be scalar a vector. Any vector inputs must be the same length.

+

The result log probability is defined to be the sum of the log probabilities for each observation/mu/sigma triple.

+
Parameters
+ + + + +
y(Sequence of) scalar(s).
mu(Sequence of) location(s).
sigma(Sequence of) scale(s).
+
+
+
Returns
The log of the product of densities.
+
Template Parameters
+ + + + +
T_yType of scalar outcome.
T_locType of location.
T_scaleType of scale.
+
+
+ +

Definition at line 45 of file cauchy_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::cauchy_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+inline
+
+ +

Definition at line 147 of file cauchy_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::cauchy_rng (const double mu,
const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 22 of file cauchy_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::cbrt (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file cbrt.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::cbrt (const vara)
+
+inline
+
+ +

Returns the cube root of the specified variable (C99).

+

See cbrt() for the double-based version.

+

The derivative is

+

$\frac{d}{dx} x^{1/3} = \frac{1}{3 x^{2/3}}$.

+

+\[ \mbox{cbrt}(x) = \begin{cases} \sqrt[3]{x} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{cbrt}(x)}{\partial x} = \begin{cases} \frac{1}{3x^{2/3}} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aSpecified variable.
+
+
+
Returns
Cube root of the variable.
+ +

Definition at line 56 of file cbrt.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::ceil (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 11 of file ceil.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::ceil (const vara)
+
+inline
+
+ +

Return the ceiling of the specified variable (cmath).

+

The derivative of the ceiling function is defined and zero everywhere but at integers, and we set them to zero for convenience,

+

$\frac{d}{dx} {\lceil x \rceil} = 0$.

+

The ceiling function rounds up. For double values, this is the smallest integral value that is not less than the specified value. Although this function is not differentiable because it is discontinuous at integral values, its gradient is returned as zero everywhere.

+

+\[ \mbox{ceil}(x) = \begin{cases} \lceil x\rceil & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{ceil}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aInput variable.
+
+
+
Returns
Ceiling of the variable.
+ +

Definition at line 60 of file ceil.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_low , typename T_high >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_bounded (const char * function,
const char * name,
const T_y & y,
const T_low & low,
const T_high & high 
)
+
+inline
+
+ +

Return true if the value is between the low and high values, inclusively.

+
Template Parameters
+ + + + +
T_yType of value
T_lowType of low value
T_highType of high value
+
+
+
Parameters
+ + + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yValue to check
lowLow bound
highHigh bound
+
+
+
Returns
true if the value is between low and high, inclusively.
+
Exceptions
+ + +
<code>std::domain_error</code>otherwise. This also throws if any of the arguments are NaN.
+
+
+ +

Definition at line 95 of file check_bounded.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_cholesky_factor (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified matrix is a valid Cholesky factor.

+

A Cholesky factor is a lower triangular matrix whose diagonal elements are all positive. Note that Cholesky factors need not be square, but require at least as many rows M as columns N (i.e., M >= N).

+
Template Parameters
+ + +
T_yType of elements of Cholesky factor
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is a valid Cholesky factor
+
Exceptions
+ + +
<code>std::domain_error</code>if y is not a valid Choleksy factor, if number of rows is less than the number of columns, if there are 0 columns, or if any element in matrix is NaN
+
+
+ +

Definition at line 35 of file check_cholesky_factor.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_cholesky_factor_corr (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+ +

Return true if the specified matrix is a valid Cholesky factor of a correlation matrix.

+

A Cholesky factor is a lower triangular matrix whose diagonal elements are all positive. Note that Cholesky factors need not be square, but require at least as many rows M as columns N (i.e., M >= N).

+

Tolerance is specified by math::CONSTRAINT_TOLERANCE.

+
Template Parameters
+ + +
T_yType of elements of Cholesky factor
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is a valid Cholesky factor of a correlation matrix
+
Exceptions
+ + +
<code>std::domain_error</code>if y is not a valid Choleksy factor, if number of rows is less than the number of columns, if there are 0 columns, or if any element in matrix is NaN
+
+
+ +

Definition at line 39 of file check_cholesky_factor_corr.hpp.

+ +
+
+ +
+
+
+template<typename T_y , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_column_index (const char * function,
const char * name,
const Eigen::Matrix< T_y, R, C > & y,
const size_t i 
)
+
+inline
+
+ +

Return true if the specified index is a valid column of the matrix.

+

By default, this is a 1-indexed check (as opposed to 0-indexed). Behavior can be changed by setting stan::error_index::value. This function will throw an std::out_of_range exception if the index is out of bounds.

+
Template Parameters
+ + + + +
T_yType of scalar.
RNumber of rows of the matrix
CNumber of columns of the matrix
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix
iIndex to check
+
+
+
Returns
true if the index is a valid column index of the matrix.
+
Exceptions
+ + +
std::out_of_rangeif index is an invalid column index
+
+
+ +

Definition at line 37 of file check_column_index.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_consistent_size (const char * function,
const char * name,
const T & x,
size_t expected_size 
)
+
+inline
+
+ +

Return true if the dimension of x is consistent, which is defined to be expected_size if x is a vector or 1 if x is not a vector.

+
Template Parameters
+ + +
TType of value
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
xVariable to check for consistent size
expected_sizeExpected size if x is a vector
+
+
+
Returns
true if x is scalar or if x is vector-like and has size of expected_size
+
Exceptions
+ + +
<code>invalid_argument</code>if the size is inconsistent
+
+
+ +

Definition at line 29 of file check_consistent_size.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_consistent_sizes (const char * function,
const char * name1,
const T1 & x1,
const char * name2,
const T2 & x2 
)
+
+inline
+
+ +

Return true if the dimension of x1 is consistent with x2.

+

Consistent size is defined as having the same size if vector-like or being a scalar.

+
Template Parameters
+ + + +
T1Type of x1
T2Type of x2
+
+
+
Parameters
+ + + + + + +
functionFunction name (for error messages)
name1Variable name (for error messages)
x1Variable to check for consistent size
name2Variable name (for error messages)
x2Variable to check for consistent size
+
+
+
Returns
true if x1 and x2 have consistent sizes
+
Exceptions
+ + +
<code>invalid_argument</code>if sizes are inconsistent
+
+
+ +

Definition at line 31 of file check_consistent_sizes.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_consistent_sizes (const char * function,
const char * name1,
const T1 & x1,
const char * name2,
const T2 & x2,
const char * name3,
const T3 & x3 
)
+
+inline
+
+ +

Return true if the dimension of x1, x2, and x3 are consistent.

+

Consistent size is defined as having the same size if vector-like or being a scalar.

+
Template Parameters
+ + + + +
T1Type of x1
T2Type of x2
T3Type of x3
+
+
+
Parameters
+ + + + + + + + +
functionFunction name (for error messages)
name1Variable name (for error messages)
x1Variable to check for consistent size
name2Variable name (for error messages)
x2Variable to check for consistent size
name3Variable name (for error messages)
x3Variable to check for consistent size
+
+
+
Returns
true if x1, x2, and x3 have consistent sizes
+
Exceptions
+ + +
<code>invalid_argument</code>if sizes are inconsistent
+
+
+ +

Definition at line 66 of file check_consistent_sizes.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_consistent_sizes (const char * function,
const char * name1,
const T1 & x1,
const char * name2,
const T2 & x2,
const char * name3,
const T3 & x3,
const char * name4,
const T4 & x4 
)
+
+inline
+
+ +

Return true if the dimension of x1, x2, x3, and x4 are consistent.

+

Consistent size is defined as having the same size if vector-like or being a scalar.

+
Template Parameters
+ + + + + +
T1Type of x1
T2Type of x2
T3Type of x3
T4Type of x4
+
+
+
Parameters
+ + + + + + + + + + +
functionFunction name (for error messages)
name1Variable name (for error messages)
x1Variable to check for consistent size
name2Variable name (for error messages)
x2Variable to check for consistent size
name3Variable name (for error messages)
x3Variable to check for consistent size
name4Variable name (for error messages)
x4Variable to check for consistent size
+
+
+
Returns
true if x1, x2, x3, and x4 have consistent sizes
+
Exceptions
+ + +
<code>invalid_argument</code>if sizes are inconsistent
+
+
+ +

Definition at line 107 of file check_consistent_sizes.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_consistent_sizes (const char * function,
const char * name1,
const T1 & x1,
const char * name2,
const T2 & x2,
const char * name3,
const T3 & x3,
const char * name4,
const T4 & x4,
const char * name5,
const T5 & x5 
)
+
+inline
+
+ +

Definition at line 128 of file check_consistent_sizes.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_corr_matrix (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified matrix is a valid correlation matrix.

+

A valid correlation matrix is symmetric, has a unit diagonal (all 1 values), and has all values between -1 and 1 (inclusive).

+

This function throws exceptions if the variable is not a valid correlation matrix.

+
Template Parameters
+ + +
T_yType of scalar
+
+
+
Parameters
+ + + + +
functionName of the function this was called from
nameName of the variable
yMatrix to test
+
+
+
Returns
true if the specified matrix is a valid correlation matrix
+
Exceptions
+ + + +
<code>std::invalid_argument</code>if the matrix is not square or if the matrix is 0x0
<code>std::domain_error</code>if the matrix is non-symmetric, diagonals not near 1, not positive definite, or any of the elements nan.
+
+
+ +

Definition at line 45 of file check_corr_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_cov_matrix (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified matrix is a valid covariance matrix.

+

A valid covariance matrix is a square, symmetric matrix that is positive definite.

+
Template Parameters
+ + +
TType of scalar.
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is a valid covariance matrix
+
Exceptions
+ + + +
<code>std::invalid_argument</code>if the matrix is not square or if the matrix is 0x0
<code>std::domain_error</code>if the matrix is not symmetric, if the matrix is not positive definite, or if any element of the matrix is nan
+
+
+ +

Definition at line 31 of file check_cov_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_eq >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_equal (const char * function,
const char * name,
const T_y & y,
const T_eq & eq 
)
+
+inline
+
+ +

Return true if y is equal to eq.

+

This function is vectorized over both y and eq. If both y and eq are scalar or vector-like, then each element is compared in order. If one of y or eq are vector and the other is scalar, then the scalar is broadcast to the size of the vector.

+
Template Parameters
+ + + +
T_yType of variable
T_eqType of comparison
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check equality
eqExpected value for y
+
+
+
Returns
true if y is equal to eq
+
Exceptions
+ + +
<code>std::domain_error</code>if y is unequal to eq or if any element of y or eq is NaN.
+
+
+ +

Definition at line 90 of file check_equal.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_finite (const char * function,
const char * name,
const T_y & y 
)
+
+inline
+
+ +

Return true if y is finite.

+

This function is vectorized and will check each element of y.

+
Template Parameters
+ + +
T_yType of y
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
+
+
+
Returns
true if y is finite.
+
Exceptions
+ + +
<code>domain_error</code>if y is infinity, -infinity, or NaN.
+
+
+ +

Definition at line 62 of file check_finite.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_low >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_greater (const char * function,
const char * name,
const T_y & y,
const T_low & low 
)
+
+inline
+
+ +

Return true if y is strictly greater than low.

+

This function is vectorized and will check each element of y against each element of low.

+
Template Parameters
+ + + +
T_yType of y
T_lowType of lower bound
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
lowLower bound
+
+
+
Returns
true if y is strictly greater than low.
+
Exceptions
+ + +
<code>domain_error</code>if y is not greater than low or if any element of y or low is NaN.
+
+
+ +

Definition at line 84 of file check_greater.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_low >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_greater_or_equal (const char * function,
const char * name,
const T_y & y,
const T_low & low 
)
+
+inline
+
+ +

Return true if y is greater or equal than low.

+

This function is vectorized and will check each element of y against each element of low.

+
Template Parameters
+ + + +
T_yType of y
T_lowType of lower bound
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
lowLower bound
+
+
+
Returns
true if y is greater or equal than low.
+
Exceptions
+ + +
<code>domain_error</code>if y is not greater or equal to low or if any element of y or low is NaN.
+
+
+ +

Definition at line 84 of file check_greater_or_equal.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_ldlt_factor (const char * function,
const char * name,
stan::math::LDLT_factor< T, R, C > & A 
)
+
+inline
+
+ +

Return true if the argument is a valid stan::math::LDLT_factor.

+

LDLT_factor can be constructed in an invalid state, so it must be checked. A invalid LDLT_factor is constructed from a non positive definite matrix.

+
Template Parameters
+ + + + +
TType of scalar
RRows of the matrix
CColumns of the matrix
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
Astan::math::LDLT_factor to check for validity.
+
+
+
Returns
true if the matrix is positive definite.
+
+throws std::domain_error the LDLT_factor was created improperly (A.success() == false)
+ +

Definition at line 34 of file check_ldlt_factor.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_high >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_less (const char * function,
const char * name,
const T_y & y,
const T_high & high 
)
+
+inline
+
+ +

Return true if y is strictly less than high.

+

This function is vectorized and will check each element of y against each element of high.

+
Template Parameters
+ + + +
T_yType of y
T_highType of upper bound
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
highUpper bound
+
+
+
Returns
true if y is strictly less than low.
+
Exceptions
+ + +
<code>domain_error</code>if y is not less than low or if any element of y or high is NaN.
+
+
+ +

Definition at line 81 of file check_less.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_high >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_less_or_equal (const char * function,
const char * name,
const T_y & y,
const T_high & high 
)
+
+inline
+
+ +

Return true if y is less or equal to high.

+

This function is vectorized and will check each element of y against each element of high.

+
Template Parameters
+ + + +
T_yType of y
T_highType of upper bound
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
highUpper bound
+
+
+
Returns
true if y is less than or equal to low.
+
Exceptions
+ + +
<code>std::domain_error</code>if y is not less than or equal to low or if any element of y or high is NaN.
+
+
+ +

Definition at line 81 of file check_less_or_equal.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_lower_triangular (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified matrix is lower triangular.

+

A matrix x is not lower triangular if there is a non-zero entry x[m, n] with m < n. This function only inspects the upper triangular portion of the matrix, not including the diagonal.

+
Template Parameters
+ + +
TType of scalar of the matrix
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is lower triangular.
+
Exceptions
+ + +
<code>std::domain_error</code>if the matrix is not lower triangular or if any element in the upper triangular portion is NaN
+
+
+ +

Definition at line 34 of file check_lower_triangular.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_matching_dims (const char * function,
const char * name1,
const Eigen::Matrix< T1, R1, C1 > & y1,
const char * name2,
const Eigen::Matrix< T2, R2, C2 > & y2 
)
+
+inline
+
+ +

Return true if the two matrices are of the same size.

+

This function checks not only the runtime sizes, but the static sizes as well. For example, a 4x1 matrix is not the same as a vector with 4 elements.

+
Template Parameters
+ + + + + + + +
T1Scalar type of the first matrix
T2Scalar type of the second matrix
R1Rows specified at compile time of the first matrix
C1Columns specified at compile time of the first matrix
R2Rows specified at compile time of the second matrix
C2Columns specified at compile time of the second matrix
+
+
+
Parameters
+ + + + + + +
functionFunction name (for error messages)
name1Variable name for the first matrix (for error messages)
y1First matrix
name2Variable name for the second matrix (for error messages)
y2Second matrix
+
+
+
Returns
true if the dimensions of the two matrices match
+
Exceptions
+ + +
<code>std::invalid_argument</code>if the dimensions of the matrices do not match
+
+
+ +

Definition at line 37 of file check_matching_dims.hpp.

+ +
+
+ +
+
+
+template<typename T_y1 , typename T_y2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_matching_sizes (const char * function,
const char * name1,
const T_y1 & y1,
const char * name2,
const T_y2 & y2 
)
+
+inline
+
+ +

Return true if two structures at the same size.

+

This function only checks the runtime sizes for variables that implement a size() method.

+
Template Parameters
+ + + +
T_y1Type of the first variable
T_y2Type of the second variable
+
+
+
Parameters
+ + + + + + +
functionFunction name (for error messages)
name1First variable name (for error messages)
y1First variable
name2Second variable name (for error messages)
y2Second variable
+
+
+
Returns
true if the sizes match
+
Exceptions
+ + +
<code>std::invalid_argument</code>if the sizes do not match
+
+
+ +

Definition at line 29 of file check_matching_sizes.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_multiplicable (const char * function,
const char * name1,
const T1 & y1,
const char * name2,
const T2 & y2 
)
+
+inline
+
+ +

Return true if the matrices can be multiplied.

+

This checks the runtime sizes to determine whether the two matrices are multiplicable. This allows Eigen matrices, vectors, and row vectors to be checked.

+
Template Parameters
+ + + +
T1Type of first matrix
T2Type of second matrix
+
+
+
Parameters
+ + + + + + +
functionFunction name (for error messages)
name1Variable name for the first matrix (for error messages)
y1First matrix
name2Variable name for the second matrix (for error messages)
y2Second matrix
+
+
+
Returns
true if the two matrices are multiplicable
+
Exceptions
+ + +
<code>std::invalid_argument</code>if the matrices are not multiplicable or if either matrix is size 0 for either rows or columns
+
+
+ +

Definition at line 33 of file check_multiplicable.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_nonnegative (const char * function,
const char * name,
const T_y & y 
)
+
+inline
+
+ +

Return true if y is non-negative.

+

This function is vectorized and will check each element of y.

+
Template Parameters
+ + +
T_yType of y
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
+
+
+
Returns
true if y is greater than or equal to 0.
+
Exceptions
+ + +
<code>domain_error</code>if y is negative or if any element of y is NaN.
+
+
+ +

Definition at line 66 of file check_nonnegative.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_nonzero_size (const char * function,
const char * name,
const T_y & y 
)
+
+inline
+
+ +

Return true if the specified matrix/vector is of non-zero size.

+

Throws a std:invalid_argument otherwise. The message will indicate that the variable name "has size 0".

+
Template Parameters
+ + +
T_yType of container
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yContainer to test. This will accept matrices and vectors
+
+
+
Returns
true if the the specified matrix/vector is of non-zero size
+
Exceptions
+ + +
<code>std::invalid_argument</code>if the specified matrix/vector has zero size
+
+
+ +

Definition at line 30 of file check_nonzero_size.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_not_nan (const char * function,
const char * name,
const T_y & y 
)
+
+inline
+
+ +

Return true if y is not NaN.

+

This function is vectorized and will check each element of y. If any element is NaN, this function will throw an exception.

+
Template Parameters
+ + +
T_yType of y
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
+
+
+
Returns
true if y is not NaN.
+
Exceptions
+ + +
<code>domain_error</code>if any element of y is NaN.
+
+
+ +

Definition at line 63 of file check_not_nan.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_ordered (const char * function,
const char * name,
const std::vector< T_y > & y 
)
+
+ +

Return true if the specified vector is sorted into strictly increasing order.

+
Template Parameters
+ + +
T_yType of scalar
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
ystd::vector to test
+
+
+
Returns
true if the vector is ordered
+
Exceptions
+ + +
<code>std::domain_error</code>if the vector elements are not ordered, if there are duplicated values, or if any element is NaN.
+
+
+ +

Definition at line 30 of file check_ordered.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_ordered (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, 1 > & y 
)
+
+ +

Return true if the specified vector is sorted into strictly increasing order.

+
Template Parameters
+ + +
T_yType of scalar
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVector to test
+
+
+
Returns
true if the vector is ordered
+
Exceptions
+ + +
<code>std::domain_error</code>if the vector elements are not ordered, if there are duplicated values, or if any element is NaN.
+
+
+ +

Definition at line 31 of file check_ordered.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_pos_definite (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified square, symmetric matrix is positive definite.

+
Template Parameters
+ + +
T_yType of scalar of the matrix
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is positive definite
+
Exceptions
+ + + +
<code>std::invalid_argument</code>if the matrix is not square or if the matrix has 0 size.
<code>std::domain_error</code>if the matrix is not symmetric, if it is not positive definite, or if any element is NaN.
+
+
+ +

Definition at line 37 of file check_pos_definite.hpp.

+ +
+
+ +
+
+
+template<typename Derived >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_pos_definite (const char * function,
const char * name,
const Eigen::LDLT< Derived > & cholesky 
)
+
+inline
+
+ +

Return true if the specified LDLT transform of a matrix is positive definite.

+
Template Parameters
+ + +
DerivedDerived type of the Eigen::LDLT transform.
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
choleskyEigen::LDLT to test, whose progenitor must not have any NaN elements
+
+
+
Returns
true if the matrix is positive definite
+
Exceptions
+ + +
<code>std::domain_error</code>if the matrix is not positive definite.
+
+
+ +

Definition at line 77 of file check_pos_definite.hpp.

+ +
+
+ +
+
+
+template<typename Derived >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_pos_definite (const char * function,
const char * name,
const Eigen::LLT< Derived > & cholesky 
)
+
+inline
+
+ +

Return true if the specified LLT transform of a matrix is positive definite.

+
Template Parameters
+ + +
DerivedDerived type of the Eigen::LLT transform.
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
choleskyEigen::LLT to test, whose progenitor must not have any NaN elements
+
+
+
Returns
true if the matrix is positive definite
+
Exceptions
+ + +
<code>std::domain_error</code>if the diagonal of the L matrix is not positive.
+
+
+ +

Definition at line 103 of file check_pos_definite.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_pos_semidefinite (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified matrix is positive definite.

+
Template Parameters
+ + +
T_yscalar type of the matrix
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is positive semi-definite.
+
Exceptions
+ + + +
<code>std::invalid_argument</code>if the matrix is not square or if the matrix has 0 size.
<code>std::domain_error</code>if the matrix is not symmetric, or if it is not positive semi-definite, or if any element of the matrix is NaN.
+
+
+ +

Definition at line 35 of file check_pos_semidefinite.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_positive (const char * function,
const char * name,
const T_y & y 
)
+
+inline
+
+ +

Return true if y is positive.

+

This function is vectorized and will check each element of y.

+
Template Parameters
+ + +
T_yType of y
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
+
+
+
Returns
true if y is greater than 0.
+
Exceptions
+ + +
<code>domain_error</code>if y is negative or zero or if any element of y is NaN.
+
+
+ +

Definition at line 68 of file check_positive.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_positive_finite (const char * function,
const char * name,
const T_y & y 
)
+
+inline
+
+ +

Return true if y is positive and finite.

+

This function is vectorized and will check each element of y.

+
Template Parameters
+ + +
T_yType of y
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVariable to check
+
+
+
Returns
true if every element of y is greater than 0 and y is not infinite.
+
Exceptions
+ + +
<code>domain_error</code>if any element of y is not positive or if any element of y is NaN.
+
+
+ +

Definition at line 28 of file check_positive_finite.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_positive_ordered (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, 1 > & y 
)
+
+ +

Return true if the specified vector contains non-negative values and is sorted into strictly increasing order.

+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yVector to test
+
+
+
Returns
true if the vector is positive, ordered
+
Exceptions
+ + +
<code>std::domain_error</code>if the vector contains non-positive values, if the values are not ordered, if there are duplicated values, or if any element is NaN.
+
+
+ +

Definition at line 32 of file check_positive_ordered.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_positive_size (const char * function,
const char * name,
const char * expr,
const int size 
)
+
+inline
+
+ +

Return true if size is positive.

+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
exprExpression for the dimension size (for error messages)
sizeSize value to check
+
+
+
Returns
true if size is greater than 0.
+
Exceptions
+ + +
<code>std::invalid_argument</code>if size is zero or negative.
+
+
+ +

Definition at line 23 of file check_positive_size.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_range (const char * function,
const char * name,
const int max,
const int index,
const int nested_level,
const char * error_msg 
)
+
+inline
+
+ +

Return true if specified index is within range.

+

This check is 1-indexed by default. This behavior can be changed by setting stan::error_index::value.

+
Parameters
+ + + + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
maxMaximum size of the variable
indexIndex to check
nested_levelNested level (for error messages)
error_msgAdditional error message (for error messages)
+
+
+
Returns
true if the index is within range
+
Exceptions
+ + +
<code>std::out_of_range</code>if the index is not in range
+
+
+ +

Definition at line 29 of file check_range.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_range (const char * function,
const char * name,
const int max,
const int index,
const char * error_msg 
)
+
+inline
+
+ +

Return true if specified index is within range.

+

This check is 1-indexed by default. This behavior can be changed by setting stan::error_index::value.

+
Parameters
+ + + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
maxMaximum size of the variable
indexIndex to check
error_msgAdditional error message (for error messages)
+
+
+
Returns
true if the index is within range
+
Exceptions
+ + +
<code>std::out_of_range</code>if the index is not in range
+
+
+ +

Definition at line 62 of file check_range.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_range (const char * function,
const char * name,
const int max,
const int index 
)
+
+inline
+
+ +

Return true if specified index is within range.

+

This check is 1-indexed by default. This behavior can be changed by setting stan::error_index::value.

+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
maxMaximum size of the variable
indexIndex to check
+
+
+
Returns
true if the index is within range
+
Exceptions
+ + +
<code>std::out_of_range</code>if the index is not in range
+
+
+ +

Definition at line 89 of file check_range.hpp.

+ +
+
+ +
+
+
+template<typename T_y , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_row_index (const char * function,
const char * name,
const Eigen::Matrix< T_y, R, C > & y,
size_t i 
)
+
+inline
+
+ +

Return true if the specified index is a valid row of the matrix.

+

This check is 1-indexed by default. This behavior can be changed by setting stan::error_index::value.

+
Template Parameters
+ + + + +
TScalar type
RCompile time rows
CCompile time columns
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
iis index
+
+
+
Returns
true if the index is a valid row index in the matrix
+
Exceptions
+ + +
<code>std::out_of_range</code>if the index is out of range.
+
+
+ +

Definition at line 32 of file check_row_index.hpp.

+ +
+
+ +
+
+
+template<typename T_prob >
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_simplex (const char * function,
const char * name,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta 
)
+
+ +

Return true if the specified vector is simplex.

+

To be a simplex, all values must be greater than or equal to 0 and the values must sum to 1.

+

A valid simplex is one where the sum of hte elements is equal to 1. This function tests that the sum is within the tolerance specified by CONSTRAINT_TOLERANCE. This function only accepts Eigen vectors, statically typed vectors, not general matrices with 1 column.

+
Template Parameters
+ + +
T_probScalar type of the vector
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
thetaVector to test.
+
+
+
Returns
true if the vector is a simplex
+
Exceptions
+ + + +
<code>std::invalid_argument</code>if theta is a 0-vector.
<code>std::domain_error</code>if the vector is not a simplex or if any element is NaN.
+
+
+ +

Definition at line 41 of file check_simplex.hpp.

+ +
+
+ +
+
+
+template<typename T_size1 , typename T_size2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_size_match (const char * function,
const char * name_i,
T_size1 i,
const char * name_j,
T_size2 j 
)
+
+inline
+
+ +

Return true if the provided sizes match.

+
Template Parameters
+ + + +
T_size1Type of size 1
T_size2Type of size 2
+
+
+
Parameters
+ + + + + + +
functionFunction name (for error messages)
name_iVariable name 1 (for error messages)
iSize 1
name_jVariable name 2 (for error messages)
jSize 2
+
+
+
Returns
true if the sizes match
+
Exceptions
+ + +
<code>std::invalid_argument</code>if the sizes do not match
+
+
+ +

Definition at line 30 of file check_size_match.hpp.

+ +
+
+ +
+
+
+template<typename T_size1 , typename T_size2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_size_match (const char * function,
const char * expr_i,
const char * name_i,
T_size1 i,
const char * expr_j,
const char * name_j,
T_size2 j 
)
+
+inline
+
+ +

Return true if the provided sizes match.

+
Template Parameters
+ + + +
T_size1Type of size 1
T_size2Type of size 2
+
+
+
Parameters
+ + + + + + + + +
functionFunction name (for error messages)
expr_iExpression for variable name 1 (for error messages)
name_iVariable name 1 (for error messages)
iSize 1
expr_jExpression for variable name 2 (for error messages)
name_jVariable name 2 (for error messages)
jSize 2
+
+
+
Returns
true if the sizes match
+
Exceptions
+ + +
<code>std::invalid_argument</code>if the sizes do not match
+
+
+ +

Definition at line 67 of file check_size_match.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_spsd_matrix (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified matrix is a square, symmetric, and positive semi-definite.

+
Template Parameters
+ + +
TScalar type of the matrix
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is a square, symmetric, and positive semi-definite.
+
Exceptions
+ + + +
<code>std::invalid_argument</code>if the matrix is not square or if the matrix is 0x0
<code>std::domain_error</code>if the matrix is not symmetric or if the matrix is not positive semi-definite
+
+
+ +

Definition at line 31 of file check_spsd_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_square (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified matrix is square.

+

This check allows 0x0 matrices.

+
Template Parameters
+ + +
TType of scalar.
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is a square matrix.
+
Exceptions
+ + +
<code>std::invalid_argument</code>if the matrix is not square
+
+
+ +

Definition at line 28 of file check_square.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_std_vector_index (const char * function,
const char * name,
const std::vector< T > & y,
int i 
)
+
+inline
+
+ +

Return true if the specified index is valid in std vector.

+

This check is 1-indexed by default. This behavior can be changed by setting stan::error_index::value.

+
Template Parameters
+ + +
TScalar type
+
+
+
Parameters
+ + + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
ystd::vector to test
iIndex
+
+
+
Returns
true if the index is a valid in std vector.
+
Exceptions
+ + +
<code>std::out_of_range</code>if the index is out of range.
+
+
+ +

Definition at line 30 of file check_std_vector_index.hpp.

+ +
+
+ +
+
+
+template<typename T_y >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_symmetric (const char * function,
const char * name,
const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y 
)
+
+inline
+
+ +

Return true if the specified matrix is symmetric.

+

The error message is either 0 or 1 indexed, specified by stan::error_index::value.

+
Template Parameters
+ + +
T_yType of scalar.
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
yMatrix to test
+
+
+
Returns
true if the matrix is symmetric
+
Exceptions
+ + + +
<code>std::invalid_argument</code>if the matrix is not square.
<code>std::domain_error</code>if any element not on the main diagonal is NaN
+
+
+ +

Definition at line 37 of file check_symmetric.hpp.

+ +
+
+ +
+
+
+template<typename T_prob >
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_unit_vector (const char * function,
const char * name,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta 
)
+
+ +

Return true if the specified vector is unit vector.

+

A valid unit vector is one where the square of the elements summed is equal to 1. This function tests that the sum is within the tolerance specified by CONSTRAINT_TOLERANCE. This function only accepts Eigen vectors, statically typed vectors, not general matrices with 1 column.

+
Template Parameters
+ + +
T_probScalar type of the vector
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
thetaVector to test.
+
+
+
Returns
true if the vector is a unit vector.
+
Exceptions
+ + + +
<code>std::invalid_argument</code>if theta is a 0-vector.
<code>std::domain_error</code>if the vector is not a unit vector or if any element is NaN.
+
+
+ +

Definition at line 36 of file check_unit_vector.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::check_vector (const char * function,
const char * name,
const Eigen::Matrix< T, R, C > & x 
)
+
+inline
+
+ +

Return true if the matrix is either a row vector or column vector.

+

This function checks the runtime size of the matrix to check whether it is a row or column vector.

+
Template Parameters
+ + + + +
TScalar type of the matrix
RCompile time rows of the matrix
CCompile time columns of the matrix
+
+
+
Parameters
+ + + + +
functionFunction name (for error messages)
nameVariable name (for error messages)
xMatrix
+
+
+
Returns
true if x either has 1 columns or 1 rows
+
Exceptions
+ + +
<code>std::invalid_argument</code>if x is not a row or column vector.
+
+
+ +

Definition at line 34 of file check_vector.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::chi_square_ccdf_log (const T_y & y,
const T_dof & nu 
)
+
+ +

Definition at line 30 of file chi_square_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::chi_square_cdf (const T_y & y,
const T_dof & nu 
)
+
+ +

Calculates the chi square cumulative distribution function for the given variate and degrees of freedom.

+

y A scalar variate. nu Degrees of freedom.

+
Returns
The cdf of the chi square distribution
+ +

Definition at line 39 of file chi_square_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::chi_square_cdf_log (const T_y & y,
const T_dof & nu 
)
+
+ +

Definition at line 30 of file chi_square_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_dof >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::chi_square_log (const T_y & y,
const T_dof & nu 
)
+
+ +

The log of a chi-squared density for y with the specified degrees of freedom parameter.

+

The degrees of freedom prarameter must be greater than 0. y must be greater than or equal to 0.

+

+\begin{eqnarray*} y &\sim& \chi^2_\nu \\ \log (p (y \, |\, \nu)) &=& \log \left( \frac{2^{-\nu / 2}}{\Gamma (\nu / 2)} y^{\nu / 2 - 1} \exp^{- y / 2} \right) \\ &=& - \frac{\nu}{2} \log(2) - \log (\Gamma (\nu / 2)) + (\frac{\nu}{2} - 1) \log(y) - \frac{y}{2} \\ & & \mathrm{ where } \; y \ge 0 \end{eqnarray*} +

+
Parameters
+ + + +
yA scalar variable.
nuDegrees of freedom.
+
+
+
Exceptions
+ + + +
std::domain_errorif nu is not greater than or equal to 0
std::domain_errorif y is not greater than or equal to 0.
+
+
+
Template Parameters
+ + + +
T_yType of scalar.
T_dofType of degrees of freedom.
+
+
+ +

Definition at line 49 of file chi_square_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::chi_square_log (const T_y & y,
const T_dof & nu 
)
+
+inline
+
+ +

Definition at line 146 of file chi_square_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::chi_square_rng (const double nu,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 24 of file chi_square_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cholesky_corr_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & y,
int K 
)
+
+ +

Definition at line 20 of file cholesky_corr_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cholesky_corr_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & y,
int K,
T & lp 
)
+
+ +

Definition at line 58 of file cholesky_corr_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::cholesky_corr_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & x)
+
+ +

Definition at line 18 of file cholesky_corr_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cholesky_decompose (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+ +

Return the lower-triangular Cholesky factor (i.e., matrix square root) of the specified square, symmetric matrix.

+

The return value $L$ will be a lower-traingular matrix such that the original matrix $A$ is given by

+

$A = L \times L^T$.

Parameters
+ + +
mSymmetrix matrix.
+
+
+
Returns
Square root of matrix.
+
Exceptions
+ + +
std::domain_errorif m is not a symmetric matrix or if m is not positive definite (if m has more than 0 elements)
+
+
+ +

Definition at line 25 of file cholesky_decompose.hpp.

+ +
+
+ +
+
+ + + + + + + + +
Eigen::Matrix<var, -1, -1> stan::math::cholesky_decompose (const Eigen::Matrix< var,-1,-1 > & A)
+
+ +

Definition at line 131 of file cholesky_decompose.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cholesky_factor_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
int M,
int N 
)
+
+ +

Return the Cholesky factor of the specified size read from the specified vector.

+

A total of (N choose 2) + N + (M - N) * N elements are required to read an M by N Cholesky factor.

+
Template Parameters
+ + +
TType of scalars in matrix
+
+
+
Parameters
+ + + + +
xVector of unconstrained values
MNumber of rows
NNumber of columns
+
+
+
Returns
Cholesky factor
+ +

Definition at line 29 of file cholesky_factor_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cholesky_factor_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
int M,
int N,
T & lp 
)
+
+ +

Return the Cholesky factor of the specified size read from the specified vector and increment the specified log probability reference with the log Jacobian adjustment of the transform.

+

A total of (N choose 2) + N + N * (M - N) free parameters are required to read an M by N Cholesky factor.

+
Template Parameters
+ + +
TType of scalars in matrix
+
+
+
Parameters
+ + + + + +
xVector of unconstrained values
MNumber of rows
NNumber of columns
lpLog probability that is incremented with the log Jacobian
+
+
+
Returns
Cholesky factor
+ +

Definition at line 73 of file cholesky_factor_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::cholesky_factor_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & y)
+
+ +

Return the unconstrained vector of parameters correspdonding to the specified Cholesky factor.

+

A Cholesky factor must be lower triangular and have positive diagonal elements.

+
Parameters
+ + +
yCholesky factor.
+
+
+
Returns
Unconstrained parameters for Cholesky factor.
+
Exceptions
+ + +
std::domain_errorIf the matrix is not a Cholesky factor.
+
+
+ +

Definition at line 24 of file cholesky_factor_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::col (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m,
size_t j 
)
+
+inline
+
+ +

Return the specified column of the specified matrix using start-at-1 indexing.

+

This is equivalent to calling m.col(i - 1) and assigning the resulting template expression to a column vector.

+
Parameters
+ + + +
mMatrix.
jColumn index (count from 1).
+
+
+
Returns
Specified column of the matrix.
+ +

Definition at line 24 of file col.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
int stan::math::cols (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Return the number of columns in the specified matrix, vector, or row vector.

+
Template Parameters
+ + + + +
TType of matrix entries.
RRow type of matrix.
CColumn type of matrix.
+
+
+
Parameters
+ + +
[in]mInput matrix, vector, or row vector.
+
+
+
Returns
Number of columns.
+ +

Definition at line 20 of file cols.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, 1, C1> stan::math::columns_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > & v1,
const Eigen::Matrix< fvar< T >, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 18 of file columns_dot_product.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<double, 1, C1> stan::math::columns_dot_product (const Eigen::Matrix< double, R1, C1 > & v1,
const Eigen::Matrix< double, R2, C2 > & v2 
)
+
+inline
+
+ +

Returns the dot product of the specified vectors.

+
Parameters
+ + + +
v1First vector.
v2Second vector.
+
+
+
Returns
Dot product of the vectors.
+
Exceptions
+ + +
std::domain_errorIf the vectors are not the same size or if they are both not vector dimensioned.
+
+
+ +

Definition at line 22 of file columns_dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_same<T1, var>::value || boost::is_same<T2, var>::value, Eigen::Matrix<var, 1, C1> >::type stan::math::columns_dot_product (const Eigen::Matrix< T1, R1, C1 > & v1,
const Eigen::Matrix< T2, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 25 of file columns_dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, 1, C1> stan::math::columns_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > & v1,
const Eigen::Matrix< double, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 35 of file columns_dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, 1, C1> stan::math::columns_dot_product (const Eigen::Matrix< double, R1, C1 > & v1,
const Eigen::Matrix< fvar< T >, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 52 of file columns_dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, 1, C> stan::math::columns_dot_self (const Eigen::Matrix< fvar< T >, R, C > & x)
+
+inline
+
+ +

Definition at line 15 of file columns_dot_self.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, 1, C> stan::math::columns_dot_self (const Eigen::Matrix< T, R, C > & x)
+
+inline
+
+ +

Returns the dot product of each column of a matrix with itself.

+
Parameters
+ + +
xMatrix.
+
+
+
Template Parameters
+ + +
Tscalar type
+
+
+ +

Definition at line 16 of file columns_dot_self.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<var, 1, C> stan::math::columns_dot_self (const Eigen::Matrix< var, R, C > & x)
+
+inline
+
+ +

Returns the dot product of each column of a matrix with itself.

+
Parameters
+ + +
xMatrix.
+
+
+
Template Parameters
+ + +
Tscalar type
+
+
+ +

Definition at line 22 of file columns_dot_self.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::corr_constrain (const T x)
+
+inline
+
+ +

Return the result of transforming the specified scalar to have a valid correlation value between -1 and 1 (inclusive).

+

The transform used is the hyperbolic tangent function,

+

$f(x) = \tanh x = \frac{\exp(2x) - 1}{\exp(2x) + 1}$.

+
Parameters
+ + +
xScalar input.
+
+
+
Returns
Result of transforming the input to fall between -1 and 1.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 25 of file corr_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::math::corr_constrain (const T x,
T & lp 
)
+
+inline
+
+ +

Return the result of transforming the specified scalar to have a valid correlation value between -1 and 1 (inclusive).

+

The transform used is as specified for corr_constrain(T). The log absolute Jacobian determinant is

+

$\log | \frac{d}{dx} \tanh x | = \log (1 - \tanh^2 x)$.

+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 43 of file corr_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::corr_free (const T y)
+
+inline
+
+ +

Return the unconstrained scalar that when transformed to a valid correlation produces the specified value.

+

This function inverts the transform defined for corr_constrain(T), which is the inverse hyperbolic tangent,

+

$ f^{-1}(y) = \mbox{atanh}\, y = \frac{1}{2} \log \frac{y + 1}{y - 1}$.

+
Parameters
+ + +
yCorrelation scalar input.
+
+
+
Returns
Free scalar that transforms to the specified input.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 29 of file corr_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::corr_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type k 
)
+
+ +

Return the correlation matrix of the specified dimensionality derived from the specified vector of unconstrained values.

+

The input vector must be of length ${k \choose 2} = \frac{k(k-1)}{2}$. The values in the input vector represent unconstrained (partial) correlations among the dimensions.

+

The transform based on partial correlations is as specified in

+
    +
  • +Lewandowski, Daniel, Dorota Kurowicka, and Harry Joe. 2009. Generating random correlation matrices based on vines and extended onion method. Journal of Multivariate Analysis 100:1989–-2001.
  • +
+

The free vector entries are first constrained to be valid correlation values using corr_constrain(T).

+
Parameters
+ + + +
xVector of unconstrained partial correlations.
kDimensionality of returned correlation matrix.
+
+
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Exceptions
+ + +
std::invalid_argumentif x is not a valid correlation matrix.
+
+
+ +

Definition at line 40 of file corr_matrix_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::corr_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type k,
T & lp 
)
+
+ +

Return the correlation matrix of the specified dimensionality derived from the specified vector of unconstrained values.

+

The input vector must be of length ${k \choose 2} = \frac{k(k-1)}{2}$. The values in the input vector represent unconstrained (partial) correlations among the dimensions.

+

The transform is as specified for corr_matrix_constrain(Matrix, size_t); the paper it cites also defines the Jacobians for correlation inputs, which are composed with the correlation constrained Jacobians defined in corr_constrain(T, double) for this function.

+
Parameters
+ + + + +
xVector of unconstrained partial correlations.
kDimensionality of returned correlation matrix.
lpLog probability reference to increment.
+
+
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 78 of file corr_matrix_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::corr_matrix_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & y)
+
+ +

Return the vector of unconstrained partial correlations that define the specified correlation matrix when transformed.

+

The constraining transform is defined as for corr_matrix_constrain(Matrix, size_t). The inverse transform in this function is simpler in that it only needs to compute the $k \choose 2$ partial correlations and then free those.

+
Parameters
+ + +
yThe correlation matrix to free.
+
+
+
Returns
Vector of unconstrained values that produce the specified correlation matrix when transformed.
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Exceptions
+ + + +
std::domain_errorif the correlation matrix has no elements or is not a square matrix.
std::runtime_errorif the correlation matrix cannot be factorized by factor_cov_matrix() or if the sds returned by factor_cov_matrix() on log scale are unconstrained.
+
+
+ +

Definition at line 39 of file corr_matrix_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::cos (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 13 of file cos.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::cos (const vara)
+
+inline
+
+ +

Return the cosine of a radian-scaled variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \cos x = - \sin x$.

+

+\[ \mbox{cos}(x) = \begin{cases} \cos(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{cos}(x)}{\partial x} = \begin{cases} -\sin(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable for radians of angle.
+
+
+
Returns
Cosine of variable.
+ +

Definition at line 49 of file cos.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::cosh (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 13 of file cosh.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::cosh (const vara)
+
+inline
+
+ +

Return the hyperbolic cosine of the specified variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \cosh x = \sinh x$.

+

+\[ \mbox{cosh}(x) = \begin{cases} \cosh(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{cosh}(x)}{\partial x} = \begin{cases} \sinh(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable.
+
+
+
Returns
Hyperbolic cosine of variable.
+ +

Definition at line 50 of file cosh.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cov_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type K 
)
+
+ +

Return the symmetric, positive-definite matrix of dimensions K by K resulting from transforming the specified finite vector of size K plus (K choose 2).

+

See cov_matrix_free() for the inverse transform.

+
Parameters
+ + + +
xThe vector to convert to a covariance matrix.
KThe number of rows and columns of the resulting covariance matrix.
+
+
+
Exceptions
+ + +
std::domain_errorif (x.size() != K + (K choose 2)).
+
+
+ +

Definition at line 31 of file cov_matrix_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cov_matrix_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
typename math::index_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >::type K,
T & lp 
)
+
+ +

Return the symmetric, positive-definite matrix of dimensions K by K resulting from transforming the specified finite vector of size K plus (K choose 2).

+

See cov_matrix_free() for the inverse transform.

+
Parameters
+ + + + +
xThe vector to convert to a covariance matrix.
KThe dimensions of the resulting covariance matrix.
lpReference
+
+
+
Exceptions
+ + +
std::domain_errorif (x.size() != K + (K choose 2)).
+
+
+ +

Definition at line 71 of file cov_matrix_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cov_matrix_constrain_lkj (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
size_t k 
)
+
+ +

Return the covariance matrix of the specified dimensionality derived from constraining the specified vector of unconstrained values.

+

The input vector must be of length $k \choose 2 + k$. The first $k \choose 2$ values in the input represent unconstrained (partial) correlations and the last $k$ are unconstrained standard deviations of the dimensions.

+

The transform scales the correlation matrix transform defined in corr_matrix_constrain(Matrix, size_t) with the constrained deviations.

+
Parameters
+ + + +
xInput vector of unconstrained partial correlations and standard deviations.
kDimensionality of returned covariance matrix.
+
+
+
Returns
Covariance matrix derived from the unconstrained partial correlations and deviations.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 34 of file cov_matrix_constrain_lkj.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::cov_matrix_constrain_lkj (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
size_t k,
T & lp 
)
+
+ +

Return the covariance matrix of the specified dimensionality derived from constraining the specified vector of unconstrained values and increment the specified log probability reference with the log absolute Jacobian determinant.

+

The transform is defined as for cov_matrix_constrain(Matrix, size_t).

+

The log absolute Jacobian determinant is derived by composing the log absolute Jacobian determinant for the underlying correlation matrix as defined in cov_matrix_constrain(Matrix, size_t, T&) with the Jacobian of the transfrom of the correlation matrix into a covariance matrix by scaling by standard deviations.

+
Parameters
+ + + + +
xInput vector of unconstrained partial correlations and standard deviations.
kDimensionality of returned covariance matrix.
lpLog probability reference to increment.
+
+
+
Returns
Covariance matrix derived from the unconstrained partial correlations and deviations.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 73 of file cov_matrix_constrain_lkj.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::cov_matrix_free (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & y)
+
+ +

The covariance matrix derived from the symmetric view of the lower-triangular view of the K by K specified matrix is freed to return a vector of size K + (K choose 2).

+

This is the inverse of the cov_matrix_constrain() function so that for any finite vector x of size K

    +
  • (K choose 2),
  • +
+

x == cov_matrix_free(cov_matrix_constrain(x, K)).

+

In order for this round-trip to work (and really for this function to work), the symmetric view of its lower-triangular view must be positive definite.

+
Parameters
+ + +
yMatrix of dimensions K by K such that he symmetric view of the lower-triangular view is positive definite.
+
+
+
Returns
Vector of size K plus (K choose 2) in (-inf, inf) that produces
+
Exceptions
+ + +
std::domain_errorif y is not square, has zero dimensionality, or has a non-positive diagonal element.
+
+
+ +

Definition at line 37 of file cov_matrix_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::cov_matrix_free_lkj (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & y)
+
+ +

Return the vector of unconstrained partial correlations and deviations that transform to the specified covariance matrix.

+

The constraining transform is defined as for cov_matrix_constrain(Matrix, size_t). The inverse first factors out the deviations, then applies the freeing transfrom of corr_matrix_free(Matrix&).

+
Parameters
+ + +
yCovariance matrix to free.
+
+
+
Returns
Vector of unconstrained values that transforms to the specified covariance matrix.
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Exceptions
+ + + +
std::domain_errorif the correlation matrix has no elements or is not a square matrix.
std::runtime_errorif the correlation matrix cannot be factorized by factor_cov_matrix()
+
+
+ +

Definition at line 32 of file cov_matrix_free_lkj.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, C, C> stan::math::crossprod (const Eigen::Matrix< fvar< T >, R, C > & m)
+
+inline
+
+ +

Definition at line 17 of file crossprod.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
matrix_d stan::math::crossprod (const matrix_dM)
+
+inline
+
+ +

Returns the result of pre-multiplying a matrix by its own transpose.

+
Parameters
+ + +
MMatrix to multiply.
+
+
+
Returns
Transpose of M times M
+ +

Definition at line 17 of file crossprod.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
matrix_v stan::math::crossprod (const matrix_vM)
+
+inline
+
+ +

Returns the result of pre-multiplying a matrix by its own transpose.

+
Parameters
+ + +
MMatrix to multiply.
+
+
+
Returns
Transpose of M times M
+ +

Definition at line 17 of file crossprod.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, Eigen::Dynamic, 1> stan::math::csr_matrix_times_vector (const int & m,
const int & n,
const Eigen::Matrix< T1, Eigen::Dynamic, 1 > & w,
const std::vector< int > & v,
const std::vector< int > & u,
const Eigen::Matrix< T2, Eigen::Dynamic, 1 > & b 
)
+
+inline
+
+ +

Definition at line 79 of file csr_matrix_times_vector.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<T> stan::math::cumulative_sum (const std::vector< T > & x)
+
+inline
+
+ +

Return the cumulative sum of the specified vector.

+

The cumulative sum of a vector of values

1  is the
+
2 
+
3 @code x[0], x[1] + x[2], ..., x[1] + , ..., + x[x.size()-1]
+
Template Parameters
+ + +
TScalar type of vector.
+
+
+
Parameters
+ + +
xVector of values.
+
+
+
Returns
Cumulative sum of values.
+ +

Definition at line 23 of file cumulative_sum.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R, C> stan::math::cumulative_sum (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Return the cumulative sum of the specified matrix.

+

The cumulative sum is of the same type as the input and has values defined by

+
x(0), x(1) + x(2), ..., x(1) + , ..., + x(x.size()-1)
+
Template Parameters
+ + + + +
TScalar type of matrix.
RRow type of matrix.
CColumn type of matrix.
+
+
+
Parameters
+ + +
mMatrix of values.
+
+
+
Returns
Cumulative sum of values.
+ +

Definition at line 49 of file cumulative_sum.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::cvodes_check_flag (int flag,
const std::string & func_name 
)
+
+inline
+
+ +

Definition at line 23 of file cvodes_utils.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::cvodes_set_options (void * cvodes_mem,
double rel_tol,
double abs_tol,
long int max_num_steps 
)
+
+inline
+
+ +

Definition at line 31 of file cvodes_utils.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::cvodes_silent_err_handler (int error_code,
const char * module,
const char * function,
char * msg,
void * eh_data 
)
+
+inline
+
+ +

Definition at line 18 of file cvodes_utils.hpp.

+ +
+
+ +
+
+
+template<typename T_initial , typename T_param >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
std::vector<std::vector<typename stan::return_type<T_initial, T_param>::type> > stan::math::decouple_ode_states (const std::vector< std::vector< double > > & y,
const std::vector< T_initial > & y0,
const std::vector< T_param > & theta 
)
+
+inline
+
+ +

Takes sensitivity output from integrators and returns results in precomputed_gradients format.

+

Solution input vector size depends on requested sensitivities, which can be enabled for initials and parameters. For each sensitivity N states are computed. The input vector is expected to be ordered by states, i.e. first the N states, then optionally the N sensitivities for the initials (first the N states for the first initial and so on), finally the sensitivities for the M parameters follow optionally.

+
Template Parameters
+ + + +
T1_initialtype of scalars for initial values.
T2_paramtype of scalars for parameters.
+
+
+
Parameters
+ + + + +
[in]youtput from integrator in column-major format as a coupled system output
[in]y0initial state.
[in]thetaparameters
+
+
+
Returns
a vector of states for each entry in y in Stan var format
+ +

Definition at line 38 of file decouple_ode_states.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
std::vector<std::vector<double> > stan::math::decouple_ode_states (const std::vector< std::vector< double > > & y,
const std::vector< double > & y0,
const std::vector< double > & theta 
)
+
+inline
+
+ +

The decouple ODE states operation for the case of no sensitivities is equal to the indentity operation.

+
Parameters
+ + + + +
[in]youtput from integrator
[in]y0initial state.
[in]thetaparameters
+
+
+
Returns
y
+ +

Definition at line 89 of file decouple_ode_states.hpp.

+ +
+
+ +
+
+
+template<typename T , typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::derivative (const F & f,
const T & x,
T & fx,
T & dfx_dx 
)
+
+ +

Return the derivative of the specified univariate function at the specified argument.

+
Template Parameters
+ + + +
TArgument type
FFunction type
+
+
+
Parameters
+ + + + + +
[in]fFunction
[in]xArgument
[out]fxValue of function applied to argument
[out]dfx_dxValue of derivative
+
+
+ +

Definition at line 26 of file derivative.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
T stan::math::determinant (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the determinant of the specified square matrix.

+
Parameters
+ + +
mSpecified matrix.
+
+
+
Returns
Determinant of the matrix.
+
Exceptions
+ + +
std::domain_errorif matrix is not square.
+
+
+ +

Definition at line 18 of file determinant.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::determinant (const Eigen::Matrix< fvar< T >, R, C > & m)
+
+inline
+
+ +

Definition at line 21 of file determinant.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
var stan::math::determinant (const Eigen::Matrix< var, R, C > & m)
+
+inline
+
+ +

Definition at line 66 of file determinant.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::diag_matrix (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & v)
+
+inline
+
+ +

Return a square diagonal matrix with the specified vector of coefficients as the diagonal values.

+
Parameters
+ + +
[in]vSpecified vector.
+
+
+
Returns
Diagonal matrix with vector as diagonal values.
+ +

Definition at line 18 of file diag_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C1> stan::math::diag_post_multiply (const Eigen::Matrix< T1, R1, C1 > & m1,
const Eigen::Matrix< T2, R2, C2 > & m2 
)
+
+ +

Definition at line 14 of file diag_post_multiply.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R2, C2> stan::math::diag_pre_multiply (const Eigen::Matrix< T1, R1, C1 > & m1,
const Eigen::Matrix< T2, R2, C2 > & m2 
)
+
+ +

Definition at line 14 of file diag_pre_multiply.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::diagonal (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+inline
+
+ +

Return a column vector of the diagonal elements of the specified matrix.

+

The matrix is not required to be square.

Parameters
+ + +
mSpecified matrix.
+
+
+
Returns
Diagonal of the matrix.
+ +

Definition at line 18 of file diagonal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::digamma (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 16 of file digamma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::digamma (const stan::math::vara)
+
+inline
+
+ +

Definition at line 24 of file digamma.hpp.

+ +
+
+ +
+
+ + + + + + + + +
double stan::math::digamma (double x)
+
+ +

+\[ \mbox{digamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{digamma}(x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \frac{\partial\, \Psi(x)}{\partial x} & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \Psi(x)=\frac{\Gamma'(x)}{\Gamma(x)} \] +

+

+\[ \frac{\partial \, \Psi(x)}{\partial x} = \frac{\Gamma''(x)\Gamma(x)-(\Gamma'(x))^2}{\Gamma^2(x)} \] +

+ +

Definition at line 39 of file digamma.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::dims (const T & x,
std::vector< int > & result 
)
+
+inline
+
+ +

Definition at line 13 of file dims.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::dims (const Eigen::Matrix< T, R, C > & x,
std::vector< int > & result 
)
+
+inline
+
+ +

Definition at line 18 of file dims.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::dims (const std::vector< T > & x,
std::vector< int > & result 
)
+
+inline
+
+ +

Definition at line 25 of file dims.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<int> stan::math::dims (const T & x)
+
+inline
+
+ +

Definition at line 34 of file dims.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_prob , typename T_prior_sample_size >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob, T_prior_sample_size>::type stan::math::dirichlet_log (const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta,
const Eigen::Matrix< T_prior_sample_size, Eigen::Dynamic, 1 > & alpha 
)
+
+ +

The log of the Dirichlet density for the given theta and a vector of prior sample sizes, alpha.

+

Each element of alpha must be greater than 0. Each element of theta must be greater than or 0. Theta sums to 1.

+

+\begin{eqnarray*} \theta &\sim& \mbox{\sf{Dirichlet}} (\alpha_1, \ldots, \alpha_k) \\ \log (p (\theta \, |\, \alpha_1, \ldots, \alpha_k) ) &=& \log \left( \frac{\Gamma(\alpha_1 + \cdots + \alpha_k)}{\Gamma(\alpha_1) \cdots \Gamma(\alpha_k)} \theta_1^{\alpha_1 - 1} \cdots \theta_k^{\alpha_k - 1} \right) \\ &=& \log (\Gamma(\alpha_1 + \cdots + \alpha_k)) - \log(\Gamma(\alpha_1)) - \cdots - \log(\Gamma(\alpha_k)) + (\alpha_1 - 1) \log (\theta_1) + \cdots + (\alpha_k - 1) \log (\theta_k) \end{eqnarray*} +

+
Parameters
+ + + +
thetaA scalar vector.
alphaPrior sample sizes.
+
+
+
Returns
The log of the Dirichlet density.
+
Exceptions
+ + + + +
std::domain_errorif any element of alpha is less than or equal to 0.
std::domain_errorif any element of theta is less than 0.
std::domain_errorif the sum of theta is not 1.
+
+
+
Template Parameters
+ + + +
T_probType of scalar.
T_prior_sample_sizeType of prior sample sizes.
+
+
+ +

Definition at line 46 of file dirichlet_log.hpp.

+ +
+
+ +
+
+
+template<typename T_prob , typename T_prior_sample_size >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob, T_prior_sample_size>::type stan::math::dirichlet_log (const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta,
const Eigen::Matrix< T_prior_sample_size, Eigen::Dynamic, 1 > & alpha 
)
+
+inline
+
+ +

Definition at line 79 of file dirichlet_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::VectorXd stan::math::dirichlet_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > & alpha,
RNG & rng 
)
+
+inline
+
+ +

Return a draw from a Dirichlet distribution with specified parameters and pseudo-random number generator.

+

For prior counts greater than zero, the usual algorithm that draws gamma variates and normalizes is used.

+

For prior counts less than zero (i.e., parameters with value less than one), a log-scale version of the following algorithm is used to deal with underflow:

+
+

G. Marsaglia and W. Tsang. A simple method for generating gamma variables. ACM Transactions on Mathematical Software. 26(3):363–372, 2000.

+
+
Template Parameters
+ + +
RNGType of pseudo-random number generator.
+
+
+
Parameters
+ + + +
alphaPrior count (plus 1) parameter for Dirichlet.
rngPseudo-random number generator.
+
+
+ +

Definition at line 46 of file dirichlet_rng.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::dist (const std::vector< double > & x,
const std::vector< double > & y 
)
+
+inline
+
+ +

Definition at line 11 of file dist.hpp.

+ +
+
+ +
+
+
+template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::distance (const Eigen::Matrix< T1, R1, C1 > & v1,
const Eigen::Matrix< T2, R2, C2 > & v2 
)
+
+inline
+
+ +

Returns the distance between the specified vectors.

+
Parameters
+ + + +
v1First vector.
v2Second vector.
+
+
+
Returns
Dot product of the vectors.
+
Exceptions
+ + +
std::domain_errorIf the vectors are not the same size or if they are both not vector dimensioned.
+
+
+ +

Definition at line 25 of file distance.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::divide (const Eigen::Matrix< fvar< T >, R, C > & v,
const fvar< T > & c 
)
+
+inline
+
+ +

Definition at line 16 of file divide.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::return_type<T1, T2>::type stan::math::divide (const T1 & x,
const T2 & y 
)
+
+inline
+
+ +

Return the division of the first scalar by the second scalar.

+
Parameters
+ + + +
[in]xSpecified vector.
[in]ySpecified scalar.
+
+
+
Returns
Vector divided by the scalar.
+ +

Definition at line 20 of file divide.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_arithmetic<T>::value, Eigen::Matrix<double, R, C> >::type stan::math::divide (const Eigen::Matrix< double, R, C > & m,
c 
)
+
+inline
+
+ +

Return specified matrix divided by specified scalar.

+
Template Parameters
+ + + +
RRow type for matrix.
CColumn type for matrix.
+
+
+
Parameters
+ + + +
mMatrix.
cScalar.
+
+
+
Returns
Matrix divided by scalar.
+ +

Definition at line 23 of file divide.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R, C> stan::math::divide (const Eigen::Matrix< T1, R, C > & v,
const T2 & c 
)
+
+inline
+
+ +

Return the division of the specified column vector by the specified scalar.

+
Parameters
+ + + +
[in]vSpecified vector.
[in]cSpecified scalar.
+
+
+
Returns
Vector divided by the scalar.
+ +

Definition at line 23 of file divide.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::divide (const int x,
const int y 
)
+
+inline
+
+ +

Definition at line 24 of file divide.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::divide (const Eigen::Matrix< fvar< T >, R, C > & v,
const double c 
)
+
+inline
+
+ +

Definition at line 27 of file divide.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::divide (const Eigen::Matrix< double, R, C > & v,
const fvar< T > & c 
)
+
+inline
+
+ +

Definition at line 39 of file divide.hpp.

+ +
+
+ +
+
+
+template<typename T_shape >
+ + + + + + + + + + + + + + + + + + +
T_shape stan::math::do_lkj_constant (const T_shape & eta,
const unsigned int & K 
)
+
+ +

Definition at line 53 of file lkj_corr_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::domain_error (const char * function,
const char * name,
const T & y,
const char * msg1,
const char * msg2 
)
+
+inline
+
+ +

Throw a domain error with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing domain errors. This will allow us to change the behavior for all functions at once. (We've already changed behavior mulitple times up to Stan v2.5.0.)

+

The message is: "<function>: <name> <msg1><y><msg2>"

+
Template Parameters
+ + +
TType of variable
+
+
+
Parameters
+ + + + + + +
functionName of the function
nameName of the variable
yVariable
msg1Message to print before the variable
msg2Message to print after the variable
+
+
+
Exceptions
+ + +
std::domain_error
+
+
+ +

Definition at line 32 of file domain_error.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::domain_error (const char * function,
const char * name,
const T & y,
const char * msg1 
)
+
+inline
+
+ +

Throw a domain error with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing domain errors. This will allow us to change the behavior for all functions at once. (We've already changed behavior mulitple times up to Stan v2.5.0.)

+

The message is: "<function>: <name> <msg1><y>"

+
Template Parameters
+ + +
TType of variable
+
+
+
Parameters
+ + + + + +
functionName of the function
nameName of the variable
yVariable
msg1Message to print before the variable
+
+
+
Exceptions
+ + +
std::domain_error
+
+
+ +

Definition at line 67 of file domain_error.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::domain_error_vec (const char * function,
const char * name,
const T & y,
const size_t i,
const char * msg1,
const char * msg2 
)
+
+inline
+
+ +

Throw a domain error with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing domain errors. This will allow us to change the behavior for all functions at once. (We've already changed behavior mulitple times up to Stan v2.5.0.)

+

The message is: "<function>: <name>[<i+error_index>] <msg1><y>" where error_index is the value of stan::error_index::value which indicates whether the message should be 0 or 1 indexed.

+
Template Parameters
+ + +
TType of variable
+
+
+
Parameters
+ + + + + + + +
functionName of the function
nameName of the variable
yVariable
iIndex
msg1Message to print before the variable
msg2Message to print after the variable
+
+
+
Exceptions
+ + +
std::domain_error
+
+
+ +

Definition at line 38 of file domain_error_vec.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::domain_error_vec (const char * function,
const char * name,
const T & y,
const size_t i,
const char * msg 
)
+
+inline
+
+ +

Throw a domain error with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing domain errors. This will allow us to change the behavior for all functions at once. (We've already changed behavior mulitple times up to Stan v2.5.0.)

+

The message is: "<function>: <name>[<i+error_index>] <msg1><y>" where error_index is the value of stan::error_index::value which indicates whether the message should be 0 or 1 indexed.

+
Template Parameters
+ + +
TType of variable
+
+
+
Parameters
+ + + + + + +
functionName of the function
nameName of the variable
yVariable
iIndex
msgMessage to print before the variable
+
+
+
Exceptions
+ + +
std::domain_error
+
+
+ +

Definition at line 73 of file domain_error_vec.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::dot (const std::vector< double > & x,
const std::vector< double > & y 
)
+
+inline
+
+ +

Definition at line 11 of file dot.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > & v1,
const Eigen::Matrix< fvar< T >, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 20 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::dot_product (const Eigen::Matrix< double, R1, C1 > & v1,
const Eigen::Matrix< double, R2, C2 > & v2 
)
+
+inline
+
+ +

Returns the dot product of the specified vectors.

+
Parameters
+ + + +
v1First vector.
v2Second vector.
+
+
+
Returns
Dot product of the vectors.
+
Exceptions
+ + +
std::domain_errorIf the vectors are not the same size or if they are both not vector dimensioned.
+
+
+ +

Definition at line 22 of file dot_product.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::dot_product (const double * v1,
const double * v2,
size_t length 
)
+
+inline
+
+ +

Returns the dot product of the specified arrays of doubles.

+
Parameters
+ + + + +
v1First array.
v2Second array.
lengthLength of both arrays.
+
+
+ +

Definition at line 37 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > & v1,
const Eigen::Matrix< double, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 37 of file dot_product.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::dot_product (const std::vector< double > & v1,
const std::vector< double > & v2 
)
+
+inline
+
+ +

Returns the dot product of the specified arrays of doubles.

+
Parameters
+ + + +
v1First array.
v2Second array.
+
+
+
Exceptions
+ + +
std::domain_errorif the vectors are not the same size.
+
+
+ +

Definition at line 50 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const Eigen::Matrix< double, R1, C1 > & v1,
const Eigen::Matrix< fvar< T >, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 54 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > & v1,
const Eigen::Matrix< fvar< T >, R2, C2 > & v2,
size_typelength 
)
+
+inline
+
+ +

Definition at line 71 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > & v1,
const Eigen::Matrix< double, R2, C2 > & v2,
size_typelength 
)
+
+inline
+
+ +

Definition at line 86 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const Eigen::Matrix< double, R1, C1 > & v1,
const Eigen::Matrix< fvar< T >, R2, C2 > & v2,
size_typelength 
)
+
+inline
+
+ +

Definition at line 101 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const std::vector< fvar< T > > & v1,
const std::vector< fvar< T > > & v2 
)
+
+inline
+
+ +

Definition at line 116 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const std::vector< double > & v1,
const std::vector< fvar< T > > & v2 
)
+
+inline
+
+ +

Definition at line 130 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const std::vector< fvar< T > > & v1,
const std::vector< double > & v2 
)
+
+inline
+
+ +

Definition at line 144 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const std::vector< fvar< T > > & v1,
const std::vector< fvar< T > > & v2,
size_typelength 
)
+
+inline
+
+ +

Definition at line 158 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const std::vector< double > & v1,
const std::vector< fvar< T > > & v2,
size_typelength 
)
+
+inline
+
+ +

Definition at line 170 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::dot_product (const std::vector< fvar< T > > & v1,
const std::vector< double > & v2,
size_typelength 
)
+
+inline
+
+ +

Definition at line 182 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_same<T1, var>::value || boost::is_same<T2, var>::value, var>::type stan::math::dot_product (const Eigen::Matrix< T1, R1, C1 > & v1,
const Eigen::Matrix< T2, R2, C2 > & v2 
)
+
+inline
+
+ +

Returns the dot product.

+
Parameters
+ + + +
[in]v1First column vector.
[in]v2Second column vector.
+
+
+
Returns
Dot product of the vectors.
+
Exceptions
+ + +
std::domain_errorif length of v1 is not equal to length of v2.
+
+
+ +

Definition at line 212 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_same<T1, var>::value || boost::is_same<T2, var>::value, var>::type stan::math::dot_product (const T1 * v1,
const T2 * v2,
size_t length 
)
+
+inline
+
+ +

Returns the dot product.

+
Parameters
+ + + + +
[in]v1First array.
[in]v2Second array.
[in]lengthLength of both arrays.
+
+
+
Returns
Dot product of the arrays.
+ +

Definition at line 233 of file dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_same<T1, var>::value || boost::is_same<T2, var>::value, var>::type stan::math::dot_product (const std::vector< T1 > & v1,
const std::vector< T2 > & v2 
)
+
+inline
+
+ +

Returns the dot product.

+
Parameters
+ + + +
[in]v1First vector.
[in]v2Second vector.
+
+
+
Returns
Dot product of the vectors.
+
Exceptions
+ + +
std::domain_errorif sizes of v1 and v2 do not match.
+
+
+ +

Definition at line 249 of file dot_product.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
double stan::math::dot_self (const std::vector< double > & x)
+
+inline
+
+ +

Definition at line 11 of file dot_self.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::dot_self (const Eigen::Matrix< fvar< T >, R, C > & v)
+
+inline
+
+ +

Definition at line 16 of file dot_self.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
double stan::math::dot_self (const Eigen::Matrix< double, R, C > & v)
+
+inline
+
+ +

Returns the dot product of the specified vector with itself.

+
Parameters
+ + +
vVector.
+
+
+
Template Parameters
+ + + +
Rnumber of rows or Eigen::Dynamic for dynamic
Cnumber of rows or Eigen::Dyanmic for dynamic
+
+
+
Exceptions
+ + +
std::domain_errorIf v is not vector dimensioned.
+
+
+ +

Definition at line 18 of file dot_self.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
var stan::math::dot_self (const Eigen::Matrix< var, R, C > & v)
+
+inline
+
+ +

Returns the dot product of a vector with itself.

+
Parameters
+ + +
[in]vVector.
+
+
+
Returns
Dot product of the vector with itself.
+
Template Parameters
+ + + +
Rnumber of rows or Eigen::Dynamic for dynamic; one of R or C must be 1
Cnumber of rows or Eigen::Dyanmic for dynamic; one of R or C must be 1
+
+
+ +

Definition at line 80 of file dot_self.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::double_exponential_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 26 of file double_exponential_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::double_exponential_cdf (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Calculates the double exponential cumulative density function.

+

$ f(y|\mu, \sigma) = \begin{cases} \ \frac{1}{2} \exp\left(\frac{y-\mu}{\sigma}\right), \mbox{if } y < \mu \\ 1 - \frac{1}{2} \exp\left(-\frac{y-\mu}{\sigma}\right), \mbox{if } y \ge \mu \ \end{cases}$

+
Parameters
+ + + + +
yA scalar variate.
muThe location parameter.
sigmaThe scale parameter.
+
+
+
Returns
The cumulative density function.
+ +

Definition at line 40 of file double_exponential_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::double_exponential_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 26 of file double_exponential_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::double_exponential_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 31 of file double_exponential_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::double_exponential_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 130 of file double_exponential_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::double_exponential_rng (const double mu,
const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 23 of file double_exponential_rng.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::e ()
+
+inline
+
+ +

Return the base of the natural logarithm.

+
Returns
Base of natural logarithm.
+ +

Definition at line 95 of file constants.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::eigenvalues_sym (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+ +

Return the eigenvalues of the specified symmetric matrix in descending order of magnitude.

+

This function is more efficient than the general eigenvalues function for symmetric matrices.

+

See eigen_decompose() for more information.

Parameters
+ + +
mSpecified matrix.
+
+
+
Returns
Eigenvalues of matrix.
+ +

Definition at line 22 of file eigenvalues_sym.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::eigenvectors_sym (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+ +

Definition at line 13 of file eigenvectors_sym.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::elt_divide (const Eigen::Matrix< T1, R, C > & m1,
const Eigen::Matrix< T2, R, C > & m2 
)
+
+ +

Return the elementwise division of the specified matrices.

+
Template Parameters
+ + + + + +
T1Type of scalars in first matrix.
T2Type of scalars in second matrix.
RRow type of both matrices.
CColumn type of both matrices.
+
+
+
Parameters
+ + + +
m1First matrix
m2Second matrix
+
+
+
Returns
Elementwise division of matrices.
+ +

Definition at line 25 of file elt_divide.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::elt_divide (const Eigen::Matrix< T1, R, C > & m,
T2 s 
)
+
+ +

Return the elementwise division of the specified matrix by the specified scalar.

+
Template Parameters
+ + + + + +
T1Type of scalars in the matrix.
T2Type of the scalar.
RRow type of the matrix.
CColumn type of the matrix.
+
+
+
Parameters
+ + + +
mmatrix
sscalar
+
+
+
Returns
Elementwise division of a scalar by matrix.
+ +

Definition at line 51 of file elt_divide.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::elt_divide (T1 s,
const Eigen::Matrix< T2, R, C > & m 
)
+
+ +

Return the elementwise division of the specified scalar by the specified matrix.

+
Template Parameters
+ + + + + +
T1Type of the scalar.
T2Type of scalars in the matrix.
RRow type of the matrix.
CColumn type of the matrix.
+
+
+
Parameters
+ + + +
sscalar
mmatrix
+
+
+
Returns
Elementwise division of a scalar by matrix.
+ +

Definition at line 69 of file elt_divide.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::elt_multiply (const Eigen::Matrix< T1, R, C > & m1,
const Eigen::Matrix< T2, R, C > & m2 
)
+
+ +

Return the elementwise multiplication of the specified matrices.

+
Template Parameters
+ + + + + +
T1Type of scalars in first matrix.
T2Type of scalars in second matrix.
RRow type of both matrices.
CColumn type of both matrices.
+
+
+
Parameters
+ + + +
m1First matrix
m2Second matrix
+
+
+
Returns
Elementwise product of matrices.
+ +

Definition at line 25 of file elt_multiply.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static bool stan::math::empty_nested ()
+
+inlinestatic
+
+ +

Return true if there is no nested autodiff being executed.

+ +

Definition at line 12 of file empty_nested.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::erf (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file erf.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::erf (const vara)
+
+inline
+
+ +

The error function for variables (C99).

+

For non-variable function, see erf() from cmath.

+

The derivative is

+

$\frac{d}{dx} \mbox{erf}(x) = \frac{2}{\sqrt{\pi}} \exp(-x^2)$.

+

+\[ \mbox{erf}(x) = \begin{cases} \operatorname{erf}(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{erf}(x)}{\partial x} = \begin{cases} \frac{\partial\, \operatorname{erf}(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \operatorname{erf}(x)=\frac{2}{\sqrt{\pi}}\int_0^x e^{-t^2}dt \] +

+

+\[ \frac{\partial \, \operatorname{erf}(x)}{\partial x} = \frac{2}{\sqrt{\pi}} e^{-x^2} \] +

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
Error function applied to the variable.
+ +

Definition at line 68 of file erf.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::erfc (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file erfc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::erfc (const vara)
+
+inline
+
+ +

The complementary error function for variables (C99).

+

For non-variable function, see erfc() from <cmath>.

+

The derivative is

+

$\frac{d}{dx} \mbox{erfc}(x) = - \frac{2}{\sqrt{\pi}} \exp(-x^2)$.

+

+\[ \mbox{erfc}(x) = \begin{cases} \operatorname{erfc}(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{erfc}(x)}{\partial x} = \begin{cases} \frac{\partial\, \operatorname{erfc}(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \operatorname{erfc}(x)=\frac{2}{\sqrt{\pi}}\int_x^\infty e^{-t^2}dt \] +

+

+\[ \frac{\partial \, \operatorname{erfc}(x)}{\partial x} = -\frac{2}{\sqrt{\pi}} e^{-x^2} \] +

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
Complementary error function applied to the variable.
+ +

Definition at line 68 of file erfc.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::exp (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 10 of file exp.hpp.

+ +
+
+ +
+
+
+template<typename T , int Rows, int Cols>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Rows, Cols> stan::math::exp (const Eigen::Matrix< T, Rows, Cols > & m)
+
+inline
+
+ +

Return the element-wise exponentiation of the matrix or vector.

+
Parameters
+ + +
mThe matrix or vector.
+
+
+
Returns
ret(i, j) = exp(m(i, j))
+ +

Definition at line 19 of file exp.hpp.

+ +
+
+ +
+
+
+template<int Rows, int Cols>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<double, Rows, Cols> stan::math::exp (const Eigen::Matrix< double, Rows, Cols > & m)
+
+inline
+
+ +

Definition at line 28 of file exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::exp (const vara)
+
+inline
+
+ +

Return the exponentiation of the specified variable (cmath).

+

+\[ \mbox{exp}(x) = \begin{cases} e^x & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{exp}(x)}{\partial x} = \begin{cases} e^x & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable to exponentiate.
+
+
+
Returns
Exponentiated variable.
+ +

Definition at line 44 of file exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::exp2 (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file exp2.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::exp2 (const T y)
+
+inline
+
+ +

Return the exponent base 2 of the specified argument (C99).

+

The exponent base 2 function is defined by

+

exp2(y) = pow(2.0, y).

+
Parameters
+ + +
yValue.
+
+
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Returns
Exponent base 2 of value.
+ +

Definition at line 23 of file exp2.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::exp2 (const vara)
+
+inline
+
+ +

Exponentiation base 2 function for variables (C99).

+

For non-variable function, see boost::math::exp2().

+

The derivatie is

+

$\frac{d}{dx} 2^x = (\log 2) 2^x$.

+

+\[ \mbox{exp2}(x) = \begin{cases} 2^x & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{exp2}(x)}{\partial x} = \begin{cases} 2^x\ln2 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
Two to the power of the specified variable.
+ +

Definition at line 52 of file exp2.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_inv_scale>::type stan::math::exp_mod_normal_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_inv_scale & lambda 
)
+
+ +

Definition at line 26 of file exp_mod_normal_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_inv_scale>::type stan::math::exp_mod_normal_cdf (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_inv_scale & lambda 
)
+
+ +

Definition at line 26 of file exp_mod_normal_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_inv_scale>::type stan::math::exp_mod_normal_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_inv_scale & lambda 
)
+
+ +

Definition at line 26 of file exp_mod_normal_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_inv_scale>::type stan::math::exp_mod_normal_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_inv_scale & lambda 
)
+
+ +

Definition at line 27 of file exp_mod_normal_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_inv_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_inv_scale>::type stan::math::exp_mod_normal_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_inv_scale & lambda 
)
+
+inline
+
+ +

Definition at line 141 of file exp_mod_normal_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::exp_mod_normal_rng (const double mu,
const double sigma,
const double lambda,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 26 of file exp_mod_normal_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::expm1 (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 12 of file expm1.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::expm1 (const stan::math::vara)
+
+inline
+
+ +

The exponentiation of the specified variable minus 1 (C99).

+

The derivative is given by

+

$\frac{d}{dx} \exp(a) - 1 = \exp(a)$.

+

+\[ \mbox{expm1}(x) = \begin{cases} e^x-1 & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{expm1}(x)}{\partial x} = \begin{cases} e^x & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
Two to the power of the specified variable.
+ +

Definition at line 57 of file expm1.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_inv_scale>::type stan::math::exponential_ccdf_log (const T_y & y,
const T_inv_scale & beta 
)
+
+ +

Definition at line 27 of file exponential_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_inv_scale>::type stan::math::exponential_cdf (const T_y & y,
const T_inv_scale & beta 
)
+
+ +

Calculates the exponential cumulative distribution function for the given y and beta.

+

Inverse scale parameter must be greater than 0. y must be greater than or equal to 0.

+
Parameters
+ + + +
yA scalar variable.
betaInverse scale parameter.
+
+
+
Template Parameters
+ + + +
T_yType of scalar.
T_inv_scaleType of inverse scale.
+
+
+ +

Definition at line 40 of file exponential_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_inv_scale>::type stan::math::exponential_cdf_log (const T_y & y,
const T_inv_scale & beta 
)
+
+ +

Definition at line 28 of file exponential_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_inv_scale>::type stan::math::exponential_log (const T_y & y,
const T_inv_scale & beta 
)
+
+ +

The log of an exponential density for y with the specified inverse scale parameter.

+

Inverse scale parameter must be greater than 0. y must be greater than or equal to 0.

+

+\begin{eqnarray*} y &\sim& \mbox{\sf{Expon}}(\beta) \\ \log (p (y \, |\, \beta) ) &=& \log \left( \beta \exp^{-\beta y} \right) \\ &=& \log (\beta) - \beta y \\ & & \mathrm{where} \; y > 0 \end{eqnarray*} +

+
Parameters
+ + + +
yA scalar variable.
betaInverse scale parameter.
+
+
+
Exceptions
+ + + +
std::domain_errorif beta is not greater than 0.
std::domain_errorif y is not greater than or equal to 0.
+
+
+
Template Parameters
+ + + +
T_yType of scalar.
T_inv_scaleType of inverse scale.
+
+
+ +

Definition at line 54 of file exponential_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_inv_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_inv_scale>::type stan::math::exponential_log (const T_y & y,
const T_inv_scale & beta 
)
+
+inline
+
+ +

Definition at line 111 of file exponential_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::exponential_rng (const double beta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 24 of file exponential_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T stan::math::F32 (a,
b,
c,
d,
e,
z,
precision = 1e-6 
)
+
+ +

Definition at line 11 of file F32.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::fabs (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file fabs.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::fabs (const vara)
+
+inline
+
+ +

Return the absolute value of the variable (cmath).

+

Choosing an arbitrary value at the non-differentiable point 0,

+

$\frac{d}{dx}|x| = \mbox{sgn}(x)$.

+

where $\mbox{sgn}(x)$ is the signum function, taking values -1 if $x < 0$, 0 if $x == 0$, and 1 if $x == 1$.

+

The function abs() provides the same behavior, with abs() defined in stdlib.h and fabs() defined in cmath. The derivative is 0 if the input is 0.

+

Returns std::numeric_limits<double>::quiet_NaN() for NaN inputs.

+

+\[ \mbox{fabs}(x) = \begin{cases} |x| & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fabs}(x)}{\partial x} = \begin{cases} -1 & \mbox{if } x < 0 \\ 0 & \mbox{if } x = 0 \\ 1 & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aInput variable.
+
+
+
Returns
Absolute value of variable.
+ +

Definition at line 50 of file fabs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
bool stan::math::factor_cov_matrix (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & Sigma,
Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs,
Eigen::Array< T, Eigen::Dynamic, 1 > & sds 
)
+
+ +

This function is intended to make starting values, given a covariance matrix Sigma.

+

The transformations are hard coded as log for standard deviations and Fisher transformations (atanh()) of CPCs

+
Parameters
+ + + + +
[in]Sigmacovariance matrix
[out]CPCsfill this unbounded (does not resize)
[out]sdsfill this unbounded (does not resize)
+
+
+
Returns
false if any of the diagonals of Sigma are 0
+ +

Definition at line 27 of file factor_cov_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
void stan::math::factor_U (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & U,
Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs 
)
+
+ +

This function is intended to make starting values, given a unit upper-triangular matrix U such that U'DU is a correlation matrix.

+
Parameters
+ + + +
USigma matrix
CPCsfill this unbounded
+
+
+ +

Definition at line 29 of file factor_U.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::falling_factorial (const fvar< T > & x,
const fvar< T > & n 
)
+
+inline
+
+ +

Definition at line 15 of file falling_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::falling_factorial (const fvar< T > & x,
const double n 
)
+
+inline
+
+ +

Definition at line 30 of file falling_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::falling_factorial (const double x,
const fvar< T > & n 
)
+
+inline
+
+ +

Definition at line 43 of file falling_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::falling_factorial (const T1 x,
const T2 n 
)
+
+inline
+
+ +

+\[ \mbox{falling\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ (x)_n & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{falling\_factorial}(x, n)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \frac{\partial\, (x)_n}{\partial x} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{falling\_factorial}(x, n)}{\partial n} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \frac{\partial\, (x)_n}{\partial n} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+\[ (x)_n=\frac{\Gamma(x+1)}{\Gamma(x-n+1)} \] +

+

+\[ \frac{\partial \, (x)_n}{\partial x} = (x)_n\Psi(x+1) \] +

+

+\[ \frac{\partial \, (x)_n}{\partial n} = -(x)_n\Psi(n+1) \] +

+ +

Definition at line 54 of file falling_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::falling_factorial (const vara,
const double & b 
)
+
+inline
+
+ +

Definition at line 56 of file falling_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::falling_factorial (const vara,
const varb 
)
+
+inline
+
+ +

Definition at line 61 of file falling_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::falling_factorial (const double & a,
const varb 
)
+
+inline
+
+ +

Definition at line 66 of file falling_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fdim (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 11 of file fdim.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fdim (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 22 of file fdim.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::fdim (T1 a,
T2 b 
)
+
+inline
+
+ +

The positive difference function (C99).

+

The function is defined by

+

fdim(a, b) = (a > b) ? (a - b) : 0.0.

+
Parameters
+ + + +
aFirst value.
bSecond value.
+
+
+
Returns
Returns min(a - b, 0.0).
+ +

Definition at line 26 of file fdim.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fdim (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 32 of file fdim.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fdim (const stan::math::vara,
const stan::math::varb 
)
+
+inline
+
+ +

Return the positive difference between the first variable's the value and the second's (C99).

+

See stan::math::fdim() for the double-based version.

+

The partial derivative with respect to the first argument is

+

$\frac{\partial}{\partial x} \mbox{fdim}(x, y) = 0.0$ if $x < y$, and

+

$\frac{\partial}{\partial x} \mbox{fdim}(x, y) = 1.0$ if $x \geq y$.

+

With respect to the second argument, the partial is

+

$\frac{\partial}{\partial y} \mbox{fdim}(x, y) = 0.0$ if $x < y$, and

+

$\frac{\partial}{\partial y} \mbox{fdim}(x, y) = -\lfloor\frac{x}{y}\rfloor$ if $x \geq y$.

+

+\[ \mbox{fdim}(x, y) = \begin{cases} 0 & \mbox{if } x < y\\ x-y & \mbox{if } x \geq y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fdim}(x, y)}{\partial x} = \begin{cases} 0 & \mbox{if } x < y \\ 1 & \mbox{if } x \geq y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fdim}(x, y)}{\partial y} = \begin{cases} 0 & \mbox{if } x < y \\ -\lfloor\frac{x}{y}\rfloor & \mbox{if } x \geq y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
The positive difference between the first and second variable.
+ +

Definition at line 110 of file fdim.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fdim (const double & a,
const stan::math::varb 
)
+
+inline
+
+ +

Return the positive difference between the first value and the value of the second variable (C99).

+

See fdim(var, var) for definitions of values and derivatives.

+

The derivative with respect to the variable is

+

$\frac{d}{d y} \mbox{fdim}(c, y) = 0.0$ if $c < y$, and

+

$\frac{d}{d y} \mbox{fdim}(c, y) = -\lfloor\frac{c}{y}\rfloor$ if $c \geq y$.

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
The positive difference between the first and second arguments.
+ +

Definition at line 135 of file fdim.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fdim (const stan::math::vara,
const double & b 
)
+
+inline
+
+ +

Return the positive difference between the first variable's value and the second value (C99).

+

See fdim(var, var) for definitions of values and derivatives.

+

The derivative with respect to the variable is

+

$\frac{d}{d x} \mbox{fdim}(x, c) = 0.0$ if $x < c$, and

+

$\frac{d}{d x} \mbox{fdim}(x, c) = 1.0$ if $x \geq yc$.

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
The positive difference between the first and second arguments.
+ +

Definition at line 158 of file fdim.hpp.

+ +
+
+ +
+
+
+template<typename T , typename S >
+ + + + + + + + + + + + + + + + + + +
void stan::math::fill (T & x,
const S & y 
)
+
+ +

Fill the specified container with the specified value.

+

This base case simply assigns the value to the container.

+
Template Parameters
+ + + +
TType of reference container.
SType of value.
+
+
+
Parameters
+ + + +
xContainer.
yValue.
+
+
+ +

Definition at line 18 of file fill.hpp.

+ +
+
+ +
+
+
+template<typename T , typename S >
+ + + + + + + + + + + + + + + + + + +
void stan::math::fill (std::vector< T > & x,
const S & y 
)
+
+ +

Fill the specified container with the specified value.

+

Each container in the specified standard vector is filled recursively by calling fill.

+
Template Parameters
+ + + +
TType of container in vector.
SType of value.
+
+
+
Parameters
+ + + +
xContainer.
yValue.
+
+
+ +

Definition at line 22 of file fill.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C, typename S >
+ + + + + + + + + + + + + + + + + + +
void stan::math::fill (Eigen::Matrix< T, R, C > & x,
const S & y 
)
+
+ +

Fill the specified container with the specified value.

+

The specified matrix is filled by element.

+
Template Parameters
+ + + + + +
TType of scalar for matrix container.
RRow type of matrix.
CColumn type of matrix.
SType of value.
+
+
+
Parameters
+ + + +
xContainer.
yValue.
+
+
+ +

Definition at line 22 of file fill.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::finite_diff_grad_hessian (const F & f,
const Eigen::Matrix< double,-1, 1 > & x,
double & fx,
Eigen::Matrix< double,-1,-1 > & hess,
std::vector< Eigen::Matrix< double,-1,-1 > > & grad_hess_fx,
const double epsilon = 1e-04 
)
+
+ +

Calculate the value and the gradient of the hessian of the specified function at the specified argument using second-order autodiff and first-order finite difference.

+

The functor must implement

+

double operator()(const Eigen::Matrix<double, Eigen::Dynamic, 1>&)

+

Reference:

+

De Levie: An improved numerical approximation for the first derivative, page 3

+

4 calls to the function, f.

+
Template Parameters
+ + +
FType of function
+
+
+
Parameters
+ + + + + + + +
[in]fFunction
[in]xArgument to function
[out]fxFunction applied to argument
[out]hessHessian matrix
[out]grad_hess_fxgradient of Hessian of function at argument
[in]epsilonperturbation size
+
+
+ +

Definition at line 43 of file finite_diff_grad_hessian.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::finite_diff_gradient (const F & f,
const Eigen::Matrix< double,-1, 1 > & x,
double & fx,
Eigen::Matrix< double,-1, 1 > & grad_fx,
const double epsilon = 1e-03 
)
+
+ +

Calculate the value and the gradient of the specified function at the specified argument using finite difference.

+

The functor must implement

+

double operator()(const Eigen::Matrix<double, Eigen::Dynamic, 1>&)

+

Error should be on order of epsilon ^ 6. The reference for this algorithm is:

+

De Levie: An improved numerical approximation for the first derivative, page 3

+

This function involves 6 calls to f.

+
Template Parameters
+ + +
FType of function
+
+
+
Parameters
+ + + + + + +
[in]fFunction
[in]xArgument to function
[out]fxFunction applied to argument
[out]grad_fxGradient of function at argument
[in]epsilonperturbation size
+
+
+ +

Definition at line 39 of file finite_diff_gradient.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::finite_diff_hess_helper (const F & f,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & x,
const int lambda,
const double epsilon = 1e-03 
)
+
+ +

Definition at line 13 of file finite_diff_hessian.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::finite_diff_hessian (const F & f,
const Eigen::Matrix< double,-1, 1 > & x,
double & fx,
Eigen::Matrix< double,-1, 1 > & grad_fx,
Eigen::Matrix< double,-1,-1 > & hess_fx,
const double epsilon = 1e-03 
)
+
+ +

Calculate the value and the Hessian of the specified function at the specified argument using second-order finite difference.

+

The functor must implement

+

double operator()(const Eigen::Matrix<double, Eigen::Dynamic, 1>&)

+

Error should be on order of epsilon ^ 4, with 4 calls to the function f.

+

Reference: Eberly: Derivative Approximation by Finite Differences Page 6

+
Template Parameters
+ + +
FType of function
+
+
+
Parameters
+ + + + + + + +
[in]fFunction
[in]xArgument to function
[out]fxFunction applied to argument
[out]grad_fxGradient of function at argument
[out]hess_fxHessian of function at argument
[in]epsilonperturbation size
+
+
+ +

Definition at line 67 of file finite_diff_hessian.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::floor (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 11 of file floor.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::floor (const vara)
+
+inline
+
+ +

Return the floor of the specified variable (cmath).

+

The derivative of the floor function is defined and zero everywhere but at integers, so we set these derivatives to zero for convenience,

+

$\frac{d}{dx} {\lfloor x \rfloor} = 0$.

+

The floor function rounds down. For double values, this is the largest integral value that is not greater than the specified value. Although this function is not differentiable because it is discontinuous at integral values, its gradient is returned as zero everywhere.

+

+\[ \mbox{floor}(x) = \begin{cases} \lfloor x \rfloor & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{floor}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aInput variable.
+
+
+
Returns
Floor of the variable.
+ +

Definition at line 60 of file floor.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<typename stan::return_type<T1, T2, T3>::type> stan::math::fma (const fvar< T1 > & x1,
const fvar< T2 > & x2,
const fvar< T3 > & x3 
)
+
+inline
+
+ +

The fused multiply-add operation (C99).

+

This double-based operation delegates to fma.

+

The function is defined by

+

fma(a, b, c) = (a * b) + c.

+

+\[ \mbox{fma}(x, y, z) = \begin{cases} x\cdot y+z & \mbox{if } -\infty\leq x, y, z \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fma}(x, y, z)}{\partial x} = \begin{cases} y & \mbox{if } -\infty\leq x, y, z \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fma}(x, y, z)}{\partial y} = \begin{cases} x & \mbox{if } -\infty\leq x, y, z \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fma}(x, y, z)}{\partial z} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y, z \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + + +
x1First value.
x2Second value.
x3Third value.
+
+
+
Returns
Product of the first two values plus the third.
+ +

Definition at line 61 of file fma.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<typename stan::return_type<T1, T2, T3>::type> stan::math::fma (const T1 & x1,
const fvar< T2 > & x2,
const fvar< T3 > & x3 
)
+
+inline
+
+ +

See all-var input signature for details on the function and derivatives.

+ +

Definition at line 74 of file fma.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<typename stan::return_type<T1, T2, T3>::type> stan::math::fma (const fvar< T1 > & x1,
const T2 & x2,
const fvar< T3 > & x3 
)
+
+inline
+
+ +

See all-var input signature for details on the function and derivatives.

+ +

Definition at line 86 of file fma.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<typename stan::return_type<T1, T2, T3>::type> stan::math::fma (const fvar< T1 > & x1,
const fvar< T2 > & x2,
const T3 & x3 
)
+
+inline
+
+ +

See all-var input signature for details on the function and derivatives.

+ +

Definition at line 98 of file fma.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<typename stan::return_type<T1, T2, T3>::type> stan::math::fma (const T1 & x1,
const T2 & x2,
const fvar< T3 > & x3 
)
+
+inline
+
+ +

See all-var input signature for details on the function and derivatives.

+ +

Definition at line 110 of file fma.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<typename stan::return_type<T1, T2, T3>::type> stan::math::fma (const fvar< T1 > & x1,
const T2 & x2,
const T3 & x3 
)
+
+inline
+
+ +

See all-var input signature for details on the function and derivatives.

+ +

Definition at line 122 of file fma.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<typename stan::return_type<T1, T2, T3>::type> stan::math::fma (const T1 & x1,
const fvar< T2 > & x2,
const T3 & x3 
)
+
+inline
+
+ +

See all-var input signature for details on the function and derivatives.

+ +

Definition at line 134 of file fma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::fma (const stan::math::vara,
const stan::math::varb,
const stan::math::varc 
)
+
+inline
+
+ +

The fused multiply-add function for three variables (C99).

+

This function returns the product of the first two arguments plus the third argument.

+

The double-based version ::fma(double, double, double) is defined in <cmath>.

+

The partial derivatives are

+

$\frac{\partial}{\partial x} (x * y) + z = y$, and

+

$\frac{\partial}{\partial y} (x * y) + z = x$, and

+

$\frac{\partial}{\partial z} (x * y) + z = 1$.

+
Parameters
+ + + + +
aFirst multiplicand.
bSecond multiplicand.
cSummand.
+
+
+
Returns
Product of the multiplicands plus the summand, ($a * $b) + $c.
+ +

Definition at line 136 of file fma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::fma (const stan::math::vara,
const stan::math::varb,
const double & c 
)
+
+inline
+
+ +

The fused multiply-add function for two variables and a value (C99).

+

This function returns the product of the first two arguments plus the third argument.

+

The double-based version ::fma(double, double, double) is defined in <cmath>.

+

The partial derivatives are

+

$\frac{\partial}{\partial x} (x * y) + c = y$, and

+

$\frac{\partial}{\partial y} (x * y) + c = x$.

+
Parameters
+ + + + +
aFirst multiplicand.
bSecond multiplicand.
cSummand.
+
+
+
Returns
Product of the multiplicands plus the summand, ($a * $b) + $c.
+ +

Definition at line 161 of file fma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::fma (const stan::math::vara,
const double & b,
const stan::math::varc 
)
+
+inline
+
+ +

The fused multiply-add function for a variable, value, and variable (C99).

+

This function returns the product of the first two arguments plus the third argument.

+

The double-based version ::fma(double, double, double) is defined in <cmath>.

+

The partial derivatives are

+

$\frac{\partial}{\partial x} (x * c) + z = c$, and

+

$\frac{\partial}{\partial z} (x * c) + z = 1$.

+
Parameters
+ + + + +
aFirst multiplicand.
bSecond multiplicand.
cSummand.
+
+
+
Returns
Product of the multiplicands plus the summand, ($a * $b) + $c.
+ +

Definition at line 186 of file fma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::fma (const stan::math::vara,
const double & b,
const double & c 
)
+
+inline
+
+ +

The fused multiply-add function for a variable and two values (C99).

+

This function returns the product of the first two arguments plus the third argument.

+

The double-based version ::fma(double, double, double) is defined in <cmath>.

+

The derivative is

+

$\frac{d}{d x} (x * c) + d = c$.

+
Parameters
+ + + + +
aFirst multiplicand.
bSecond multiplicand.
cSummand.
+
+
+
Returns
Product of the multiplicands plus the summand, ($a * $b) + $c.
+ +

Definition at line 209 of file fma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::fma (const double & a,
const stan::math::varb,
const double & c 
)
+
+inline
+
+ +

The fused multiply-add function for a value, variable, and value (C99).

+

This function returns the product of the first two arguments plus the third argument.

+

The double-based version ::fma(double, double, double) is defined in <cmath>.

+

The derivative is

+

$\frac{d}{d y} (c * y) + d = c$, and

+
Parameters
+ + + + +
aFirst multiplicand.
bSecond multiplicand.
cSummand.
+
+
+
Returns
Product of the multiplicands plus the summand, ($a * $b) + $c.
+ +

Definition at line 232 of file fma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::fma (const double & a,
const double & b,
const stan::math::varc 
)
+
+inline
+
+ +

The fused multiply-add function for two values and a variable, and value (C99).

+

This function returns the product of the first two arguments plus the third argument.

+

The double-based version ::fma(double, double, double) is defined in <cmath>.

+

The derivative is

+

$\frac{\partial}{\partial z} (c * d) + z = 1$.

+
Parameters
+ + + + +
aFirst multiplicand.
bSecond multiplicand.
cSummand.
+
+
+
Returns
Product of the multiplicands plus the summand, ($a * $b) + $c.
+ +

Definition at line 255 of file fma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::fma (const double & a,
const stan::math::varb,
const stan::math::varc 
)
+
+inline
+
+ +

The fused multiply-add function for a value and two variables (C99).

+

This function returns the product of the first two arguments plus the third argument.

+

The double-based version ::fma(double, double, double) is defined in <cmath>.

+

The partial derivaties are

+

$\frac{\partial}{\partial y} (c * y) + z = c$, and

+

$\frac{\partial}{\partial z} (c * y) + z = 1$.

+
Parameters
+ + + + +
aFirst multiplicand.
bSecond multiplicand.
cSummand.
+
+
+
Returns
Product of the multiplicands plus the summand, ($a * $b) + $c.
+ +

Definition at line 280 of file fma.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmax (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 13 of file fmax.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmax (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 33 of file fmax.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmax (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 53 of file fmax.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmax (const stan::math::vara,
const stan::math::varb 
)
+
+inline
+
+ +

Returns the maximum of the two variable arguments (C99).

+

No new variable implementations are created, with this function defined as if by

+

fmax(a, b) = a if a's value is greater than b's, and .

+

fmax(a, b) = b if b's value is greater than or equal to a's.

+

+\[ \mbox{fmax}(x, y) = \begin{cases} x & \mbox{if } x \geq y \\ y & \mbox{if } x < y \\[6pt] x & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ y & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fmax}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } x \geq y \\ 0 & \mbox{if } x < y \\[6pt] 1 & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ 0 & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fmax}(x, y)}{\partial y} = \begin{cases} 0 & \mbox{if } x \geq y \\ 1 & \mbox{if } x < y \\[6pt] 0 & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ 1 & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
If the first variable's value is larger than the second's, the first variable, otherwise the second variable.
+ +

Definition at line 63 of file fmax.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmax (const stan::math::vara,
const double & b 
)
+
+inline
+
+ +

Returns the maximum of the variable and scalar, promoting the scalar to a variable if it is larger (C99).

+

For fmax(a, b), if a's value is greater than b, then a is returned, otherwise a fesh variable implementation wrapping the value b is returned.

+
Parameters
+ + + +
aFirst variable.
bSecond value
+
+
+
Returns
If the first variable's value is larger than or equal to the second value, the first variable, otherwise the second value promoted to a fresh variable.
+ +

Definition at line 95 of file fmax.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmax (const double & a,
const stan::math::varb 
)
+
+inline
+
+ +

Returns the maximum of a scalar and variable, promoting the scalar to a variable if it is larger (C99).

+

For fmax(a, b), if a is greater than b's value, then a fresh variable implementation wrapping a is returned, otherwise b is returned.

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
If the first value is larger than the second variable's value, return the first value promoted to a variable, otherwise return the second variable.
+ +

Definition at line 127 of file fmax.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmin (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 13 of file fmin.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmin (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 33 of file fmin.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmin (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 53 of file fmin.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmin (const stan::math::vara,
const stan::math::varb 
)
+
+inline
+
+ +

Returns the minimum of the two variable arguments (C99).

+

For fmin(a, b), if a's value is less than b's, then a is returned, otherwise b is returned.

+

+\[ \mbox{fmin}(x, y) = \begin{cases} x & \mbox{if } x \leq y \\ y & \mbox{if } x > y \\[6pt] x & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ y & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fmin}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } x \leq y \\ 0 & \mbox{if } x > y \\[6pt] 1 & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ 0 & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fmin}(x, y)}{\partial y} = \begin{cases} 0 & \mbox{if } x \leq y \\ 1 & \mbox{if } x > y \\[6pt] 0 & \mbox{if } -\infty\leq x\leq \infty, y = \textrm{NaN}\\ 1 & \mbox{if } -\infty\leq y\leq \infty, x = \textrm{NaN}\\ \textrm{NaN} & \mbox{if } x, y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
If the first variable's value is smaller than the second's, the first variable, otherwise the second variable.
+ +

Definition at line 59 of file fmin.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmin (const stan::math::vara,
double b 
)
+
+inline
+
+ +

Returns the minimum of the variable and scalar, promoting the scalar to a variable if it is larger (C99).

+

For fmin(a, b), if a's value is less than or equal to b, then a is returned, otherwise a fresh variable wrapping b is returned.

+
Parameters
+ + + +
aFirst variable.
bSecond value
+
+
+
Returns
If the first variable's value is less than or equal to the second value, the first variable, otherwise the second value promoted to a fresh variable.
+ +

Definition at line 89 of file fmin.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmin (double a,
const stan::math::varb 
)
+
+inline
+
+ +

Returns the minimum of a scalar and variable, promoting the scalar to a variable if it is larger (C99).

+

For fmin(a, b), if a is less than b's value, then a fresh variable implementation wrapping a is returned, otherwise b is returned.

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
If the first value is smaller than the second variable's value, return the first value promoted to a variable, otherwise return the second variable.
+ +

Definition at line 120 of file fmin.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmod (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 16 of file fmod.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmod (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 26 of file fmod.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::fmod (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 39 of file fmod.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmod (const vara,
const varb 
)
+
+inline
+
+ +

Return the floating point remainder after dividing the first variable by the second (cmath).

+

The partial derivatives with respect to the variables are defined everywhere but where $x = y$, but we set these to match other values, with

+

$\frac{\partial}{\partial x} \mbox{fmod}(x, y) = 1$, and

+

$\frac{\partial}{\partial y} \mbox{fmod}(x, y) = -\lfloor \frac{x}{y} \rfloor$.

+

+\[ \mbox{fmod}(x, y) = \begin{cases} x - \lfloor \frac{x}{y}\rfloor y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fmod}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{fmod}(x, y)}{\partial y} = \begin{cases} -\lfloor \frac{x}{y}\rfloor & \mbox{if } -\infty\leq x, y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
Floating pointer remainder of dividing the first variable by the second.
+ +

Definition at line 103 of file fmod.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmod (const vara,
const double b 
)
+
+inline
+
+ +

Return the floating point remainder after dividing the the first variable by the second scalar (cmath).

+

The derivative with respect to the variable is

+

$\frac{d}{d x} \mbox{fmod}(x, c) = \frac{1}{c}$.

+
Parameters
+ + + +
aFirst variable.
bSecond scalar.
+
+
+
Returns
Floating pointer remainder of dividing the first variable by the second scalar.
+ +

Definition at line 120 of file fmod.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::fmod (const double a,
const varb 
)
+
+inline
+
+ +

Return the floating point remainder after dividing the first scalar by the second variable (cmath).

+

The derivative with respect to the variable is

+

$\frac{d}{d y} \mbox{fmod}(c, y) = -\lfloor \frac{c}{y} \rfloor$.

+
Parameters
+ + + +
aFirst scalar.
bSecond variable.
+
+
+
Returns
Floating pointer remainder of dividing first scalar by the second variable.
+ +

Definition at line 137 of file fmod.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::frechet_ccdf_log (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+ +

Definition at line 31 of file frechet_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::frechet_cdf (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+ +

Definition at line 31 of file frechet_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::frechet_cdf_log (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+ +

Definition at line 31 of file frechet_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::frechet_log (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+ +

Definition at line 34 of file frechet_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::frechet_log (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+inline
+
+ +

Definition at line 140 of file frechet_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::frechet_rng (const double alpha,
const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 27 of file frechet_rng.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::free_cvodes_memory (N_Vector & cvodes_state,
N_Vector * cvodes_state_sens,
void * cvodes_mem,
size_t S 
)
+
+inline
+
+ +

Free memory allocated for CVODES state, sensitivity, and general memory.

+
Parameters
+ + + + + +
[in]cvodes_stateState vector.
[in]cvodes_state_sensSensivity vector.
[in]cvodes_memMemory held for CVODES.
[in]SNumber of sensitivities being calculated.
+
+
+ +

Definition at line 34 of file integrate_ode_bdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_inv_scale>::type stan::math::gamma_ccdf_log (const T_y & y,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+ +

Definition at line 35 of file gamma_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_inv_scale>::type stan::math::gamma_cdf (const T_y & y,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+ +

The cumulative density function for a gamma distribution for y with the specified shape and inverse scale parameters.

+
Parameters
+ + + + +
yA scalar variable.
alphaShape parameter.
betaInverse scale parameter.
+
+
+
Exceptions
+ + + + +
std::domain_errorif alpha is not greater than 0.
std::domain_errorif beta is not greater than 0.
std::domain_errorif y is not greater than or equal to 0.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_shapeType of shape.
T_inv_scaleType of inverse scale.
+
+
+ +

Definition at line 49 of file gamma_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_inv_scale>::type stan::math::gamma_cdf_log (const T_y & y,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+ +

Definition at line 35 of file gamma_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_shape , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_inv_scale>::type stan::math::gamma_log (const T_y & y,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+ +

The log of a gamma density for y with the specified shape and inverse scale parameters.

+

Shape and inverse scale parameters must be greater than 0. y must be greater than or equal to 0.

+

+\begin{eqnarray*} y &\sim& \mbox{\sf{Gamma}}(\alpha, \beta) \\ \log (p (y \, |\, \alpha, \beta) ) &=& \log \left( \frac{\beta^\alpha}{\Gamma(\alpha)} y^{\alpha - 1} \exp^{- \beta y} \right) \\ &=& \alpha \log(\beta) - \log(\Gamma(\alpha)) + (\alpha - 1) \log(y) - \beta y\\ & & \mathrm{where} \; y > 0 \end{eqnarray*} +

+
Parameters
+ + + + +
yA scalar variable.
alphaShape parameter.
betaInverse scale parameter.
+
+
+
Exceptions
+ + + + +
std::domain_errorif alpha is not greater than 0.
std::domain_errorif beta is not greater than 0.
std::domain_errorif y is not greater than or equal to 0.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_shapeType of shape.
T_inv_scaleType of inverse scale.
+
+
+ +

Definition at line 54 of file gamma_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_inv_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_inv_scale>::type stan::math::gamma_log (const T_y & y,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+inline
+
+ +

Definition at line 166 of file gamma_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::gamma_p (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 15 of file gamma_p.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::gamma_p (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 51 of file gamma_p.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + +
double stan::math::gamma_p (double x,
double a 
)
+
+ +

+\[ \mbox{gamma\_p}(a, z) = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ P(a, z) & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{gamma\_p}(a, z)}{\partial a} = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ \frac{\partial\, P(a, z)}{\partial a} & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{gamma\_p}(a, z)}{\partial z} = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ \frac{\partial\, P(a, z)}{\partial z} & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

+

+\[ P(a, z)=\frac{1}{\Gamma(a)}\int_0^zt^{a-1}e^{-t}dt \] +

+

+\[ \frac{\partial \, P(a, z)}{\partial a} = -\frac{\Psi(a)}{\Gamma^2(a)}\int_0^zt^{a-1}e^{-t}dt + \frac{1}{\Gamma(a)}\int_0^z (a-1)t^{a-2}e^{-t}dt \] +

+

+\[ \frac{\partial \, P(a, z)}{\partial z} = \frac{z^{a-1}e^{-z}}{\Gamma(a)} \] +

+ +

Definition at line 53 of file gamma_p.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::gamma_p (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 86 of file gamma_p.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::gamma_p (const stan::math::vara,
const stan::math::varb 
)
+
+inline
+
+ +

Definition at line 104 of file gamma_p.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::gamma_p (const stan::math::vara,
const double & b 
)
+
+inline
+
+ +

Definition at line 109 of file gamma_p.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::gamma_p (const double & a,
const stan::math::varb 
)
+
+inline
+
+ +

Definition at line 114 of file gamma_p.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::gamma_q (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 15 of file gamma_q.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::gamma_q (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 51 of file gamma_q.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + +
double stan::math::gamma_q (double x,
double a 
)
+
+ +

+\[ \mbox{gamma\_q}(a, z) = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ Q(a, z) & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{gamma\_q}(a, z)}{\partial a} = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ \frac{\partial\, Q(a, z)}{\partial a} & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{gamma\_q}(a, z)}{\partial z} = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ \frac{\partial\, Q(a, z)}{\partial z} & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

+

+\[ Q(a, z)=\frac{1}{\Gamma(a)}\int_z^\infty t^{a-1}e^{-t}dt \] +

+

+\[ \frac{\partial \, Q(a, z)}{\partial a} = -\frac{\Psi(a)}{\Gamma^2(a)}\int_z^\infty t^{a-1}e^{-t}dt + \frac{1}{\Gamma(a)}\int_z^\infty (a-1)t^{a-2}e^{-t}dt \] +

+

+\[ \frac{\partial \, Q(a, z)}{\partial z} = -\frac{z^{a-1}e^{-z}}{\Gamma(a)} \] +

+ +

Definition at line 53 of file gamma_q.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::gamma_q (const stan::math::vara,
const stan::math::varb 
)
+
+inline
+
+ +

Definition at line 58 of file gamma_q.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::gamma_q (const stan::math::vara,
const double & b 
)
+
+inline
+
+ +

Definition at line 63 of file gamma_q.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::gamma_q (const double & a,
const stan::math::varb 
)
+
+inline
+
+ +

Definition at line 68 of file gamma_q.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::gamma_q (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 86 of file gamma_q.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::gamma_rng (const double alpha,
const double beta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 30 of file gamma_rng.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type< T_y, typename return_type<T_F, T_G, T_V, T_W, T_m0, T_C0>::type >::type stan::math::gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > & F,
const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > & G,
const Eigen::Matrix< T_V, Eigen::Dynamic, Eigen::Dynamic > & V,
const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > & W,
const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > & m0,
const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > & C0 
)
+
+ +

The log of a Gaussian dynamic linear model (GDLM).

+

This distribution is equivalent to, for $t = 1:T$,

+\begin{eqnarray*} y_t & \sim N(F' \theta_t, V) \\ \theta_t & \sim N(G \theta_{t-1}, W) \\ \theta_0 & \sim N(m_0, C_0) \end{eqnarray*} +

+

If V is a vector, then the Kalman filter is applied sequentially.

+
Parameters
+ + + + + + + + +
yA r x T matrix of observations. Rows are variables, columns are observations.
FA n x r matrix. The design matrix.
GA n x n matrix. The transition matrix.
VA r x r matrix. The observation covariance matrix.
WA n x n matrix. The state covariance matrix.
m0A n x 1 matrix. The mean vector of the distribution of the initial state.
C0A n x n matrix. The covariance matrix of the distribution of the initial state.
+
+
+
Returns
The log of the joint density of the GDLM.
+
Exceptions
+ + +
std::domain_errorif a matrix in the Kalman filter is not positive semi-definite.
+
+
+
Template Parameters
+ + + + + + + + +
T_yType of scalar.
T_FType of design matrix.
T_GType of transition matrix.
T_VType of observation covariance matrix.
T_WType of state covariance matrix.
T_m0Type of initial state mean vector.
T_C0Type of initial state covariance matrix.
+
+
+ +

Definition at line 79 of file gaussian_dlm_obs_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type< T_y, typename return_type<T_F, T_G, T_V, T_W, T_m0, T_C0>::type >::type stan::math::gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > & F,
const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > & G,
const Eigen::Matrix< T_V, Eigen::Dynamic, Eigen::Dynamic > & V,
const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > & W,
const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > & m0,
const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > & C0 
)
+
+inline
+
+ +

Definition at line 225 of file gaussian_dlm_obs_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type< T_y, typename return_type<T_F, T_G, T_V, T_W, T_m0, T_C0>::type >::type stan::math::gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > & F,
const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > & G,
const Eigen::Matrix< T_V, Eigen::Dynamic, 1 > & V,
const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > & W,
const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > & m0,
const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > & C0 
)
+
+ +

The log of a Gaussian dynamic linear model (GDLM) with uncorrelated observation disturbances.

+

This distribution is equivalent to, for $t = 1:T$,

+\begin{eqnarray*} y_t & \sim N(F' \theta_t, diag(V)) \\ \theta_t & \sim N(G \theta_{t-1}, W) \\ \theta_0 & \sim N(m_0, C_0) \end{eqnarray*} +

+

If V is a vector, then the Kalman filter is applied sequentially.

+
Parameters
+ + + + + + + + +
yA r x T matrix of observations. Rows are variables, columns are observations.
FA n x r matrix. The design matrix.
GA n x n matrix. The transition matrix.
VA size r vector. The diagonal of the observation covariance matrix.
WA n x n matrix. The state covariance matrix.
m0A n x 1 matrix. The mean vector of the distribution of the initial state.
C0A n x n matrix. The covariance matrix of the distribution of the initial state.
+
+
+
Returns
The log of the joint density of the GDLM.
+
Exceptions
+ + +
std::domain_errorif a matrix in the Kalman filter is not semi-positive definite.
+
+
+
Template Parameters
+ + + + + + + + +
T_yType of scalar.
T_FType of design matrix.
T_GType of transition matrix.
T_VType of observation variances
T_WType of state covariance matrix.
T_m0Type of initial state mean vector.
T_C0Type of initial state covariance matrix.
+
+
+ +

Definition at line 285 of file gaussian_dlm_obs_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_F , typename T_G , typename T_V , typename T_W , typename T_m0 , typename T_C0 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, typename return_type<T_F, T_G, T_V, T_W, T_m0, T_C0>::type>::type stan::math::gaussian_dlm_obs_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_F, Eigen::Dynamic, Eigen::Dynamic > & F,
const Eigen::Matrix< T_G, Eigen::Dynamic, Eigen::Dynamic > & G,
const Eigen::Matrix< T_V, Eigen::Dynamic, 1 > & V,
const Eigen::Matrix< T_W, Eigen::Dynamic, Eigen::Dynamic > & W,
const Eigen::Matrix< T_m0, Eigen::Dynamic, 1 > & m0,
const Eigen::Matrix< T_C0, Eigen::Dynamic, Eigen::Dynamic > & C0 
)
+
+inline
+
+ +

Definition at line 442 of file gaussian_dlm_obs_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const std::vector< T > & x,
size_t i,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one index.

+

If the index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + +
xVector from which to get a value.
iIndex into vector plus 1.
error_msgError message if the index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at i - 1
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 27 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const std::vector< std::vector< T > > & x,
size_t i1,
size_t i2,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 53 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const std::vector< std::vector< std::vector< T > > > & x,
size_t i1,
size_t i2,
size_t i3,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 81 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< T > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 111 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
size_t i5,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
i5Fifth index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 143 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
size_t i5,
size_t i6,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
i5Fifth index plus 1.
i6Sixth index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 178 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
size_t i5,
size_t i6,
size_t i7,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
i5Fifth index plus 1.
i6Sixth index plus 1.
i7Seventh index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 216 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
size_t i5,
size_t i6,
size_t i7,
size_t i8,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
i5Fifth index plus 1.
i6Sixth index plus 1.
i7Seventh index plus 1.
i8Eigth index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 256 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & x,
size_t m,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a copy of the row of the specified vector at the specified base-one row index.

+

If the index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+

Warning: Because a copy is involved, it is inefficient to access element of matrices by first using this method to get a row then using a second call to get the value at a specified column.

+
Parameters
+ + + + + +
xMatrix from which to get a row
mIndex into matrix plus 1.
error_msgError message if the index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Row of matrix at i - 1.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 297 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & x,
size_t m,
size_t n,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified matrix at the specified base-one row and column indexes.

+

If either index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + +
xMatrix from which to get a row
mRow index plus 1.
nColumn index plus 1.
error_msgError message if either index is out of range.
idxNested index level to report in error message if either index is out of range.
+
+
+
Returns
Value of matrix at row m - 1 and column n - 1.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 324 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
size_t m,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified column vector at the specified base-one index.

+

If the index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + +
xColumn vector from which to get a value.
mRow index plus 1.
error_msgError message if the index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of column vector at row m - 1.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 351 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
const T& stan::math::get_base1 (const Eigen::Matrix< T, 1, Eigen::Dynamic > & x,
size_t n,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified row vector at the specified base-one index.

+

If the index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + +
xRow vector from which to get a value.
nColumn index plus 1.
error_msgError message if the index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of row vector at column n - 1.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 376 of file get_base1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (std::vector< T > & x,
size_t i,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one index.

+

If the index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + +
xVector from which to get a value.
iIndex into vector plus 1.
error_msgError message if the index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at i - 1
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 27 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (std::vector< std::vector< T > > & x,
size_t i1,
size_t i2,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 53 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (std::vector< std::vector< std::vector< T > > > & x,
size_t i1,
size_t i2,
size_t i3,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 81 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< T > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 111 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
size_t i5,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
i5Fifth index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 144 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
size_t i5,
size_t i6,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
i5Fifth index plus 1.
i6Sixth index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 179 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
size_t i5,
size_t i6,
size_t i7,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
i5Fifth index plus 1.
i6Sixth index plus 1.
i7Seventh index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 217 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< std::vector< T > > > > > > > > & x,
size_t i1,
size_t i2,
size_t i3,
size_t i4,
size_t i5,
size_t i6,
size_t i7,
size_t i8,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified vector at the specified base-one indexes.

+

If an index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + + + + + + + +
xVector from which to get a value.
i1First index plus 1.
i2Second index plus 1.
i3Third index plus 1.
i4Fourth index plus 1.
i5Fifth index plus 1.
i6Sixth index plus 1.
i7Seventh index plus 1.
i8Eigth index plus 1.
error_msgError message if an index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of vector at indexes.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 258 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Block<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> > stan::math::get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & x,
size_t m,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a copy of the row of the specified vector at the specified base-one row index.

+

If the index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+

Warning: Because a copy is involved, it is inefficient to access element of matrices by first using this method to get a row then using a second call to get the value at a specified column.

+
Parameters
+ + + + + +
xMatrix from which to get a row
mIndex into matrix plus 1.
error_msgError message if the index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Row of matrix at i - 1.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 301 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & x,
size_t m,
size_t n,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified matrix at the specified base-one row and column indexes.

+

If either index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + + +
xMatrix from which to get a row
mRow index plus 1.
nColumn index plus 1.
error_msgError message if either index is out of range.
idxNested index level to report in error message if either index is out of range.
+
+
+
Returns
Value of matrix at row m - 1 and column n - 1.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 328 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
size_t m,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified column vector at the specified base-one index.

+

If the index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + +
xColumn vector from which to get a value.
mRow index plus 1.
error_msgError message if the index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of column vector at row m - 1.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 355 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T& stan::math::get_base1_lhs (Eigen::Matrix< T, 1, Eigen::Dynamic > & x,
size_t n,
const char * error_msg,
size_t idx 
)
+
+inline
+
+ +

Return a reference to the value of the specified row vector at the specified base-one index.

+

If the index is out of range, throw a std::out_of_range exception with the specified error message and index indicated.

+
Parameters
+ + + + + +
xRow vector from which to get a value.
nColumn index plus 1.
error_msgError message if the index is out of range.
idxNested index level to report in error message if the index is out of range.
+
+
+
Returns
Value of row vector at column n - 1.
+
Template Parameters
+ + +
Ttype of value.
+
+
+ +

Definition at line 380 of file get_base1_lhs.hpp.

+ +
+
+ +
+
+
+template<typename T_lp , typename T_lp_accum >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_lp, T_lp_accum>::type stan::math::get_lp (const T_lp & lp,
const stan::math::accumulator< T_lp_accum > & lp_accum 
)
+
+inline
+
+ +

Definition at line 14 of file get_lp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
static void stan::math::grad (varivi)
+
+static
+
+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad (varv,
Eigen::Matrix< var, Eigen::Dynamic, 1 > & x,
Eigen::VectorXd & g 
)
+
+ +

Propagate chain rule to calculate gradients starting from the specified variable.

+

Resizes the input vector to be the correct size.

+

The grad() function does not itself recover any memory. use recover_memory() or recover_memory_nested() to recover memory.

+
Parameters
+ + + + +
[in]vValue of function being differentiated
[in]xVariables being differentiated with respect to
[out]gGradient, d/dx v, evaluated at x.
+
+
+ +

Definition at line 26 of file grad.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
static void stan::math::grad (varivi)
+
+static
+
+ +

Compute the gradient for all variables starting from the specified root variable implementation.

+

Does not recover memory. This chainable variable's adjoint is initialized using the method init_dependent() and then the chain rule is applied working down the stack from this vari and calling each vari's chain() method in turn.

+

This function computes a nested gradient only going back as far as the last nesting.

+

This function does not recover any memory from the computation.

+
Parameters
+ + +
viVariable implementation for root of partial derivative propagation.
+
+
+ +

Definition at line 30 of file grad.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad_2F1 (T & gradA,
T & gradC,
a,
b,
c,
z,
precision = 1e-6 
)
+
+ +

Definition at line 13 of file grad_2F1.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad_F32 (T * g,
a,
b,
c,
d,
e,
z,
precision = 1e-6 
)
+
+ +

Definition at line 11 of file grad_F32.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad_hessian (const F & f,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & x,
double & fx,
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & H,
std::vector< Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > > & grad_H 
)
+
+ +

Calculate the value, the Hessian, and the gradient of the Hessian of the specified function at the specified argument.

+

The functor must implement

+

stan::math::fvar<stan::math::fvar<stan::math::var> > operator()(const Eigen::Matrix<stan::math::fvar<stan::math::fvar<stan::math::var> >, Eigen::Dynamic, 1>&)

+

using only operations that are defined for stan::math::fvar and stan::math::var.

+

This latter constraint usually requires the functions to be defined in terms of the libraries defined in Stan or in terms of functions with appropriately general namespace imports that eventually depend on functions defined in Stan.

+
Template Parameters
+ + +
FType of function
+
+
+
Parameters
+ + + + + + +
[in]fFunction
[in]xArgument to function
[out]fxFunction applied to argument
[out]HHessian of function at argument
[out]grad_HGradient of the Hessian of function at argument
+
+
+ +

Definition at line 45 of file grad_hessian.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad_inc_beta (double & g1,
double & g2,
double a,
double b,
double z 
)
+
+ +

Definition at line 17 of file grad_inc_beta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad_inc_beta (stan::math::fvar< T > & g1,
stan::math::fvar< T > & g2,
stan::math::fvar< T > a,
stan::math::fvar< T > b,
stan::math::fvar< T > z 
)
+
+ +

Definition at line 24 of file grad_inc_beta.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad_inc_beta (varg1,
varg2,
const vara,
const varb,
const varz 
)
+
+ +

Definition at line 24 of file grad_inc_beta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad_reg_inc_beta (T & g1,
T & g2,
a,
b,
z,
digammaA,
digammaB,
digammaSum,
betaAB 
)
+
+ +

Definition at line 14 of file grad_reg_inc_beta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T stan::math::grad_reg_inc_gamma (a,
z,
g,
dig,
precision = 1e-6 
)
+
+ +

Definition at line 16 of file grad_reg_inc_gamma.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::grad_tr_mat_times_hessian (const F & f,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & x,
const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & M,
Eigen::Matrix< double, Eigen::Dynamic, 1 > & grad_tr_MH 
)
+
+ +

Definition at line 20 of file grad_tr_mat_times_hessian.hpp.

+ +
+
+ +
+
+
+template<typename T , typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::gradient (const F & f,
const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
T & fx,
Eigen::Matrix< T, Eigen::Dynamic, 1 > & grad_fx 
)
+
+ +

Calculate the value and the gradient of the specified function at the specified argument.

+

The functor must implement

+

stan::math::fvar<T> operator()(const Eigen::Matrix<T, Eigen::Dynamic, 1>&)

+

using only operations that are defined for stan::math::fvar. This latter constraint usually requires the functions to be defined in terms of the libraries defined in Stan or in terms of functions with appropriately general namespace imports that eventually depend on functions defined in Stan.

+

Time and memory usage is on the order of the size of the fully unfolded expression for the function applied to the argument, independently of dimension.

+
Template Parameters
+ + +
FType of function
+
+
+
Parameters
+ + + + + +
[in]fFunction
[in]xArgument to function
[out]fxFunction applied to argument
[out]grad_fxGradient of function at argument
+
+
+ +

Definition at line 41 of file gradient.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::gradient (const F & f,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & x,
double & fx,
Eigen::Matrix< double, Eigen::Dynamic, 1 > & grad_fx 
)
+
+ +

Calculate the value and the gradient of the specified function at the specified argument.

+

The functor must implement

+

stan::math::var operator()(const Eigen::Matrix<stan::math::var, Eigen::Dynamic, 1>&)

+

using only operations that are defined for stan::math::var. This latter constraint usually requires the functions to be defined in terms of the libraries defined in Stan or in terms of functions with appropriately general namespace imports that eventually depend on functions defined in Stan.

+

Time and memory usage is on the order of the size of the fully unfolded expression for the function applied to the argument, independently of dimension.

+
Template Parameters
+ + +
FType of function
+
+
+
Parameters
+ + + + + +
[in]fFunction
[in]xArgument to function
[out]fxFunction applied to argument
[out]grad_fxGradient of function at argument
+
+
+ +

Definition at line 43 of file gradient.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::gradient_dot_vector (const F & f,
const Eigen::Matrix< T1, Eigen::Dynamic, 1 > & x,
const Eigen::Matrix< T2, Eigen::Dynamic, 1 > & v,
T1 & fx,
T1 & grad_fx_dot_v 
)
+
+ +

Definition at line 17 of file gradient_dot_vector.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::gumbel_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & beta 
)
+
+ +

Definition at line 28 of file gumbel_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::gumbel_cdf (const T_y & y,
const T_loc & mu,
const T_scale & beta 
)
+
+ +

Definition at line 28 of file gumbel_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::gumbel_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & beta 
)
+
+ +

Definition at line 28 of file gumbel_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::gumbel_log (const T_y & y,
const T_loc & mu,
const T_scale & beta 
)
+
+ +

Definition at line 28 of file gumbel_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::gumbel_log (const T_y & y,
const T_loc & mu,
const T_scale & beta 
)
+
+inline
+
+ +

Definition at line 118 of file gumbel_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::gumbel_rng (const double mu,
const double beta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 24 of file gumbel_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::head (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & v,
size_t n 
)
+
+inline
+
+ +

Return the specified number of elements as a vector from the front of the specified vector.

+
Template Parameters
+ + +
TType of value in vector
+
+
+
Parameters
+ + + +
vVector input
nSize of return
+
+
+
Returns
The first n elements of v
+ +

Definition at line 24 of file head.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::head (const Eigen::Matrix< T, 1, Eigen::Dynamic > & rv,
size_t n 
)
+
+inline
+
+ +

Return the specified number of elements as a row vector from the front of the specified row vector.

+
Template Parameters
+ + +
TType of value in vector
+
+
+
Parameters
+ + + +
rvRow vector
nSize of return row vector
+
+
+
Returns
The first n elements of rv
+ +

Definition at line 42 of file head.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
std::vector<T> stan::math::head (const std::vector< T > & sv,
size_t n 
)
+
+ +

Return the specified number of elements as a standard vector from the front of the specified standard vector.

+
Template Parameters
+ + +
TType of value in vector
+
+
+
Parameters
+ + + +
svStandard vector
nSize of return
+
+
+
Returns
The first n elements of sv
+ +

Definition at line 58 of file head.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::hessian (const F & f,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & x,
double & fx,
Eigen::Matrix< double, Eigen::Dynamic, 1 > & grad,
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & H 
)
+
+ +

Calculate the value, the gradient, and the Hessian, of the specified function at the specified argument in O(N^2) time and O(N^2) space.

+

The functor must implement

+

stan::math::fvar<stan::math::var> operator()(const Eigen::Matrix<stan::math::fvar<stan::math::var>, Eigen::Dynamic, 1>&)

+

using only operations that are defined for stan::math::fvar and stan::math::var.

+

This latter constraint usually requires the functions to be defined in terms of the libraries defined in Stan or in terms of functions with appropriately general namespace imports that eventually depend on functions defined in Stan.

+
Template Parameters
+ + +
FType of function
+
+
+
Parameters
+ + + + + + +
[in]fFunction
[in]xArgument to function
[out]fxFunction applied to argument
[out]gradgradient of function at argument
[out]HHessian of function at argument
+
+
+ +

Definition at line 45 of file hessian.hpp.

+ +
+
+ +
+
+
+template<typename T , typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::hessian (const F & f,
const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
T & fx,
Eigen::Matrix< T, Eigen::Dynamic, 1 > & grad,
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & H 
)
+
+ +

Definition at line 74 of file hessian.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::hessian_times_vector (const F & f,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & x,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & v,
double & fx,
Eigen::Matrix< double, Eigen::Dynamic, 1 > & Hv 
)
+
+ +

Definition at line 16 of file hessian_times_vector.hpp.

+ +
+
+ +
+
+
+template<typename T , typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::hessian_times_vector (const F & f,
const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
const Eigen::Matrix< T, Eigen::Dynamic, 1 > & v,
T & fx,
Eigen::Matrix< T, Eigen::Dynamic, 1 > & Hv 
)
+
+ +

Definition at line 45 of file hessian_times_vector.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_N , typename T_a , typename T_b >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::hypergeometric_log (const T_n & n,
const T_N & N,
const T_a & a,
const T_b & b 
)
+
+ +

Definition at line 29 of file hypergeometric_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_N , typename T_a , typename T_b >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::hypergeometric_log (const T_n & n,
const T_N & N,
const T_a & a,
const T_b & b 
)
+
+inline
+
+ +

Definition at line 86 of file hypergeometric_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
int stan::math::hypergeometric_rng (int N,
int a,
int b,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 16 of file hypergeometric_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::hypot (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 13 of file hypot.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::hypot (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 22 of file hypot.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::hypot (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 31 of file hypot.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::hypot (const vara,
const varb 
)
+
+inline
+
+ +

Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99).

+

See hypot() for double-based function.

+

The partial derivatives are given by

+

$\frac{\partial}{\partial x} \sqrt{x^2 + y^2} = \frac{x}{\sqrt{x^2 + y^2}}$, and

+

$\frac{\partial}{\partial y} \sqrt{x^2 + y^2} = \frac{y}{\sqrt{x^2 + y^2}}$.

+
Parameters
+ + + +
aLength of first side.
bLength of second side.
+
+
+
Returns
Length of hypoteneuse.
+ +

Definition at line 53 of file hypot.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::hypot (const vara,
double b 
)
+
+inline
+
+ +

Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99).

+

See hypot() for double-based function.

+

The derivative is

+

$\frac{d}{d x} \sqrt{x^2 + c^2} = \frac{x}{\sqrt{x^2 + c^2}}$.

+
Parameters
+ + + +
aLength of first side.
bLength of second side.
+
+
+
Returns
Length of hypoteneuse.
+ +

Definition at line 71 of file hypot.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::hypot (double a,
const varb 
)
+
+inline
+
+ +

Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99).

+

See hypot() for double-based function.

+

The derivative is

+

$\frac{d}{d y} \sqrt{c^2 + y^2} = \frac{y}{\sqrt{c^2 + y^2}}$.

+

+\[ \mbox{hypot}(x, y) = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \text{ or } y < 0 \\ \sqrt{x^2+y^2} & \mbox{if } x, y\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{hypot}(x, y)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \text{ or } y < 0 \\ \frac{x}{\sqrt{x^2+y^2}} & \mbox{if } x, y\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{hypot}(x, y)}{\partial y} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \text{ or } y < 0 \\ \frac{y}{\sqrt{x^2+y^2}} & \mbox{if } x, y\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aLength of first side.
bLength of second side.
+
+
+
Returns
Length of hypoteneuse.
+ +

Definition at line 116 of file hypot.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::ibeta (const double a,
const double b,
const double x 
)
+
+inline
+
+ +

The normalized incomplete beta function of a, b, and x.

+

Used to compute the cumulative density function for the beta distribution.

+
Parameters
+ + + + +
aShape parameter a <= 0; a and b can't both be 0
bShape parameter b <= 0
xRandom variate. 0 <= x <= 1
+
+
+
Exceptions
+ + +
ifconstraints are violated or if any argument is NaN
+
+
+
Returns
The normalized incomplete beta function.
+ +

Definition at line 23 of file ibeta.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::ibeta (const vara,
const varb,
const varx 
)
+
+inline
+
+ +

The normalized incomplete beta function of a, b, and x.

+

Used to compute the cumulative density function for the beta distribution.

+

Partial derivatives are those specified by wolfram alpha. The values were checked using both finite differences and by independent code for calculating the derivatives found in JSS (paper by Boik and Robison-Cox).

+
Parameters
+ + + + +
aShape parameter.
bShape parameter.
xRandom variate.
+
+
+
Returns
The normalized incomplete beta function.
+
Exceptions
+ + +
ifany argument is NaN.
+
+
+ +

Definition at line 238 of file ibeta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::identity_constrain (x)
+
+inline
+
+ +

Returns the result of applying the identity constraint transform to the input.

+

This method is effectively a no-op and is mainly useful as a placeholder in auto-generated code.

+
Parameters
+ + +
xFree scalar.
+
+
+
Returns
Transformed input.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 22 of file identity_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::math::identity_constrain (const T x,
T &  
)
+
+inline
+
+ +

Returns the result of applying the identity constraint transform to the input and increments the log probability reference with the log absolute Jacobian determinant.

+

This method is effectively a no-op and mainly useful as a placeholder in auto-generated code.

+
Parameters
+ + +
xFree scalar. lp Reference to log probability.
+
+
+
Returns
Transformed input.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 41 of file identity_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::identity_free (const T y)
+
+inline
+
+ +

Returns the result of applying the inverse of the identity constraint transform to the input.

+

This method is effectively a no-op and mainly useful as a placeholder in auto-generated code.

+
Parameters
+ + +
yConstrained scalar.
+
+
+
Returns
The input.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 21 of file identity_free.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::if_else (bool c,
const vary_true,
const vary_false 
)
+
+inline
+
+ +

If the specified condition is true, return the first variable, otherwise return the second variable.

+
Parameters
+ + + + +
cBoolean condition.
y_trueVariable to return if condition is true.
y_falseVariable to return if condition is false.
+
+
+ +

Definition at line 17 of file if_else.hpp.

+ +
+
+ +
+
+
+template<typename T_true , typename T_false >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_true, T_false>::type stan::math::if_else (const bool c,
const T_true y_true,
const T_false y_false 
)
+
+inline
+
+ +

Return the second argument if the first argument is true and otherwise return the second argument.

+

This is just a convenience method to provide a function with the same behavior as the built-in ternary operator. In general, this function behaves as if defined by

+

if_else(c, y1, y0) = c ? y1 : y0.

+
Parameters
+ + + + +
cBoolean condition value.
y_trueValue to return if condition is true.
y_falseValue to return if condition is false.
+
+
+ +

Definition at line 25 of file if_else.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::if_else (bool c,
double y_true,
const vary_false 
)
+
+inline
+
+ +

If the specified condition is true, return a new variable constructed from the first scalar, otherwise return the second variable.

+
Parameters
+ + + + +
cBoolean condition.
y_trueValue to promote to variable and return if condition is true.
y_falseVariable to return if condition is false.
+
+
+ +

Definition at line 29 of file if_else.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::if_else (bool c,
const vary_true,
const double y_false 
)
+
+inline
+
+ +

If the specified condition is true, return the first variable, otherwise return a new variable constructed from the second scalar.

+
Parameters
+ + + + +
cBoolean condition.
y_trueVariable to return if condition is true.
y_falseValue to promote to variable and return if condition is false.
+
+
+ +

Definition at line 44 of file if_else.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::inc_beta (const double & a,
const double & b,
const double & x 
)
+
+inline
+
+ +

Definition at line 10 of file inc_beta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::inc_beta (const fvar< T > & a,
const fvar< T > & b,
const fvar< T > & x 
)
+
+inline
+
+ +

Definition at line 20 of file inc_beta.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::inc_beta (const stan::math::vara,
const stan::math::varb,
const stan::math::varc 
)
+
+inline
+
+ +

Definition at line 45 of file inc_beta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T stan::math::inc_beta_dda (a,
b,
z,
digamma_a,
digamma_ab 
)
+
+ +

Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a.

+

The power series used to compute the deriative tends to converge slowly when a and b are large, especially if z approaches 1. The implementation will throw an exception if the series have not converged within 100,000 iterations. The current implementation has been tested for values of a and b up to 12500 and z = 0.999.

+
Template Parameters
+ + +
Tscalar types of arguments
+
+
+
Parameters
+ + + + + + +
aa
bb
zupper bound of the integral
digamma_avalue of digamma(a)
digamma_abvalue of digamma(b)
+
+
+
Returns
partial derivative of the incomplete beta with respect to a
+
Precondition
a >= 0
+
+b >= 0
+
+0 <= z <= 1
+ +

Definition at line 39 of file inc_beta_dda.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
T stan::math::inc_beta_ddb (a,
b,
z,
digamma_b,
digamma_ab 
)
+
+ +

Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to b.

+

The power series used to compute the deriative tends to converge slowly when a and b are large, especailly if z approaches 1. The implementation will throw an exception if the series have not converged within 100,000 iterations. The current implementation has been tested for values of a and b up to 12500 and z = 0.999.

+
Template Parameters
+ + +
Tscalar types of arguments
+
+
+
Parameters
+ + + + + + +
aa
bb
zupper bound of the integral
digamma_bvalue of digamma(b)
digamma_abvalue of digamma(b)
+
+
+
Returns
partial derivative of the incomplete beta with respect to b
+
Precondition
a >= 0
+
+b >= 0
+
+0 <= z <= 1
+ +

Definition at line 39 of file inc_beta_ddb.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
T stan::math::inc_beta_ddz (a,
b,
z 
)
+
+ +

Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to z.

+
Template Parameters
+ + +
Tscalar types of arguments
+
+
+
Parameters
+ + + + +
aa
bb
zupper bound of the integral
+
+
+
Returns
partial derivative of the incomplete beta with respect to z
+
Precondition
a > 0
+
+b > 0
+
+0 < z <= 1
+ +

Definition at line 27 of file inc_beta_ddz.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::inc_beta_ddz (double a,
double b,
double z 
)
+
+ +

Definition at line 35 of file inc_beta_ddz.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::initialize (T & x,
const T & v 
)
+
+inline
+
+ +

Definition at line 17 of file initialize.hpp.

+ +
+
+ +
+
+
+template<typename T , typename V >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_arithmetic<V>::value, void>::type stan::math::initialize (T & x,
v 
)
+
+inline
+
+ +

Definition at line 23 of file initialize.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C, typename V >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::initialize (Eigen::Matrix< T, R, C > & x,
const V & v 
)
+
+inline
+
+ +

Definition at line 27 of file initialize.hpp.

+ +
+
+ +
+
+
+template<typename T , typename V >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::initialize (std::vector< T > & x,
const V & v 
)
+
+inline
+
+ +

Definition at line 32 of file initialize.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::initialize_variable (varvariable,
const varvalue 
)
+
+inline
+
+ +

Initialize variable to value.

+

(Function may look pointless, but its needed to bottom out recursion.)

+ +

Definition at line 15 of file initialize_variable.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::initialize_variable (Eigen::Matrix< var, R, C > & matrix,
const varvalue 
)
+
+inline
+
+ +

Initialize every cell in the matrix to the specified value.

+ +

Definition at line 24 of file initialize_variable.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::initialize_variable (std::vector< T > & variables,
const varvalue 
)
+
+inline
+
+ +

Initialize the variables in the standard vector recursively.

+ +

Definition at line 34 of file initialize_variable.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
unsigned int stan::math::int_step (const T y)
+
+ +

The integer step, or Heaviside, function.

+

For double NaN input, int_step(NaN) returns 0.

+

+\[ \mbox{int\_step}(x) = \begin{cases} 0 & \mbox{if } x \leq 0 \\ 1 & \mbox{if } x > 0 \\[6pt] 0 & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
yValue to test.
+
+
+
Returns
1 if value is greater than 0 and 0 otherwise
+
Template Parameters
+ + +
TScalar argument type.
+
+
+ +

Definition at line 25 of file int_step.hpp.

+ +
+
+ +
+
+
+template<typename F , typename T_initial , typename T_param >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
std::vector<std::vector<typename stan::return_type<T_initial, T_param>::type> > stan::math::integrate_ode_bdf (const F & f,
const std::vector< T_initial > & y0,
const double t0,
const std::vector< double > & ts,
const std::vector< T_param > & theta,
const std::vector< double > & x,
const std::vector< int > & x_int,
std::ostream * msgs = 0,
double relative_tolerance = 1e-10,
double absolute_tolerance = 1e-10,
long int max_num_steps = 1e8 
)
+
+ +

Return the solutions for the specified system of ordinary differential equations given the specified initial state, initial times, times of desired solution, and parameters and data, writing error and warning messages to the specified stream.

+

This function is templated to allow the initial times to be either data or autodiff variables and the parameters to be data or autodiff variables. The autodiff-based implementation for reverse-mode are defined in namespace stan::math and may be invoked via argument-dependent lookup by including their headers.

+

The solver used is based on the backward differentiation formula which is an implicit numerical integration scheme appropiate for stiff ODE systems.

+
Template Parameters
+ + + + +
Ftype of ODE system function.
T_initialtype of scalars for initial values.
T_paramtype of scalars for parameters.
+
+
+
Parameters
+ + + + + + + + + + + + +
[in]ffunctor for the base ordinary differential equation.
[in]y0initial state.
[in]t0initial time.
[in]tstimes of the desired solutions, in strictly increasing order, all greater than the initial time.
[in]thetaparameter vector for the ODE.
[in]xcontinuous data vector for the ODE.
[in]x_intinteger data vector for the ODE.
[in,out]msgsthe print stream for warning messages.
[in]relative_tolerancerelative tolerance passed to CVODE.
[in]absolute_toleranceabsolute tolerance passed to CVODE.
[in]max_num_stepsmaximal number of admissable steps between time-points
+
+
+
Returns
a vector of states, each state being a vector of the same size as the state variable, corresponding to a time in ts.
+ +

Definition at line 83 of file integrate_ode_bdf.hpp.

+ +
+
+ +
+
+
+template<typename F , typename T1 , typename T2 >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
std::vector<std::vector<typename stan::return_type<T1, T2>::type> > stan::math::integrate_ode_rk45 (const F & f,
const std::vector< T1 > y0,
const double t0,
const std::vector< double > & ts,
const std::vector< T2 > & theta,
const std::vector< double > & x,
const std::vector< int > & x_int,
std::ostream * msgs = 0,
double relative_tolerance = 1e-6,
double absolute_tolerance = 1e-6,
int max_num_steps = 1E6 
)
+
+ +

Return the solutions for the specified system of ordinary differential equations given the specified initial state, initial times, times of desired solution, and parameters and data, writing error and warning messages to the specified stream.

+

Warning: If the system of equations is stiff, roughly defined by having varying time scales across dimensions, then this solver is likely to be slow.

+

This function is templated to allow the initial times to be either data or autodiff variables and the parameters to be data or autodiff variables. The autodiff-based implementation for reverse-mode are defined in namespace stan::math and may be invoked via argument-dependent lookup by including their headers.

+

This function uses the Dormand-Prince method as implemented in Boost's boost::numeric::odeint::runge_kutta_dopri5 integrator.

+
Template Parameters
+ + + + +
Ftype of ODE system function.
T1type of scalars for initial values.
T2type of scalars for parameters.
+
+
+
Parameters
+ + + + + + + + + + + + +
[in]ffunctor for the base ordinary differential equation.
[in]y0initial state.
[in]t0initial time.
[in]tstimes of the desired solutions, in strictly increasing order, all greater than the initial time.
[in]thetaparameter vector for the ODE.
[in]xcontinuous data vector for the ODE.
[in]x_intinteger data vector for the ODE.
[out]msgsthe print stream for warning messages.
[in]relative_tolerancerelative tolerance parameter for Boost's ode solver. Defaults to 1e-6.
[in]absolute_toleranceabsolute tolerance parameter for Boost's ode solver. Defaults to 1e-6.
[in]max_num_stepsmaximum number of steps to take within the Boost ode solver.
+
+
+
Returns
a vector of states, each state being a vector of the same size as the state variable, corresponding to a time in ts.
+ +

Definition at line 67 of file integrate_ode_rk45.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::inv (const T x)
+
+inline
+
+ +

Definition at line 12 of file inv.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::inv (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file inv.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::inv (const vara)
+
+inline
+
+ +

+\[ \mbox{inv}(x) = \begin{cases} \frac{1}{x} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{inv}(x)}{\partial x} = \begin{cases} -\frac{1}{x^2} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 42 of file inv.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::inv_chi_square_ccdf_log (const T_y & y,
const T_dof & nu 
)
+
+ +

Definition at line 33 of file inv_chi_square_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::inv_chi_square_cdf (const T_y & y,
const T_dof & nu 
)
+
+ +

Definition at line 33 of file inv_chi_square_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::inv_chi_square_cdf_log (const T_y & y,
const T_dof & nu 
)
+
+ +

Definition at line 33 of file inv_chi_square_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_dof >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::inv_chi_square_log (const T_y & y,
const T_dof & nu 
)
+
+ +

The log of an inverse chi-squared density for y with the specified degrees of freedom parameter.

+

The degrees of freedom prarameter must be greater than 0. y must be greater than 0.

+

+\begin{eqnarray*} y &\sim& \mbox{\sf{Inv-}}\chi^2_\nu \\ \log (p (y \, |\, \nu)) &=& \log \left( \frac{2^{-\nu / 2}}{\Gamma (\nu / 2)} y^{- (\nu / 2 + 1)} \exp^{-1 / (2y)} \right) \\ &=& - \frac{\nu}{2} \log(2) - \log (\Gamma (\nu / 2)) - (\frac{\nu}{2} + 1) \log(y) - \frac{1}{2y} \\ & & \mathrm{ where } \; y > 0 \end{eqnarray*} +

+
Parameters
+ + + +
yA scalar variable.
nuDegrees of freedom.
+
+
+
Exceptions
+ + + +
std::domain_errorif nu is not greater than or equal to 0
std::domain_errorif y is not greater than or equal to 0.
+
+
+
Template Parameters
+ + + +
T_yType of scalar.
T_dofType of degrees of freedom.
+
+
+ +

Definition at line 52 of file inv_chi_square_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof>::type stan::math::inv_chi_square_log (const T_y & y,
const T_dof & nu 
)
+
+inline
+
+ +

Definition at line 142 of file inv_chi_square_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::inv_chi_square_rng (const double nu,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 28 of file inv_chi_square_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::inv_cloglog (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file inv_cloglog.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::inv_cloglog (const stan::math::vara)
+
+inline
+
+ +

Return the inverse complementary log-log function applied specified variable (stan).

+

See stan::math::inv_cloglog() for the double-based version.

+

The derivative is given by

+

$\frac{d}{dx} \mbox{cloglog}^{-1}(x) = \exp (x - \exp (x))$.

+
Parameters
+ + +
aVariable argument.
+
+
+
Returns
The inverse complementary log-log of the specified argument.
+ +

Definition at line 36 of file inv_cloglog.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::inv_cloglog (x)
+
+inline
+
+ +

The inverse complementary log-log function.

+

The function is defined by

+

inv_cloglog(x) = 1 - exp(-exp(x)).

+

This function can be used to implement the inverse link function for complementary-log-log regression.

+

+\[ \mbox{inv\_cloglog}(y) = \begin{cases} \mbox{cloglog}^{-1}(y) & \mbox{if } -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{inv\_cloglog}(y)}{\partial y} = \begin{cases} \frac{\partial\, \mbox{cloglog}^{-1}(y)}{\partial y} & \mbox{if } -\infty\leq y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \] +

+

+\[ \mbox{cloglog}^{-1}(y) = 1 - \exp \left( - \exp(y) \right) \] +

+

+\[ \frac{\partial \, \mbox{cloglog}^{-1}(y)}{\partial y} = \exp(y-\exp(y)) \] +

+
Parameters
+ + +
xArgument.
+
+
+
Returns
Inverse complementary log-log of the argument.
+ +

Definition at line 49 of file inv_cloglog.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::inv_gamma_ccdf_log (const T_y & y,
const T_shape & alpha,
const T_scale & beta 
)
+
+ +

Definition at line 35 of file inv_gamma_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::inv_gamma_cdf (const T_y & y,
const T_shape & alpha,
const T_scale & beta 
)
+
+ +

The CDF of an inverse gamma density for y with the specified shape and scale parameters.

+

y, shape, and scale parameters must be greater than 0.

+
Parameters
+ + + + +
yA scalar variable.
alphaShape parameter.
betaScale parameter.
+
+
+
Exceptions
+ + + + +
std::domain_errorif alpha is not greater than 0.
std::domain_errorif beta is not greater than 0.
std::domain_errorif y is not greater than 0.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_shapeType of shape.
T_scaleType of scale.
+
+
+ +

Definition at line 51 of file inv_gamma_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::inv_gamma_cdf_log (const T_y & y,
const T_shape & alpha,
const T_scale & beta 
)
+
+ +

Definition at line 35 of file inv_gamma_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::inv_gamma_log (const T_y & y,
const T_shape & alpha,
const T_scale & beta 
)
+
+ +

The log of an inverse gamma density for y with the specified shape and scale parameters.

+

Shape and scale parameters must be greater than 0. y must be greater than 0.

+
Parameters
+ + + + +
yA scalar variable.
alphaShape parameter.
betaScale parameter.
+
+
+
Exceptions
+ + + + +
std::domain_errorif alpha is not greater than 0.
std::domain_errorif beta is not greater than 0.
std::domain_errorif y is not greater than 0.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_shapeType of shape.
T_scaleType of scale.
+
+
+ +

Definition at line 51 of file inv_gamma_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::inv_gamma_log (const T_y & y,
const T_shape & alpha,
const T_scale & beta 
)
+
+inline
+
+ +

Definition at line 163 of file inv_gamma_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::inv_gamma_rng (const double alpha,
const double beta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 30 of file inv_gamma_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::inv_logit (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file inv_logit.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::inv_logit (const stan::math::vara)
+
+inline
+
+ +

The inverse logit function for variables (stan).

+

See stan::math::inv_logit() for the double-based version.

+

The derivative of inverse logit is

+

$\frac{d}{dx} \mbox{logit}^{-1}(x) = \mbox{logit}^{-1}(x) (1 - \mbox{logit}^{-1}(x))$.

+
Parameters
+ + +
aArgument variable.
+
+
+
Returns
Inverse logit of argument.
+ +

Definition at line 34 of file inv_logit.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::inv_logit (const T a)
+
+inline
+
+ +

Returns the inverse logit function applied to the argument.

+

The inverse logit function is defined by

+

$\mbox{logit}^{-1}(x) = \frac{1}{1 + \exp(-x)}$.

+

This function can be used to implement the inverse link function for logistic regression.

+

The inverse to this function is stan::math::logit.

+

+\[ \mbox{inv\_logit}(y) = \begin{cases} \mbox{logit}^{-1}(y) & \mbox{if } -\infty\leq y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{inv\_logit}(y)}{\partial y} = \begin{cases} \frac{\partial\, \mbox{logit}^{-1}(y)}{\partial y} & \mbox{if } -\infty\leq y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \] +

+

+\[ \mbox{logit}^{-1}(y) = \frac{1}{1 + \exp(-y)} \] +

+

+\[ \frac{\partial \, \mbox{logit}^{-1}(y)}{\partial y} = \frac{\exp(y)}{(\exp(y)+1)^2} \] +

+
Parameters
+ + +
aArgument.
+
+
+
Returns
Inverse logit of argument.
+ +

Definition at line 52 of file inv_logit.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::inv_Phi (const fvar< T > & p)
+
+inline
+
+ +

Definition at line 15 of file inv_Phi.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
double stan::math::inv_Phi (double p)
+
+inline
+
+ +

The inverse of the unit normal cumulative distribution function.

+

The return value for a specified input probability, $p$, is the unit normal variate, $x$, such that

+

$\Phi(x) = \int_{-\infty}^x \mbox{\sf Norm}(x|0, 1) \ dx = p$

+

Algorithm first derived in 2003 by Peter Jon Aklam at http://home.online.no/~pjacklam/notes/invnorm/

+
Parameters
+ + +
pArgument between 0 and 1.
+
+
+
Returns
Real number
+ +

Definition at line 26 of file inv_Phi.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::inv_Phi (const stan::math::varp)
+
+inline
+
+ +

The inverse of unit normal cumulative density function.

+

See stan::math::inv_Phi() for the double-based version.

+

The derivative is the reciprocal of unit normal density function,

+
Parameters
+ + +
pProbability
+
+
+
Returns
The unit normal inverse cdf evaluated at p
+ +

Definition at line 37 of file inv_Phi.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::inv_sqrt (const T x)
+
+inline
+
+ +

Definition at line 12 of file inv_sqrt.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::inv_sqrt (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file inv_sqrt.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::inv_sqrt (const vara)
+
+inline
+
+ +

+\[ \mbox{inv\_sqrt}(x) = \begin{cases} \frac{1}{\sqrt{x}} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{inv\_sqrt}(x)}{\partial x} = \begin{cases} -\frac{1}{2\sqrt{x^3}} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 42 of file inv_sqrt.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::inv_square (const T x)
+
+inline
+
+ +

Definition at line 12 of file inv_square.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::inv_square (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file inv_square.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::inv_square (const vara)
+
+inline
+
+ +

+\[ \mbox{inv\_square}(x) = \begin{cases} \frac{1}{x^2} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{inv\_square}(x)}{\partial x} = \begin{cases} -\frac{2}{x^3} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 42 of file inv_square.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_dof , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_dof, T_scale>::type stan::math::inv_wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & W,
const T_dof & nu,
const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > & S 
)
+
+ +

The log of the Inverse-Wishart density for the given W, degrees of freedom, and scale matrix.

+

The scale matrix, S, must be k x k, symmetric, and semi-positive definite.

+

+\begin{eqnarray*} W &\sim& \mbox{\sf{Inv-Wishart}}_{\nu} (S) \\ \log (p (W \, |\, \nu, S) ) &=& \log \left( \left(2^{\nu k/2} \pi^{k (k-1) /4} \prod_{i=1}^k{\Gamma (\frac{\nu + 1 - i}{2})} \right)^{-1} \times \left| S \right|^{\nu/2} \left| W \right|^{-(\nu + k + 1) / 2} \times \exp (-\frac{1}{2} \mbox{tr} (S W^{-1})) \right) \\ &=& -\frac{\nu k}{2}\log(2) - \frac{k (k-1)}{4} \log(\pi) - \sum_{i=1}^{k}{\log (\Gamma (\frac{\nu+1-i}{2}))} +\frac{\nu}{2} \log(\det(S)) - \frac{\nu+k+1}{2}\log (\det(W)) - \frac{1}{2} \mbox{tr}(S W^{-1}) \end{eqnarray*} +

+
Parameters
+ + + + +
WA scalar matrix
nuDegrees of freedom
SThe scale matrix
+
+
+
Returns
The log of the Inverse-Wishart density at W given nu and S.
+
Exceptions
+ + + +
std::domain_errorif nu is not greater than k-1
std::domain_errorif S is not square, not symmetric, or not semi-positive definite.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_dofType of degrees of freedom.
T_scaleType of scale.
+
+
+ +

Definition at line 52 of file inv_wishart_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_dof, T_scale>::type stan::math::inv_wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & W,
const T_dof & nu,
const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > & S 
)
+
+inline
+
+ +

Definition at line 125 of file inv_wishart_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> stan::math::inv_wishart_rng (const double nu,
const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & S,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 21 of file inv_wishart_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::invalid_argument (const char * function,
const char * name,
const T & y,
const char * msg1,
const char * msg2 
)
+
+inline
+
+ +

Throw an invalid_argument exception with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing invalid argument. This will allow us to change the behavior for all functions at once.

+

The message is: "<function>: <name> <msg1><y><msg2>"

+
Template Parameters
+ + +
TType of variable
+
+
+
Parameters
+ + + + + + +
functionName of the function
nameName of the variable
yVariable
msg1Message to print before the variable
msg2Message to print after the variable
+
+
+
Exceptions
+ + +
std::invalid_argument
+
+
+ +

Definition at line 31 of file invalid_argument.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::invalid_argument (const char * function,
const char * name,
const T & y,
const char * msg1 
)
+
+inline
+
+ +

Throw an invalid_argument exception with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing invalid argument. This will allow us to change the behavior for all functions at once. (We've already changed behavior mulitple times up to Stan v2.5.0.)

+

The message is: "<function>: <name> <msg1><y>"

+
Template Parameters
+ + +
TType of variable
+
+
+
Parameters
+ + + + + +
functionName of the function
nameName of the variable
yVariable
msg1Message to print before the variable
+
+
+
Exceptions
+ + +
std::invalid_argument
+
+
+ +

Definition at line 66 of file invalid_argument.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::invalid_argument_vec (const char * function,
const char * name,
const T & y,
const size_t i,
const char * msg1,
const char * msg2 
)
+
+inline
+
+ +

Throw an invalid argument exception with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing invalid arguments. This will allow us to change the behavior for all functions at once. (We've already changed behavior mulitple times up to Stan v2.5.0.)

+

The message is: "<function>: <name>[<i+error_index>] <msg1><y>" where error_index is the value of stan::error_index::value which indicates whether the message should be 0 or 1 indexed.

+
Template Parameters
+ + +
TType of variable
+
+
+
Parameters
+ + + + + + + +
functionName of the function
nameName of the variable
yVariable
iIndex
msg1Message to print before the variable
msg2Message to print after the variable
+
+
+
Exceptions
+ + +
std::invalid_argument
+
+
+ +

Definition at line 38 of file invalid_argument_vec.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::invalid_argument_vec (const char * function,
const char * name,
const T & y,
const size_t i,
const char * msg 
)
+
+inline
+
+ +

Throw an invalid argument exception with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing invalid arguments. This will allow us to change the behavior for all functions at once. (We've already changed behavior mulitple times up to Stan v2.5.0.)

+

The message is: "<function>: <name>[<i+error_index>] <msg1><y>" where error_index is the value of stan::error_index::value which indicates whether the message should be 0 or 1 indexed.

+
Template Parameters
+ + +
TType of variable
+
+
+
Parameters
+ + + + + + +
functionName of the function
nameName of the variable
yVariable
iIndex
msgMessage to print before the variable
+
+
+
Exceptions
+ + +
std::invalid_argument
+
+
+ +

Definition at line 74 of file invalid_argument_vec.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R, C> stan::math::inverse (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the inverse of the specified matrix.

+
Parameters
+ + +
mSpecified matrix.
+
+
+
Returns
Inverse of the matrix.
+ +

Definition at line 18 of file inverse.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::inverse (const Eigen::Matrix< fvar< T >, R, C > & m)
+
+inline
+
+ +

Definition at line 20 of file inverse.hpp.

+ +
+
+ +
+
+
+template<typename Vector >
+ + + + + + + + + + + + + + + + + + +
void stan::math::inverse_softmax (const Vector & simplex,
Vector & y 
)
+
+ +

Writes the inverse softmax of the simplex argument into the second argument.

+

See stan::math::softmax for the inverse function and a definition of the relation.

+

The inverse softmax function is defined by

+

$\mbox{inverse\_softmax}(x)[i] = \log x[i]$.

+

This function defines the inverse of stan::math::softmax up to a scaling factor.

+

Because of the definition, values of 0.0 in the simplex are converted to negative infinity, and values of 1.0 are converted to 0.0.

+

There is no check that the input vector is a valid simplex vector.

+
Parameters
+ + + +
simplexSimplex vector input.
yVector into which the inverse softmax is written.
+
+
+
Exceptions
+ + +
std::invalid_argumentif size of the input and output vectors differ.
+
+
+ +

Definition at line 34 of file inverse_softmax.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::inverse_spd (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+inline
+
+ +

Returns the inverse of the specified symmetric, pos/neg-definite matrix.

+
Parameters
+ + +
mSpecified matrix.
+
+
+
Returns
Inverse of the matrix.
+ +

Definition at line 20 of file inverse_spd.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
bool stan::math::is_aligned (T * ptr,
unsigned int bytes_aligned 
)
+
+ +

Return true if the specified pointer is aligned on the number of bytes.

+

This doesn't really make sense other than for powers of 2.

+
Parameters
+ + + +
ptrPointer to test.
bytes_alignedNumber of bytes of alignment required.
+
+
+
Returns
true if pointer is aligned.
+
Template Parameters
+ + +
Typeof object to which pointer points.
+
+
+ +

Definition at line 30 of file stack_alloc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
int stan::math::is_inf (const double x)
+
+inline
+
+ +

Returns 1 if the input is infinite and 0 otherwise.

+

Delegates to boost::math::isinf.

+
Parameters
+ + +
xValue to test.
+
+
+
Returns
1 if the value is infinite.
+ +

Definition at line 19 of file is_inf.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
int stan::math::is_inf (const fvar< T > & x)
+
+inline
+
+ +

Returns 1 if the input's value is infinite and 0 otherwise.

+

Delegates to stan::math::is_inf.

+
Parameters
+ + +
xValue to test.
+
+
+
Returns
1 if the value is infinite and 0 otherwise.
+ +

Definition at line 22 of file is_inf.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
int stan::math::is_inf (const varv)
+
+inline
+
+ +

Returns 1 if the input's value is infinite and 0 otherwise.

+

Delegates to stan::math::is_inf.

+
Parameters
+ + +
vValue to test.
+
+
+
Returns
1 if the value is infinite and 0 otherwise.
+ +

Definition at line 23 of file is_inf.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
bool stan::math::is_nan (double x)
+
+inline
+
+ +

Returns 1 if the input is NaN and 0 otherwise.

+

Delegates to boost::math::isnan.

+
Parameters
+ + +
xValue to test.
+
+
+
Returns
1 if the value is NaN.
+ +

Definition at line 18 of file is_nan.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
bool stan::math::is_nan (const varv)
+
+inline
+
+ +

Returns 1 if the input's value is NaN and 0 otherwise.

+

Delegates to stan::math::is_nan(double).

+
Parameters
+ + +
vValue to test.
+
+
+
Returns
1 if the value is NaN and 0 otherwise.
+ +

Definition at line 21 of file is_nan.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
int stan::math::is_nan (const fvar< T > & x)
+
+inline
+
+ +

Returns 1 if the input's value is NaN and 0 otherwise.

+

Delegates to stan::math::is_nan.

+
Parameters
+ + +
xValue to test.
+
+
+
Returns
1 if the value is NaN and 0 otherwise.
+ +

Definition at line 22 of file is_nan.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
bool stan::math::is_uninitialized (x)
+
+inline
+
+ +

Returns true if the specified variable is uninitialized.

+

Arithmetic types are always initialized by definition (the value is not specified).

+
Template Parameters
+ + +
TType of object to test.
+
+
+
Parameters
+ + +
xObject to test.
+
+
+
Returns
true if the specified object is uninitialized.
+
+false if input is NaN.
+ +

Definition at line 19 of file is_uninitialized.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
bool stan::math::is_uninitialized (var x)
+
+inline
+
+ +

Returns true if the specified variable is uninitialized.

+

This overload of the stan::math::is_uninitialized() function delegates the return to the is_uninitialized() method on the specified variable.

+
Parameters
+ + +
xObject to test.
+
+
+
Returns
true if the specified object is uninitialized.
+ +

Definition at line 23 of file is_uninitialized.hpp.

+ +
+
+ +
+
+
+template<typename T , typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::jacobian (const F & f,
const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
Eigen::Matrix< T, Eigen::Dynamic, 1 > & fx,
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & J 
)
+
+ +

Definition at line 14 of file jacobian.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::jacobian (const F & f,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & x,
Eigen::Matrix< double, Eigen::Dynamic, 1 > & fx,
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & J 
)
+
+ +

Definition at line 15 of file jacobian.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TL >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::math::lb_constrain (const T x,
const TL lb 
)
+
+inline
+
+ +

Return the lower-bounded value for the specified unconstrained input and specified lower bound.

+

The transform applied is

+

$f(x) = \exp(x) + L$

+

where $L$ is the constant lower bound.

+

If the lower bound is negative infinity, this function reduces to identity_constrain(x).

+
Parameters
+ + + +
xUnconstrained scalar input.
lbLower-bound on constrained ouptut.
+
+
+
Returns
Lower-bound constrained value correspdonding to inputs.
+
Template Parameters
+ + + +
TType of scalar.
TLType of lower bound.
+
+
+ +

Definition at line 35 of file lb_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TL >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T, TL>::type stan::math::lb_constrain (const T x,
const TL lb,
T & lp 
)
+
+inline
+
+ +

Return the lower-bounded value for the speicifed unconstrained input and specified lower bound, incrementing the specified reference with the log absolute Jacobian determinant of the transform.

+

If the lower bound is negative infinity, this function reduces to identity_constraint(x, lp).

+
Parameters
+ + + + +
xUnconstrained scalar input.
lbLower-bound on output.
lpReference to log probability to increment.
+
+
+
Returns
Loer-bound constrained value corresponding to inputs.
+
Template Parameters
+ + + +
TType of scalar.
TLType of lower bound.
+
+
+ +

Definition at line 61 of file lb_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TL >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T, TL>::type stan::math::lb_free (const T y,
const TL lb 
)
+
+inline
+
+ +

Return the unconstrained value that produces the specified lower-bound constrained value.

+

If the lower bound is negative infinity, it is ignored and the function reduces to identity_free(y).

+
Parameters
+ + + +
yInput scalar.
lbLower bound.
+
+
+
Returns
Unconstrained value that produces the input when constrained.
+
Template Parameters
+ + + +
TType of scalar.
TLType of lower bound.
+
+
+
Exceptions
+ + +
std::domain_errorif y is lower than the lower bound.
+
+
+ +

Definition at line 32 of file lb_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::lbeta (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 16 of file lbeta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::lbeta (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 28 of file lbeta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::lbeta (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 38 of file lbeta.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::lbeta (const T1 a,
const T2 b 
)
+
+inline
+
+ +

Return the log of the beta function applied to the specified arguments.

+

The beta function is defined for $a > 0$ and $b > 0$ by

+

$\mbox{B}(a, b) = \frac{\Gamma(a) \Gamma(b)}{\Gamma(a+b)}$.

+

This function returns its log,

+

$\log \mbox{B}(a, b) = \log \Gamma(a) + \log \Gamma(b) - \log \Gamma(a+b)$.

+

See boost::math::lgamma() for the double-based and stan::math for the variable-based log Gamma function.

+

+\[ \mbox{lbeta}(\alpha, \beta) = \begin{cases} \ln\int_0^1 u^{\alpha - 1} (1 - u)^{\beta - 1} \, du & \mbox{if } \alpha, \beta>0 \\[6pt] \textrm{NaN} & \mbox{if } \alpha = \textrm{NaN or } \beta = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{lbeta}(\alpha, \beta)}{\partial \alpha} = \begin{cases} \Psi(\alpha)-\Psi(\alpha+\beta) & \mbox{if } \alpha, \beta>0 \\[6pt] \textrm{NaN} & \mbox{if } \alpha = \textrm{NaN or } \beta = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{lbeta}(\alpha, \beta)}{\partial \beta} = \begin{cases} \Psi(\beta)-\Psi(\alpha+\beta) & \mbox{if } \alpha, \beta>0 \\[6pt] \textrm{NaN} & \mbox{if } \alpha = \textrm{NaN or } \beta = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst value
bSecond value
+
+
+
Returns
Log of the beta function applied to the two values.
+
Template Parameters
+ + + +
T1Type of first value.
T2Type of second value.
+
+
+ +

Definition at line 59 of file lbeta.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::lgamma (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file lgamma.hpp.

+ +
+
+ +
+
+ + + + + + + + +
double stan::math::lgamma (double x)
+
+ +

+\[ \mbox{lgamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \ln\Gamma(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{lgamma}(x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 31 of file lgamma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::lgamma (const stan::math::vara)
+
+inline
+
+ +

The log gamma function for variables (C99).

+

The derivatie is the digamma function,

+

$\frac{d}{dx} \Gamma(x) = \psi^{(0)}(x)$.

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
Log gamma of the variable.
+ +

Definition at line 35 of file lgamma.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_covar , typename T_shape >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_covar, T_shape>::type stan::math::lkj_corr_cholesky_log (const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > & L,
const T_shape & eta 
)
+
+ +

Definition at line 56 of file lkj_corr_cholesky_log.hpp.

+ +
+
+ +
+
+
+template<typename T_covar , typename T_shape >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_covar, T_shape>::type stan::math::lkj_corr_cholesky_log (const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > & L,
const T_shape & eta 
)
+
+inline
+
+ +

Definition at line 99 of file lkj_corr_cholesky_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::MatrixXd stan::math::lkj_corr_cholesky_rng (const size_t K,
const double eta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 52 of file lkj_corr_cholesky_rng.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_shape >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_shape>::type stan::math::lkj_corr_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const T_shape & eta 
)
+
+ +

Definition at line 86 of file lkj_corr_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_shape>::type stan::math::lkj_corr_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const T_shape & eta 
)
+
+inline
+
+ +

Definition at line 122 of file lkj_corr_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::MatrixXd stan::math::lkj_corr_rng (const size_t K,
const double eta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 52 of file lkj_corr_rng.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_loc, T_scale, T_shape>::type stan::math::lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_loc, Eigen::Dynamic, 1 > & mu,
const Eigen::Matrix< T_scale, Eigen::Dynamic, 1 > & sigma,
const T_shape & eta 
)
+
+ +

Definition at line 24 of file lkj_cov_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_loc, T_scale, T_shape>::type stan::math::lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_loc, Eigen::Dynamic, 1 > & mu,
const Eigen::Matrix< T_scale, Eigen::Dynamic, 1 > & sigma,
const T_shape & eta 
)
+
+inline
+
+ +

Definition at line 74 of file lkj_cov_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_loc, T_scale, T_shape>::type stan::math::lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const T_loc & mu,
const T_scale & sigma,
const T_shape & eta 
)
+
+ +

Definition at line 87 of file lkj_cov_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_loc, T_scale, T_shape>::type stan::math::lkj_cov_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const T_loc & mu,
const T_scale & sigma,
const T_shape & eta 
)
+
+inline
+
+ +

Definition at line 124 of file lkj_cov_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<typename stan::return_type<T, int>::type> stan::math::lmgamma (int x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 16 of file lmgamma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::lmgamma (int a,
const stan::math::varb 
)
+
+inline
+
+ +

Definition at line 28 of file lmgamma.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::lmgamma (const int k,
x 
)
+
+inline
+
+ +

Return the natural logarithm of the multivariate gamma function with the speciifed dimensions and argument.

+

The multivariate gamma function $\Gamma_k(x)$ for dimensionality $k$ and argument $x$ is defined by

+

$\Gamma_k(x) = \pi^{k(k-1)/4} \, \prod_{j=1}^k \Gamma(x + (1 - j)/2)$,

+

where $\Gamma()$ is the gamma function.

+

+\[ \mbox{lmgamma}(n, x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \ln\Gamma_n(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{lmgamma}(n, x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \frac{\partial\, \ln\Gamma_n(x)}{\partial x} & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \ln\Gamma_n(x) = \pi^{n(n-1)/4} \, \prod_{j=1}^n \Gamma(x + (1 - j)/2) \] +

+

+\[ \frac{\partial \, \ln\Gamma_n(x)}{\partial x} = \sum_{j=1}^n \Psi(x + (1 - j) / 2) \] +

+
Parameters
+ + + +
kNumber of dimensions.
xFunction argument.
+
+
+
Returns
Natural log of the multivariate gamma function.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 57 of file lmgamma.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file log.hpp.

+ +
+
+ +
+
+
+template<typename T , int Rows, int Cols>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Rows, Cols> stan::math::log (const Eigen::Matrix< T, Rows, Cols > & m)
+
+inline
+
+ +

Return the element-wise logarithm of the matrix or vector.

+
Parameters
+ + +
mThe matrix or vector.
+
+
+
Returns
ret(i, j) = log(m(i, j))
+ +

Definition at line 17 of file log.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::log (const vara)
+
+inline
+
+ +

Return the natural log of the specified variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \log x = \frac{1}{x}$.

+

+\[ \mbox{log}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < 0\\ \ln(x) & \mbox{if } x \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0\\ \frac{1}{x} & \mbox{if } x\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable whose log is taken.
+
+
+
Returns
Natural log of variable.
+ +

Definition at line 50 of file log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log10 (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file log10.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::log10 (const vara)
+
+inline
+
+ +

Return the base 10 log of the specified variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \log_{10} x = \frac{1}{x \log 10}$.

+

+\[ \mbox{log10}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < 0\\ \log_{10}(x) & \mbox{if } x \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log10}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0\\ \frac{1}{x \ln10} & \mbox{if } x\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable whose log is taken.
+
+
+
Returns
Base 10 log of variable.
+ +

Definition at line 54 of file log10.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::log10 ()
+
+inline
+
+ +

Return natural logarithm of ten.

+
Returns
Natural logarithm of ten.
+ +

Definition at line 114 of file constants.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log1m (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 16 of file log1m.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::log1m (const stan::math::vara)
+
+inline
+
+ +

The log (1 - x) function for variables.

+

The derivative is given by

+

$\frac{d}{dx} \log (1 - x) = -\frac{1}{1 - x}$.

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
The variable representing log of 1 minus the variable.
+ +

Definition at line 32 of file log1m.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::log1m (x)
+
+inline
+
+ +

Return the natural logarithm of one minus the specified value.

+

The main use of this function is to cut down on intermediate values during algorithmic differentiation.

+

+\[ \mbox{log1m}(x) = \begin{cases} \ln(1-x) & \mbox{if } x \leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log1m}(x)}{\partial x} = \begin{cases} -\frac{1}{1-x} & \mbox{if } x \leq 1 \\ \textrm{NaN} & \mbox{if } x > 1\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
xSpecified value.
+
+
+
Returns
Natural log of one minus x.
+ +

Definition at line 40 of file log1m.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log1m_exp (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 16 of file log1m_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::log1m_exp (const stan::math::vara)
+
+inline
+
+ +

Return the log of 1 minus the exponential of the specified variable.

+ +

Definition at line 38 of file log1m_exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::log1m_exp (const T a)
+
+inline
+
+ +

Calculates the log of 1 minus the exponential of the specified value without overflow log1m_exp(x) = log(1-exp(x)).

+

This function is only defined for x<0

+

+\[ \mbox{log1m\_exp}(x) = \begin{cases} \ln(1-\exp(x)) & \mbox{if } x < 0 \\ \textrm{NaN} & \mbox{if } x \geq 0\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{asinh}(x)}{\partial x} = \begin{cases} -\frac{\exp(x)}{1-\exp(x)} & \mbox{if } x < 0 \\ \textrm{NaN} & \mbox{if } x \geq 0\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 41 of file log1m_exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log1m_inv_logit (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file log1m_inv_logit.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::log1m_inv_logit (const T u)
+
+inline
+
+ +

Returns the natural logarithm of 1 minus the inverse logit of the specified argument.

+

+\[ \mbox{log1m\_inv\_logit}(x) = \begin{cases} -\ln(\exp(x)+1) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log1m\_inv\_logit}(x)}{\partial x} = \begin{cases} -\frac{\exp(x)}{\exp(x)+1} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Template Parameters
+ + +
TScalar type
+
+
+
Parameters
+ + +
uInput.
+
+
+
Returns
log of 1 minus the inverse logit of the input.
+ +

Definition at line 36 of file log1m_inv_logit.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log1p (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 16 of file log1p.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::log1p (const stan::math::vara)
+
+inline
+
+ +

The log (1 + x) function for variables (C99).

+

The derivative is given by

+

$\frac{d}{dx} \log (1 + x) = \frac{1}{1 + x}$.

+
Parameters
+ + +
aThe variable.
+
+
+
Returns
The log of 1 plus the variable.
+ +

Definition at line 34 of file log1p.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::log1p (const T x)
+
+inline
+
+ +

Return the natural logarithm of one plus the specified value.

+

The main use of this function is to cut down on intermediate values during algorithmic differentiation.

+

+\[ \mbox{log1p}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \ln(1+x)& \mbox{if } x\geq -1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log1p}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < -1\\ \frac{1}{1+x} & \mbox{if } x\geq -1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
xSpecified value.
+
+
+
Returns
Natural log of one plus x.
+ +

Definition at line 39 of file log1p.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log1p_exp (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 13 of file log1p_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::log1p_exp (const stan::math::vara)
+
+inline
+
+ +

Return the log of 1 plus the exponential of the specified variable.

+ +

Definition at line 28 of file log1p_exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::log1p_exp (const T a)
+
+inline
+
+ +

Calculates the log of 1 plus the exponential of the specified value without overflow.

+

This function is related to other special functions by:

+

log1p_exp(x)

+

= log1p(exp(a))

+

= log(1 + exp(x))

+

= log_sum_exp(0, x).

+

+\[ \mbox{log1p\_exp}(x) = \begin{cases} \ln(1+\exp(x)) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log1p\_exp}(x)}{\partial x} = \begin{cases} \frac{\exp(x)}{1+\exp(x)} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 44 of file log1p_exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log2 (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 17 of file log2.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::log2 (const T a)
+
+inline
+
+ +

Returns the base 2 logarithm of the argument (C99).

+

The function is defined by:

+

log2(a) = log(a) / std::log(2.0).

+
Template Parameters
+ + +
Ttype of scalar
+
+
+
Parameters
+ + +
aValue.
+
+
+
Returns
Base 2 logarithm of the value.
+ +

Definition at line 25 of file log2.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::log2 ()
+
+inline
+
+ +

Return natural logarithm of two.

+
Returns
Natural logarithm of two.
+ +

Definition at line 35 of file log2.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::log2 (const stan::math::vara)
+
+inline
+
+ +

Returns the base 2 logarithm of the specified variable (C99).

+

See stan::math::log2() for the double-based version.

+

The derivative is

+

$\frac{d}{dx} \log_2 x = \frac{1}{x \log 2}$.

+

+\[ \mbox{log2}(x) = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \\ \log_2(x) & \mbox{if } x\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log2}(x)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x < 0 \\ \frac{1}{x\ln2} & \mbox{if } x\geq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aSpecified variable.
+
+
+
Returns
Base 2 logarithm of the variable.
+ +

Definition at line 53 of file log2.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
var stan::math::log_determinant (const Eigen::Matrix< var, R, C > & m)
+
+inline
+
+ +

Definition at line 13 of file log_determinant.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
T stan::math::log_determinant (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the log absolute determinant of the specified square matrix.

+
Parameters
+ + +
mSpecified matrix.
+
+
+
Returns
log absolute determinant of the matrix.
+
Exceptions
+ + +
std::domain_errorif matrix is not square.
+
+
+ +

Definition at line 18 of file log_determinant.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log_determinant (const Eigen::Matrix< fvar< T >, R, C > & m)
+
+inline
+
+ +

Definition at line 20 of file log_determinant.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::log_determinant_ldlt (stan::math::LDLT_factor< T, R, C > & A)
+
+inline
+
+ +

Definition at line 12 of file log_determinant_ldlt.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + + + + +
var stan::math::log_determinant_ldlt (stan::math::LDLT_factor< var, R, C > & A)
+
+ +

Definition at line 48 of file log_determinant_ldlt.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
var stan::math::log_determinant_spd (const Eigen::Matrix< var, R, C > & m)
+
+inline
+
+ +

Definition at line 15 of file log_determinant_spd.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
T stan::math::log_determinant_spd (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the log absolute determinant of the specified square matrix.

+
Parameters
+ + +
mSpecified matrix.
+
+
+
Returns
log absolute determinant of the matrix.
+
Exceptions
+ + +
std::domain_errorif matrix is not square.
+
+
+ +

Definition at line 19 of file log_determinant_spd.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_diff_exp (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 14 of file log_diff_exp.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T2> stan::math::log_diff_exp (const T1 & x1,
const fvar< T2 > & x2 
)
+
+inline
+
+ +

Definition at line 26 of file log_diff_exp.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T1> stan::math::log_diff_exp (const fvar< T1 > & x1,
const T2 & x2 
)
+
+inline
+
+ +

Definition at line 37 of file log_diff_exp.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::log_diff_exp (const T1 x,
const T2 y 
)
+
+inline
+
+ +

The natural logarithm of the difference of the natural exponentiation of x1 and the natural exponentiation of x2.

+

This function is only defined for x<0

+

+\[ \mbox{log\_diff\_exp}(x, y) = \begin{cases} \textrm{NaN} & \mbox{if } x \leq y\\ \ln(\exp(x)-\exp(y)) & \mbox{if } x > y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log\_diff\_exp}(x, y)}{\partial x} = \begin{cases} \textrm{NaN} & \mbox{if } x \leq y\\ \frac{\exp(x)}{\exp(x)-\exp(y)} & \mbox{if } x > y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log\_diff\_exp}(x, y)}{\partial y} = \begin{cases} \textrm{NaN} & \mbox{if } x \leq y\\ -\frac{\exp(y)}{\exp(x)-\exp(y)} & \mbox{if } x > y \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 50 of file log_diff_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_diff_exp (const stan::math::vara,
const stan::math::varb 
)
+
+inline
+
+ +

Returns the log sum of exponentials.

+ +

Definition at line 54 of file log_diff_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_diff_exp (const stan::math::vara,
const double & b 
)
+
+inline
+
+ +

Returns the log sum of exponentials.

+ +

Definition at line 61 of file log_diff_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_diff_exp (const double & a,
const stan::math::varb 
)
+
+inline
+
+ +

Returns the log sum of exponentials.

+ +

Definition at line 68 of file log_diff_exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_falling_factorial (const fvar< T > & x,
const fvar< T > & n 
)
+
+inline
+
+ +

Definition at line 15 of file log_falling_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_falling_factorial (const double x,
const fvar< T > & n 
)
+
+inline
+
+ +

Definition at line 27 of file log_falling_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_falling_factorial (const fvar< T > & x,
const double n 
)
+
+inline
+
+ +

Definition at line 37 of file log_falling_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::log_falling_factorial (const T1 x,
const T2 n 
)
+
+inline
+
+ +

+\[ \mbox{log\_falling\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \ln (x)_n & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{log\_falling\_factorial}(x, n)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \Psi(x) & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log\_falling\_factorial}(x, n)}{\partial n} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ -\Psi(n) & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 41 of file log_falling_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_falling_factorial (const vara,
const double & b 
)
+
+inline
+
+ +

Definition at line 68 of file log_falling_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_falling_factorial (const vara,
const varb 
)
+
+inline
+
+ +

Definition at line 73 of file log_falling_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_falling_factorial (const double & a,
const varb 
)
+
+inline
+
+ +

Definition at line 78 of file log_falling_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::log_inv_logit (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file log_inv_logit.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::log_inv_logit (const T & u)
+
+inline
+
+ +

Returns the natural logarithm of the inverse logit of the specified argument.

+

+\[ \mbox{log\_inv\_logit}(x) = \begin{cases} \ln\left(\frac{1}{1+\exp(-x)}\right)& \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log\_inv\_logit}(x)}{\partial x} = \begin{cases} \frac{1}{1+\exp(x)} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Template Parameters
+ + +
TScalar type
+
+
+
Parameters
+ + +
uInput.
+
+
+
Returns
log of the inverse logit of the input.
+ +

Definition at line 36 of file log_inv_logit.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::math::log_inv_logit_diff (const T & alpha,
const T & beta 
)
+
+inline
+
+ +

Definition at line 26 of file ordered_logistic_log.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::log_mix (double theta,
double lambda1,
double lambda2 
)
+
+ +

Return the log mixture density with specified mixing proportion and log densities.

+

+\[ \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \log \left( \theta \lambda_1 + (1 - \theta) \lambda_2 \right). \] +

+

+\[ \frac{\partial}{\partial \theta} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = FIXME \] +

+

+\[ \frac{\partial}{\partial \lambda_1} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = FIXME \] +

+

+\[ \frac{\partial}{\partial \lambda_2} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = FIXME \] +

+
Parameters
+ + + + +
[in]thetamixing proportion in [0, 1].
lambda1first log density.
lambda2second log density.
+
+
+
Returns
log mixture of densities in specified proportion
+ +

Definition at line 46 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T_theta , typename T_lambda1 , typename T_lambda2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_theta, T_lambda1, T_lambda2>::type stan::math::log_mix (const T_theta & theta,
const T_lambda1 & lambda1,
const T_lambda2 & lambda2 
)
+
+inline
+
+ +

Return the log mixture density with specified mixing proportion and log densities and its derivative at each.

+

+\[ \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \log \left( \theta \exp(\lambda_1) + (1 - \theta) \exp(\lambda_2) \right). \] +

+

+\[ \frac{\partial}{\partial \theta} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \dfrac{\exp(\lambda_1) - \exp(\lambda_2)} {\left( \theta \exp(\lambda_1) + (1 - \theta) \exp(\lambda_2) \right)} \] +

+

+\[ \frac{\partial}{\partial \lambda_1} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \dfrac{\theta \exp(\lambda_1)} {\left( \theta \exp(\lambda_1) + (1 - \theta) \exp(\lambda_2) \right)} \] +

+

+\[ \frac{\partial}{\partial \lambda_2} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \dfrac{\theta \exp(\lambda_2)} {\left( \theta \exp(\lambda_1) + (1 - \theta) \exp(\lambda_2) \right)} \] +

+
Template Parameters
+ + + + +
T_thetatheta scalar type.
T_lambda1lambda1 scalar type.
T_lambda2lambda2 scalar type.
+
+
+
Parameters
+ + + + +
[in]thetamixing proportion in [0, 1].
[in]lambda1first log density.
[in]lambda2second log density.
+
+
+
Returns
log mixture of densities in specified proportion
+ +

Definition at line 88 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_mix (const fvar< T > & theta,
const fvar< T > & lambda1,
const fvar< T > & lambda2 
)
+
+inline
+
+ +

Return the log mixture density with specified mixing proportion and log densities and its derivative at each.

+

+\[ \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \log \left( \theta \exp(\lambda_1) + (1 - \theta) \exp(\lambda_2) \right). \] +

+

+\[ \frac{\partial}{\partial \theta} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \dfrac{\exp(\lambda_1) - \exp(\lambda_2)} {\left( \theta \exp(\lambda_1) + (1 - \theta) \exp(\lambda_2) \right)} \] +

+

+\[ \frac{\partial}{\partial \lambda_1} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \dfrac{\theta \exp(\lambda_1)} {\left( \theta \exp(\lambda_1) + (1 - \theta) \exp(\lambda_2) \right)} \] +

+

+\[ \frac{\partial}{\partial \lambda_2} \mbox{log\_mix}(\theta, \lambda_1, \lambda_2) = \dfrac{\theta \exp(\lambda_2)} {\left( \theta \exp(\lambda_1) + (1 - \theta) \exp(\lambda_2) \right)} \] +

+
Template Parameters
+ + +
Tscalar type.
+
+
+
Parameters
+ + + + +
[in]thetamixing proportion in [0, 1].
[in]lambda1first log density.
[in]lambda2second log density.
+
+
+
Returns
log mixture of densities in specified proportion
+ +

Definition at line 117 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_mix (const fvar< T > & theta,
const fvar< T > & lambda1,
const double lambda2 
)
+
+inline
+
+ +

Definition at line 143 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_mix (const fvar< T > & theta,
const double lambda1,
const fvar< T > & lambda2 
)
+
+inline
+
+ +

Definition at line 168 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_mix (const double theta,
const fvar< T > & lambda1,
const fvar< T > & lambda2 
)
+
+inline
+
+ +

Definition at line 193 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_mix (const fvar< T > & theta,
const double lambda1,
const double lambda2 
)
+
+inline
+
+ +

Definition at line 217 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_mix (const double theta,
const fvar< T > & lambda1,
const double lambda2 
)
+
+inline
+
+ +

Definition at line 238 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_mix (const double theta,
const double lambda1,
const fvar< T > & lambda2 
)
+
+inline
+
+ +

Definition at line 259 of file log_mix.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::log_mix_partial_helper (const double & theta_val,
const double & lambda1_val,
const double & lambda2_val,
double & one_m_exp_lam2_m_lam1,
double & one_m_t_prod_exp_lam2_m_lam1,
double & one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1 
)
+
+inline
+
+ +

Definition at line 28 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T_theta , typename T_lambda1 , typename T_lambda2 , int N>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::log_mix_partial_helper (const T_theta & theta,
const T_lambda1 & lambda1,
const T_lambda2 & lambda2,
typename boost::math::tools::promote_args< T_theta, T_lambda1, T_lambda2 >::type(&) partials_array[N] 
)
+
+inline
+
+ +

Definition at line 29 of file log_mix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_rising_factorial (const fvar< T > & x,
const fvar< T > & n 
)
+
+inline
+
+ +

Definition at line 16 of file log_rising_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_rising_factorial (const fvar< T > & x,
const double n 
)
+
+inline
+
+ +

Definition at line 28 of file log_rising_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_rising_factorial (const double x,
const fvar< T > & n 
)
+
+inline
+
+ +

Definition at line 39 of file log_rising_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::log_rising_factorial (const T1 x,
const T2 n 
)
+
+inline
+
+ +

+\[ \mbox{log\_rising\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \ln x^{(n)} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{log\_rising\_factorial}(x, n)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \Psi(x+n) - \Psi(x) & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log\_rising\_factorial}(x, n)}{\partial n} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \Psi(x+n) & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+ +

Definition at line 41 of file log_rising_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_rising_factorial (const vara,
const double & b 
)
+
+inline
+
+ +

Definition at line 49 of file log_rising_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_rising_factorial (const vara,
const varb 
)
+
+inline
+
+ +

Definition at line 54 of file log_rising_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_rising_factorial (const double & a,
const varb 
)
+
+inline
+
+ +

Definition at line 59 of file log_rising_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1> stan::math::log_softmax (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > & alpha)
+
+inline
+
+ +

Definition at line 16 of file log_softmax.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::log_softmax (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & v)
+
+inline
+
+ +

Return the natural logarithm of the softmax of the specified vector.

+

$ \log \mbox{softmax}(y) \ = \ y - \log \sum_{k=1}^K \exp(y_k) \ = \ y - \mbox{log\_sum\_exp}(y). $

+

For the log softmax function, the entries in the Jacobian are $ \frac{\partial}{\partial y_m} \mbox{softmax}(y)[k] = \left\{ \begin{array}{ll} 1 - \mbox{softmax}(y)[m] & \mbox{ if } m = k, \mbox{ and} \\[6pt] \mbox{softmax}(y)[m] & \mbox{ if } m \neq k. \end{array} \right. $

+
Template Parameters
+ + +
TScalar type of values in vector.
+
+
+
Parameters
+ + +
[in]vVector to transform.
+
+
+
Returns
Unit simplex result of the softmax transform of the vector.
+ +

Definition at line 44 of file log_softmax.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<var, Eigen::Dynamic, 1> stan::math::log_softmax (const Eigen::Matrix< var, Eigen::Dynamic, 1 > & alpha)
+
+inline
+
+ +

Return the softmax of the specified Eigen vector.

+

Softmax is guaranteed to return a simplex.

+

The gradient calculations are unfolded.

+
Parameters
+ + +
alphaUnconstrained input vector.
+
+
+
Returns
Softmax of the input.
+
Exceptions
+ + +
std::domain_errorIf the input vector is size 0.
+
+
+ +

Definition at line 61 of file log_softmax.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
fvar<T> stan::math::log_sum_exp (const std::vector< fvar< T > > & v)
+
+ +

Definition at line 14 of file log_sum_exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_sum_exp (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 15 of file log_sum_exp.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + + + + +
fvar<T> stan::math::log_sum_exp (const Eigen::Matrix< fvar< T >, R, C > & v)
+
+ +

Definition at line 19 of file log_sum_exp.hpp.

+ +
+
+ +
+
+ + + + + + + + +
double stan::math::log_sum_exp (const std::vector< double > & x)
+
+ +

Return the log of the sum of the exponentiated values of the specified sequence of values.

+

The function is defined as follows to prevent overflow in exponential calculations.

+

$\log \sum_{n=1}^N \exp(x_n) = \max(x) + \log \sum_{n=1}^N \exp(x_n - \max(x))$.

+
Parameters
+ + +
[in]xarray of specified values
+
+
+
Returns
The log of the sum of the exponentiated vector values.
+ +

Definition at line 24 of file log_sum_exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_sum_exp (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 26 of file log_sum_exp.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + + + + +
double stan::math::log_sum_exp (const Eigen::Matrix< double, R, C > & x)
+
+ +

Return the log of the sum of the exponentiated values of the specified matrix of values.

+

The matrix may be a full matrix, a vector, or a row vector.

+

The function is defined as follows to prevent overflow in exponential calculations.

+

$\log \sum_{n=1}^N \exp(x_n) = \max(x) + \log \sum_{n=1}^N \exp(x_n - \max(x))$.

+
Parameters
+ + +
[in]xMatrix of specified values
+
+
+
Returns
The log of the sum of the exponentiated vector values.
+ +

Definition at line 28 of file log_sum_exp.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::log_sum_exp (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 36 of file log_sum_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::log_sum_exp (const std::vector< var > & x)
+
+inline
+
+ +

Returns the log sum of exponentials.

+ +

Definition at line 45 of file log_sum_exp.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::log_sum_exp (const T2 & a,
const T1 & b 
)
+
+inline
+
+ +

Calculates the log sum of exponetials without overflow.

+

$\log (\exp(a) + \exp(b)) = m + \log(\exp(a-m) + \exp(b-m))$,

+

where $m = max(a, b)$.

+

+\[ \mbox{log\_sum\_exp}(x, y) = \begin{cases} \ln(\exp(x)+\exp(y)) & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log\_sum\_exp}(x, y)}{\partial x} = \begin{cases} \frac{\exp(x)}{\exp(x)+\exp(y)} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{log\_sum\_exp}(x, y)}{\partial y} = \begin{cases} \frac{\exp(y)}{\exp(x)+\exp(y)} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
athe first variable
bthe second variable
+
+
+ +

Definition at line 48 of file log_sum_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_sum_exp (const stan::math::vara,
const stan::math::varb 
)
+
+inline
+
+ +

Returns the log sum of exponentials.

+ +

Definition at line 50 of file log_sum_exp.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
var stan::math::log_sum_exp (const Eigen::Matrix< var, R, C > & x)
+
+inline
+
+ +

Returns the log sum of exponentials.

+
Parameters
+ + +
xmatrix
+
+
+ +

Definition at line 54 of file log_sum_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_sum_exp (const stan::math::vara,
const double & b 
)
+
+inline
+
+ +

Returns the log sum of exponentials.

+ +

Definition at line 57 of file log_sum_exp.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::log_sum_exp (const double & a,
const stan::math::varb 
)
+
+inline
+
+ +

Returns the log sum of exponentials.

+ +

Definition at line 64 of file log_sum_exp.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::logical_and (const T1 x1,
const T2 x2 
)
+
+inline
+
+ +

The logical and function which returns 1 if both arguments are unequal to zero and 0 otherwise.

+

Equivalent to x1 != 0 && x2 != 0.

+

+\[ \mbox{operator\&\&}(x, y) = \begin{cases} 0 & \mbox{if } x = 0 \textrm{ or } y=0 \\ 1 & \mbox{if } x, y \neq 0 \\[6pt] 1 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
x1First argument
x2Second argument
+
+
+
Returns
true if both x1 and x2 are not equal to 0.
+ +

Definition at line 30 of file logical_and.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::logical_eq (const T1 x1,
const T2 x2 
)
+
+inline
+
+ +

Return 1 if the first argument is equal to the second.

+

Equivalent to x1 == x2.

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
x1First argument
x2Second argument
+
+
+
Returns
true iff x1 == x2
+ +

Definition at line 19 of file logical_eq.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::logical_gt (const T1 x1,
const T2 x2 
)
+
+inline
+
+ +

Return 1 if the first argument is strictly greater than the second.

+

Equivalent to x1 < x2.

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
x1First argument
x2Second argument
+
+
+
Returns
true iff x1 > x2
+ +

Definition at line 19 of file logical_gt.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::logical_gte (const T1 x1,
const T2 x2 
)
+
+inline
+
+ +

Return 1 if the first argument is greater than or equal to the second.

+

Equivalent to x1 >= x2.

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
x1First argument
x2Second argument
+
+
+
Returns
true iff x1 >= x2
+ +

Definition at line 19 of file logical_gte.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::logical_lt (T1 x1,
T2 x2 
)
+
+inline
+
+ +

Return 1 if the first argument is strictly less than the second.

+

Equivalent to x1 < x2.

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
x1First argument
x2Second argument
+
+
+
Returns
true iff x1 < x2
+ +

Definition at line 20 of file logical_lt.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::logical_lte (const T1 x1,
const T2 x2 
)
+
+inline
+
+ +

Return 1 if the first argument is less than or equal to the second.

+

Equivalent to x1 <= x2.

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
x1First argument
x2Second argument
+
+
+
Returns
true iff x1 <= x2
+ +

Definition at line 19 of file logical_lte.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
int stan::math::logical_negation (const T x)
+
+inline
+
+ +

The logical negation function which returns 1 if the input is equal to zero and 0 otherwise.

+
Template Parameters
+ + +
TType to compare to zero.
+
+
+
Parameters
+ + +
xValue to compare to zero.
+
+
+
Returns
1 if input is equal to zero.
+ +

Definition at line 17 of file logical_negation.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::logical_neq (const T1 x1,
const T2 x2 
)
+
+inline
+
+ +

Return 1 if the first argument is unequal to the second.

+

Equivalent to x1 != x2.

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
x1First argument
x2Second argument
+
+
+
Returns
true iff x1 != x2
+ +

Definition at line 19 of file logical_neq.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::logical_or (T1 x1,
T2 x2 
)
+
+inline
+
+ +

The logical or function which returns 1 if either argument is unequal to zero and 0 otherwise.

+

Equivalent to x1 != 0 || x2 != 0.

+

+\[ \mbox{operator||}(x, y) = \begin{cases} 0 & \mbox{if } x, y=0 \\ 1 & \mbox{if } x \neq 0 \textrm{ or } y\neq0\\[6pt] 1 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
x1First argument
x2Second argument
+
+
+
Returns
true if either x1 or x2 is not equal to 0.
+ +

Definition at line 29 of file logical_or.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::logistic_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 31 of file logistic_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::logistic_cdf (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 31 of file logistic_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::logistic_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 30 of file logistic_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::logistic_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 32 of file logistic_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::logistic_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+inline
+
+ +

Definition at line 142 of file logistic_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::logistic_rng (const double mu,
const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 24 of file logistic_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::logit (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 17 of file logit.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::logit (const T a)
+
+inline
+
+ +

Returns the logit function applied to the argument.

+

The logit function is defined as for $x \in [0, 1]$ by returning the log odds of $x$ treated as a probability,

+

$\mbox{logit}(x) = \log \left( \frac{x}{1 - x} \right)$.

+

The inverse to this function is stan::math::inv_logit.

+

+\[ \mbox{logit}(x) = \begin{cases} \textrm{NaN}& \mbox{if } x < 0 \textrm{ or } x > 1\\ \ln\frac{x}{1-x} & \mbox{if } 0\leq x \leq 1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{logit}(x)}{\partial x} = \begin{cases} \textrm{NaN}& \mbox{if } x < 0 \textrm{ or } x > 1\\ \frac{1}{x-x^2}& \mbox{if } 0\leq x\leq 1 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aArgument.
+
+
+
Returns
Logit of the argument.
+ +

Definition at line 44 of file logit.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::lognormal_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 25 of file lognormal_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::lognormal_cdf (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 25 of file lognormal_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::lognormal_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 25 of file lognormal_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::lognormal_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 33 of file lognormal_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::lognormal_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+inline
+
+ +

Definition at line 158 of file lognormal_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::lognormal_rng (const double mu,
const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 21 of file lognormal_rng.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TL , typename TU >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T, TL, TU>::type stan::math::lub_constrain (const T x,
TL lb,
TU ub 
)
+
+inline
+
+ +

Return the lower- and upper-bounded scalar derived by transforming the specified free scalar given the specified lower and upper bounds.

+

The transform is the transformed and scaled inverse logit,

+

$f(x) = L + (U - L) \mbox{logit}^{-1}(x)$

+

If the lower bound is negative infinity and upper bound finite, this function reduces to ub_constrain(x, ub). If the upper bound is positive infinity and the lower bound finite, this function reduces to lb_constrain(x, lb). If the upper bound is positive infinity and the lower bound negative infinity, this function reduces to identity_constrain(x).

+
Parameters
+ + + + +
xFree scalar to transform.
lbLower bound.
ubUpper bound.
+
+
+
Returns
Lower- and upper-bounded scalar derived from transforming the free scalar.
+
Template Parameters
+ + + + +
TType of scalar.
TLType of lower bound.
TUType of upper bound.
+
+
+
Exceptions
+ + +
std::domain_errorif ub <= lb
+
+
+ +

Definition at line 45 of file lub_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TL , typename TU >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T, TL, TU>::type stan::math::lub_constrain (const T x,
const TL lb,
const TU ub,
T & lp 
)
+
+ +

Return the lower- and upper-bounded scalar derived by transforming the specified free scalar given the specified lower and upper bounds and increment the specified log probability with the log absolute Jacobian determinant.

+

The transform is as defined in lub_constrain(T, double, double). The log absolute Jacobian determinant is given by

+

$\log \left| \frac{d}{dx} \left( L + (U-L) \mbox{logit}^{-1}(x) \right) \right|$

+

$ {} = \log | (U-L) \, (\mbox{logit}^{-1}(x)) \, (1 - \mbox{logit}^{-1}(x)) |$

+

$ {} = \log (U - L) + \log (\mbox{logit}^{-1}(x)) + \log (1 - \mbox{logit}^{-1}(x))$

+

If the lower bound is negative infinity and upper bound finite, this function reduces to ub_constrain(x, ub, lp). If the upper bound is positive infinity and the lower bound finite, this function reduces to lb_constrain(x, lb, lp). If the upper bound is positive infinity and the lower bound negative infinity, this function reduces to identity_constrain(x, lp).

+
Parameters
+ + + + + +
xFree scalar to transform.
lbLower bound.
ubUpper bound.
lpLog probability scalar reference.
+
+
+
Returns
Lower- and upper-bounded scalar derived from transforming the free scalar.
+
Template Parameters
+ + + + +
TType of scalar.
TLType of lower bound.
TUType of upper bound.
+
+
+
Exceptions
+ + +
std::domain_errorif ub <= lb
+
+
+ +

Definition at line 115 of file lub_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TL , typename TU >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T, TL, TU>::type stan::math::lub_free (const T y,
TL lb,
TU ub 
)
+
+inline
+
+ +

Return the unconstrained scalar that transforms to the specified lower- and upper-bounded scalar given the specified bounds.

+

The transfrom in lub_constrain(T, double, double), is reversed by a transformed and scaled logit,

+

$f^{-1}(y) = \mbox{logit}(\frac{y - L}{U - L})$

+

where $U$ and $L$ are the lower and upper bounds.

+

If the lower bound is negative infinity and upper bound finite, this function reduces to ub_free(y, ub). If the upper bound is positive infinity and the lower bound finite, this function reduces to lb_free(x, lb). If the upper bound is positive infinity and the lower bound negative infinity, this function reduces to identity_free(y).

+
Template Parameters
+ + +
TType of scalar.
+
+
+
Parameters
+ + + + +
yScalar input.
lbLower bound.
ubUpper bound.
+
+
+
Returns
The free scalar that transforms to the input scalar given the bounds.
+
Exceptions
+ + +
std::invalid_argumentif the lower bound is greater than the upper bound, y is less than the lower bound, or y is greater than the upper bound
+
+
+ +

Definition at line 47 of file lub_free.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::machine_precision ()
+
+inline
+
+ +

Returns the difference between 1.0 and the next value representable.

+
Returns
Minimum positive number.
+ +

Definition at line 151 of file constants.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
const Eigen::Array<T, Eigen::Dynamic, 1> stan::math::make_nu (const T eta,
const size_t K 
)
+
+ +

This function calculates the degrees of freedom for the t distribution that corresponds to the shape parameter in the Lewandowski et.

+

al. distribution

+
Parameters
+ + + +
etahyperparameter on (0, inf), eta = 1 <-> correlation matrix is uniform
Knumber of variables in covariance matrix
+
+
+ +

Definition at line 22 of file make_nu.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_Mu , typename T_Sigma , typename T_D >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_Mu, T_Sigma, T_D>::type stan::math::matrix_normal_prec_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_Mu, Eigen::Dynamic, Eigen::Dynamic > & Mu,
const Eigen::Matrix< T_Sigma, Eigen::Dynamic, Eigen::Dynamic > & Sigma,
const Eigen::Matrix< T_D, Eigen::Dynamic, Eigen::Dynamic > & D 
)
+
+ +

The log of the matrix normal density for the given y, mu, Sigma and D where Sigma and D are given as precision matrices, not covariance matrices.

+
Parameters
+ + + + + +
yAn mxn matrix.
MuThe mean matrix.
SigmaThe mxm inverse covariance matrix (i.e., the precision matrix) of the rows of y.
DThe nxn inverse covariance matrix (i.e., the precision matrix) of the columns of y.
+
+
+
Returns
The log of the matrix normal density.
+
Exceptions
+ + +
std::domain_errorif Sigma or D are not square, not symmetric, or not semi-positive definite.
+
+
+
Template Parameters
+ + + + + +
T_yType of scalar.
T_MuType of location.
T_SigmaType of Sigma.
T_DType of D.
+
+
+ +

Definition at line 43 of file matrix_normal_prec_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_Mu , typename T_Sigma , typename T_D >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_Mu, T_Sigma, T_D>::type stan::math::matrix_normal_prec_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_Mu, Eigen::Dynamic, Eigen::Dynamic > & Mu,
const Eigen::Matrix< T_Sigma, Eigen::Dynamic, Eigen::Dynamic > & Sigma,
const Eigen::Matrix< T_D, Eigen::Dynamic, Eigen::Dynamic > & D 
)
+
+ +

Definition at line 112 of file matrix_normal_prec_log.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
int stan::math::max (const std::vector< int > & x)
+
+inline
+
+ +

Returns the maximum coefficient in the specified column vector.

+
Parameters
+ + +
xSpecified vector.
+
+
+
Returns
Maximum coefficient value in the vector.
+
Template Parameters
+ + +
Typeof values being compared and returned
+
+
+
Exceptions
+ + +
std::domain_errorIf the size of the vector is zero.
+
+
+ +

Definition at line 21 of file max.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::max (const std::vector< T > & x)
+
+inline
+
+ +

Returns the maximum coefficient in the specified column vector.

+
Parameters
+ + +
xSpecified vector.
+
+
+
Returns
Maximum coefficient value in the vector.
+
Template Parameters
+ + +
TType of values being compared and returned
+
+
+ +

Definition at line 39 of file max.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
T stan::math::max (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the maximum coefficient in the specified vector, row vector, or matrix.

+
Parameters
+ + +
mSpecified vector, row vector, or matrix.
+
+
+
Returns
Maximum coefficient value in the vector.
+ +

Definition at line 56 of file max.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::mdivide_left (const Eigen::Matrix< fvar< T >, R1, C1 > & A,
const Eigen::Matrix< fvar< T >, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 24 of file mdivide_left.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_left (const Eigen::Matrix< T1, R1, C1 > & A,
const Eigen::Matrix< T2, R2, C2 > & b 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b.

+
Parameters
+ + + +
AMatrix.
bRight hand side matrix or vector.
+
+
+
Returns
x = A^-1 b, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif A is not square or the rows of b don't match the size of A.
+
+
+ +

Definition at line 25 of file mdivide_left.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::mdivide_left (const Eigen::Matrix< double, R1, C1 > & A,
const Eigen::Matrix< fvar< T >, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 68 of file mdivide_left.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::mdivide_left (const Eigen::Matrix< fvar< T >, R1, C1 > & A,
const Eigen::Matrix< double, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 94 of file mdivide_left.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left (const Eigen::Matrix< var, R1, C1 > & A,
const Eigen::Matrix< var, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 274 of file mdivide_left.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left (const Eigen::Matrix< var, R1, C1 > & A,
const Eigen::Matrix< double, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 301 of file mdivide_left.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left (const Eigen::Matrix< double, R1, C1 > & A,
const Eigen::Matrix< var, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 328 of file mdivide_left.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2, typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T2>, R1, C2> stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< double, R1, C1 > & A,
const Eigen::Matrix< fvar< T2 >, R2, C2 > & b 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b given an LDLT_factor of A.

+
Parameters
+ + + +
ALDLT_factor
bRight hand side matrix or vector.
+
+
+
Returns
x = b A^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif rows of b don't match the size of A.
+
+
+ +

Definition at line 25 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2, typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< T1, R1, C1 > & A,
const Eigen::Matrix< T2, R2, C2 > & b 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b given an LDLT_factor of A.

+
Parameters
+ + + +
ALDLT_factor
bRight hand side matrix or vector.
+
+
+
Returns
x = b A^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif rows of b don't match the size of A.
+
+
+ +

Definition at line 26 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< var, R1, C1 > & A,
const Eigen::Matrix< var, R2, C2 > & b 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b given an LDLT_factor of A.

+
Parameters
+ + + +
ALDLT_factor
bRight hand side matrix or vector.
+
+
+
Returns
x = b A^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif rows of b don't match the size of A.
+
+
+ +

Definition at line 246 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< var, R1, C1 > & A,
const Eigen::Matrix< double, R2, C2 > & b 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b given an LDLT_factor of A.

+
Parameters
+ + + +
ALDLT_factor
bRight hand side matrix or vector.
+
+
+
Returns
x = b A^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif rows of b don't match the size of A.
+
+
+ +

Definition at line 274 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< double, R1, C1 > & A,
const Eigen::Matrix< var, R2, C2 > & b 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b given an LDLT_factor of A.

+
Parameters
+ + + +
ALDLT_factor
bRight hand side matrix or vector.
+
+
+
Returns
x = b A^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif rows of b don't match the size of A.
+
+
+ +

Definition at line 302 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_left_spd (const Eigen::Matrix< T1, R1, C1 > & A,
const Eigen::Matrix< T2, R2, C2 > & b 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b where A is symmetric positive definite.

+
Parameters
+ + + +
AMatrix.
bRight hand side matrix or vector.
+
+
+
Returns
x = A^-1 b, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif A is not square or the rows of b don't match the size of A.
+
+
+ +

Definition at line 28 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_spd (const Eigen::Matrix< var, R1, C1 > & A,
const Eigen::Matrix< var, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 248 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_spd (const Eigen::Matrix< var, R1, C1 > & A,
const Eigen::Matrix< double, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 275 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_spd (const Eigen::Matrix< double, R1, C1 > & A,
const Eigen::Matrix< var, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 302 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+
+template<int TriView, typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_left_tri (const Eigen::Matrix< T1, R1, C1 > & A,
const Eigen::Matrix< T2, R2, C2 > & b 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b when A is triangular.

+
Parameters
+ + + +
ATriangular matrix. Specify upper or lower with TriView being Eigen::Upper or Eigen::Lower.
bRight hand side matrix or vector.
+
+
+
Returns
x = A^-1 b, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif A is not square or the rows of b don't match the size of A.
+
+
+ +

Definition at line 27 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+
+template<int TriView, typename T , int R1, int C1>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R1, C1> stan::math::mdivide_left_tri (const Eigen::Matrix< T, R1, C1 > & A)
+
+inline
+
+ +

Returns the solution of the system Ax=b when A is triangular and b=I.

+
Parameters
+ + +
ATriangular matrix. Specify upper or lower with TriView being Eigen::Upper or Eigen::Lower.
+
+
+
Returns
x = A^-1 .
+
Exceptions
+ + +
std::domain_errorif A is not square
+
+
+ +

Definition at line 50 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+
+template<int TriView, int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_tri (const Eigen::Matrix< var, R1, C1 > & A,
const Eigen::Matrix< var, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 304 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+
+template<int TriView, int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_tri (const Eigen::Matrix< double, R1, C1 > & A,
const Eigen::Matrix< var, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 330 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+
+template<int TriView, int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C2> stan::math::mdivide_left_tri (const Eigen::Matrix< var, R1, C1 > & A,
const Eigen::Matrix< double, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 356 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_left_tri_low (const Eigen::Matrix< T1, R1, C1 > & A,
const Eigen::Matrix< T2, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 16 of file mdivide_left_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::mdivide_left_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > & A,
const Eigen::Matrix< fvar< T >, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 22 of file mdivide_left_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R1, C1> stan::math::mdivide_left_tri_low (const Eigen::Matrix< T, R1, C1 > & A)
+
+inline
+
+ +

Definition at line 32 of file mdivide_left_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::mdivide_left_tri_low (const Eigen::Matrix< double, R1, C1 > & A,
const Eigen::Matrix< fvar< T >, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 68 of file mdivide_left_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::mdivide_left_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > & A,
const Eigen::Matrix< double, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 109 of file mdivide_left_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::mdivide_right (const Eigen::Matrix< fvar< T >, R1, C1 > & A,
const Eigen::Matrix< fvar< T >, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 24 of file mdivide_right.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_right (const Eigen::Matrix< T1, R1, C1 > & b,
const Eigen::Matrix< T2, R2, C2 > & A 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b.

+
Parameters
+ + + +
AMatrix.
bRight hand side matrix or vector.
+
+
+
Returns
x = b A^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif A is not square or the rows of b don't match the size of A.
+
+
+ +

Definition at line 26 of file mdivide_right.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::mdivide_right (const Eigen::Matrix< fvar< T >, R1, C1 > & A,
const Eigen::Matrix< double, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 68 of file mdivide_right.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::mdivide_right (const Eigen::Matrix< double, R1, C1 > & A,
const Eigen::Matrix< fvar< T >, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 95 of file mdivide_right.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_right_ldlt (const Eigen::Matrix< T1, R1, C1 > & b,
const stan::math::LDLT_factor< T2, R2, C2 > & A 
)
+
+inline
+
+ +

Returns the solution of the system xA=b given an LDLT_factor of A.

+
Parameters
+ + + +
ALDLT_factor
bRight hand side matrix or vector.
+
+
+
Returns
x = A^-1 b, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif rows of b don't match the size of A.
+
+
+ +

Definition at line 26 of file mdivide_right_ldlt.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<double, R1, C2> stan::math::mdivide_right_ldlt (const Eigen::Matrix< double, R1, C1 > & b,
const stan::math::LDLT_factor< double, R2, C2 > & A 
)
+
+inline
+
+ +

Definition at line 38 of file mdivide_right_ldlt.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_right_spd (const Eigen::Matrix< T1, R1, C1 > & b,
const Eigen::Matrix< T2, R2, C2 > & A 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b where A is symmetric positive definite.

+
Parameters
+ + + +
AMatrix.
bRight hand side matrix or vector.
+
+
+
Returns
x = b A^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif A is not square or the rows of b don't match the size of A.
+
+
+ +

Definition at line 29 of file mdivide_right_spd.hpp.

+ +
+
+ +
+
+
+template<int TriView, typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_right_tri (const Eigen::Matrix< T1, R1, C1 > & b,
const Eigen::Matrix< T2, R2, C2 > & A 
)
+
+inline
+
+ +

Returns the solution of the system Ax=b when A is triangular.

+
Parameters
+ + + +
ATriangular matrix. Specify upper or lower with TriView being Eigen::Upper or Eigen::Lower.
bRight hand side matrix or vector.
+
+
+
Returns
x = b A^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif A is not square or the rows of b don't match the size of A.
+
+
+ +

Definition at line 29 of file mdivide_right_tri.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::mdivide_right_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > & A,
const Eigen::Matrix< fvar< T >, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 22 of file mdivide_right_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R1, C2> stan::math::mdivide_right_tri_low (const Eigen::Matrix< T1, R1, C1 > & b,
const Eigen::Matrix< T2, R2, C2 > & A 
)
+
+inline
+
+ +

Returns the solution of the system tri(A)x=b when tri(A) is a lower triangular view of the matrix A.

+
Parameters
+ + + +
AMatrix.
bRight hand side matrix or vector.
+
+
+
Returns
x = b * tri(A)^-1, solution of the linear system.
+
Exceptions
+ + +
std::domain_errorif A is not square or the rows of b don't match the size of A.
+
+
+ +

Definition at line 25 of file mdivide_right_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::mdivide_right_tri_low (const Eigen::Matrix< fvar< T >, R1, C1 > & A,
const Eigen::Matrix< double, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 68 of file mdivide_right_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::mdivide_right_tri_low (const Eigen::Matrix< double, R1, C1 > & A,
const Eigen::Matrix< fvar< T >, R2, C2 > & b 
)
+
+inline
+
+ +

Definition at line 103 of file mdivide_right_tri_low.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::mean (const std::vector< T > & v)
+
+inline
+
+ +

Returns the sample mean (i.e., average) of the coefficients in the specified standard vector.

+
Parameters
+ + +
vSpecified vector.
+
+
+
Returns
Sample mean of vector coefficients.
+
Exceptions
+ + +
std::domain_errorif the size of the vector is less than 1.
+
+
+ +

Definition at line 23 of file mean.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::mean (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the sample mean (i.e., average) of the coefficients in the specified vector, row vector, or matrix.

+
Parameters
+ + +
mSpecified vector, row vector, or matrix.
+
+
+
Returns
Sample mean of vector coefficients.
+ +

Definition at line 40 of file mean.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
int stan::math::min (const std::vector< int > & x)
+
+inline
+
+ +

Returns the minimum coefficient in the specified column vector.

+
Parameters
+ + +
xSpecified vector.
+
+
+
Returns
Minimum coefficient value in the vector.
+
Template Parameters
+ + +
Typeof values being compared and returned
+
+
+ +

Definition at line 20 of file min.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::min (const std::vector< T > & x)
+
+inline
+
+ +

Returns the minimum coefficient in the specified column vector.

+
Parameters
+ + +
xSpecified vector.
+
+
+
Returns
Minimum coefficient value in the vector.
+
Template Parameters
+ + +
Typeof values being compared and returned
+
+
+ +

Definition at line 38 of file min.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
T stan::math::min (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the minimum coefficient in the specified matrix, vector, or row vector.

+
Parameters
+ + +
mSpecified matrix, vector, or row vector.
+
+
+
Returns
Minimum coefficient value in the vector.
+ +

Definition at line 55 of file min.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::minus (const T & x)
+
+inline
+
+ +

Returns the negation of the specified scalar or matrix.

+
Template Parameters
+ + +
TType of subtrahend.
+
+
+
Parameters
+ + +
xSubtrahend.
+
+
+
Returns
Negation of subtrahend.
+ +

Definition at line 16 of file minus.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::modified_bessel_first_kind (int v,
const fvar< T > & z 
)
+
+inline
+
+ +

Definition at line 15 of file modified_bessel_first_kind.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::modified_bessel_first_kind (const int & v,
const vara 
)
+
+inline
+
+ +

Definition at line 27 of file modified_bessel_first_kind.hpp.

+ +
+
+ +
+
+
+template<typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T2 stan::math::modified_bessel_first_kind (const int v,
const T2 z 
)
+
+inline
+
+ +

+\[ \mbox{modified\_bessel\_first\_kind}(v, z) = \begin{cases} I_v(z) & \mbox{if } -\infty\leq z \leq \infty \\[6pt] \textrm{error} & \mbox{if } z = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{modified\_bessel\_first\_kind}(v, z)}{\partial z} = \begin{cases} \frac{\partial\, I_v(z)}{\partial z} & \mbox{if } -\infty\leq z\leq \infty \\[6pt] \textrm{error} & \mbox{if } z = \textrm{NaN} \end{cases} \] +

+

+\[ {I_v}(z) = \left(\frac{1}{2}z\right)^v\sum_{k=0}^\infty \frac{\left(\frac{1}{4}z^2\right)^k}{k!\Gamma(v+k+1)} \] +

+

+\[ \frac{\partial \, I_v(z)}{\partial z} = I_{v-1}(z)-\frac{v}{z}I_v(z) \] +

+ +

Definition at line 39 of file modified_bessel_first_kind.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::modified_bessel_second_kind (int v,
const fvar< T > & z 
)
+
+inline
+
+ +

Definition at line 15 of file modified_bessel_second_kind.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::modified_bessel_second_kind (const int & v,
const vara 
)
+
+inline
+
+ +

Definition at line 27 of file modified_bessel_second_kind.hpp.

+ +
+
+ +
+
+
+template<typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T2 stan::math::modified_bessel_second_kind (const int v,
const T2 z 
)
+
+inline
+
+ +

+\[ \mbox{modified\_bessel\_second\_kind}(v, z) = \begin{cases} \textrm{error} & \mbox{if } z \leq 0 \\ K_v(z) & \mbox{if } z > 0 \\[6pt] \textrm{NaN} & \mbox{if } z = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{modified\_bessel\_second\_kind}(v, z)}{\partial z} = \begin{cases} \textrm{error} & \mbox{if } z \leq 0 \\ \frac{\partial\, K_v(z)}{\partial z} & \mbox{if } z > 0 \\[6pt] \textrm{NaN} & \mbox{if } z = \textrm{NaN} \end{cases} \] +

+

+\[ {K_v}(z) = \frac{\pi}{2}\cdot\frac{I_{-v}(z) - I_{v}(z)}{\sin(v\pi)} \] +

+

+\[ \frac{\partial \, K_v(z)}{\partial z} = -\frac{v}{z}K_v(z)-K_{v-1}(z) \] +

+ +

Definition at line 42 of file modified_bessel_second_kind.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::modulus (const int x,
const int y 
)
+
+inline
+
+ +

Definition at line 10 of file modulus.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_covar , typename T_w >
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_covar, T_w>::type stan::math::multi_gp_cholesky_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > & L,
const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > & w 
)
+
+ +

The log of a multivariate Gaussian Process for the given y, w, and a Cholesky factor L of the kernel matrix Sigma.

+

Sigma = LL', a square, semi-positive definite matrix.. y is a dxN matrix, where each column is a different observation and each row is a different output dimension. The Gaussian Process is assumed to have a scaled kernel matrix with a different scale for each output dimension. This distribution is equivalent to: for (i in 1:d) row(y, i) ~ multi_normal(0, (1/w[i])*LL').

+
Parameters
+ + + + +
yA dxN matrix
LThe Cholesky decomposition of a kernel matrix
wA d-dimensional vector of positve inverse scale parameters for each output.
+
+
+
Returns
The log of the multivariate GP density.
+
Exceptions
+ + +
std::domain_errorif Sigma is not square, not symmetric, or not semi-positive definite.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_covarType of kernel.
T_wType of weight.
+
+
+ +

Definition at line 43 of file multi_gp_cholesky_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_covar , typename T_w >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_covar, T_w>::type stan::math::multi_gp_cholesky_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > & L,
const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > & w 
)
+
+inline
+
+ +

Definition at line 106 of file multi_gp_cholesky_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_covar , typename T_w >
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_covar, T_w>::type stan::math::multi_gp_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > & Sigma,
const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > & w 
)
+
+ +

The log of a multivariate Gaussian Process for the given y, Sigma, and w.

+

y is a dxN matrix, where each column is a different observation and each row is a different output dimension. The Gaussian Process is assumed to have a scaled kernel matrix with a different scale for each output dimension. This distribution is equivalent to: for (i in 1:d) row(y, i) ~ multi_normal(0, (1/w[i])*Sigma).

+
Parameters
+ + + + +
yA dxN matrix
SigmaThe NxN kernel matrix
wA d-dimensional vector of positve inverse scale parameters for each output.
+
+
+
Returns
The log of the multivariate GP density.
+
Exceptions
+ + +
std::domain_errorif Sigma is not square, not symmetric, or not semi-positive definite.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_covarType of kernel.
T_wType of weight.
+
+
+ +

Definition at line 45 of file multi_gp_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_covar , typename T_w >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_covar, T_w>::type stan::math::multi_gp_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & y,
const Eigen::Matrix< T_covar, Eigen::Dynamic, Eigen::Dynamic > & Sigma,
const Eigen::Matrix< T_w, Eigen::Dynamic, 1 > & w 
)
+
+inline
+
+ +

Definition at line 112 of file multi_gp_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_covar >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_covar>::type stan::math::multi_normal_cholesky_log (const T_y & y,
const T_loc & mu,
const T_covar & L 
)
+
+ +

The log of the multivariate normal density for the given y, mu, and a Cholesky factor L of the variance matrix.

+

Sigma = LL', a square, semi-positive definite matrix.

+
Parameters
+ + + + +
yA scalar vector
muThe mean vector of the multivariate normal distribution.
LThe Cholesky decomposition of a variance matrix of the multivariate normal distribution
+
+
+
Returns
The log of the multivariate normal density.
+
Exceptions
+ + +
std::domain_errorif LL' is not square, not symmetric, or not semi-positive definite.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_locType of location.
T_covarType of scale.
+
+
+ +

Definition at line 47 of file multi_normal_cholesky_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_covar >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_covar>::type stan::math::multi_normal_cholesky_log (const T_y & y,
const T_loc & mu,
const T_covar & L 
)
+
+inline
+
+ +

Definition at line 153 of file multi_normal_cholesky_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::VectorXd stan::math::multi_normal_cholesky_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > & mu,
const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & S,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 29 of file multi_normal_cholesky_rng.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_covar >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_covar>::type stan::math::multi_normal_log (const T_y & y,
const T_loc & mu,
const T_covar & Sigma 
)
+
+ +

Definition at line 27 of file multi_normal_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_covar >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_covar>::type stan::math::multi_normal_log (const T_y & y,
const T_loc & mu,
const T_covar & Sigma 
)
+
+inline
+
+ +

Definition at line 128 of file multi_normal_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_covar >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_covar>::type stan::math::multi_normal_prec_log (const T_y & y,
const T_loc & mu,
const T_covar & Sigma 
)
+
+ +

Definition at line 35 of file multi_normal_prec_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_covar >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_covar>::type stan::math::multi_normal_prec_log (const T_y & y,
const T_loc & mu,
const T_covar & Sigma 
)
+
+inline
+
+ +

Definition at line 143 of file multi_normal_prec_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::VectorXd stan::math::multi_normal_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > & mu,
const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & S,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 24 of file multi_normal_rng.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_dof , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_loc, T_scale>::type stan::math::multi_student_t_log (const T_y & y,
const T_dof & nu,
const T_loc & mu,
const T_scale & Sigma 
)
+
+ +

Return the log of the multivariate Student t distribution at the specified arguments.

+
Template Parameters
+ + +
proptoCarry out calculations up to a proportion
+
+
+ +

Definition at line 35 of file multi_student_t_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_loc, T_scale>::type stan::math::multi_student_t_log (const T_y & y,
const T_dof & nu,
const T_loc & mu,
const T_scale & Sigma 
)
+
+inline
+
+ +

Definition at line 170 of file multi_student_t_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::VectorXd stan::math::multi_student_t_rng (const double nu,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & mu,
const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & s,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 29 of file multi_student_t_rng.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_prob >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::multinomial_log (const std::vector< int > & ns,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta 
)
+
+ +

Definition at line 24 of file multinomial_log.hpp.

+ +
+
+ +
+
+
+template<typename T_prob >
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_prob>::type stan::math::multinomial_log (const std::vector< int > & ns,
const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > & theta 
)
+
+ +

Definition at line 59 of file multinomial_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
std::vector<int> stan::math::multinomial_rng (const Eigen::Matrix< double, Eigen::Dynamic, 1 > & theta,
const int N,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 23 of file multinomial_rng.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::multiply (const Eigen::Matrix< fvar< T >, R1, C1 > & m,
const fvar< T > & c 
)
+
+inline
+
+ +

Definition at line 21 of file multiply.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_arithmetic<T>::value, Eigen::Matrix<double, R, C> >::type stan::math::multiply (const Eigen::Matrix< double, R, C > & m,
c 
)
+
+inline
+
+ +

Return specified matrix multiplied by specified scalar.

+
Template Parameters
+ + + +
RRow type for matrix.
CColumn type for matrix.
+
+
+
Parameters
+ + + +
mMatrix.
cScalar.
+
+
+
Returns
Product of matrix and scalar.
+ +

Definition at line 26 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c< (boost::is_scalar<T1>::value || boost::is_same<T1, var>::value) && (boost::is_scalar<T2>::value || boost::is_same<T2, var>::value), typename boost::math::tools::promote_args<T1, T2>::type>::type stan::math::multiply (const T1 & v,
const T2 & c 
)
+
+inline
+
+ +

Return the product of two scalars.

+
Parameters
+ + + +
[in]vFirst scalar.
[in]cSpecified scalar.
+
+
+
Returns
Product of scalars.
+ +

Definition at line 32 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R2, C2> stan::math::multiply (const Eigen::Matrix< fvar< T >, R2, C2 > & m,
const double c 
)
+
+inline
+
+ +

Definition at line 33 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R2, C2> stan::math::multiply (const T1 & c,
const Eigen::Matrix< T2, R2, C2 > & m 
)
+
+inline
+
+ +

Return the product of scalar and matrix.

+
Parameters
+ + + +
[in]cSpecified scalar.
[in]mMatrix.
+
+
+
Returns
Product of scalar and matrix.
+ +

Definition at line 44 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::multiply (const Eigen::Matrix< double, R1, C1 > & m,
const fvar< T > & c 
)
+
+inline
+
+ +

Definition at line 45 of file multiply.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_arithmetic<T>::value, Eigen::Matrix<double, R, C> >::type stan::math::multiply (c,
const Eigen::Matrix< double, R, C > & m 
)
+
+inline
+
+ +

Return specified scalar multiplied by specified matrix.

+
Template Parameters
+ + + +
RRow type for matrix.
CColumn type for matrix.
+
+
+
Parameters
+ + + +
cScalar.
mMatrix.
+
+
+
Returns
Product of scalar and matrix.
+ +

Definition at line 46 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::multiply (const fvar< T > & c,
const Eigen::Matrix< fvar< T >, R1, C1 > & m 
)
+
+inline
+
+ +

Definition at line 57 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T1 , int R1, int C1, typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R1, C1> stan::math::multiply (const Eigen::Matrix< T1, R1, C1 > & m,
const T2 & c 
)
+
+inline
+
+ +

Return the product of scalar and matrix.

+
Parameters
+ + + +
[in]mMatrix.
[in]cSpecified scalar.
+
+
+
Returns
Product of scalar and matrix.
+ +

Definition at line 58 of file multiply.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<double, R1, C2> stan::math::multiply (const Eigen::Matrix< double, R1, C1 > & m1,
const Eigen::Matrix< double, R2, C2 > & m2 
)
+
+inline
+
+ +

Return the product of the specified matrices.

+

The number of columns in the first matrix must be the same as the number of rows in the second matrix.

Parameters
+ + + +
m1First matrix.
m2Second matrix.
+
+
+
Returns
The product of the first and second matrices.
+
Exceptions
+ + +
std::domain_errorif the number of columns of m1 does not match the number of rows of m2.
+
+
+ +

Definition at line 63 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::multiply (const double c,
const Eigen::Matrix< fvar< T >, R1, C1 > & m 
)
+
+inline
+
+ +

Definition at line 64 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C1> stan::math::multiply (const fvar< T > & c,
const Eigen::Matrix< double, R1, C1 > & m 
)
+
+inline
+
+ +

Definition at line 71 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c< boost::is_same<T1, var>::value || boost::is_same<T2, var>::value, Eigen::Matrix<var, R1, C2> >::type stan::math::multiply (const Eigen::Matrix< T1, R1, C1 > & m1,
const Eigen::Matrix< T2, R2, C2 > & m2 
)
+
+inline
+
+ +

Return the product of the specified matrices.

+

The number of columns in the first matrix must be the same as the number of rows in the second matrix.

Parameters
+ + + +
[in]m1First matrix.
[in]m2Second matrix.
+
+
+
Returns
The product of the first and second matrices.
+
Exceptions
+ + +
std::domain_errorif the number of columns of m1 does not match the number of rows of m2.
+
+
+ +

Definition at line 77 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::multiply (const Eigen::Matrix< fvar< T >, R1, C1 > & m1,
const Eigen::Matrix< fvar< T >, R2, C2 > & m2 
)
+
+inline
+
+ +

Definition at line 78 of file multiply.hpp.

+ +
+
+ +
+
+
+template<int C1, int R2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::multiply (const Eigen::Matrix< double, 1, C1 > & rv,
const Eigen::Matrix< double, R2, 1 > & v 
)
+
+inline
+
+ +

Return the scalar product of the specified row vector and specified column vector.

+

The return is the same as the dot product. The two vectors must be the same size.

Parameters
+ + + +
rvRow vector.
vColumn vector.
+
+
+
Returns
Scalar result of multiplying row vector by column vector.
+
Exceptions
+ + +
std::domain_errorif rv and v are not the same size.
+
+
+ +

Definition at line 81 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::multiply (const Eigen::Matrix< fvar< T >, R1, C1 > & m1,
const Eigen::Matrix< double, R2, C2 > & m2 
)
+
+inline
+
+ +

Definition at line 97 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, C2> stan::math::multiply (const Eigen::Matrix< double, R1, C1 > & m1,
const Eigen::Matrix< fvar< T >, R2, C2 > & m2 
)
+
+inline
+
+ +

Definition at line 116 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T1 , int C1, typename T2 , int R2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c< boost::is_same<T1, var>::value || boost::is_same<T2, var>::value, var >::type stan::math::multiply (const Eigen::Matrix< T1, 1, C1 > & rv,
const Eigen::Matrix< T2, R2, 1 > & v 
)
+
+inline
+
+ +

Return the scalar product of the specified row vector and specified column vector.

+

The return is the same as the dot product. The two vectors must be the same size.

Parameters
+ + + +
[in]rvRow vector.
[in]vColumn vector.
+
+
+
Returns
Scalar result of multiplying row vector by column vector.
+
Exceptions
+ + +
std::domain_errorif rv and v are not the same size
+
+
+ +

Definition at line 129 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int C1, int R2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::multiply (const Eigen::Matrix< fvar< T >, 1, C1 > & rv,
const Eigen::Matrix< fvar< T >, R2, 1 > & v 
)
+
+inline
+
+ +

Definition at line 135 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int C1, int R2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::multiply (const Eigen::Matrix< fvar< T >, 1, C1 > & rv,
const Eigen::Matrix< double, R2, 1 > & v 
)
+
+inline
+
+ +

Definition at line 146 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T , int C1, int R2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::multiply (const Eigen::Matrix< double, 1, C1 > & rv,
const Eigen::Matrix< fvar< T >, R2, 1 > & v 
)
+
+inline
+
+ +

Definition at line 157 of file multiply.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::multiply_log (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 15 of file multiply_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::multiply_log (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 25 of file multiply_log.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::multiply_log (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 35 of file multiply_log.hpp.

+ +
+
+ +
+
+
+template<typename T_a , typename T_b >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_a, T_b>::type stan::math::multiply_log (const T_a a,
const T_b b 
)
+
+inline
+
+ +

Calculated the value of the first argument times log of the second argument while behaving properly with 0 inputs.

+

$ a * \log b $.

+

+\[ \mbox{multiply\_log}(x, y) = \begin{cases} 0 & \mbox{if } x=y=0\\ x\ln y & \mbox{if } x, y\neq0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{multiply\_log}(x, y)}{\partial x} = \begin{cases} \infty & \mbox{if } x=y=0\\ \ln y & \mbox{if } x, y\neq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{multiply\_log}(x, y)}{\partial y} = \begin{cases} \infty & \mbox{if } x=y=0\\ \frac{x}{y} & \mbox{if } x, y\neq 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
athe first variable
bthe second variable
+
+
+
Returns
a * log(b)
+ +

Definition at line 51 of file multiply_log.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::multiply_log (const vara,
const varb 
)
+
+inline
+
+ +

Return the value of a*log(b).

+

When both a and b are 0, the value returned is 0. The partial deriviative with respect to a is log(b). The partial deriviative with respect to b is a/b. When a and b are both 0, this is set to Inf.

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
Value of a*log(b)
+ +

Definition at line 74 of file multiply_log.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::multiply_log (const vara,
const double b 
)
+
+inline
+
+ +

Return the value of a*log(b).

+

When both a and b are 0, the value returned is 0. The partial deriviative with respect to a is log(b).

+
Parameters
+ + + +
aFirst variable.
bSecond scalar.
+
+
+
Returns
Value of a*log(b)
+ +

Definition at line 87 of file multiply_log.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::multiply_log (const double a,
const varb 
)
+
+inline
+
+ +

Return the value of a*log(b).

+

When both a and b are 0, the value returned is 0. The partial deriviative with respect to b is a/b. When a and b are both 0, this is set to Inf.

+
Parameters
+ + + +
aFirst scalar.
bSecond variable.
+
+
+
Returns
Value of a*log(b)
+ +

Definition at line 101 of file multiply_log.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, R, R> stan::math::multiply_lower_tri_self_transpose (const Eigen::Matrix< fvar< T >, R, C > & m)
+
+inline
+
+ +

Definition at line 17 of file multiply_lower_tri_self_transpose.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
matrix_d stan::math::multiply_lower_tri_self_transpose (const matrix_dL)
+
+inline
+
+ +

Returns the result of multiplying the lower triangular portion of the input matrix by its own transpose.

+
Parameters
+ + +
LMatrix to multiply.
+
+
+
Returns
The lower triangular values in L times their own transpose.
+
Exceptions
+ + +
std::domain_errorIf the input matrix is not square.
+
+
+ +

Definition at line 18 of file multiply_lower_tri_self_transpose.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
matrix_v stan::math::multiply_lower_tri_self_transpose (const matrix_vL)
+
+inline
+
+ +

Definition at line 19 of file multiply_lower_tri_self_transpose.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_location , typename T_precision >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_location, T_precision>::type stan::math::neg_binomial_2_ccdf_log (const T_n & n,
const T_location & mu,
const T_precision & phi 
)
+
+ +

Definition at line 18 of file neg_binomial_2_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_location , typename T_precision >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_location, T_precision>::type stan::math::neg_binomial_2_cdf (const T_n & n,
const T_location & mu,
const T_precision & phi 
)
+
+ +

Definition at line 26 of file neg_binomial_2_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_location , typename T_precision >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_location, T_precision>::type stan::math::neg_binomial_2_cdf_log (const T_n & n,
const T_location & mu,
const T_precision & phi 
)
+
+ +

Definition at line 19 of file neg_binomial_2_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_location , typename T_precision >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_location, T_precision>::type stan::math::neg_binomial_2_log (const T_n & n,
const T_location & mu,
const T_precision & phi 
)
+
+ +

Definition at line 37 of file neg_binomial_2_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_location , typename T_precision >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_location, T_precision>::type stan::math::neg_binomial_2_log (const T_n & n,
const T_location & mu,
const T_precision & phi 
)
+
+inline
+
+ +

Definition at line 141 of file neg_binomial_2_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_log_location , typename T_precision >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_log_location, T_precision>::type stan::math::neg_binomial_2_log_log (const T_n & n,
const T_log_location & eta,
const T_precision & phi 
)
+
+ +

Definition at line 35 of file neg_binomial_2_log_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_log_location , typename T_precision >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_log_location, T_precision>::type stan::math::neg_binomial_2_log_log (const T_n & n,
const T_log_location & eta,
const T_precision & phi 
)
+
+inline
+
+ +

Definition at line 142 of file neg_binomial_2_log_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
int stan::math::neg_binomial_2_log_rng (const double eta,
const double phi,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 28 of file neg_binomial_2_log_rng.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
int stan::math::neg_binomial_2_rng (const double mu,
const double phi,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 28 of file neg_binomial_2_rng.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_shape , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_shape, T_inv_scale>::type stan::math::neg_binomial_ccdf_log (const T_n & n,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+ +

Definition at line 34 of file neg_binomial_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_shape , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_shape, T_inv_scale>::type stan::math::neg_binomial_cdf (const T_n & n,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+ +

Definition at line 29 of file neg_binomial_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_shape , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_shape, T_inv_scale>::type stan::math::neg_binomial_cdf_log (const T_n & n,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+ +

Definition at line 34 of file neg_binomial_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_shape , typename T_inv_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_shape, T_inv_scale>::type stan::math::neg_binomial_log (const T_n & n,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+ +

Definition at line 39 of file neg_binomial_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_shape , typename T_inv_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_shape, T_inv_scale>::type stan::math::neg_binomial_log (const T_n & n,
const T_shape & alpha,
const T_inv_scale & beta 
)
+
+inline
+
+ +

Definition at line 183 of file neg_binomial_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
int stan::math::neg_binomial_rng (const double alpha,
const double beta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 29 of file neg_binomial_rng.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::negative_infinity ()
+
+inline
+
+ +

Return negative infinity.

+
Returns
Negative infinity.
+ +

Definition at line 132 of file constants.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static size_t stan::math::nested_size ()
+
+inlinestatic
+
+ +

Definition at line 10 of file nested_size.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::normal_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 26 of file normal_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::normal_cdf (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Calculates the normal cumulative distribution function for the given variate, location, and scale.

+

$\Phi(x) = \frac{1}{\sqrt{2 \pi}} \int_{-\inf}^x e^{-t^2/2} dt$.

+
Parameters
+ + + + +
yA scalar variate.
muThe location of the normal distribution.
sigmaThe scale of the normal distriubtion
+
+
+
Returns
The unit normal cdf evaluated at the specified arguments.
+
Template Parameters
+ + + + +
T_yType of y.
T_locType of mean parameter.
T_scaleType of standard deviation paramater.
+
+
+ +

Definition at line 40 of file normal_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::normal_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 26 of file normal_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::normal_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

The log of the normal density for the specified scalar(s) given the specified mean(s) and deviation(s).

+

y, mu, or sigma can each be either a scalar or a vector. Any vector inputs must be the same length.

+

The result log probability is defined to be the sum of the log probabilities for each observation/mean/deviation triple.

Parameters
+ + + + +
y(Sequence of) scalar(s).
mu(Sequence of) location parameter(s) for the normal distribution.
sigma(Sequence of) scale parameters for the normal distribution.
+
+
+
Returns
The log of the product of the densities.
+
Exceptions
+ + +
std::domain_errorif the scale is not positive.
+
+
+
Template Parameters
+ + + +
T_yUnderlying type of scalar in sequence.
T_locType of location parameter.
+
+
+ +

Definition at line 45 of file normal_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::normal_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma 
)
+
+inline
+
+ +

Definition at line 138 of file normal_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::normal_rng (const double mu,
const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 19 of file normal_rng.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::not_a_number ()
+
+inline
+
+ +

Return (quiet) not-a-number.

+
Returns
Quiet not-a-number.
+ +

Definition at line 141 of file constants.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
int stan::math::num_elements (const T & x)
+
+inline
+
+ +

Returns 1, the number of elements in a primitive type.

+
Parameters
+ + +
xArgument of primitive type.
+
+
+
Returns
1
+ +

Definition at line 19 of file num_elements.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
int stan::math::num_elements (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the size of the specified matrix.

+
Parameters
+ + +
margument matrix
+
+
+
Returns
size of matrix
+ +

Definition at line 31 of file num_elements.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
int stan::math::num_elements (const std::vector< T > & v)
+
+inline
+
+ +

Returns the number of elements in the specified vector.

+

This assumes it is not ragged and that each of its contained elements has the same number of elements.

+
Parameters
+ + +
vargument vector
+
+
+
Returns
number of contained arguments
+ +

Definition at line 45 of file num_elements.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
bool stan::math::operator! (const vara)
+
+inline
+
+ +

Prefix logical negation for the value of variables (C++).

+

The expression (!a) is equivalent to negating the scalar value of the variable a.

+

Note that this is the only logical operator defined for variables. Overridden logical conjunction (&&) and disjunction (||) operators do not apply the same "short circuit" rules as the built-in logical operators.

+

+\[ \mbox{operator!}(x) = \begin{cases} 0 & \mbox{if } x \neq 0 \\ 1 & \mbox{if } x = 0 \\[6pt] 0 & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable to negate.
+
+
+
Returns
True if variable is non-zero.
+ +

Definition at line 31 of file operator_unary_not.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator!= (const fvar< T > & x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 14 of file operator_not_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator!= (const fvar< T > & x,
double y 
)
+
+inline
+
+ +

Definition at line 21 of file operator_not_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator!= (const vara,
const varb 
)
+
+inline
+
+ +

Inequality operator comparing two variables' values (C++).

+

+\[ \mbox{operator!=}(x, y) = \begin{cases} 0 & \mbox{if } x = y\\ 1 & \mbox{if } x \neq y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
True if the first variable's value is not the same as the second's.
+ +

Definition at line 26 of file operator_not_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator!= (double x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 28 of file operator_not_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator!= (const vara,
const double b 
)
+
+inline
+
+ +

Inequality operator comparing a variable's value and a double (C++).

+
Parameters
+ + + +
aFirst variable.
bSecond value.
+
+
+
Returns
True if the first variable's value is not the same as the second value.
+ +

Definition at line 39 of file operator_not_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator!= (const double a,
const varb 
)
+
+inline
+
+ +

Inequality operator comparing a double and a variable's value (C++).

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
True if the first value is not the same as the second variable's value.
+ +

Definition at line 52 of file operator_not_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator* (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 14 of file operator_multiplication.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator* (double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 22 of file operator_multiplication.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator* (const fvar< T > & x1,
double x2 
)
+
+inline
+
+ +

Definition at line 29 of file operator_multiplication.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator* (const vara,
const varb 
)
+
+inline
+
+ +

Multiplication operator for two variables (C++).

+

The partial derivatives are

+

$\frac{\partial}{\partial x} (x * y) = y$, and

+

$\frac{\partial}{\partial y} (x * y) = x$.

+

+\[ \mbox{operator*}(x, y) = \begin{cases} xy & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator*}(x, y)}{\partial x} = \begin{cases} y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator*}(x, y)}{\partial y} = \begin{cases} x & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable operand.
bSecond variable operand.
+
+
+
Returns
Variable result of multiplying operands.
+ +

Definition at line 83 of file operator_multiplication.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator* (const vara,
const double b 
)
+
+inline
+
+ +

Multiplication operator for a variable and a scalar (C++).

+

The partial derivative for the variable is

+

$\frac{\partial}{\partial x} (x * c) = c$, and

+
Parameters
+ + + +
aVariable operand.
bScalar operand.
+
+
+
Returns
Variable result of multiplying operands.
+ +

Definition at line 98 of file operator_multiplication.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator* (const double a,
const varb 
)
+
+inline
+
+ +

Multiplication operator for a scalar and a variable (C++).

+

The partial derivative for the variable is

+

$\frac{\partial}{\partial y} (c * y) = c$.

+
Parameters
+ + + +
aScalar operand.
bVariable operand.
+
+
+
Returns
Variable result of multiplying the operands.
+ +

Definition at line 115 of file operator_multiplication.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator+ (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 13 of file operator_addition.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator+ (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 20 of file operator_addition.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator+ (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 27 of file operator_addition.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::operator+ (const vara)
+
+inline
+
+ +

Unary plus operator for variables (C++).

+

The function simply returns its input, because

+

$\frac{d}{dx} +x = \frac{d}{dx} x = 1$.

+

The effect of unary plus on a built-in C++ scalar type is integer promotion. Because variables are all double-precision floating point already, promotion is not necessary.

+

+\[ \mbox{operator+}(x) = \begin{cases} x & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator+}(x)}{\partial x} = \begin{cases} 1 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aArgument variable.
+
+
+
Returns
The input reference.
+ +

Definition at line 43 of file operator_unary_plus.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator+ (const vara,
const varb 
)
+
+inline
+
+ +

Addition operator for variables (C++).

+

The partial derivatives are defined by

+

$\frac{\partial}{\partial x} (x+y) = 1$, and

+

$\frac{\partial}{\partial y} (x+y) = 1$.

+

+\[ \mbox{operator+}(x, y) = \begin{cases} x+y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator+}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator+}(x, y)}{\partial y} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable operand.
bSecond variable operand.
+
+
+
Returns
Variable result of adding two variables.
+ +

Definition at line 84 of file operator_addition.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator+ (const vara,
const double b 
)
+
+inline
+
+ +

Addition operator for variable and scalar (C++).

+

The derivative with respect to the variable is

+

$\frac{d}{dx} (x + c) = 1$.

+
Parameters
+ + + +
aFirst variable operand.
bSecond scalar operand.
+
+
+
Returns
Result of adding variable and scalar.
+ +

Definition at line 99 of file operator_addition.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator+ (const double a,
const varb 
)
+
+inline
+
+ +

Addition operator for scalar and variable (C++).

+

The derivative with respect to the variable is

+

$\frac{d}{dy} (c + y) = 1$.

+
Parameters
+ + + +
aFirst scalar operand.
bSecond variable operand.
+
+
+
Returns
Result of adding variable and scalar.
+ +

Definition at line 116 of file operator_addition.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var& stan::math::operator++ (vara)
+
+inline
+
+ +

Prefix increment operator for variables (C++).

+

Following C++, (++a) is defined to behave exactly as (a = a + 1.0) does, but is faster and uses less memory. In particular, the result is an assignable lvalue.

+
Parameters
+ + +
aVariable to increment.
+
+
+
Returns
Reference the result of incrementing this input variable.
+ +

Definition at line 36 of file operator_unary_increment.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator++ (vara,
int  
)
+
+inline
+
+ +

Postfix increment operator for variables (C++).

+

Following C++, the expression (a++) is defined to behave like the sequence of operations

+

var temp = a; a = a + 1.0; return temp;

+
Parameters
+ + +
aVariable to increment.
+
+
+
Returns
Input variable.
+ +

Definition at line 52 of file operator_unary_increment.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::operator- (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file operator_unary_minus.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator- (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 14 of file operator_subtraction.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator- (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 21 of file operator_subtraction.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator- (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 28 of file operator_subtraction.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::operator- (const vara)
+
+inline
+
+ +

Unary negation operator for variables (C++).

+

$\frac{d}{dx} -x = -1$.

+

+\[ \mbox{operator-}(x) = \begin{cases} -x & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator-}(x)}{\partial x} = \begin{cases} -1 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aArgument variable.
+
+
+
Returns
Negation of variable.
+ +

Definition at line 51 of file operator_unary_negative.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator- (const vara,
const varb 
)
+
+inline
+
+ +

Subtraction operator for variables (C++).

+

The partial derivatives are defined by

+

$\frac{\partial}{\partial x} (x-y) = 1$, and

+

$\frac{\partial}{\partial y} (x-y) = -1$.

+

+\[ \mbox{operator-}(x, y) = \begin{cases} x-y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator-}(x, y)}{\partial x} = \begin{cases} 1 & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator-}(x, y)}{\partial y} = \begin{cases} -1 & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable operand.
bSecond variable operand.
+
+
+
Returns
Variable result of subtracting the second variable from the first.
+ +

Definition at line 99 of file operator_subtraction.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator- (const vara,
const double b 
)
+
+inline
+
+ +

Subtraction operator for variable and scalar (C++).

+

The derivative for the variable is

+

$\frac{\partial}{\partial x} (x-c) = 1$, and

+
Parameters
+ + + +
aFirst variable operand.
bSecond scalar operand.
+
+
+
Returns
Result of subtracting the scalar from the variable.
+ +

Definition at line 114 of file operator_subtraction.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator- (const double a,
const varb 
)
+
+inline
+
+ +

Subtraction operator for scalar and variable (C++).

+

The derivative for the variable is

+

$\frac{\partial}{\partial y} (c-y) = -1$, and

+
Parameters
+ + + +
aFirst scalar operand.
bSecond variable operand.
+
+
+
Returns
Result of sutracting a variable from a scalar.
+ +

Definition at line 131 of file operator_subtraction.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var& stan::math::operator-- (vara)
+
+inline
+
+ +

Prefix decrement operator for variables (C++).

+

Following C++, (–a) is defined to behave exactly as

+

a = a - 1.0)

+

does, but is faster and uses less memory. In particular, the result is an assignable lvalue.

+
Parameters
+ + +
aVariable to decrement.
+
+
+
Returns
Reference the result of decrementing this input variable.
+ +

Definition at line 40 of file operator_unary_decrement.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator-- (vara,
int  
)
+
+inline
+
+ +

Postfix decrement operator for variables (C++).

+

Following C++, the expression (a–) is defined to behave like the sequence of operations

+

var temp = a; a = a - 1.0; return temp;

+
Parameters
+ + +
aVariable to decrement.
+
+
+
Returns
Input variable.
+ +

Definition at line 56 of file operator_unary_decrement.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator/ (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 14 of file operator_division.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator/ (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 22 of file operator_division.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::operator/ (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 30 of file operator_division.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::operator/ (const Eigen::Matrix< fvar< T >, R, C > & v,
const fvar< T > & c 
)
+
+inline
+
+ +

Definition at line 51 of file divide.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::operator/ (const Eigen::Matrix< fvar< T >, R, C > & v,
const double c 
)
+
+inline
+
+ +

Definition at line 57 of file divide.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::operator/ (const Eigen::Matrix< double, R, C > & v,
const fvar< T > & c 
)
+
+inline
+
+ +

Definition at line 63 of file divide.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator/ (const vara,
const varb 
)
+
+inline
+
+ +

Division operator for two variables (C++).

+

The partial derivatives for the variables are

+

$\frac{\partial}{\partial x} (x/y) = 1/y$, and

+

$\frac{\partial}{\partial y} (x/y) = -x / y^2$.

+

+\[ \mbox{operator/}(x, y) = \begin{cases} \frac{x}{y} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator/}(x, y)}{\partial x} = \begin{cases} \frac{1}{y} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{operator/}(x, y)}{\partial y} = \begin{cases} -\frac{x}{y^2} & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable operand.
bSecond variable operand.
+
+
+
Returns
Variable result of dividing the first variable by the second.
+ +

Definition at line 96 of file operator_division.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator/ (const vara,
const double b 
)
+
+inline
+
+ +

Division operator for dividing a variable by a scalar (C++).

+

The derivative with respect to the variable is

+

$\frac{\partial}{\partial x} (x/c) = 1/c$.

+
Parameters
+ + + +
aVariable operand.
bScalar operand.
+
+
+
Returns
Variable result of dividing the variable by the scalar.
+ +

Definition at line 111 of file operator_division.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::operator/ (const double a,
const varb 
)
+
+inline
+
+ +

Division operator for dividing a scalar by a variable (C++).

+

The derivative with respect to the variable is

+

$\frac{d}{d y} (c/y) = -c / y^2$.

+
Parameters
+ + + +
aScalar operand.
bVariable operand.
+
+
+
Returns
Variable result of dividing the scalar by the variable.
+ +

Definition at line 128 of file operator_division.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator< (const fvar< T > & x,
double y 
)
+
+inline
+
+ +

Definition at line 12 of file operator_less_than.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator< (double x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 18 of file operator_less_than.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator< (const fvar< T > & x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 24 of file operator_less_than.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator< (const vara,
const varb 
)
+
+inline
+
+ +

Less than operator comparing variables' values (C++).

+

+\[ \mbox{operator\textless}(x, y) = \begin{cases} 0 & \mbox{if } x \geq y \\ 1 & \mbox{if } x < y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
True if first variable's value is less than second's.
+ +

Definition at line 24 of file operator_less_than.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator< (const vara,
const double b 
)
+
+inline
+
+ +

Less than operator comparing variable's value and a double (C++).

+
Parameters
+ + + +
aFirst variable.
bSecond value.
+
+
+
Returns
True if first variable's value is less than second value.
+ +

Definition at line 36 of file operator_less_than.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator< (const double a,
const varb 
)
+
+inline
+
+ +

Less than operator comparing a double and variable's value (C++).

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
True if first value is less than second variable's value.
+ +

Definition at line 48 of file operator_less_than.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator<= (const fvar< T > & x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 14 of file operator_less_than_or_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator<= (const fvar< T > & x,
double y 
)
+
+inline
+
+ +

Definition at line 21 of file operator_less_than_or_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator<= (const vara,
const varb 
)
+
+inline
+
+ +

Less than or equal operator comparing two variables' values (C++).

+

+\[ \mbox{operator\textless=}(x, y) = \begin{cases} 0 & \mbox{if } x > y\\ 1 & \mbox{if } x \leq y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
True if first variable's value is less than or equal to the second's.
+ +

Definition at line 26 of file operator_less_than_or_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator<= (double x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 28 of file operator_less_than_or_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator<= (const vara,
const double b 
)
+
+inline
+
+ +

Less than or equal operator comparing a variable's value and a scalar (C++).

+
Parameters
+ + + +
aFirst variable.
bSecond value.
+
+
+
Returns
True if first variable's value is less than or equal to the second value.
+ +

Definition at line 39 of file operator_less_than_or_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator<= (const double a,
const varb 
)
+
+inline
+
+ +

Less than or equal operator comparing a double and variable's value (C++).

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
True if first value is less than or equal to the second variable's value.
+ +

Definition at line 52 of file operator_less_than_or_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator== (const fvar< T > & x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 14 of file operator_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator== (const fvar< T > & x,
double y 
)
+
+inline
+
+ +

Definition at line 21 of file operator_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator== (const vara,
const varb 
)
+
+inline
+
+ +

Equality operator comparing two variables' values (C++).

+

+\[ \mbox{operator==}(x, y) = \begin{cases} 0 & \mbox{if } x \neq y\\ 1 & \mbox{if } x = y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
True if the first variable's value is the same as the second's.
+ +

Definition at line 26 of file operator_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator== (double x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 28 of file operator_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator== (const vara,
const double b 
)
+
+inline
+
+ +

Equality operator comparing a variable's value and a double (C++).

+
Parameters
+ + + +
aFirst variable.
bSecond value.
+
+
+
Returns
True if the first variable's value is the same as the second value.
+ +

Definition at line 39 of file operator_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator== (const double a,
const varb 
)
+
+inline
+
+ +

Equality operator comparing a scalar and a variable's value (C++).

+
Parameters
+ + + +
aFirst scalar.
bSecond variable.
+
+
+
Returns
True if the variable's value is equal to the scalar.
+ +

Definition at line 51 of file operator_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator> (const fvar< T > & x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 14 of file operator_greater_than.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator> (const fvar< T > & x,
double y 
)
+
+inline
+
+ +

Definition at line 21 of file operator_greater_than.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator> (const vara,
const varb 
)
+
+inline
+
+ +

Greater than operator comparing variables' values (C++).

+

+\[ \mbox{operator\textgreater}(x, y) = \begin{cases} 0 & \mbox{if } x \leq y\\ 1 & \mbox{if } x > y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
True if first variable's value is greater than second's.
+ +

Definition at line 25 of file operator_greater_than.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator> (double x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 28 of file operator_greater_than.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator> (const vara,
const double b 
)
+
+inline
+
+ +

Greater than operator comparing variable's value and double (C++).

+
Parameters
+ + + +
aFirst variable.
bSecond value.
+
+
+
Returns
True if first variable's value is greater than second value.
+ +

Definition at line 37 of file operator_greater_than.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator> (const double a,
const varb 
)
+
+inline
+
+ +

Greater than operator comparing a double and a variable's value (C++).

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
True if first value is greater than second variable's value.
+ +

Definition at line 49 of file operator_greater_than.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator>= (const fvar< T > & x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 14 of file operator_greater_than_or_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator>= (const fvar< T > & x,
double y 
)
+
+inline
+
+ +

Definition at line 21 of file operator_greater_than_or_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator>= (const vara,
const varb 
)
+
+inline
+
+ +

Greater than or equal operator comparing two variables' values (C++).

+

+\[ \mbox{operator\textgreater=}(x, y) = \begin{cases} 0 & \mbox{if } x < y\\ 1 & \mbox{if } x \geq y \\[6pt] 0 & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
aFirst variable.
bSecond variable.
+
+
+
Returns
True if first variable's value is greater than or equal to the second's.
+ +

Definition at line 27 of file operator_greater_than_or_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator>= (double x,
const fvar< T > & y 
)
+
+inline
+
+ +

Definition at line 28 of file operator_greater_than_or_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator>= (const vara,
const double b 
)
+
+inline
+
+ +

Greater than or equal operator comparing variable's value and double (C++).

+
Parameters
+ + + +
aFirst variable.
bSecond value.
+
+
+
Returns
True if first variable's value is greater than or equal to second value.
+ +

Definition at line 40 of file operator_greater_than_or_equal.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
bool stan::math::operator>= (const double a,
const varb 
)
+
+inline
+
+ +

Greater than or equal operator comparing double and variable's value (C++).

+
Parameters
+ + + +
aFirst value.
bSecond variable.
+
+
+
Returns
True if the first value is greater than or equal to the second variable's value.
+ +

Definition at line 53 of file operator_greater_than_or_equal.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x)
+
+ +

Return an increasing ordered vector derived from the specified free vector.

+

The returned constrained vector will have the same dimensionality as the specified free vector.

+
Parameters
+ + +
xFree vector of scalars.
+
+
+
Returns
Positive, increasing ordered vector.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 23 of file ordered_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
T & lp 
)
+
+inline
+
+ +

Return a positive valued, increasing ordered vector derived from the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform.

+

The returned constrained vector will have the same dimensionality as the specified free vector.

+
Parameters
+ + + +
xFree vector of scalars.
lpLog probability reference.
+
+
+
Returns
Positive, increasing ordered vector.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 56 of file ordered_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::ordered_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & y)
+
+ +

Return the vector of unconstrained scalars that transform to the specified positive ordered vector.

+

This function inverts the constraining operation defined in ordered_constrain(Matrix),

+
Parameters
+ + +
yVector of positive, ordered scalars.
+
+
+
Returns
Free vector that transforms into the input vector.
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Exceptions
+ + +
std::domain_errorif y is not a vector of positive, ordered scalars.
+
+
+ +

Definition at line 26 of file ordered_free.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_lambda , typename T_cut >
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_lambda, T_cut>::type stan::math::ordered_logistic_log (int y,
const T_lambda & lambda,
const Eigen::Matrix< T_cut, Eigen::Dynamic, 1 > & c 
)
+
+ +

Returns the (natural) log probability of the specified integer outcome given the continuous location and specified cutpoints in an ordered logistic model.

+

Typically the continous location will be the dot product of a vector of regression coefficients and a vector of predictors for the outcome.

+
Template Parameters
+ + + + +
proptoTrue if calculating up to a proportion.
T_locLocation type.
T_cutCut-point type.
+
+
+
Parameters
+ + + + +
yOutcome.
lambdaLocation.
cPositive increasing vector of cutpoints.
+
+
+
Returns
Log probability of outcome given location and cutpoints.
+
Exceptions
+ + +
std::domain_errorIf the outcome is not between 1 and the number of cutpoints plus 2; if the cutpoint vector is empty; if the cutpoint vector contains a non-positive, non-finite value; or if the cutpoint vector is not sorted in ascending order.
+
+
+ +

Definition at line 61 of file ordered_logistic_log.hpp.

+ +
+
+ +
+
+
+template<typename T_lambda , typename T_cut >
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_lambda, T_cut>::type stan::math::ordered_logistic_log (int y,
const T_lambda & lambda,
const Eigen::Matrix< T_cut, Eigen::Dynamic, 1 > & c 
)
+
+ +

Definition at line 107 of file ordered_logistic_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
int stan::math::ordered_logistic_rng (const double eta,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > & c,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 24 of file ordered_logistic_rng.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::out_of_range (const char * function,
const int max,
const int index,
const char * msg1 = "",
const char * msg2 = "" 
)
+
+inline
+
+ +

Throw an out_of_range exception with a consistently formatted message.

+

This is an abstraction for all Stan functions to use when throwing out of range. This will allow us to change the behavior for all functions at once.

+

The message is: "<function>: index <index> out of range; expecting index to be between " "1 and <max><msg1><msg2>"

+
Parameters
+ + + + + + +
functionName of the function
maxMax
indexIndex
msg1Message to print. Default is "".
msg2Message to print. Default is "".
+
+
+ +

Definition at line 30 of file out_of_range.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::owens_t (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 14 of file owens_t.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::owens_t (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 34 of file owens_t.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::owens_t (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 48 of file owens_t.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::owens_t (const double h,
const double a 
)
+
+inline
+
+ +

The Owen's T function of h and a.

+

Used to compute the cumulative density function for the skew normal distribution.

+

+\[ \mbox{owens\_t}(h, a) = \begin{cases} \mbox{owens\_t}(h, a) & \mbox{if } -\infty\leq h, a \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } h = \textrm{NaN or } a = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{owens\_t}(h, a)}{\partial h} = \begin{cases} \frac{\partial\, \mbox{owens\_t}(h, a)}{\partial h} & \mbox{if } -\infty\leq h, a\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } h = \textrm{NaN or } a = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{owens\_t}(h, a)}{\partial a} = \begin{cases} \frac{\partial\, \mbox{owens\_t}(h, a)}{\partial a} & \mbox{if } -\infty\leq h, a\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } h = \textrm{NaN or } a = \textrm{NaN} \end{cases} \] +

+

+\[ \mbox{owens\_t}(h, a) = \frac{1}{2\pi} \int_0^a \frac{\exp(-\frac{1}{2}h^2(1+x^2))}{1+x^2}dx \] +

+

+\[ \frac{\partial \, \mbox{owens\_t}(h, a)}{\partial h} = -\frac{1}{2\sqrt{2\pi}} \operatorname{erf}\left(\frac{ha}{\sqrt{2}}\right) \exp\left(-\frac{h^2}{2}\right) \] +

+

+\[ \frac{\partial \, \mbox{owens\_t}(h, a)}{\partial a} = \frac{\exp\left(-\frac{1}{2}h^2(1+a^2)\right)}{2\pi (1+a^2)} \] +

+
Template Parameters
+ + + +
T1Type of first argument.
T2Type of second argument.
+
+
+
Parameters
+ + + +
hFirst argument
aSecond argument
+
+
+
Returns
The Owen's T function.
+ +

Definition at line 62 of file owens_t.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::owens_t (const varh,
const vara 
)
+
+inline
+
+ +

The Owen's T function of h and a.

+

Used to compute the cumulative density function for the skew normal distribution.

+
Parameters
+ + + +
hvar parameter.
avar parameter.
+
+
+
Returns
The Owen's T function.
+ +

Definition at line 71 of file owens_t.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::owens_t (const varh,
double a 
)
+
+inline
+
+ +

The Owen's T function of h and a.

+

Used to compute the cumulative density function for the skew normal distribution.

+
Parameters
+ + + +
hvar parameter.
adouble parameter.
+
+
+
Returns
The Owen's T function.
+ +

Definition at line 85 of file owens_t.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::owens_t (double h,
const vara 
)
+
+inline
+
+ +

The Owen's T function of h and a.

+

Used to compute the cumulative density function for the skew normal distribution.

+
Parameters
+ + + +
hdouble parameter.
avar parameter.
+
+
+
Returns
The Owen's T function.
+ +

Definition at line 99 of file owens_t.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale, T_shape>::type stan::math::pareto_ccdf_log (const T_y & y,
const T_scale & y_min,
const T_shape & alpha 
)
+
+ +

Definition at line 25 of file pareto_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale, T_shape>::type stan::math::pareto_cdf (const T_y & y,
const T_scale & y_min,
const T_shape & alpha 
)
+
+ +

Definition at line 26 of file pareto_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale, T_shape>::type stan::math::pareto_cdf_log (const T_y & y,
const T_scale & y_min,
const T_shape & alpha 
)
+
+ +

Definition at line 25 of file pareto_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale, T_shape>::type stan::math::pareto_log (const T_y & y,
const T_scale & y_min,
const T_shape & alpha 
)
+
+ +

Definition at line 29 of file pareto_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale , typename T_shape >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale, T_shape>::type stan::math::pareto_log (const T_y & y,
const T_scale & y_min,
const T_shape & alpha 
)
+
+inline
+
+ +

Definition at line 132 of file pareto_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::pareto_rng (const double y_min,
const double alpha,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 21 of file pareto_rng.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::pareto_type_2_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & lambda,
const T_shape & alpha 
)
+
+ +

Definition at line 26 of file pareto_type_2_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::pareto_type_2_cdf (const T_y & y,
const T_loc & mu,
const T_scale & lambda,
const T_shape & alpha 
)
+
+ +

Definition at line 27 of file pareto_type_2_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::pareto_type_2_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & lambda,
const T_shape & alpha 
)
+
+ +

Definition at line 27 of file pareto_type_2_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::pareto_type_2_log (const T_y & y,
const T_loc & mu,
const T_scale & lambda,
const T_shape & alpha 
)
+
+ +

Definition at line 30 of file pareto_type_2_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::pareto_type_2_log (const T_y & y,
const T_loc & mu,
const T_scale & lambda,
const T_shape & alpha 
)
+
+inline
+
+ +

Definition at line 149 of file pareto_type_2_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::pareto_type_2_rng (const double mu,
const double lambda,
const double alpha,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 22 of file pareto_type_2_rng.hpp.

+ +
+
+ +
+
+
+template<typename T , typename F >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::partial_derivative (const F & f,
const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
int n,
T & fx,
T & dfx_dxn 
)
+
+ +

Return the partial derivative of the specified multiivariate function at the specified argument.

+
Template Parameters
+ + + +
TArgument type
FFunction type
+
+
+
Parameters
+ + + + + + +
fFunction
[in]xArgument vector
[in]nIndex of argument with which to take derivative
[out]fxValue of function applied to argument
[out]dfx_dxnValue of partial derivative
+
+
+ +

Definition at line 27 of file partial_derivative.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::Phi (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file Phi.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::Phi (const T x)
+
+inline
+
+ +

The unit normal cumulative distribution function.

+

The return value for a specified input is the probability that a random unit normal variate is less than or equal to the specified value, defined by

+

$\Phi(x) = \int_{-\infty}^x \mbox{\sf Norm}(x|0, 1) \ dx$

+

This function can be used to implement the inverse link function for probit regression.

+

Phi will underflow to 0 below -37.5 and overflow to 1 above 8

+
Parameters
+ + +
xArgument.
+
+
+
Returns
Probability random sample is less than or equal to argument.
+ +

Definition at line 31 of file Phi.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::Phi (const stan::math::vara)
+
+inline
+
+ +

The unit normal cumulative density function for variables (stan).

+

See stan::math::Phi() for the double-based version.

+

The derivative is the unit normal density function,

+

$\frac{d}{dx} \Phi(x) = \mbox{\sf Norm}(x|0, 1) = \frac{1}{\sqrt{2\pi}} \exp(-\frac{1}{2} x^2)$.

+

+\[ \mbox{Phi}(x) = \begin{cases} 0 & \mbox{if } x < -37.5 \\ \Phi(x) & \mbox{if } -37.5 \leq x \leq 8.25 \\ 1 & \mbox{if } x > 8.25 \\[6pt] \textrm{error} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{Phi}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } x < -27.5 \\ \frac{\partial\, \Phi(x)}{\partial x} & \mbox{if } -27.5 \leq x \leq 27.5 \\ 0 & \mbox{if } x > 27.5 \\[6pt] \textrm{error} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \Phi(x) = \frac{1}{\sqrt{2\pi}} \int_{0}^{x} e^{-t^2/2} dt \] +

+

+\[ \frac{\partial \, \Phi(x)}{\partial x} = \frac{e^{-x^2/2}}{\sqrt{2\pi}} \] +

+
Parameters
+ + +
aVariable argument.
+
+
+
Returns
The unit normal cdf evaluated at the specified argument.
+ +

Definition at line 66 of file Phi.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::Phi_approx (x)
+
+inline
+
+ +

Approximation of the unit normal CDF.

+

http://www.jiem.org/index.php/jiem/article/download/60/27

+

This function can be used to implement the inverse link function for probit regression.

+
Parameters
+ + +
xArgument.
+
+
+
Returns
Probability random sample is less than or equal to argument.
+ +

Definition at line 23 of file Phi_approx.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::Phi_approx (const stan::math::vara)
+
+inline
+
+ +

Approximation of the unit normal CDF for variables (stan).

+

http://www.jiem.org/index.php/jiem/article/download/60/27

+

+\[ \mbox{Phi\_approx}(x) = \begin{cases} \Phi_{\mbox{\footnotesize approx}}(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{Phi\_approx}(x)}{\partial x} = \begin{cases} \frac{\partial\, \Phi_{\mbox{\footnotesize approx}}(x)}{\partial x} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \Phi_{\mbox{\footnotesize approx}}(x) = \mbox{logit}^{-1}(0.07056 \, x^3 + 1.5976 \, x) \] +

+

+\[ \frac{\partial \, \Phi_{\mbox{\footnotesize approx}}(x)}{\partial x} = -\Phi_{\mbox{\footnotesize approx}}^2(x) e^{-0.07056x^3 - 1.5976x}(-0.21168x^2-1.5976) \] +

+
Parameters
+ + +
aVariable argument.
+
+
+
Returns
The corresponding unit normal cdf approximation.
+ +

Definition at line 47 of file Phi_approx.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::pi ()
+
+inline
+
+ +

Return the value of pi.

+
Returns
Pi.
+ +

Definition at line 86 of file constants.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_rate >
+ + + + + + + + + + + + + + + + + + +
return_type<T_rate>::type stan::math::poisson_ccdf_log (const T_n & n,
const T_rate & lambda 
)
+
+ +

Definition at line 27 of file poisson_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_rate >
+ + + + + + + + + + + + + + + + + + +
return_type<T_rate>::type stan::math::poisson_cdf (const T_n & n,
const T_rate & lambda 
)
+
+ +

Definition at line 28 of file poisson_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_rate >
+ + + + + + + + + + + + + + + + + + +
return_type<T_rate>::type stan::math::poisson_cdf_log (const T_n & n,
const T_rate & lambda 
)
+
+ +

Definition at line 27 of file poisson_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_rate >
+ + + + + + + + + + + + + + + + + + +
return_type<T_rate>::type stan::math::poisson_log (const T_n & n,
const T_rate & lambda 
)
+
+ +

Definition at line 29 of file poisson_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_rate >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
return_type<T_rate>::type stan::math::poisson_log (const T_n & n,
const T_rate & lambda 
)
+
+inline
+
+ +

Definition at line 101 of file poisson_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_n , typename T_log_rate >
+ + + + + + + + + + + + + + + + + + +
return_type<T_log_rate>::type stan::math::poisson_log_log (const T_n & n,
const T_log_rate & alpha 
)
+
+ +

Definition at line 32 of file poisson_log_log.hpp.

+ +
+
+ +
+
+
+template<typename T_n , typename T_log_rate >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
return_type<T_log_rate>::type stan::math::poisson_log_log (const T_n & n,
const T_log_rate & alpha 
)
+
+inline
+
+ +

Definition at line 112 of file poisson_log_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::poisson_log_rng (const double alpha,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 23 of file poisson_log_rng.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::poisson_rng (const double lambda,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 24 of file poisson_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::positive_constrain (const T x)
+
+inline
+
+ +

Return the positive value for the specified unconstrained input.

+

The transform applied is

+

$f(x) = \exp(x)$.

+
Parameters
+ + +
xArbitrary input scalar.
+
+
+
Returns
Input transformed to be positive.
+ +

Definition at line 22 of file positive_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::math::positive_constrain (const T x,
T & lp 
)
+
+inline
+
+ +

Return the positive value for the specified unconstrained input, incrementing the scalar reference with the log absolute Jacobian determinant.

+

See positive_constrain(T) for details of the transform. The log absolute Jacobian determinant is

+

$\log | \frac{d}{dx} \mbox{exp}(x) | = \log | \mbox{exp}(x) | = x$.

+
Parameters
+ + + +
xArbitrary input scalar.
lpLog probability reference.
+
+
+
Returns
Input transformed to be positive.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 44 of file positive_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::positive_free (const T y)
+
+inline
+
+ +

Return the unconstrained value corresponding to the specified positive-constrained value.

+

The transform is the inverse of the transform $f$ applied by positive_constrain(T), namely

+

$f^{-1}(x) = \log(x)$.

+

The input is validated using stan::math::check_positive().

+
Parameters
+ + +
yInput scalar.
+
+
+
Returns
Unconstrained value that produces the input when constrained.
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Exceptions
+ + +
std::domain_errorif the variable is negative.
+
+
+ +

Definition at line 29 of file positive_free.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::positive_infinity ()
+
+inline
+
+ +

Return positive infinity.

+
Returns
Positive infinity.
+ +

Definition at line 123 of file constants.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::positive_ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x)
+
+ +

Return an increasing positive ordered vector derived from the specified free vector.

+

The returned constrained vector will have the same dimensionality as the specified free vector.

+
Parameters
+ + +
xFree vector of scalars.
+
+
+
Returns
Positive, increasing ordered vector.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 23 of file positive_ordered_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::positive_ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x,
T & lp 
)
+
+inline
+
+ +

Return a positive valued, increasing positive ordered vector derived from the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform.

+

The returned constrained vector will have the same dimensionality as the specified free vector.

+
Parameters
+ + + +
xFree vector of scalars.
lpLog probability reference.
+
+
+
Returns
Positive, increasing ordered vector.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 55 of file positive_ordered_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::positive_ordered_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & y)
+
+ +

Return the vector of unconstrained scalars that transform to the specified positive ordered vector.

+

This function inverts the constraining operation defined in positive_ordered_constrain(Matrix),

+
Parameters
+ + +
yVector of positive, ordered scalars.
+
+
+
Returns
Free vector that transforms into the input vector.
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Exceptions
+ + +
std::domain_errorif y is not a vector of positive, ordered scalars.
+
+
+ +

Definition at line 26 of file positive_ordered_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::pow (const fvar< T > & x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 18 of file pow.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::pow (const double x1,
const fvar< T > & x2 
)
+
+inline
+
+ +

Definition at line 30 of file pow.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::pow (const fvar< T > & x1,
const double x2 
)
+
+inline
+
+ +

Definition at line 40 of file pow.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::pow (const varbase,
const varexponent 
)
+
+inline
+
+ +

Return the base raised to the power of the exponent (cmath).

+

The partial derivatives are

+

$\frac{\partial}{\partial x} \mbox{pow}(x, y) = y x^{y-1}$, and

+

$\frac{\partial}{\partial y} \mbox{pow}(x, y) = x^y \ \log x$.

+

+\[ \mbox{pow}(x, y) = \begin{cases} x^y & \mbox{if } -\infty\leq x, y \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{pow}(x, y)}{\partial x} = \begin{cases} yx^{y-1} & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{pow}(x, y)}{\partial y} = \begin{cases} x^y\ln x & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } y = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + + +
baseBase variable.
exponentExponent variable.
+
+
+
Returns
Base raised to the exponent.
+ +

Definition at line 103 of file pow.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::pow (const varbase,
const double exponent 
)
+
+inline
+
+ +

Return the base variable raised to the power of the exponent scalar (cmath).

+

The derivative for the variable is

+

$\frac{d}{dx} \mbox{pow}(x, c) = c x^{c-1}$.

+
Parameters
+ + + +
baseBase variable.
exponentExponent scalar.
+
+
+
Returns
Base raised to the exponent.
+ +

Definition at line 119 of file pow.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::pow (const double base,
const varexponent 
)
+
+inline
+
+ +

Return the base scalar raised to the power of the exponent variable (cmath).

+

The derivative for the variable is

+

$\frac{d}{d y} \mbox{pow}(c, y) = c^y \log c $.

+
Parameters
+ + + +
baseBase scalar.
exponentExponent variable.
+
+
+
Returns
Base raised to the exponent.
+ +

Definition at line 141 of file pow.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + + + + + + + +
var stan::math::precomputed_gradients (const double value,
const std::vector< var > & operands,
const std::vector< double > & gradients 
)
+
+ +

This function returns a var for an expression that has the specified value, vector of operands, and vector of partial derivatives of value with respect to the operands.

+
Parameters
+ + + + +
[in]valueThe value of the resulting dependent variable.
[in]operandsoperands.
[in]gradientsvector of partial derivatives of result with respect to operands.
+
+
+
Returns
An auto-diff variable that uses the precomputed gradients provided.
+ +

Definition at line 98 of file precomputed_gradients.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
double stan::math::primitive_value (const varv)
+
+inline
+
+ +

Return the primitive double value for the specified auto-diff variable.

+
Parameters
+ + +
vinput variable.
+
+
+
Returns
value of input.
+ +

Definition at line 17 of file primitive_value.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
double stan::math::primitive_value (const fvar< T > & v)
+
+inline
+
+ +

Return the primitive value of the specified forward-mode autodiff variable.

+

This function applies recursively to higher-order autodiff types to return a primitive double value.

+
Template Parameters
+ + +
Tscalar type for autodiff variable.
+
+
+
Parameters
+ + +
vinput variable.
+
+
+
Returns
primitive value of input.
+ +

Definition at line 22 of file primitive_value.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::enable_if<boost::is_arithmetic<T>, T>::type stan::math::primitive_value (x)
+
+inline
+
+ +

Return the value of the specified arithmetic argument unmodified with its own declared type.

+

This template function can only be instantiated with arithmetic types as defined by Boost's is_arithmetic trait metaprogram.

+

This function differs from stan::math::value_of in that it does not cast all return types to double.

+
Template Parameters
+ + +
Ttype of arithmetic input.
+
+
+
Parameters
+ + +
xinput.
+
+
+
Returns
input unmodified.
+ +

Definition at line 30 of file primitive_value.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::disable_if<boost::is_arithmetic<T>, double>::type stan::math::primitive_value (const T & x)
+
+inline
+
+ +

Return the primitive value of the specified argument.

+

This implementation only applies to non-arithmetic types as defined by Boost's is_arithmetic trait metaprogram.

+
Template Parameters
+ + +
Ttype of non-arithmetic input.
+
+
+
Parameters
+ + +
xinput.
+
+
+
Returns
value of input.
+ +

Definition at line 47 of file primitive_value.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + +
void stan::math::print_mat_size (int n,
std::ostream & o 
)
+
+ +

Helper function to return the matrix size as either "dynamic" or "1".

+
Parameters
+ + + +
nEigen matrix size specification.
oOutput stream.
+
+
+
Returns
String representing size.
+ +

Definition at line 26 of file assign.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
void stan::math::print_stack (std::ostream & o)
+
+inline
+
+ +

Prints the auto-dif variable stack.

+

This function is used for debugging purposes.

+

Only works if all members of stack are vari* as it casts to vari*.

+
Parameters
+ + +
oostream to modify
+
+
+ +

Definition at line 20 of file print_stack.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::prob_constrain (const T x)
+
+inline
+
+ +

Return a probability value constrained to fall between 0 and 1 (inclusive) for the specified free scalar.

+

The transform is the inverse logit,

+

$f(x) = \mbox{logit}^{-1}(x) = \frac{1}{1 + \exp(x)}$.

+
Parameters
+ + +
xFree scalar.
+
+
+
Returns
Probability-constrained result of transforming the free scalar.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 27 of file prob_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::math::prob_constrain (const T x,
T & lp 
)
+
+inline
+
+ +

Return a probability value constrained to fall between 0 and 1 (inclusive) for the specified free scalar and increment the specified log probability reference with the log absolute Jacobian determinant of the transform.

+

The transform is as defined for prob_constrain(T). The log absolute Jacobian determinant is

+

The log absolute Jacobian determinant is

+

$\log | \frac{d}{dx} \mbox{logit}^{-1}(x) |$

+

$\log ((\mbox{logit}^{-1}(x)) (1 - \mbox{logit}^{-1}(x))$

+

$\log (\mbox{logit}^{-1}(x)) + \log (1 - \mbox{logit}^{-1}(x))$.

+
Parameters
+ + + +
xFree scalar.
lpLog probability reference.
+
+
+
Returns
Probability-constrained result of transforming the free scalar.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 55 of file prob_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::prob_free (const T y)
+
+inline
+
+ +

Return the free scalar that when transformed to a probability produces the specified scalar.

+

The function that reverses the constraining transform specified in prob_constrain(T) is the logit function,

+

$f^{-1}(y) = \mbox{logit}(y) = \frac{1 - y}{y}$.

+
Parameters
+ + +
yScalar input.
+
+
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Exceptions
+ + +
std::domain_errorif y is less than 0 or greater than 1.
+
+
+ +

Definition at line 27 of file prob_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::prod (const std::vector< T > & v)
+
+inline
+
+ +

Returns the product of the coefficients of the specified standard vector.

+
Parameters
+ + +
vSpecified vector.
+
+
+
Returns
Product of coefficients of vector.
+ +

Definition at line 17 of file prod.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
T stan::math::prod (const Eigen::Matrix< T, R, C > & v)
+
+inline
+
+ +

Returns the product of the coefficients of the specified column vector.

+
Parameters
+ + +
vSpecified vector.
+
+
+
Returns
Product of coefficients of vector.
+ +

Definition at line 32 of file prod.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename F >
+ + + + + +
+ + + + + + + + +
common_type<T1, T2>::type stan::math::promote_common (const F & u)
+
+inline
+
+ +

Definition at line 14 of file promote_common.hpp.

+ +
+
+ +
+
+
+template<typename T , typename S >
+ + + + + + + + +
promote_scalar_type<T, S>::type stan::math::promote_scalar (const S & x)
+
+ +

This is the top-level function to call to promote the scalar types of an input of type S to type T.

+
Template Parameters
+ + + +
Tscalar type of output.
Sinput type.
+
+
+
Parameters
+ + +
xinput vector.
+
+
+
Returns
input vector with scalars promoted to type T.
+ +

Definition at line 67 of file promote_scalar.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::qr_Q (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+ +

Definition at line 14 of file qr_Q.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<fvar<T>, Eigen::Dynamic, Eigen::Dynamic> stan::math::qr_Q (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+ +

Definition at line 15 of file qr_Q.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::qr_R (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+ +

Definition at line 14 of file qr_R.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<fvar<T>, Eigen::Dynamic, Eigen::Dynamic> stan::math::qr_R (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+ +

Definition at line 15 of file qr_R.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, int CB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, CB, CB> stan::math::quad_form (const Eigen::Matrix< T, RA, CA > & A,
const Eigen::Matrix< T, RB, CB > & B 
)
+
+inline
+
+ +

Compute B^T A B.

+ +

Definition at line 21 of file quad_form.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::math::quad_form (const Eigen::Matrix< T, RA, CA > & A,
const Eigen::Matrix< T, RB, 1 > & B 
)
+
+inline
+
+ +

Definition at line 33 of file quad_form.hpp.

+ +
+
+ +
+
+
+template<typename TA , int RA, int CA, typename TB , int RB, int CB>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c< boost::is_same<TA, var>::value || boost::is_same<TB, var>::value, Eigen::Matrix<var, CB, CB> >::type stan::math::quad_form (const Eigen::Matrix< TA, RA, CA > & A,
const Eigen::Matrix< TB, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 124 of file quad_form.hpp.

+ +
+
+ +
+
+
+template<typename TA , int RA, int CA, typename TB , int RB>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c< boost::is_same<TA, var>::value || boost::is_same<TB, var>::value, var >::type stan::math::quad_form (const Eigen::Matrix< TA, RA, CA > & A,
const Eigen::Matrix< TB, RB, 1 > & B 
)
+
+inline
+
+ +

Definition at line 141 of file quad_form.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix< typename boost::math::tools::promote_args<T1, T2>::type, Eigen::Dynamic, Eigen::Dynamic> stan::math::quad_form_diag (const Eigen::Matrix< T1, Eigen::Dynamic, Eigen::Dynamic > & mat,
const Eigen::Matrix< T2, R, C > & vec 
)
+
+inline
+
+ +

Definition at line 17 of file quad_form_diag.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, int CB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, CB, CB> stan::math::quad_form_sym (const Eigen::Matrix< fvar< T >, RA, CA > & A,
const Eigen::Matrix< double, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 14 of file quad_form_sym.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, int CB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, CB, CB> stan::math::quad_form_sym (const Eigen::Matrix< T, RA, CA > & A,
const Eigen::Matrix< T, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 19 of file quad_form_sym.hpp.

+ +
+
+ +
+
+
+template<typename TA , int RA, int CA, typename TB , int RB, int CB>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c< boost::is_same<TA, var>::value || boost::is_same<TB, var>::value, Eigen::Matrix<var, CB, CB> >::type stan::math::quad_form_sym (const Eigen::Matrix< TA, RA, CA > & A,
const Eigen::Matrix< TB, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 25 of file quad_form_sym.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::quad_form_sym (const Eigen::Matrix< fvar< T >, RA, CA > & A,
const Eigen::Matrix< double, RB, 1 > & B 
)
+
+inline
+
+ +

Definition at line 28 of file quad_form_sym.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
T stan::math::quad_form_sym (const Eigen::Matrix< T, RA, CA > & A,
const Eigen::Matrix< T, RB, 1 > & B 
)
+
+inline
+
+ +

Definition at line 34 of file quad_form_sym.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, int CB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, CB, CB> stan::math::quad_form_sym (const Eigen::Matrix< double, RA, CA > & A,
const Eigen::Matrix< fvar< T >, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 39 of file quad_form_sym.hpp.

+ +
+
+ +
+
+
+template<typename TA , int RA, int CA, typename TB , int RB>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c< boost::is_same<TA, var>::value || boost::is_same<TB, var>::value, var >::type stan::math::quad_form_sym (const Eigen::Matrix< TA, RA, CA > & A,
const Eigen::Matrix< TB, RB, 1 > & B 
)
+
+inline
+
+ +

Definition at line 43 of file quad_form_sym.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::quad_form_sym (const Eigen::Matrix< double, RA, CA > & A,
const Eigen::Matrix< fvar< T >, RB, 1 > & B 
)
+
+inline
+
+ +

Definition at line 53 of file quad_form_sym.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::rank (const std::vector< T > & v,
int s 
)
+
+inline
+
+ +

Return the number of components of v less than v[s].

+
Template Parameters
+ + +
TType of elements.
+
+
+
Parameters
+ + + +
[in]vInput vector.
[in]sPosition in vector.
+
+
+
Returns
Number of components of v less than v[s].
+ +

Definition at line 20 of file rank.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
int stan::math::rank (const Eigen::Matrix< T, R, C > & v,
int s 
)
+
+inline
+
+ +

Return the number of components of v less than v[s].

+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+
Parameters
+ + + +
[in]vInput vector.
sIndex for input vector.
+
+
+
Returns
Number of components of v less than v[s].
+ +

Definition at line 42 of file rank.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale>::type stan::math::rayleigh_ccdf_log (const T_y & y,
const T_scale & sigma 
)
+
+ +

Definition at line 27 of file rayleigh_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale>::type stan::math::rayleigh_cdf (const T_y & y,
const T_scale & sigma 
)
+
+ +

Definition at line 28 of file rayleigh_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale>::type stan::math::rayleigh_cdf_log (const T_y & y,
const T_scale & sigma 
)
+
+ +

Definition at line 28 of file rayleigh_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_scale >
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale>::type stan::math::rayleigh_log (const T_y & y,
const T_scale & sigma 
)
+
+ +

Definition at line 29 of file rayleigh_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
return_type<T_y, T_scale>::type stan::math::rayleigh_log (const T_y & y,
const T_scale & sigma 
)
+
+inline
+
+ +

Definition at line 109 of file rayleigh_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::rayleigh_rng (const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 24 of file rayleigh_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::read_corr_L (const Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs,
const size_t K 
)
+
+ +

Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations.

+

It is generally better to work with the Cholesky factor rather than the correlation matrix itself when the determinant, inverse, etc. of the correlation matrix is needed for some statistical calculation.

+

See read_corr_matrix(Array, size_t, T) for more information.

+
Parameters
+ + + +
CPCsThe (K choose 2) canonical partial correlations in (-1, 1).
KDimensionality of correlation matrix.
+
+
+
Returns
Cholesky factor of correlation matrix for specified canonical partial correlations.
+
Template Parameters
+ + +
TType of underlying scalar.
+
+
+ +

Definition at line 41 of file read_corr_L.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::read_corr_L (const Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs,
const size_t K,
T & log_prob 
)
+
+ +

Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations, incrementing the specified scalar reference with the log absolute determinant of the Jacobian of the transformation.

+

The implementation is Ben Goodrich's Cholesky factor-based approach to the C-vine method of:

+
    +
  • +Daniel Lewandowski, Dorota Kurowicka, and Harry Joe, Generating random correlation matrices based on vines and extended onion method Journal of Multivariate Analysis 100 (2009) 1989–2001
  • +
+
Parameters
+ + + + +
CPCsThe (K choose 2) canonical partial correlations in (-1, 1).
KDimensionality of correlation matrix.
log_probReference to variable to increment with the log Jacobian determinant.
+
+
+
Returns
Cholesky factor of correlation matrix for specified partial correlations.
+
Template Parameters
+ + +
TType of underlying scalar.
+
+
+ +

Definition at line 95 of file read_corr_L.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::read_corr_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs,
const size_t K 
)
+
+ +

Return the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations.

+

See read_corr_matrix(Array, size_t, T) for more information.

+
Parameters
+ + + +
CPCsThe (K choose 2) canonical partial correlations in (-1, 1).
KDimensionality of correlation matrix.
+
+
+
Returns
Cholesky factor of correlation matrix for specified canonical partial correlations.
+
Template Parameters
+ + +
TType of underlying scalar.
+
+
+ +

Definition at line 28 of file read_corr_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::read_corr_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs,
const size_t K,
T & log_prob 
)
+
+ +

Return the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations, incrementing the specified scalar reference with the log absolute determinant of the Jacobian of the transformation.

+

It is usually preferable to utilize the version that returns the Cholesky factor of the correlation matrix rather than the correlation matrix itself in statistical calculations.

+
Parameters
+ + + + +
CPCsThe (K choose 2) canonical partial correlations in (-1, 1).
KDimensionality of correlation matrix.
log_probReference to variable to increment with the log Jacobian determinant.
+
+
+
Returns
Correlation matrix for specified partial correlations.
+
Template Parameters
+ + +
TType of underlying scalar.
+
+
+ +

Definition at line 56 of file read_corr_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::read_cov_L (const Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs,
const Eigen::Array< T, Eigen::Dynamic, 1 > & sds,
T & log_prob 
)
+
+ +

This is the function that should be called prior to evaluating the density of any elliptical distribution.

+
Parameters
+ + + + +
CPCson (-1, 1)
sdson (0, inf)
log_probthe log probability value to increment with the Jacobian
+
+
+
Returns
Cholesky factor of covariance matrix for specified partial correlations.
+ +

Definition at line 23 of file read_cov_L.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::read_cov_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs,
const Eigen::Array< T, Eigen::Dynamic, 1 > & sds,
T & log_prob 
)
+
+ +

A generally worse alternative to call prior to evaluating the density of an elliptical distribution.

+
Parameters
+ + + + +
CPCson (-1, 1)
sdson (0, inf)
log_probthe log probability value to increment with the Jacobian
+
+
+
Returns
Covariance matrix for specified partial correlations.
+ +

Definition at line 23 of file read_cov_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::read_cov_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > & CPCs,
const Eigen::Array< T, Eigen::Dynamic, 1 > & sds 
)
+
+ +

Builds a covariance matrix from CPCs and standard deviations.

+
Parameters
+ + + +
CPCsin (-1, 1)
sdsin (0, inf)
+
+
+ +

Definition at line 41 of file read_cov_matrix.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static void stan::math::recover_memory ()
+
+inlinestatic
+
+ +

Recover memory used for all variables for reuse.

+
Exceptions
+ + +
std::logic_errorif empty_nested() returns false
+
+
+ +

Definition at line 18 of file recover_memory.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static void stan::math::recover_memory_nested ()
+
+inlinestatic
+
+ +

Recover only the memory used for the top nested call.

+

If there is nothing on the nested stack, then a std::logic_error exception is thrown.

+
Exceptions
+ + +
std::logic_errorif empty_nested() returns true
+
+
+ +

Definition at line 20 of file recover_memory_nested.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
std::vector<T> stan::math::rep_array (const T & x,
int n 
)
+
+inline
+
+ +

Definition at line 13 of file rep_array.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
std::vector<std::vector<T> > stan::math::rep_array (const T & x,
int m,
int n 
)
+
+inline
+
+ +

Definition at line 21 of file rep_array.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
std::vector<std::vector<std::vector<T> > > stan::math::rep_array (const T & x,
int k,
int m,
int n 
)
+
+inline
+
+ +

Definition at line 31 of file rep_array.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T>::type, Eigen::Dynamic, Eigen::Dynamic> stan::math::rep_matrix (const T & x,
int m,
int n 
)
+
+inline
+
+ +

Definition at line 16 of file rep_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::rep_matrix (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & v,
int n 
)
+
+inline
+
+ +

Definition at line 26 of file rep_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::rep_matrix (const Eigen::Matrix< T, 1, Eigen::Dynamic > & rv,
int m 
)
+
+inline
+
+ +

Definition at line 36 of file rep_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T>::type, 1, Eigen::Dynamic> stan::math::rep_row_vector (const T & x,
int m 
)
+
+inline
+
+ +

Definition at line 15 of file rep_row_vector.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T>::type, Eigen::Dynamic, 1> stan::math::rep_vector (const T & x,
int n 
)
+
+inline
+
+ +

Definition at line 16 of file rep_vector.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::resize (T & x,
std::vector< size_t > dims 
)
+
+inline
+
+ +

Recursively resize the specified vector of vectors, which must bottom out at scalar values, Eigen vectors or Eigen matrices.

+
Parameters
+ + + +
xArray-like object to resize.
dimsNew dimensions.
+
+
+
Template Parameters
+ + +
TType of object being resized.
+
+
+ +

Definition at line 63 of file resize.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::rising_factorial (const fvar< T > & x,
const fvar< T > & n 
)
+
+inline
+
+ +

Definition at line 16 of file rising_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::rising_factorial (const fvar< T > & x,
const double n 
)
+
+inline
+
+ +

Definition at line 28 of file rising_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::rising_factorial (const double x,
const fvar< T > & n 
)
+
+inline
+
+ +

Definition at line 41 of file rising_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::rising_factorial (const T1 x,
const T2 n 
)
+
+inline
+
+ +

+\[ \mbox{rising\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ x^{(n)} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{rising\_factorial}(x, n)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \frac{\partial\, x^{(n)}}{\partial x} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{rising\_factorial}(x, n)}{\partial n} = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \frac{\partial\, x^{(n)}}{\partial n} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

+

+\[ x^{(n)}=\frac{\Gamma(x+n)}{\Gamma(x)} \] +

+

+\[ \frac{\partial \, x^{(n)}}{\partial x} = x^{(n)}(\Psi(x+n)-\Psi(x)) \] +

+

+\[ \frac{\partial \, x^{(n)}}{\partial n} = (x)_n\Psi(x+n) \] +

+ +

Definition at line 54 of file rising_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::rising_factorial (const vara,
const double & b 
)
+
+inline
+
+ +

Definition at line 54 of file rising_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::rising_factorial (const vara,
const varb 
)
+
+inline
+
+ +

Definition at line 59 of file rising_factorial.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::rising_factorial (const double & a,
const varb 
)
+
+inline
+
+ +

Definition at line 64 of file rising_factorial.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::round (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 11 of file round.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::round (const vara)
+
+inline
+
+ +

Returns the rounded form of the specified variable (C99).

+

See round() for the double-based version.

+

The derivative is zero everywhere but numbers half way between whole numbers, so for convenience the derivative is defined to be everywhere zero,

+

$\frac{d}{dx} \mbox{round}(x) = 0$.

+

+\[ \mbox{round}(x) = \begin{cases} \lceil x \rceil & \mbox{if } x-\lfloor x\rfloor \geq 0.5 \\ \lfloor x \rfloor & \mbox{if } x-\lfloor x\rfloor < 0.5 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{round}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aSpecified variable.
+
+
+
Returns
Rounded variable.
+ +

Definition at line 57 of file round.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::row (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m,
size_t i 
)
+
+inline
+
+ +

Return the specified row of the specified matrix, using start-at-1 indexing.

+

This is equivalent to calling m.row(i - 1) and assigning the resulting template expression to a row vector.

+
Template Parameters
+ + +
TScalar value type for matrix.
+
+
+
Parameters
+ + + +
mMatrix.
iRow index (count from 1).
+
+
+
Returns
Specified row of the matrix.
+ +

Definition at line 25 of file row.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
int stan::math::rows (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Return the number of rows in the specified matrix, vector, or row vector.

+
Template Parameters
+ + + + +
TType of matrix entries.
RRow type of matrix.
CColumn type of matrix.
+
+
+
Parameters
+ + +
[in]mInput matrix, vector, or row vector.
+
+
+
Returns
Number of rows.
+ +

Definition at line 20 of file rows.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, 1> stan::math::rows_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > & v1,
const Eigen::Matrix< fvar< T >, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 18 of file rows_dot_product.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<double, R1, 1> stan::math::rows_dot_product (const Eigen::Matrix< double, R1, C1 > & v1,
const Eigen::Matrix< double, R2, C2 > & v2 
)
+
+inline
+
+ +

Returns the dot product of the specified vectors.

+
Parameters
+ + + +
v1First vector.
v2Second vector.
+
+
+
Returns
Dot product of the vectors.
+
Exceptions
+ + +
std::domain_errorIf the vectors are not the same size or if they are both not vector dimensioned.
+
+
+ +

Definition at line 22 of file rows_dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<boost::is_same<T1, var>::value || boost::is_same<T2, var>::value, Eigen::Matrix<var, R1, 1> >::type stan::math::rows_dot_product (const Eigen::Matrix< T1, R1, C1 > & v1,
const Eigen::Matrix< T2, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 25 of file rows_dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, 1> stan::math::rows_dot_product (const Eigen::Matrix< double, R1, C1 > & v1,
const Eigen::Matrix< fvar< T >, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 35 of file rows_dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R1, 1> stan::math::rows_dot_product (const Eigen::Matrix< fvar< T >, R1, C1 > & v1,
const Eigen::Matrix< double, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 52 of file rows_dot_product.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, R, 1> stan::math::rows_dot_self (const Eigen::Matrix< fvar< T >, R, C > & x)
+
+inline
+
+ +

Definition at line 15 of file rows_dot_self.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R, 1> stan::math::rows_dot_self (const Eigen::Matrix< T, R, C > & x)
+
+inline
+
+ +

Returns the dot product of each row of a matrix with itself.

+
Parameters
+ + +
xMatrix.
+
+
+
Template Parameters
+ + +
Tscalar type
+
+
+ +

Definition at line 16 of file rows_dot_self.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::scaled_add (std::vector< double > & x,
const std::vector< double > & y,
const double lambda 
)
+
+inline
+
+ +

Definition at line 11 of file scaled_add.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_scale>::type stan::math::scaled_inv_chi_square_ccdf_log (const T_y & y,
const T_dof & nu,
const T_scale & s 
)
+
+ +

Definition at line 33 of file scaled_inv_chi_square_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_scale>::type stan::math::scaled_inv_chi_square_cdf (const T_y & y,
const T_dof & nu,
const T_scale & s 
)
+
+ +

The CDF of a scaled inverse chi-squared density for y with the specified degrees of freedom parameter and scale parameter.

+
Parameters
+ + + + +
yA scalar variable.
nuDegrees of freedom.
sScale parameter.
+
+
+
Exceptions
+ + + + +
std::domain_errorif nu is not greater than 0
std::domain_errorif s is not greater than 0.
std::domain_errorif y is not greater than 0.
+
+
+
Template Parameters
+ + + +
T_yType of scalar.
T_dofType of degrees of freedom.
+
+
+ +

Definition at line 48 of file scaled_inv_chi_square_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_scale>::type stan::math::scaled_inv_chi_square_cdf_log (const T_y & y,
const T_dof & nu,
const T_scale & s 
)
+
+ +

Definition at line 34 of file scaled_inv_chi_square_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_dof , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_scale>::type stan::math::scaled_inv_chi_square_log (const T_y & y,
const T_dof & nu,
const T_scale & s 
)
+
+ +

The log of a scaled inverse chi-squared density for y with the specified degrees of freedom parameter and scale parameter.

+

+\begin{eqnarray*} y &\sim& \mbox{\sf{Inv-}}\chi^2(\nu, s^2) \\ \log (p (y \, |\, \nu, s)) &=& \log \left( \frac{(\nu / 2)^{\nu / 2}}{\Gamma (\nu / 2)} s^\nu y^{- (\nu / 2 + 1)} \exp^{-\nu s^2 / (2y)} \right) \\ &=& \frac{\nu}{2} \log(\frac{\nu}{2}) - \log (\Gamma (\nu / 2)) + \nu \log(s) - (\frac{\nu}{2} + 1) \log(y) - \frac{\nu s^2}{2y} \\ & & \mathrm{ where } \; y > 0 \end{eqnarray*} +

+
Parameters
+ + + + +
yA scalar variable.
nuDegrees of freedom.
sScale parameter.
+
+
+
Exceptions
+ + + + +
std::domain_errorif nu is not greater than 0
std::domain_errorif s is not greater than 0.
std::domain_errorif y is not greater than 0.
+
+
+
Template Parameters
+ + + +
T_yType of scalar.
T_dofType of degrees of freedom.
+
+
+ +

Definition at line 53 of file scaled_inv_chi_square_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_scale>::type stan::math::scaled_inv_chi_square_log (const T_y & y,
const T_dof & nu,
const T_scale & s 
)
+
+inline
+
+ +

Definition at line 175 of file scaled_inv_chi_square_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::scaled_inv_chi_square_rng (const double nu,
const double s,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 28 of file scaled_inv_chi_square_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::sd (const std::vector< T > & v)
+
+inline
+
+ +

Returns the unbiased sample standard deviation of the coefficients in the specified column vector.

+
Parameters
+ + +
vSpecified vector.
+
+
+
Returns
Sample variance of vector.
+ +

Definition at line 22 of file sd.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::sd (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the unbiased sample standard deviation of the coefficients in the specified vector, row vector, or matrix.

+
Parameters
+ + +
mSpecified vector, row vector or matrix.
+
+
+
Returns
Sample variance.
+ +

Definition at line 37 of file sd.hpp.

+ +
+
+ +
+
+ + + + + + + + +
var stan::math::sd (const std::vector< var > & v)
+
+ +

Return the sample standard deviation of the specified standard vector.

+

Raise domain error if size is not greater than zero.

+
Parameters
+ + +
[in]va vector
+
+
+
Returns
sample standard deviation of specified vector
+ +

Definition at line 65 of file sd.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + + + + +
var stan::math::sd (const Eigen::Matrix< var, R, C > & m)
+
+ +

Definition at line 82 of file sd.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::segment (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & v,
size_t i,
size_t n 
)
+
+inline
+
+ +

Return the specified number of elements as a vector starting from the specified element - 1 of the specified vector.

+ +

Definition at line 19 of file segment.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::segment (const Eigen::Matrix< T, 1, Eigen::Dynamic > & v,
size_t i,
size_t n 
)
+
+inline
+
+ +

Definition at line 35 of file segment.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + + + + + + + +
std::vector<T> stan::math::segment (const std::vector< T > & sv,
size_t i,
size_t n 
)
+
+ +

Definition at line 52 of file segment.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static void stan::math::set_zero_all_adjoints ()
+
+static
+
+ +

Reset all adjoint values in the stack to zero.

+ +

Definition at line 14 of file set_zero_all_adjoints.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static void stan::math::set_zero_all_adjoints_nested ()
+
+static
+
+ +

Reset all adjoint values in the top nested portion of the stack to zero.

+ +

Definition at line 17 of file set_zero_all_adjoints_nested.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
int stan::math::sign (const T & z)
+
+inline
+
+ +

Definition at line 9 of file sign.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::simplex_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & y)
+
+ +

Return the simplex corresponding to the specified free vector.

+

A simplex is a vector containing values greater than or equal to 0 that sum to 1. A vector with (K-1) unconstrained values will produce a simplex of size K.

+

The transform is based on a centered stick-breaking process.

+
Parameters
+ + +
yFree vector input of dimensionality K - 1.
+
+
+
Returns
Simplex of dimensionality K.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 30 of file simplex_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::simplex_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & y,
T & lp 
)
+
+ +

Return the simplex corresponding to the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform.

+

The simplex transform is defined through a centered stick-breaking process.

+
Parameters
+ + + +
yFree vector input of dimensionality K - 1.
lpLog probability reference to increment.
+
+
+
Returns
Simplex of dimensionality K.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 69 of file simplex_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::simplex_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x)
+
+ +

Return an unconstrained vector that when transformed produces the specified simplex.

+

It applies to a simplex of dimensionality K and produces an unconstrained vector of dimensionality (K-1).

+

The simplex transform is defined through a centered stick-breaking process.

+
Parameters
+ + +
xSimplex of dimensionality K.
+
+
+
Returns
Free vector of dimensionality (K-1) that transfroms to the simplex.
+
Template Parameters
+ + +
TType of scalar.
+
+
+
Exceptions
+ + +
std::domain_errorif x is not a valid simplex
+
+
+ +

Definition at line 30 of file simplex_free.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::sin (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file sin.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::sin (const vara)
+
+inline
+
+ +

Return the sine of a radian-scaled variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \sin x = \cos x$.

+

+\[ \mbox{sin}(x) = \begin{cases} \sin(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{sin}(x)}{\partial x} = \begin{cases} \cos(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable for radians of angle.
+
+
+
Returns
Sine of variable.
+ +

Definition at line 49 of file sin.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::singular_values (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+ +

Return the vector of the singular values of the specified matrix in decreasing order of magnitude.

+

See the documentation for svd() for information on the signular values.

Parameters
+ + +
mSpecified matrix.
+
+
+
Returns
Singular values of the matrix.
+ +

Definition at line 21 of file singular_values.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::sinh (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file sinh.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::sinh (const vara)
+
+inline
+
+ +

Return the hyperbolic sine of the specified variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \sinh x = \cosh x$.

+

+\[ \mbox{sinh}(x) = \begin{cases} \sinh(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{sinh}(x)}{\partial x} = \begin{cases} \cosh(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable.
+
+
+
Returns
Hyperbolic sine of variable.
+ +

Definition at line 49 of file sinh.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
int stan::math::size (const std::vector< T > & x)
+
+inline
+
+ +

Return the size of the specified standard vector.

+
Template Parameters
+ + +
TType of elements.
+
+
+
Parameters
+ + +
[in]xInput vector.
+
+
+
Returns
Size of input vector.
+ +

Definition at line 17 of file size.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::skew_normal_ccdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_shape & alpha 
)
+
+ +

Definition at line 27 of file skew_normal_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::skew_normal_cdf (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_shape & alpha 
)
+
+ +

Definition at line 27 of file skew_normal_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::skew_normal_cdf_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_shape & alpha 
)
+
+ +

Definition at line 27 of file skew_normal_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::skew_normal_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_shape & alpha 
)
+
+ +

Definition at line 28 of file skew_normal_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale, T_shape>::type stan::math::skew_normal_log (const T_y & y,
const T_loc & mu,
const T_scale & sigma,
const T_shape & alpha 
)
+
+inline
+
+ +

Definition at line 147 of file skew_normal_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::skew_normal_rng (const double mu,
const double sigma,
const double alpha,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 22 of file skew_normal_rng.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1> stan::math::softmax (const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > & alpha)
+
+inline
+
+ +

Definition at line 14 of file softmax.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::softmax (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & v)
+
+inline
+
+ +

Return the softmax of the specified vector.

+

$ \mbox{softmax}(y) = \frac{\exp(y)} {\sum_{k=1}^K \exp(y_k)}, $

+

The entries in the Jacobian of the softmax function are given by $ \begin{array}{l} \displaystyle \frac{\partial}{\partial y_m} \mbox{softmax}(y)[k] \\[8pt] \displaystyle \mbox{ } \ \ \ = \left\{ \begin{array}{ll} \mbox{softmax}(y)[k] - \mbox{softmax}(y)[k] \times \mbox{softmax}(y)[m] & \mbox{ if } m = k, \mbox{ and} \\[6pt] \mbox{softmax}(y)[k] * \mbox{softmax}(y)[m] & \mbox{ if } m \neq k. \end{array} \right. \end{array} $

+
Template Parameters
+ + +
TScalar type of values in vector.
+
+
+
Parameters
+ + +
[in]vVector to transform.
+
+
+
Returns
Unit simplex result of the softmax transform of the vector.
+ +

Definition at line 46 of file softmax.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<var, Eigen::Dynamic, 1> stan::math::softmax (const Eigen::Matrix< var, Eigen::Dynamic, 1 > & alpha)
+
+inline
+
+ +

Return the softmax of the specified Eigen vector.

+

Softmax is guaranteed to return a simplex.

+

The gradient calculations are unfolded.

+
Parameters
+ + +
alphaUnconstrained input vector.
+
+
+
Returns
Softmax of the input.
+
Exceptions
+ + +
std::domain_errorIf the input vector is size 0.
+
+
+ +

Definition at line 59 of file softmax.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector< fvar<T> > stan::math::sort_asc (std::vector< fvar< T > > xs)
+
+inline
+
+ +

Definition at line 17 of file sort_asc.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<T> stan::math::sort_asc (std::vector< T > xs)
+
+inline
+
+ +

Return the specified standard vector in ascending order.

+
Parameters
+ + +
xsStandard vector to order.
+
+
+
Returns
Standard vector ordered.
+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+ +

Definition at line 20 of file sort.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
std::vector<var> stan::math::sort_asc (std::vector< varxs)
+
+inline
+
+ +

Return the specified standard vector in ascending order with gradients kept.

+
Parameters
+ + +
xsStandard vector to order.
+
+
+
Returns
Standard vector ordered.
+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+ +

Definition at line 21 of file sort_asc.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::sort_asc (Eigen::Matrix< fvar< T >, R, C > xs)
+
+inline
+
+ +

Definition at line 25 of file sort_asc.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<var, R, C> stan::math::sort_asc (Eigen::Matrix< var, R, C > xs)
+
+inline
+
+ +

Return the specified eigen vector in ascending order with gradients kept.

+
Parameters
+ + +
xsEigen vector to order.
+
+
+
Returns
Eigen vector ordered.
+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+ +

Definition at line 35 of file sort_asc.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R, C> stan::math::sort_asc (Eigen::Matrix< T, R, C > xs)
+
+inline
+
+ +

Return the specified eigen vector in ascending order.

+
Parameters
+ + +
xsEigen vector to order.
+
+
+
Returns
Eigen vector ordered.
+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+ +

Definition at line 46 of file sort.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector< fvar<T> > stan::math::sort_desc (std::vector< fvar< T > > xs)
+
+inline
+
+ +

Definition at line 17 of file sort_desc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
std::vector<var> stan::math::sort_desc (std::vector< varxs)
+
+inline
+
+ +

Return the specified standard vector in descending order with gradients kept.

+
Parameters
+ + +
xsStandard vector to order.
+
+
+
Returns
Standard vector ordered.
+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+ +

Definition at line 21 of file sort_desc.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::sort_desc (Eigen::Matrix< fvar< T >, R, C > xs)
+
+inline
+
+ +

Definition at line 25 of file sort_desc.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<T> stan::math::sort_desc (std::vector< T > xs)
+
+inline
+
+ +

Return the specified standard vector in descending order.

+
Parameters
+ + +
xsStandard vector to order.
+
+
+
Returns
Standard vector ordered.
+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+ +

Definition at line 33 of file sort.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<var, R, C> stan::math::sort_desc (Eigen::Matrix< var, R, C > xs)
+
+inline
+
+ +

Return the specified eigen vector in descending order with gradients kept.

+
Parameters
+ + +
xsEigen vector to order.
+
+
+
Returns
Eigen vector ordered.
+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+ +

Definition at line 35 of file sort_desc.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R, C> stan::math::sort_desc (Eigen::Matrix< T, R, C > xs)
+
+inline
+
+ +

Return the specified eigen vector in descending order.

+
Parameters
+ + +
xsEigen vector to order.
+
+
+
Returns
Eigen vector ordered.
+
Template Parameters
+ + +
TType of elements of the vector.
+
+
+ +

Definition at line 60 of file sort.hpp.

+ +
+
+ +
+
+
+template<typename C >
+ + + + + + + + +
std::vector<int> stan::math::sort_indices_asc (const C & xs)
+
+ +

Return a sorted copy of the argument container in ascending order.

+
Template Parameters
+ + +
Ctype of container
+
+
+
Parameters
+ + +
xsContainer to sort
+
+
+
Returns
sorted version of container
+ +

Definition at line 23 of file sort_indices_asc.hpp.

+ +
+
+ +
+
+
+template<typename C >
+ + + + + + + + +
std::vector<int> stan::math::sort_indices_desc (const C & xs)
+
+ +

Return a sorted copy of the argument container in ascending order.

+
Template Parameters
+ + +
Ctype of container
+
+
+
Parameters
+ + +
xsContainer to sort
+
+
+
Returns
sorted version of container
+ +

Definition at line 23 of file sort_indices_desc.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::sqrt (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file sqrt.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::sqrt (const vara)
+
+inline
+
+ +

Return the square root of the specified variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \sqrt{x} = \frac{1}{2 \sqrt{x}}$.

+

+\[ \mbox{sqrt}(x) = \begin{cases} \textrm{NaN} & x < 0 \\ \sqrt{x} & \mbox{if } x\geq 0\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{sqrt}(x)}{\partial x} = \begin{cases} \textrm{NaN} & x < 0 \\ \frac{1}{2\sqrt{x}} & x\geq 0\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable whose square root is taken.
+
+
+
Returns
Square root of variable.
+ +

Definition at line 50 of file sqrt.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
double stan::math::sqrt2 ()
+
+inline
+
+ +

Return the square root of two.

+
Returns
Square root of two.
+ +

Definition at line 104 of file constants.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::square (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file square.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::square (const T x)
+
+inline
+
+ +

Return the square of the specified argument.

+

$\mbox{square}(x) = x^2$.

+

The implementation of square(x) is just x * x. Given this, this method is mainly useful in cases where x is not a simple primitive type, particularly when it is an auto-dif type.

+
Parameters
+ + +
xInput to square.
+
+
+
Returns
Square of input.
+
Template Parameters
+ + +
TType of scalar.
+
+
+ +

Definition at line 22 of file square.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::square (const varx)
+
+inline
+
+ +

Return the square of the input variable.

+

Using square(x) is more efficient than using x * x.

+

+\[ \mbox{square}(x) = \begin{cases} x^2 & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{square}(x)}{\partial x} = \begin{cases} 2x & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
xVariable to square.
+
+
+
Returns
Square of variable.
+ +

Definition at line 46 of file square.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2, typename T1 , typename T2 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T1, T2>::type stan::math::squared_distance (const Eigen::Matrix< T1, R1, C1 > & v1,
const Eigen::Matrix< T2, R2, C2 > & v2 
)
+
+inline
+
+ +

Returns the squared distance between the specified vectors.

+
Parameters
+ + + +
v1First vector.
v2Second vector.
+
+
+
Returns
Dot product of the vectors.
+
Exceptions
+ + +
std::domain_errorIf the vectors are not the same size or if they are both not vector dimensioned.
+
+
+ +

Definition at line 22 of file squared_distance.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::squared_distance (const Eigen::Matrix< var, R1, C1 > & v1,
const Eigen::Matrix< var, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 112 of file squared_distance.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::squared_distance (const Eigen::Matrix< var, R1, C1 > & v1,
const Eigen::Matrix< double, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 122 of file squared_distance.hpp.

+ +
+
+ +
+
+
+template<int R1, int C1, int R2, int C2>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
var stan::math::squared_distance (const Eigen::Matrix< double, R1, C1 > & v1,
const Eigen::Matrix< var, R2, C2 > & v2 
)
+
+inline
+
+ +

Definition at line 132 of file squared_distance.hpp.

+ +
+
+ +
+
+ + + + + + + + + + + + + + + + + + +
void stan::math::stan_print (std::ostream * o,
const varx 
)
+
+ +

Definition at line 10 of file stan_print.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
void stan::math::stan_print (std::ostream * o,
const T & x 
)
+
+ +

Definition at line 12 of file stan_print.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
void stan::math::stan_print (std::ostream * o,
const std::vector< T > & x 
)
+
+ +

Definition at line 17 of file stan_print.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
void stan::math::stan_print (std::ostream * o,
const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x 
)
+
+ +

Definition at line 27 of file stan_print.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
void stan::math::stan_print (std::ostream * o,
const Eigen::Matrix< T, 1, Eigen::Dynamic > & x 
)
+
+ +

Definition at line 38 of file stan_print.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
void stan::math::stan_print (std::ostream * o,
const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & x 
)
+
+ +

Definition at line 49 of file stan_print.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static void stan::math::start_nested ()
+
+inlinestatic
+
+ +

Record the current position so that recover_memory_nested() can find it.

+ +

Definition at line 13 of file start_nested.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::step (const stan::math::vara)
+
+inline
+
+ +

Return the step, or heaviside, function applied to the specified variable (stan).

+

See stan::math::step() for the double-based version.

+

The derivative of the step function is zero everywhere but at 0, so for convenience, it is taken to be everywhere zero,

+

$\mbox{step}(x) = 0$.

+
Parameters
+ + +
aVariable argument.
+
+
+
Returns
The constant variable with value 1.0 if the argument's value is greater than or equal to 0.0, and value 0.0 otherwise.
+ +

Definition at line 25 of file step.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
int stan::math::step (const T y)
+
+inline
+
+ +

The step, or Heaviside, function.

+

The function is defined by

+

step(y) = (y < 0.0) ? 0 : 1.

+

+\[ \mbox{step}(x) = \begin{cases} 0 & \mbox{if } x \leq 0 \\ 1 & \mbox{if } x > 0 \\[6pt] 0 & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
yScalar argument.
+
+
+
Returns
1 if the specified argument is greater than or equal to 0.0, and 0 otherwise.
+ +

Definition at line 29 of file step.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_loc, T_scale>::type stan::math::student_t_ccdf_log (const T_y & y,
const T_dof & nu,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 33 of file student_t_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_loc, T_scale>::type stan::math::student_t_cdf (const T_y & y,
const T_dof & nu,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 33 of file student_t_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_loc, T_scale>::type stan::math::student_t_cdf_log (const T_y & y,
const T_dof & nu,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

Definition at line 33 of file student_t_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_dof , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_loc, T_scale>::type stan::math::student_t_log (const T_y & y,
const T_dof & nu,
const T_loc & mu,
const T_scale & sigma 
)
+
+ +

The log of the Student-t density for the given y, nu, mean, and scale parameter.

+

The scale parameter must be greater than 0.

+

+\begin{eqnarray*} y &\sim& t_{\nu} (\mu, \sigma^2) \\ \log (p (y \, |\, \nu, \mu, \sigma) ) &=& \log \left( \frac{\Gamma((\nu + 1) /2)} {\Gamma(\nu/2)\sqrt{\nu \pi} \sigma} \left( 1 + \frac{1}{\nu} (\frac{y - \mu}{\sigma})^2 \right)^{-(\nu + 1)/2} \right) \\ &=& \log( \Gamma( (\nu+1)/2 )) - \log (\Gamma (\nu/2) - \frac{1}{2} \log(\nu \pi) - \log(\sigma) -\frac{\nu + 1}{2} \log (1 + \frac{1}{\nu} (\frac{y - \mu}{\sigma})^2) \end{eqnarray*} +

+
Parameters
+ + + + + +
yA scalar variable.
nuDegrees of freedom.
muThe mean of the Student-t distribution.
sigmaThe scale parameter of the Student-t distribution.
+
+
+
Returns
The log of the Student-t density at y.
+
Exceptions
+ + + +
std::domain_errorif sigma is not greater than 0.
std::domain_errorif nu is not greater than 0.
+
+
+
Template Parameters
+ + + + + +
T_yType of scalar.
T_dofType of degrees of freedom.
T_locType of location.
T_scaleType of scale.
+
+
+ +

Definition at line 58 of file student_t_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_dof, T_loc, T_scale>::type stan::math::student_t_log (const T_y & y,
const T_dof & nu,
const T_loc & mu,
const T_scale & sigma 
)
+
+inline
+
+ +

Definition at line 222 of file student_t_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::student_t_rng (const double nu,
const double mu,
const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 28 of file student_t_rng.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::sub (std::vector< double > & x,
std::vector< double > & y,
std::vector< double > & result 
)
+
+inline
+
+ +

Definition at line 10 of file sub.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::sub_col (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m,
size_t i,
size_t j,
size_t nrows 
)
+
+inline
+
+ +

Return a nrows x 1 subcolumn starting at (i-1, j-1).

+
Parameters
+ + + + + +
mMatrix
iStarting row + 1
jStarting column + 1
nrowsNumber of rows in block
+
+
+ +

Definition at line 22 of file sub_col.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::sub_row (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m,
size_t i,
size_t j,
size_t ncols 
)
+
+inline
+
+ +

Return a 1 x nrows subrow starting at (i-1, j-1).

+
Parameters
+ + + + + +
mMatrix
iStarting row + 1
jStarting column + 1
ncolsNumber of columns in block
+
+
+ +

Definition at line 23 of file sub_row.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::subtract (const Eigen::Matrix< T1, R, C > & m1,
const Eigen::Matrix< T2, R, C > & m2 
)
+
+inline
+
+ +

Return the result of subtracting the second specified matrix from the first specified matrix.

+

The return scalar type is the promotion of the input types.

+
Template Parameters
+ + + + + +
T1Scalar type of first matrix.
T2Scalar type of second matrix.
RRow type of matrices.
CColumn type of matrices.
+
+
+
Parameters
+ + + +
m1First matrix.
m2Second matrix.
+
+
+
Returns
Difference between first matrix and second matrix.
+ +

Definition at line 27 of file subtract.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::subtract (const T1 & c,
const Eigen::Matrix< T2, R, C > & m 
)
+
+inline
+
+ +

Definition at line 43 of file subtract.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C> stan::math::subtract (const Eigen::Matrix< T1, R, C > & m,
const T2 & c 
)
+
+inline
+
+ +

Definition at line 56 of file subtract.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::sum (const std::vector< T > & xs)
+
+inline
+
+ +

Return the sum of the values in the specified standard vector.

+
Template Parameters
+ + +
TType of elements summed.
+
+
+
Parameters
+ + +
xsStandard vector to sum.
+
+
+
Returns
Sum of elements.
+ +

Definition at line 18 of file sum.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::sum (const std::vector< fvar< T > > & m)
+
+inline
+
+ +

Return the sum of the entries of the specified standard vector.

+
Template Parameters
+ + +
TType of vector entries.
+
+
+
Parameters
+ + +
mVector.
+
+
+
Returns
Sum of vector entries.
+ +

Definition at line 20 of file sum.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::sum (const Eigen::Matrix< fvar< T >, R, C > & m)
+
+inline
+
+ +

Return the sum of the entries of the specified matrix.

+
Template Parameters
+ + + + +
TType of matrix entries.
RRow type of matrix.
CColumn type of matrix.
+
+
+
Parameters
+ + +
mMatrix.
+
+
+
Returns
Sum of matrix entries.
+ +

Definition at line 21 of file sum.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
double stan::math::sum (const Eigen::Matrix< T, R, C > & v)
+
+inline
+
+ +

Returns the sum of the coefficients of the specified column vector.

+
Template Parameters
+ + + + +
TType of elements in matrix.
RRow type of matrix.
CColumn type of matrix.
+
+
+
Parameters
+ + +
vSpecified vector.
+
+
+
Returns
Sum of coefficients of vector.
+ +

Definition at line 22 of file sum.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
var stan::math::sum (const Eigen::Matrix< var, R, C > & m)
+
+inline
+
+ +

Returns the sum of the coefficients of the specified matrix, column vector or row vector.

+
Template Parameters
+ + + +
RRow type for matrix.
CColumn type for matrix.
+
+
+
Parameters
+ + +
mSpecified matrix or vector.
+
+
+
Returns
Sum of coefficients of matrix.
+ +

Definition at line 50 of file sum.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::sum (const std::vector< var > & m)
+
+inline
+
+ +

Returns the sum of the entries of the specified vector.

+
Parameters
+ + +
mVector.
+
+
+
Returns
Sum of vector entries.
+ +

Definition at line 53 of file sum.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::tail (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & v,
size_t n 
)
+
+inline
+
+ +

Return the specified number of elements as a vector from the back of the specified vector.

+ +

Definition at line 23 of file tail.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::tail (const Eigen::Matrix< T, 1, Eigen::Dynamic > & rv,
size_t n 
)
+
+inline
+
+ +

Return the specified number of elements as a row vector from the back of the specified row vector.

+ +

Definition at line 38 of file tail.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + + + + + + + + + + + +
std::vector<T> stan::math::tail (const std::vector< T > & sv,
size_t n 
)
+
+ +

Definition at line 46 of file tail.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::tan (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file tan.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::tan (const vara)
+
+inline
+
+ +

Return the tangent of a radian-scaled variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \tan x = \sec^2 x$.

+

+\[ \mbox{tan}(x) = \begin{cases} \tan(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{tan}(x)}{\partial x} = \begin{cases} \sec^2(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable for radians of angle.
+
+
+
Returns
Tangent of variable.
+ +

Definition at line 49 of file tan.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::tanh (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 14 of file tanh.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::tanh (const vara)
+
+inline
+
+ +

Return the hyperbolic tangent of the specified variable (cmath).

+

The derivative is defined by

+

$\frac{d}{dx} \tanh x = \frac{1}{\cosh^2 x}$.

+

+\[ \mbox{tanh}(x) = \begin{cases} \tanh(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{tanh}(x)}{\partial x} = \begin{cases} \mbox{sech}^2(x) & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aVariable.
+
+
+
Returns
Hyperbolic tangent of variable.
+ +

Definition at line 50 of file tanh.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, R, R> stan::math::tcrossprod (const Eigen::Matrix< fvar< T >, R, C > & m)
+
+inline
+
+ +

Definition at line 17 of file tcrossprod.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
matrix_d stan::math::tcrossprod (const matrix_dM)
+
+inline
+
+ +

Returns the result of post-multiplying a matrix by its own transpose.

+
Parameters
+ + +
MMatrix to multiply.
+
+
+
Returns
M times its transpose.
+ +

Definition at line 17 of file tcrossprod.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
matrix_v stan::math::tcrossprod (const matrix_vM)
+
+inline
+
+ +

Returns the result of post-multiplying a matrix by its own transpose.

+
Parameters
+ + +
MMatrix to multiply.
+
+
+
Returns
M times its transpose.
+ +

Definition at line 25 of file tcrossprod.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::tgamma (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 15 of file tgamma.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::tgamma (const stan::math::vara)
+
+inline
+
+ +

Return the Gamma function applied to the specified variable (C99).

+

See boost::math::tgamma() for the double-based version.

+

The derivative with respect to the argument is

+

$\frac{d}{dx} \Gamma(x) = \Gamma(x) \Psi^{(0)}(x)$

+

where $\Psi^{(0)}(x)$ is the digamma function.

+

See boost::math::digamma() for the double-based version.

+

+\[ \mbox{tgamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Gamma(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{tgamma}(x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \frac{\partial\, \Gamma(x)}{\partial x} & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \Gamma(x)=\int_0^{\infty} u^{x - 1} \exp(-u) \, du \] +

+

+\[ \frac{\partial \, \Gamma(x)}{\partial x} = \Gamma(x)\Psi(x) \] +

+
Parameters
+ + +
aArgument to function.
+
+
+
Returns
The Gamma function applied to the specified argument.
+ +

Definition at line 65 of file tgamma.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
std::vector<T> stan::math::to_array_1d (const Eigen::Matrix< T, R, C > & matrix)
+
+inline
+
+ +

Definition at line 15 of file to_array_1d.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<T> stan::math::to_array_1d (const std::vector< T > & x)
+
+inline
+
+ +

Definition at line 29 of file to_array_1d.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<typename scalar_type<T>::type> stan::math::to_array_1d (const std::vector< std::vector< T > > & x)
+
+inline
+
+ +

Definition at line 36 of file to_array_1d.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector< std::vector<T> > stan::math::to_array_2d (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & matrix)
+
+inline
+
+ +

Definition at line 13 of file to_array_2d.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::to_fvar (const T & x)
+
+inline
+
+ +

Definition at line 12 of file to_fvar.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<fvar<T> > stan::math::to_fvar (const std::vector< T > & v)
+
+inline
+
+ +

Definition at line 14 of file to_fvar.hpp.

+ +
+
+ +
+
+
+template<int R, int C, typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, R, C> stan::math::to_fvar (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Definition at line 16 of file to_fvar.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::to_fvar (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 19 of file to_fvar.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<double>, R, C> stan::math::to_fvar (const Eigen::Matrix< double, R, C > & m)
+
+inline
+
+ +

Definition at line 23 of file to_fvar.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
std::vector<fvar<T> > stan::math::to_fvar (const std::vector< T > & v,
const std::vector< T > & d 
)
+
+inline
+
+ +

Definition at line 24 of file to_fvar.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::to_fvar (const Eigen::Matrix< T, R, C > & val,
const Eigen::Matrix< T, R, C > & deriv 
)
+
+inline
+
+ +

Definition at line 33 of file to_fvar.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<fvar<T> > stan::math::to_fvar (const std::vector< fvar< T > > & v)
+
+inline
+
+ +

Definition at line 34 of file to_fvar.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::to_matrix (Eigen::Matrix< T, R, C > matrix)
+
+inline
+
+ +

Definition at line 16 of file to_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> stan::math::to_matrix (const std::vector< std::vector< T > > & vec)
+
+inline
+
+ +

Definition at line 23 of file to_matrix.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> stan::math::to_matrix (const std::vector< std::vector< int > > & vec)
+
+inline
+
+ +

Definition at line 40 of file to_matrix.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::to_row_vector (const Eigen::Matrix< T, R, C > & matrix)
+
+inline
+
+ +

Definition at line 16 of file to_row_vector.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, 1, Eigen::Dynamic> stan::math::to_row_vector (const std::vector< T > & vec)
+
+inline
+
+ +

Definition at line 24 of file to_row_vector.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<double, 1, Eigen::Dynamic> stan::math::to_row_vector (const std::vector< int > & vec)
+
+inline
+
+ +

Definition at line 30 of file to_row_vector.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::to_var (const double & x)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]xA scalar value
+
+
+
Returns
An automatic differentiation variable with the input value.
+ +

Definition at line 17 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
std::vector<var> stan::math::to_var (const std::vector< double > & v)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]vA std::vector<double>
+
+
+
Returns
A std::vector<var> with the values set
+ +

Definition at line 20 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
matrix_v stan::math::to_var (const stan::math::matrix_dm)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]mA Matrix with scalars
+
+
+
Returns
A Matrix with automatic differentiation variables
+ +

Definition at line 21 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::to_var (const varx)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]xAn automatic differentiation variable.
+
+
+
Returns
An automatic differentiation variable with the input value.
+ +

Definition at line 29 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
std::vector<var> stan::math::to_var (const std::vector< var > & v)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]vA std::vector<var>
+
+
+
Returns
A std::vector<var>
+ +

Definition at line 35 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
matrix_v stan::math::to_var (const matrix_vm)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]mA Matrix with automatic differentiation variables.
+
+
+
Returns
A Matrix with automatic differentiation variables.
+ +

Definition at line 36 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
vector_v stan::math::to_var (const stan::math::vector_dv)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]vA Vector of scalars
+
+
+
Returns
A Vector of automatic differentiation variables with values of v
+ +

Definition at line 48 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
vector_v stan::math::to_var (const vector_vv)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]vA Vector of automatic differentiation variables
+
+
+
Returns
A Vector of automatic differentiation variables with values of v
+ +

Definition at line 63 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
row_vector_v stan::math::to_var (const stan::math::row_vector_drv)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]rvA row vector of scalars
+
+
+
Returns
A row vector of automatic differentation variables with values of rv.
+ +

Definition at line 75 of file to_var.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
row_vector_v stan::math::to_var (const row_vector_vrv)
+
+inline
+
+ +

Converts argument to an automatic differentiation variable.

+

Returns a stan::math::var variable with the input value.

+
Parameters
+ + +
[in]rvA row vector with automatic differentiation variables
+
+
+
Returns
A row vector with automatic differentiation variables with values of rv.
+ +

Definition at line 90 of file to_var.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::to_vector (const Eigen::Matrix< T, R, C > & matrix)
+
+inline
+
+ +

Definition at line 16 of file to_vector.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::to_vector (const std::vector< T > & vec)
+
+inline
+
+ +

Definition at line 24 of file to_vector.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<double, Eigen::Dynamic, 1> stan::math::to_vector (const std::vector< int > & vec)
+
+inline
+
+ +

Definition at line 30 of file to_vector.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::trace (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & m)
+
+inline
+
+ +

Returns the trace of the specified matrix.

+

The trace is defined as the sum of the elements on the diagonal. The matrix is not required to be square. Returns 0 if matrix is empty.

+
Parameters
+ + +
[in]mSpecified matrix.
+
+
+
Returns
Trace of the matrix.
+ +

Definition at line 20 of file trace.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::trace (const T & m)
+
+inline
+
+ +

Definition at line 26 of file trace.hpp.

+ +
+
+ +
+
+
+template<typename T1 , int R1, int C1, typename T2 , int R2, int C2, typename T3 , int R3, int C3>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::enable_if_c<stan::is_var<T1>::value || stan::is_var<T2>::value || stan::is_var<T3>::value, var>::type stan::math::trace_gen_inv_quad_form_ldlt (const Eigen::Matrix< T1, R1, C1 > & D,
const stan::math::LDLT_factor< T2, R2, C2 > & A,
const Eigen::Matrix< T3, R3, C3 > & B 
)
+
+inline
+
+ +

Compute the trace of an inverse quadratic form.

+

I.E., this computes trace(D B^T A^-1 B) where D is a square matrix and the LDLT_factor of A is provided.

+ +

Definition at line 27 of file trace_gen_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , int R1, int C1, int R2, int C2, int R3, int C3>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::enable_if_c<!stan::is_var<T1>::value && !stan::is_var<T2>::value && !stan::is_var<T3>::value, typename boost::math::tools::promote_args<T1, T2, T3>::type>::type stan::math::trace_gen_inv_quad_form_ldlt (const Eigen::Matrix< T1, R1, C1 > & D,
const stan::math::LDLT_factor< T2, R2, C2 > & A,
const Eigen::Matrix< T3, R3, C3 > & B 
)
+
+inline
+
+ +

Definition at line 30 of file trace_gen_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+
+template<int RD, int CD, int RA, int CA, int RB, int CB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::trace_gen_quad_form (const Eigen::Matrix< fvar< T >, RD, CD > & D,
const Eigen::Matrix< fvar< T >, RA, CA > & A,
const Eigen::Matrix< fvar< T >, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 15 of file trace_gen_quad_form.hpp.

+ +
+
+ +
+
+
+template<int RD, int CD, int RA, int CA, int RB, int CB>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::trace_gen_quad_form (const Eigen::Matrix< double, RD, CD > & D,
const Eigen::Matrix< double, RA, CA > & A,
const Eigen::Matrix< double, RB, CB > & B 
)
+
+inline
+
+ +

Compute trace(D B^T A B).

+ +

Definition at line 17 of file trace_gen_quad_form.hpp.

+ +
+
+ +
+
+
+template<typename TD , int RD, int CD, typename TA , int RA, int CA, typename TB , int RB, int CB>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::enable_if_c< boost::is_same<TD, var>::value || boost::is_same<TA, var>::value || boost::is_same<TB, var>::value, var >::type stan::math::trace_gen_quad_form (const Eigen::Matrix< TD, RD, CD > & D,
const Eigen::Matrix< TA, RA, CA > & A,
const Eigen::Matrix< TB, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 116 of file trace_gen_quad_form.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , int R2, int C2, int R3, int C3>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<!stan::is_var<T1>::value && !stan::is_var<T2>::value, typename boost::math::tools::promote_args<T1, T2>::type>::type stan::math::trace_inv_quad_form_ldlt (const stan::math::LDLT_factor< T1, R2, C2 > & A,
const Eigen::Matrix< T2, R3, C3 > & B 
)
+
+inline
+
+ +

Definition at line 27 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+
+template<typename T2 , int R2, int C2, typename T3 , int R3, int C3>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c<stan::is_var<T2>::value || stan::is_var<T3>::value, var>::type stan::math::trace_inv_quad_form_ldlt (const stan::math::LDLT_factor< T2, R2, C2 > & A,
const Eigen::Matrix< T3, R3, C3 > & B 
)
+
+inline
+
+ +

Compute the trace of an inverse quadratic form.

+

I.E., this computes trace(B^T A^-1 B) where the LDLT_factor of A is provided.

+ +

Definition at line 177 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, int CB>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
double stan::math::trace_quad_form (const Eigen::Matrix< double, RA, CA > & A,
const Eigen::Matrix< double, RB, CB > & B 
)
+
+inline
+
+ +

Compute trace(B^T A B).

+ +

Definition at line 17 of file trace_quad_form.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, int CB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::trace_quad_form (const Eigen::Matrix< fvar< T >, RA, CA > & A,
const Eigen::Matrix< fvar< T >, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 18 of file trace_quad_form.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, int CB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::trace_quad_form (const Eigen::Matrix< fvar< T >, RA, CA > & A,
const Eigen::Matrix< double, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 30 of file trace_quad_form.hpp.

+ +
+
+ +
+
+
+template<int RA, int CA, int RB, int CB, typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
fvar<T> stan::math::trace_quad_form (const Eigen::Matrix< double, RA, CA > & A,
const Eigen::Matrix< fvar< T >, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 42 of file trace_quad_form.hpp.

+ +
+
+ +
+
+
+template<typename TA , int RA, int CA, typename TB , int RB, int CB>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::enable_if_c< boost::is_same<TA, var>::value || boost::is_same<TB, var>::value, var >::type stan::math::trace_quad_form (const Eigen::Matrix< TA, RA, CA > & A,
const Eigen::Matrix< TB, RB, CB > & B 
)
+
+inline
+
+ +

Definition at line 98 of file trace_quad_form.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<T, C, R> stan::math::transpose (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Definition at line 12 of file transpose.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::trigamma (x)
+
+inline
+
+ +

+\[ \mbox{trigamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi_1(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+

+\[ \frac{\partial\, \mbox{trigamma}(x)}{\partial x} = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \frac{\partial\, \Psi_1(x)}{\partial x} & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \Psi_1(x)=\sum_{n=0}^\infty \frac{1}{(x+n)^2} \] +

+

+\[ \frac{\partial \, \Psi_1(x)}{\partial x} = -2\sum_{n=0}^\infty \frac{1}{(x+n)^3} \] +

+ +

Definition at line 50 of file trigamma.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::trunc (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 12 of file trunc.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
var stan::math::trunc (const vara)
+
+inline
+
+ +

Returns the truncatation of the specified variable (C99).

+

See trunc() for the double-based version.

+

The derivative is zero everywhere but at integer values, so for convenience the derivative is defined to be everywhere zero,

+

$\frac{d}{dx} \mbox{trunc}(x) = 0$.

+

+\[ \mbox{trunc}(x) = \begin{cases} \lfloor x \rfloor & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+

+\[ \frac{\partial\, \mbox{trunc}(x)}{\partial x} = \begin{cases} 0 & \mbox{if } -\infty\leq x\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+
Parameters
+ + +
aSpecified variable.
+
+
+
Returns
Truncation of the variable.
+ +

Definition at line 60 of file trunc.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TU >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T, TU>::type stan::math::ub_constrain (const T x,
const TU ub 
)
+
+inline
+
+ +

Return the upper-bounded value for the specified unconstrained scalar and upper bound.

+

The transform is

+

$f(x) = U - \exp(x)$

+

where $U$ is the upper bound.

+

If the upper bound is positive infinity, this function reduces to identity_constrain(x).

+
Parameters
+ + + +
xFree scalar.
ubUpper bound.
+
+
+
Returns
Transformed scalar with specified upper bound.
+
Template Parameters
+ + + +
TType of scalar.
TUType of upper bound.
+
+
+ +

Definition at line 37 of file ub_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TU >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T, TU>::type stan::math::ub_constrain (const T x,
const TU ub,
T & lp 
)
+
+inline
+
+ +

Return the upper-bounded value for the specified unconstrained scalar and upper bound and increment the specified log probability reference with the log absolute Jacobian determinant of the transform.

+

The transform is as specified for ub_constrain(T, double). The log absolute Jacobian determinant is

+

$ \log | \frac{d}{dx} -\mbox{exp}(x) + U | = \log | -\mbox{exp}(x) + 0 | = x$.

+

If the upper bound is positive infinity, this function reduces to identity_constrain(x, lp).

+
Parameters
+ + + + +
xFree scalar.
ubUpper bound.
lpLog probability reference.
+
+
+
Returns
Transformed scalar with specified upper bound.
+
Template Parameters
+ + + +
TType of scalar.
TUType of upper bound.
+
+
+ +

Definition at line 70 of file ub_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , typename TU >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T, TU>::type stan::math::ub_free (const T y,
const TU ub 
)
+
+inline
+
+ +

Return the free scalar that corresponds to the specified upper-bounded value with respect to the specified upper bound.

+

The transform is the reverse of the ub_constrain(T, double) transform,

+

$f^{-1}(y) = \log -(y - U)$

+

where $U$ is the upper bound.

+

If the upper bound is positive infinity, this function reduces to identity_free(y).

+
Parameters
+ + + +
yUpper-bounded scalar.
ubUpper bound.
+
+
+
Returns
Free scalar corresponding to upper-bounded scalar.
+
Template Parameters
+ + + +
TType of scalar.
TUType of upper bound.
+
+
+
Exceptions
+ + +
std::invalid_argumentif y is greater than the upper bound.
+
+
+ +

Definition at line 39 of file ub_free.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_low , typename T_high >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_low, T_high>::type stan::math::uniform_ccdf_log (const T_y & y,
const T_low & alpha,
const T_high & beta 
)
+
+ +

Definition at line 25 of file uniform_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_low , typename T_high >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_low, T_high>::type stan::math::uniform_cdf (const T_y & y,
const T_low & alpha,
const T_high & beta 
)
+
+ +

Definition at line 24 of file uniform_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_low , typename T_high >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_low, T_high>::type stan::math::uniform_cdf_log (const T_y & y,
const T_low & alpha,
const T_high & beta 
)
+
+ +

Definition at line 25 of file uniform_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_low , typename T_high >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_low, T_high>::type stan::math::uniform_log (const T_y & y,
const T_low & alpha,
const T_high & beta 
)
+
+ +

The log of a uniform density for the given y, lower, and upper bound.

+

+\begin{eqnarray*} y &\sim& \mbox{\sf{U}}(\alpha, \beta) \\ \log (p (y \, |\, \alpha, \beta)) &=& \log \left( \frac{1}{\beta-\alpha} \right) \\ &=& \log (1) - \log (\beta - \alpha) \\ &=& -\log (\beta - \alpha) \\ & & \mathrm{ where } \; y \in [\alpha, \beta], \log(0) \; \mathrm{otherwise} \end{eqnarray*} +

+
Parameters
+ + + + +
yA scalar variable.
alphaLower bound.
betaUpper bound.
+
+
+
Exceptions
+ + +
std::invalid_argumentif the lower bound is greater than or equal to the lower bound
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_lowType of lower bound.
T_highType of upper bound.
+
+
+ +

Definition at line 48 of file uniform_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_low , typename T_high >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_low, T_high>::type stan::math::uniform_log (const T_y & y,
const T_low & alpha,
const T_high & beta 
)
+
+inline
+
+ +

Definition at line 126 of file uniform_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::uniform_rng (const double alpha,
const double beta,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 21 of file uniform_rng.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::unit_vector_constrain (const Eigen::Matrix< fvar< T >, R, C > & y)
+
+inline
+
+ +

Definition at line 20 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + + + + +
Eigen::Matrix<T, R, C> stan::math::unit_vector_constrain (const Eigen::Matrix< T, R, C > & y)
+
+ +

Return the unit length vector corresponding to the free vector y.

+

See https://en.wikipedia.org/wiki/N-sphere#Generating_random_points

+
Parameters
+ + +
yvector of K unrestricted variables
+
+
+
Returns
Unit length vector of dimension K
+
Template Parameters
+ + +
TScalar type.
+
+
+ +

Definition at line 25 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<T, R, C> stan::math::unit_vector_constrain (const Eigen::Matrix< T, R, C > & y,
T & lp 
)
+
+ +

Return the unit length vector corresponding to the free vector y.

+

See https://en.wikipedia.org/wiki/N-sphere#Generating_random_points

+
Parameters
+ + +
yvector of K unrestricted variables
+
+
+
Returns
Unit length vector of dimension K
+
Parameters
+ + +
lpLog probability reference to increment.
+
+
+
Template Parameters
+ + +
TScalar type.
+
+
+ +

Definition at line 45 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<fvar<T>, R, C> stan::math::unit_vector_constrain (const Eigen::Matrix< fvar< T >, R, C > & y,
fvar< T > & lp 
)
+
+inline
+
+ +

Definition at line 54 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + + + + +
Eigen::Matrix<var, R, C> stan::math::unit_vector_constrain (const Eigen::Matrix< var, R, C > & y)
+
+ +

Return the unit length vector corresponding to the free vector y.

+

See https://en.wikipedia.org/wiki/N-sphere#Generating_random_points

+
Parameters
+ + +
yvector of K unrestricted variables
+
+
+
Returns
Unit length vector of dimension K
+
Template Parameters
+ + +
TScalar type.
+
+
+ +

Definition at line 64 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + + + + + + + + + + + + + + +
Eigen::Matrix<var, R, C> stan::math::unit_vector_constrain (const Eigen::Matrix< var, R, C > & y,
varlp 
)
+
+ +

Return the unit length vector corresponding to the free vector y.

+

See https://en.wikipedia.org/wiki/N-sphere#Generating_random_points

+
Parameters
+ + +
yvector of K unrestricted variables
+
+
+
Returns
Unit length vector of dimension K
+
Parameters
+ + +
lpLog probability reference to increment.
+
+
+
Template Parameters
+ + +
TScalar type.
+
+
+ +

Definition at line 112 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + + + + +
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::unit_vector_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > & x)
+
+ +

Transformation of a unit length vector to a "free" vector However, we are just fixing the unidentified radius to 1.

+

Thus, the transformation is just the identity

+
Parameters
+ + +
xunit vector of dimension K
+
+
+
Returns
Unit vector of dimension K considered "free"
+
Template Parameters
+ + +
TScalar type.
+
+
+ +

Definition at line 24 of file unit_vector_free.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::validate_non_negative_index (const char * var_name,
const char * expr,
int val 
)
+
+inline
+
+ +

Definition at line 12 of file validate_non_negative_index.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
T stan::math::value_of (const fvar< T > & v)
+
+inline
+
+ +

Return the value of the specified variable.

+
Parameters
+ + +
vVariable.
+
+
+
Returns
Value of variable.
+ +

Definition at line 16 of file value_of.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<typename child_type<T>::type> stan::math::value_of (const std::vector< T > & x)
+
+inline
+
+ +

Convert a std::vector of type T to a std::vector of child_type<T>::type.

+
Template Parameters
+ + +
TScalar type in std::vector
+
+
+
Parameters
+ + +
[in]xstd::vector to be converted
+
+
+
Returns
std::vector of values
+ +

Definition at line 22 of file value_of.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
double stan::math::value_of (const varv)
+
+inline
+
+ +

Return the value of the specified variable.

+

This function is used internally by auto-dif functions along with stan::math::value_of(T x) to extract the double value of either a scalar or an auto-dif variable. This function will be called when the argument is a stan::math::var even if the function is not referred to by namespace because of argument-dependent lookup.

+
Parameters
+ + +
vVariable.
+
+
+
Returns
Value of variable.
+ +

Definition at line 22 of file value_of.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
double stan::math::value_of (const T x)
+
+inline
+
+ +

Return the value of the specified scalar argument converted to a double value.

+

See the stan::math::primitive_value function to extract values without casting to double.

+

This function is meant to cover the primitive types. For types requiring pass-by-reference, this template function should be specialized.

+
Template Parameters
+ + +
TType of scalar.
+
+
+
Parameters
+ + +
xScalar to convert to double.
+
+
+
Returns
Value of scalar cast to a double.
+ +

Definition at line 24 of file value_of.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<typename child_type<T>::type, R, C> stan::math::value_of (const Eigen::Matrix< T, R, C > & M)
+
+inline
+
+ +

Convert a matrix of type T to a matrix of doubles.

+

T must implement value_of. See test/math/fwd/mat/fun/value_of.cpp for fvar and var usage.

+
Template Parameters
+ + + + +
TScalar type in matrix
RRows of matrix
CColumns of matrix
+
+
+
Parameters
+ + +
[in]MMatrix to be converted
+
+
+
Returns
Matrix of values
+ +

Definition at line 25 of file value_of.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
std::vector<double> stan::math::value_of (const std::vector< double > & x)
+
+inline
+
+ +

Return the specified argument.

+

See value_of(T) for a polymorphic implementation using static casts.

+

This inline pass-through no-op should be compiled away.

+
Parameters
+ + +
xSpecified std::vector.
+
+
+
Returns
Specified std::vector.
+ +

Definition at line 42 of file value_of.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<double, R, C> stan::math::value_of (const Eigen::Matrix< double, R, C > & x)
+
+inline
+
+ +

Return the specified argument.

+

See value_of(T) for a polymorphic implementation using static casts.

+

This inline pass-through no-op should be compiled away.

+
Parameters
+ + +
xSpecified matrix.
+
+
+
Returns
Specified matrix.
+ +

Definition at line 47 of file value_of.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
double stan::math::value_of< double > (const double x)
+
+inline
+
+ +

Return the specified argument.

+

See value_of(T) for a polymorphic implementation using static casts.

+

This inline pass-through no-op should be compiled away.

+
Parameters
+ + +
xSpecified value.
+
+
+
Returns
Specified value.
+ +

Definition at line 40 of file value_of.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
double stan::math::value_of_rec (const varv)
+
+inline
+
+ +

Return the value of the specified variable.

+
Parameters
+ + +
vVariable.
+
+
+
Returns
Value of variable.
+ +

Definition at line 15 of file value_of_rec.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
double stan::math::value_of_rec (const fvar< T > & v)
+
+inline
+
+ +

Return the value of the specified variable.

+

T must implement value_of_rec.

+
Template Parameters
+ + +
TScalar type
+
+
+
Parameters
+ + +
vVariable.
+
+
+
Returns
Value of variable.
+ +

Definition at line 21 of file value_of_rec.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
std::vector<double> stan::math::value_of_rec (const std::vector< T > & x)
+
+inline
+
+ +

Convert a std::vector of type T to a std::vector of doubles.

+

T must implement value_of_rec. See test/math/fwd/mat/fun/value_of_rec.cpp for fvar and var usage.

+
Template Parameters
+ + +
TScalar type in std::vector
+
+
+
Parameters
+ + +
[in]xstd::vector to be converted
+
+
+
Returns
std::vector of values
+ +

Definition at line 23 of file value_of_rec.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
double stan::math::value_of_rec (const T x)
+
+inline
+
+ +

Return the value of the specified scalar argument converted to a double value.

+

See the stan::math::primitive_value function to extract values without casting to double.

+

This function is meant to cover the primitive types. For types requiring pass-by-reference, this template function should be specialized.

+
Template Parameters
+ + +
TType of scalar.
+
+
+
Parameters
+ + +
xScalar to convert to double.
+
+
+
Returns
Value of scalar cast to a double.
+ +

Definition at line 24 of file value_of_rec.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<double, R, C> stan::math::value_of_rec (const Eigen::Matrix< T, R, C > & M)
+
+inline
+
+ +

Convert a matrix of type T to a matrix of doubles.

+

T must implement value_of_rec. See test/unit/math/fwd/mat/fun/value_of_test.cpp for fvar and var usage.

+
Template Parameters
+ + + + +
TScalar type in matrix
RRows of matrix
CColumns of matrix
+
+
+
Parameters
+ + +
[in]MMatrix to be converted
+
+
+
Returns
Matrix of values
+ +

Definition at line 24 of file value_of_rec.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
std::vector<double> stan::math::value_of_rec (const std::vector< double > & x)
+
+inline
+
+ +

Return the specified argument.

+

See value_of_rec(T) for a polymorphic implementation using static casts.

+

This inline pass-through no-op should be compiled away.

+
Parameters
+ + +
xSpecified std::vector.
+
+
+
Returns
Specified std::vector.
+ +

Definition at line 43 of file value_of_rec.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + +
+ + + + + + + + +
Eigen::Matrix<double, R, C> stan::math::value_of_rec (const Eigen::Matrix< double, R, C > & x)
+
+inline
+
+ +

Return the specified argument.

+

See value_of_rec(T) for a polymorphic implementation using static casts.

+

This inline pass-through no-op should be compiled away.

+
Parameters
+ + +
xSpecified matrix.
+
+
+
Returns
Specified matrix.
+ +

Definition at line 46 of file value_of_rec.hpp.

+ +
+
+ +
+
+
+template<>
+ + + + + +
+ + + + + + + + +
double stan::math::value_of_rec< double > (const double x)
+
+inline
+
+ +

Return the specified argument.

+

See value_of(T) for a polymorphic implementation using static casts.

+

This inline pass-through no-op should be compiled away.

+
Parameters
+ + +
xSpecified value.
+
+
+
Returns
Specified value.
+ +

Definition at line 40 of file value_of_rec.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::variance (const std::vector< T > & v)
+
+inline
+
+ +

Returns the sample variance (divide by length - 1) of the coefficients in the specified standard vector.

+
Parameters
+ + +
vSpecified vector.
+
+
+
Returns
Sample variance of vector.
+
Exceptions
+ + +
std::domain_errorif the size of the vector is less than 1.
+
+
+ +

Definition at line 24 of file variance.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
boost::math::tools::promote_args<T>::type stan::math::variance (const Eigen::Matrix< T, R, C > & m)
+
+inline
+
+ +

Returns the sample variance (divide by length - 1) of the coefficients in the specified column vector.

+
Parameters
+ + +
mSpecified vector.
+
+
+
Returns
Sample variance of vector.
+ +

Definition at line 46 of file variance.hpp.

+ +
+
+ +
+
+ + + + + + + + +
var stan::math::variance (const std::vector< var > & v)
+
+ +

Return the sample variance of the specified standard vector.

+

Raise domain error if size is not greater than zero.

+
Parameters
+ + +
[in]va vector
+
+
+
Returns
sample variance of specified vector
+ +

Definition at line 52 of file variance.hpp.

+ +
+
+ +
+
+
+template<int R, int C>
+ + + + + + + + +
var stan::math::variance (const Eigen::Matrix< var, R, C > & m)
+
+ +

Definition at line 69 of file variance.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_loc , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::von_mises_log (T_y const & y,
T_loc const & mu,
T_scale const & kappa 
)
+
+ +

Definition at line 27 of file von_mises_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_loc , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_loc, T_scale>::type stan::math::von_mises_log (T_y const & y,
T_loc const & mu,
T_scale const & kappa 
)
+
+inline
+
+ +

Definition at line 135 of file von_mises_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::von_mises_rng (const double mu,
const double kappa,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 31 of file von_mises_rng.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::weibull_ccdf_log (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+ +

Definition at line 29 of file weibull_ccdf_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::weibull_cdf (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+ +

Definition at line 29 of file weibull_cdf.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::weibull_cdf_log (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+ +

Definition at line 29 of file weibull_cdf_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_shape , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::weibull_log (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+ +

Definition at line 32 of file weibull_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_shape , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_shape, T_scale>::type stan::math::weibull_log (const T_y & y,
const T_shape & alpha,
const T_scale & sigma 
)
+
+inline
+
+ +

Definition at line 143 of file weibull_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
double stan::math::weibull_rng (const double alpha,
const double sigma,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 23 of file weibull_rng.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_alpha , typename T_tau , typename T_beta , typename T_delta >
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_alpha, T_tau, T_beta, T_delta>::type stan::math::wiener_log (const T_y & y,
const T_alpha & alpha,
const T_tau & tau,
const T_beta & beta,
const T_delta & delta 
)
+
+ +

The log of the first passage time density function for a (Wiener) drift diffusion model for the given $y$, boundary separation $\alpha$, nondecision time $\tau$, relative bias $\beta$, and drift rate $\delta$.

+

$\alpha$ and $\tau$ must be greater than 0, and $\beta$ must be between 0 and 1. $y$ should contain reaction times in seconds (strictly positive) with upper-boundary responses.

+
Parameters
+ + + + + + +
yA scalar variate.
alphaThe boundary separation.
tauThe nondecision time.
betaThe relative bias.
deltaThe drift rate.
+
+
+
Returns
The log of the Wiener first passage time density of the specified arguments.
+ +

Definition at line 72 of file wiener_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_alpha , typename T_tau , typename T_beta , typename T_delta >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
return_type<T_y, T_alpha, T_tau, T_beta, T_delta>::type stan::math::wiener_log (const T_y & y,
const T_alpha & alpha,
const T_tau & tau,
const T_beta & beta,
const T_delta & delta 
)
+
+inline
+
+ +

Definition at line 225 of file wiener_log.hpp.

+ +
+
+ +
+
+
+template<bool propto, typename T_y , typename T_dof , typename T_scale >
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_dof, T_scale>::type stan::math::wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & W,
const T_dof & nu,
const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > & S 
)
+
+ +

The log of the Wishart density for the given W, degrees of freedom, and scale matrix.

+

The scale matrix, S, must be k x k, symmetric, and semi-positive definite. Dimension, k, is implicit. nu must be greater than k-1

+

+\begin{eqnarray*} W &\sim& \mbox{\sf{Wishart}}_{\nu} (S) \\ \log (p (W \, |\, \nu, S) ) &=& \log \left( \left(2^{\nu k/2} \pi^{k (k-1) /4} \prod_{i=1}^k{\Gamma (\frac{\nu + 1 - i}{2})} \right)^{-1} \times \left| S \right|^{-\nu/2} \left| W \right|^{(\nu - k - 1) / 2} \times \exp (-\frac{1}{2} \mbox{tr} (S^{-1} W)) \right) \\ &=& -\frac{\nu k}{2}\log(2) - \frac{k (k-1)}{4} \log(\pi) - \sum_{i=1}^{k}{\log (\Gamma (\frac{\nu+1-i}{2}))} -\frac{\nu}{2} \log(\det(S)) + \frac{\nu-k-1}{2}\log (\det(W)) - \frac{1}{2} \mbox{tr} (S^{-1}W) \end{eqnarray*} +

+
Parameters
+ + + + +
WA scalar matrix
nuDegrees of freedom
SThe scale matrix
+
+
+
Returns
The log of the Wishart density at W given nu and S.
+
Exceptions
+ + + +
std::domain_errorif nu is not greater than k-1
std::domain_errorif S is not square, not symmetric, or not semi-positive definite.
+
+
+
Template Parameters
+ + + + +
T_yType of scalar.
T_dofType of degrees of freedom.
T_scaleType of scale.
+
+
+ +

Definition at line 58 of file wishart_log.hpp.

+ +
+
+ +
+
+
+template<typename T_y , typename T_dof , typename T_scale >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
boost::math::tools::promote_args<T_y, T_dof, T_scale>::type stan::math::wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > & W,
const T_dof & nu,
const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > & S 
)
+
+inline
+
+ +

Definition at line 127 of file wishart_log.hpp.

+ +
+
+ +
+
+
+template<class RNG >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> stan::math::wishart_rng (const double nu,
const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > & S,
RNG & rng 
)
+
+inline
+
+ +

Definition at line 29 of file wishart_rng.hpp.

+ +
+
+

Variable Documentation

+ +
+
+ + + + +
const double stan::math::CONSTRAINT_TOLERANCE = 1E-8
+
+ +

The tolerance for checking arithmetic bounds In rank and in simplexes.

+

The default value is 1E-8.

+ +

Definition at line 11 of file constraint_tolerance.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::E = boost::math::constants::e<double>()
+
+ +

The base of the natural logarithm, $ e $.

+ +

Definition at line 15 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::EPSILON = std::numeric_limits<double>::epsilon()
+
+ +

Smallest positive value.

+ +

Definition at line 61 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::INFTY = std::numeric_limits<double>::infinity()
+
+ +

Positive infinity.

+ +

Definition at line 44 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::INV_SQRT_2 = 1.0 / SQRT_2
+
+ +

The value of 1 over the square root of 2, $ 1 / \sqrt{2} $.

+ +

Definition at line 27 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::INV_SQRT_TWO_PI = 1.0 / std::sqrt(2.0 * boost::math::constants::pi<double>())
+
+ +

Definition at line 166 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_10 = std::log(10.0)
+
+ +

The natural logarithm of 10, $ \log 10 $.

+ +

Definition at line 39 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_2 = std::log(2.0)
+
+ +

The natural logarithm of 2, $ \log 2 $.

+ +

Definition at line 33 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_HALF = std::log(0.5)
+
+ +

Definition at line 179 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_PI = std::log(boost::math::constants::pi<double>())
+
+ +

Definition at line 170 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_PI_OVER_FOUR = std::log(boost::math::constants::pi<double>()) / 4.0
+
+ +

Log pi divided by 4 $ \log \pi / 4 $.

+ +

Definition at line 79 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_SQRT_PI = std::log(SQRT_PI)
+
+ +

Definition at line 173 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_TWO = std::log(2.0)
+
+ +

Definition at line 177 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_TWO_PI = LOG_TWO + LOG_PI
+
+ +

Definition at line 193 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::LOG_ZERO = std::log(0.0)
+
+ +

Definition at line 175 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const std::string stan::math::MAJOR_VERSION = STAN_STRING(STAN_MATH_MAJOR)
+
+ +

Major version number for Stan math library.

+ +

Definition at line 22 of file version.hpp.

+ +
+
+ +
+
+ + + + +
const std::string stan::math::MINOR_VERSION = STAN_STRING(STAN_MATH_MINOR)
+
+ +

Minor version number for Stan math library.

+ +

Definition at line 25 of file version.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEG_LOG_PI = - LOG_PI
+
+ +

Definition at line 186 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEG_LOG_SQRT_PI = -std::log(std::sqrt(boost::math::constants::pi<double>()))
+
+ +

Definition at line 189 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEG_LOG_SQRT_TWO_PI = - std::log(std::sqrt(2.0 * boost::math::constants::pi<double>()))
+
+ +

Definition at line 184 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEG_LOG_TWO = - LOG_TWO
+
+ +

Definition at line 181 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEG_LOG_TWO_OVER_TWO = - LOG_TWO / 2.0
+
+ +

Definition at line 191 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEG_LOG_TWO_PI = - LOG_TWO_PI
+
+ +

Definition at line 195 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEG_TWO_OVER_SQRT_PI = -TWO_OVER_SQRT_PI
+
+ +

Definition at line 163 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEGATIVE_EPSILON = - std::numeric_limits<double>::epsilon()
+
+ +

Largest negative value (i.e., smallest absolute value).

+ +

Definition at line 67 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NEGATIVE_INFTY = - std::numeric_limits<double>::infinity()
+
+ +

Negative infinity.

+ +

Definition at line 50 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::NOT_A_NUMBER = std::numeric_limits<double>::quiet_NaN()
+
+ +

(Quiet) not-a-number value.

+ +

Definition at line 56 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const std::string stan::math::PATCH_VERSION = STAN_STRING(STAN_MATH_PATCH)
+
+ +

Patch version for Stan math library.

+ +

Definition at line 28 of file version.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::POISSON_MAX_RATE = std::pow(2.0, 30)
+
+ +

Largest rate parameter allowed in Poisson RNG.

+ +

Definition at line 72 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::SQRT_2 = std::sqrt(2.0)
+
+ +

The value of the square root of 2, $ \sqrt{2} $.

+ +

Definition at line 21 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::SQRT_2_TIMES_SQRT_PI = SQRT_2 * SQRT_PI
+
+ +

Definition at line 158 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::SQRT_PI = std::sqrt(boost::math::constants::pi<double>())
+
+ +

Definition at line 156 of file constants.hpp.

+ +
+
+ +
+
+ + + + +
const double stan::math::TWO_OVER_SQRT_PI = 2.0 / SQRT_PI
+
+ +

Definition at line 161 of file constants.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/namespacestan_1_1math_1_1detail.html b/doc/api/html/namespacestan_1_1math_1_1detail.html new file mode 100644 index 00000000000..969a5abc446 --- /dev/null +++ b/doc/api/html/namespacestan_1_1math_1_1detail.html @@ -0,0 +1,119 @@ + + + + + + +Stan Math Library: stan::math::detail Namespace Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::detail Namespace Reference
+
+
+ + + + + + +

+Classes

struct  bounded
 
struct  bounded< T_y, T_low, T_high, true >
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/namespacestd.html b/doc/api/html/namespacestd.html new file mode 100644 index 00000000000..c2ad92f48d8 --- /dev/null +++ b/doc/api/html/namespacestd.html @@ -0,0 +1,199 @@ + + + + + + +Stan Math Library: std Namespace Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ +
+
+ +
+
std Namespace Reference
+
+
+ + + + + + + +

+Classes

struct  numeric_limits< stan::math::fvar< T > >
 
struct  numeric_limits< stan::math::var >
 Specialization of numeric limits for var objects. More...
 
+ + + + + + + +

+Functions

int isinf (const stan::math::var &a)
 Checks if the given number is infinite. More...
 
int isnan (const stan::math::var &a)
 Checks if the given number is NaN. More...
 
+

Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
int std::isinf (const stan::math::vara)
+
+inline
+
+ +

Checks if the given number is infinite.

+

Return true if the value of the a is positive or negative infinity.

+
Parameters
+ + +
aVariable to test.
+
+
+
Returns
true if value is infinite.
+ +

Definition at line 18 of file std_isinf.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + + +
int std::isnan (const stan::math::vara)
+
+inline
+
+ +

Checks if the given number is NaN.

+

Return true if the value of the specified variable is not a number.

+
Parameters
+ + +
aVariable to test.
+
+
+
Returns
true if value is not a number.
+ +

Definition at line 18 of file std_isnan.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/nav_f.png b/doc/api/html/nav_f.png new file mode 100644 index 0000000000000000000000000000000000000000..72a58a529ed3a9ed6aa0c51a79cf207e026deee2 GIT binary patch literal 153 zcmeAS@N?(olHy`uVBq!ia0vp^j6iI`!2~2XGqLUlQVE_ejv*C{Z|{2ZH7M}7UYxc) zn!W8uqtnIQ>_z8U literal 0 HcmV?d00001 diff --git a/doc/api/html/nav_g.png b/doc/api/html/nav_g.png new file mode 100644 index 0000000000000000000000000000000000000000..2093a237a94f6c83e19ec6e5fd42f7ddabdafa81 GIT binary patch literal 95 zcmeAS@N?(olHy`uVBq!ia0vp^j6lrB!3HFm1ilyoDK$?Q$B+ufw|5PB85lU25BhtE tr?otc=hd~V+ws&_A@j8Fiv!KF$B+ufw|5=67#uj90@pIL wZ=Q8~_Ju`#59=RjDrmm`tMD@M=!-l18IR?&vFVdQ&MBb@0HFXL + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_ccdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
neg_binomial_2_ccdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type stan::math::neg_binomial_2_ccdf_log (const T_n &n, const T_location &mu, const T_precision &phi)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__ccdf__log_8hpp_source.html b/doc/api/html/neg__binomial__2__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..2abb10aecf4 --- /dev/null +++ b/doc/api/html/neg__binomial__2__ccdf__log_8hpp_source.html @@ -0,0 +1,180 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_ccdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
neg_binomial_2_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_CCDF_LOG_HPP
+
3 
+ + + + + + +
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  // Temporary neg_binomial_2_ccdf implementation that
+
15  // transforms the input parameters and calls neg_binomial_ccdf
+
16  template <typename T_n, typename T_location, typename T_precision>
+
17  typename return_type<T_location, T_precision>::type
+ +
19  const T_location& mu,
+
20  const T_precision& phi) {
+ + + +
24 
+
25  // check if any vectors are zero length
+
26  if (!(stan::length(n)
+
27  && stan::length(mu)
+
28  && stan::length(phi)))
+
29  return 0.0;
+
30 
+
31  static const char* function("stan::math::neg_binomial_2_cdf");
+
32  check_positive_finite(function, "Location parameter", mu);
+
33  check_positive_finite(function, "Precision parameter", phi);
+
34  check_not_nan(function, "Random variable", n);
+
35  check_consistent_sizes(function,
+
36  "Random variable", n,
+
37  "Location parameter", mu,
+
38  "Precision Parameter", phi);
+
39 
+ +
41  VectorView<const T_precision> phi_vec(phi);
+
42 
+
43  size_t size_beta = max_size(mu, phi);
+
44 
+ +
46  T_location, T_precision> beta_vec(size_beta);
+
47  for (size_t i = 0; i < size_beta; ++i)
+
48  beta_vec[i] = phi_vec[i] / mu_vec[i];
+
49 
+
50  return neg_binomial_ccdf_log(n, phi, beta_vec.data());
+
51  }
+
52  }
+
53 }
+
54 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
return_type< T_location, T_precision >::type neg_binomial_2_ccdf_log(const T_n &n, const T_location &mu, const T_precision &phi)
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
return_type< T_shape, T_inv_scale >::type neg_binomial_ccdf_log(const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
VectorBuilderHelper< T1, used, contains_vector< T2, T3, T4, T5, T6, T7 >::value >::type data()
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__cdf_8hpp.html b/doc/api/html/neg__binomial__2__cdf_8hpp.html new file mode 100644 index 00000000000..a6dd96d8671 --- /dev/null +++ b/doc/api/html/neg__binomial__2__cdf_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
neg_binomial_2_cdf.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type stan::math::neg_binomial_2_cdf (const T_n &n, const T_location &mu, const T_precision &phi)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__cdf_8hpp_source.html b/doc/api/html/neg__binomial__2__cdf_8hpp_source.html new file mode 100644 index 00000000000..bd9c84c01da --- /dev/null +++ b/doc/api/html/neg__binomial__2__cdf_8hpp_source.html @@ -0,0 +1,289 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
neg_binomial_2_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_CDF_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <limits>
+
19 
+
20 namespace stan {
+
21  namespace math {
+
22 
+
23  template <typename T_n, typename T_location,
+
24  typename T_precision>
+
25  typename return_type<T_location, T_precision>::type
+
26  neg_binomial_2_cdf(const T_n& n,
+
27  const T_location& mu,
+
28  const T_precision& phi) {
+
29  static const char* function("stan::prob::neg_binomial_2_cdf");
+
30  typedef typename stan::partials_return_type<T_n, T_location,
+
31  T_precision>::type
+
32  T_partials_return;
+
33 
+ + + +
37 
+
38  T_partials_return P(1.0);
+
39  // check if any vectors are zero length
+
40  if (!(stan::length(n)
+
41  && stan::length(mu)
+
42  && stan::length(phi)))
+
43  return P;
+
44 
+
45  // Validate arguments
+
46  check_positive_finite(function, "Location parameter", mu);
+
47  check_positive_finite(function, "Precision parameter", phi);
+
48  check_not_nan(function, "Random variable", n);
+
49  check_consistent_sizes(function,
+
50  "Random variable", n,
+
51  "Location parameter", mu,
+
52  "Precision Parameter", phi);
+
53 
+
54  // Wrap arguments in vector views
+
55  VectorView<const T_n> n_vec(n);
+ +
57  VectorView<const T_precision> phi_vec(phi);
+
58  size_t size = max_size(n, mu, phi);
+
59 
+
60  // Compute vectorized CDF and gradient
+ + + + +
65  using stan::math::digamma;
+
66 
+ +
68  operands_and_partials(mu, phi);
+
69 
+
70  // Explicit return for extreme values
+
71  // The gradients are technically ill-defined, but treated as zero
+
72  for (size_t i = 0; i < stan::length(n); i++) {
+
73  if (value_of(n_vec[i]) < 0)
+
74  return operands_and_partials.value(0.0);
+
75  }
+
76 
+
77  // Cache a few expensive function calls if phi is a parameter
+ +
79  T_partials_return, T_precision>
+
80  digamma_phi_vec(stan::length(phi));
+
81 
+ +
83  T_partials_return, T_precision>
+
84  digamma_sum_vec(stan::length(phi));
+
85 
+ +
87  for (size_t i = 0; i < stan::length(phi); i++) {
+
88  const T_partials_return n_dbl = value_of(n_vec[i]);
+
89  const T_partials_return phi_dbl = value_of(phi_vec[i]);
+
90 
+
91  digamma_phi_vec[i] = digamma(phi_dbl);
+
92  digamma_sum_vec[i] = digamma(n_dbl + phi_dbl + 1);
+
93  }
+
94  }
+
95 
+
96  for (size_t i = 0; i < size; i++) {
+
97  // Explicit results for extreme values
+
98  // The gradients are technically ill-defined, but treated as zero
+
99  if (value_of(n_vec[i]) == std::numeric_limits<int>::max())
+
100  return operands_and_partials.value(1.0);
+
101 
+
102  const T_partials_return n_dbl = value_of(n_vec[i]);
+
103  const T_partials_return mu_dbl = value_of(mu_vec[i]);
+
104  const T_partials_return phi_dbl = value_of(phi_vec[i]);
+
105 
+
106  const T_partials_return p_dbl = phi_dbl / (mu_dbl + phi_dbl);
+
107  const T_partials_return d_dbl = 1.0 / ((mu_dbl + phi_dbl)
+
108  * (mu_dbl + phi_dbl));
+
109 
+
110  const T_partials_return P_i =
+
111  inc_beta(phi_dbl, n_dbl + 1.0, p_dbl);
+
112 
+
113  P *= P_i;
+
114 
+ +
116  operands_and_partials.d_x1[i] +=
+
117  - inc_beta_ddz(phi_dbl, n_dbl + 1.0, p_dbl) * phi_dbl * d_dbl / P_i;
+
118 
+ +
120  operands_and_partials.d_x2[i]
+
121  += inc_beta_dda(phi_dbl, n_dbl + 1, p_dbl,
+
122  digamma_phi_vec[i],
+
123  digamma_sum_vec[i]) / P_i
+
124  + inc_beta_ddz(phi_dbl, n_dbl + 1.0, p_dbl)
+
125  * mu_dbl * d_dbl / P_i;
+
126  }
+
127  }
+
128 
+ +
130  for (size_t i = 0; i < stan::length(mu); ++i)
+
131  operands_and_partials.d_x1[i] *= P;
+
132  }
+
133 
+ +
135  for (size_t i = 0; i < stan::length(phi); ++i)
+
136  operands_and_partials.d_x2[i] *= P;
+
137  }
+
138 
+
139  return operands_and_partials.value(P);
+
140  }
+
141 
+
142  }
+
143 }
+
144 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_location, T_precision >::type neg_binomial_2_cdf(const T_n &n, const T_location &mu, const T_precision &phi)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T inc_beta_dda(T a, T b, T z, T digamma_a, T digamma_ab)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a.
+ + +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T inc_beta_ddz(T a, T b, T z)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to z.
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ +
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__cdf__log_8hpp.html b/doc/api/html/neg__binomial__2__cdf__log_8hpp.html new file mode 100644 index 00000000000..95b3162035c --- /dev/null +++ b/doc/api/html/neg__binomial__2__cdf__log_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_cdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type stan::math::neg_binomial_2_cdf_log (const T_n &n, const T_location &mu, const T_precision &phi)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__cdf__log_8hpp_source.html b/doc/api/html/neg__binomial__2__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..62159a7766e --- /dev/null +++ b/doc/api/html/neg__binomial__2__cdf__log_8hpp_source.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_cdf_log.hpp Source File + + + + + + + + + + +
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neg_binomial_2_cdf_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_CDF_LOG_HPP
+
3 
+ + + + + + + +
11 #include <cmath>
+
12 
+
13 namespace stan {
+
14  namespace math {
+
15 
+
16  template <typename T_n, typename T_location,
+
17  typename T_precision>
+
18  typename return_type<T_location, T_precision>::type
+
19  neg_binomial_2_cdf_log(const T_n& n,
+
20  const T_location& mu,
+
21  const T_precision& phi) {
+ + + +
25  using std::log;
+
26 
+
27  // check if any vectors are zero length
+
28  if (!(stan::length(n)
+
29  && stan::length(mu)
+
30  && stan::length(phi)))
+
31  return 0.0;
+
32 
+
33  static const char* function("stan::math::neg_binomial_2_cdf");
+
34  check_positive_finite(function, "Location parameter", mu);
+
35  check_positive_finite(function, "Precision parameter", phi);
+
36  check_not_nan(function, "Random variable", n);
+
37  check_consistent_sizes(function,
+
38  "Random variable", n,
+
39  "Location parameter", mu,
+
40  "Precision Parameter", phi);
+
41 
+
42  VectorView<const T_n> n_vec(n);
+ +
44  VectorView<const T_precision> phi_vec(phi);
+
45 
+
46  size_t size_phi_mu = max_size(mu, phi);
+ +
48  T_location, T_precision> phi_mu(size_phi_mu);
+
49  for (size_t i = 0; i < size_phi_mu; i++)
+
50  phi_mu[i] = phi_vec[i] / (phi_vec[i] + mu_vec[i]);
+
51 
+
52  size_t size_n = length(n);
+ +
54  T_n> np1(size_n);
+
55  for (size_t i = 0; i < size_n; i++)
+
56  if (n_vec[i] < 0)
+
57  return log(0.0);
+
58  else
+
59  np1[i] = n_vec[i] + 1.0;
+
60 
+
61  return beta_cdf_log(phi_mu.data(), phi, np1.data());
+
62  }
+
63 
+
64  }
+
65 }
+
66 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
return_type< T_y, T_scale_succ, T_scale_fail >::type beta_cdf_log(const T_y &y, const T_scale_succ &alpha, const T_scale_fail &beta)
+ +
VectorBuilder allocates type T1 values to be used as intermediate values.
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
VectorBuilderHelper< T1, used, contains_vector< T2, T3, T4, T5, T6, T7 >::value >::type data()
+
return_type< T_location, T_precision >::type neg_binomial_2_cdf_log(const T_n &n, const T_location &mu, const T_precision &phi)
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__log_8hpp.html b/doc/api/html/neg__binomial__2__log_8hpp.html new file mode 100644 index 00000000000..4e7e1e18d7e --- /dev/null +++ b/doc/api/html/neg__binomial__2__log_8hpp.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_log.hpp File Reference + + + + + + + + + + +
+
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+
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+
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+ + + + + + + +

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+ + + + + + + +

+Functions

template<bool propto, typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type stan::math::neg_binomial_2_log (const T_n &n, const T_location &mu, const T_precision &phi)
 
template<typename T_n , typename T_location , typename T_precision >
return_type< T_location, T_precision >::type stan::math::neg_binomial_2_log (const T_n &n, const T_location &mu, const T_precision &phi)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__log_8hpp_source.html b/doc/api/html/neg__binomial__2__log_8hpp_source.html new file mode 100644 index 00000000000..a8d2e49b755 --- /dev/null +++ b/doc/api/html/neg__binomial__2__log_8hpp_source.html @@ -0,0 +1,299 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_log.hpp Source File + + + + + + + + + + +
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neg_binomial_2_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_LOG_HPP
+
3 
+
4 #include <boost/math/special_functions/digamma.hpp>
+
5 #include <boost/random/negative_binomial_distribution.hpp>
+
6 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + + + + + +
26 #include <cmath>
+
27 
+
28 namespace stan {
+
29 
+
30  namespace math {
+
31 
+
32  // NegBinomial(n|mu, phi) [mu >= 0; phi > 0; n >= 0]
+
33  template <bool propto,
+
34  typename T_n,
+
35  typename T_location, typename T_precision>
+
36  typename return_type<T_location, T_precision>::type
+
37  neg_binomial_2_log(const T_n& n,
+
38  const T_location& mu,
+
39  const T_precision& phi) {
+
40  typedef typename stan::partials_return_type<T_n, T_location,
+
41  T_precision>::type
+
42  T_partials_return;
+
43 
+
44  static const char* function("stan::math::neg_binomial_2_log");
+
45 
+ + + + + +
51 
+
52  // check if any vectors are zero length
+
53  if (!(stan::length(n)
+
54  && stan::length(mu)
+
55  && stan::length(phi)))
+
56  return 0.0;
+
57 
+
58  T_partials_return logp(0.0);
+
59  check_nonnegative(function, "Failures variable", n);
+
60  check_positive_finite(function, "Location parameter", mu);
+
61  check_positive_finite(function, "Precision parameter", phi);
+
62  check_consistent_sizes(function,
+
63  "Failures variable", n,
+
64  "Location parameter", mu,
+
65  "Precision parameter", phi);
+
66 
+
67  // check if no variables are involved and prop-to
+ +
69  return 0.0;
+
70 
+ +
72  using stan::math::digamma;
+
73  using stan::math::lgamma;
+
74  using std::log;
+
75  using std::log;
+
76 
+
77  // set up template expressions wrapping scalars into vector views
+
78  VectorView<const T_n> n_vec(n);
+ +
80  VectorView<const T_precision> phi_vec(phi);
+
81  size_t size = max_size(n, mu, phi);
+
82 
+ +
84  operands_and_partials(mu, phi);
+
85 
+
86  size_t len_ep = max_size(mu, phi);
+
87  size_t len_np = max_size(n, phi);
+
88 
+ +
90  for (size_t i = 0, size = length(mu); i < size; ++i)
+
91  mu__[i] = value_of(mu_vec[i]);
+
92 
+ +
94  for (size_t i = 0, size = length(phi); i < size; ++i)
+
95  phi__[i] = value_of(phi_vec[i]);
+
96 
+ +
98  for (size_t i = 0, size = length(phi); i < size; ++i)
+
99  log_phi[i] = log(phi__[i]);
+
100 
+ +
102  log_mu_plus_phi(len_ep);
+
103  for (size_t i = 0; i < len_ep; ++i)
+
104  log_mu_plus_phi[i] = log(mu__[i] + phi__[i]);
+
105 
+ +
107  n_plus_phi(len_np);
+
108  for (size_t i = 0; i < len_np; ++i)
+
109  n_plus_phi[i] = n_vec[i] + phi__[i];
+
110 
+
111  for (size_t i = 0; i < size; i++) {
+ +
113  logp -= lgamma(n_vec[i] + 1.0);
+ +
115  logp += multiply_log(phi__[i], phi__[i]) - lgamma(phi__[i]);
+ +
117  logp -= (n_plus_phi[i])*log_mu_plus_phi[i];
+ +
119  logp += multiply_log(n_vec[i], mu__[i]);
+ +
121  logp += lgamma(n_plus_phi[i]);
+
122 
+ +
124  operands_and_partials.d_x1[i]
+
125  += n_vec[i]/mu__[i]
+
126  - (n_vec[i] + phi__[i])
+
127  / (mu__[i] + phi__[i]);
+ +
129  operands_and_partials.d_x2[i]
+
130  += 1.0 - n_plus_phi[i]/(mu__[i] + phi__[i])
+
131  + log_phi[i] - log_mu_plus_phi[i] - digamma(phi__[i])
+
132  + digamma(n_plus_phi[i]);
+
133  }
+
134  return operands_and_partials.value(logp);
+
135  }
+
136 
+
137  template <typename T_n,
+
138  typename T_location, typename T_precision>
+
139  inline
+ +
141  neg_binomial_2_log(const T_n& n,
+
142  const T_location& mu,
+
143  const T_precision& phi) {
+
144  return neg_binomial_2_log<false>(n, mu, phi);
+
145  }
+
146  }
+
147 }
+
148 #endif
+
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
This class builds partial derivatives with respect to a set of operands.
+ +
return_type< T_location, T_precision >::type neg_binomial_2_log(const T_n &n, const T_location &mu, const T_precision &phi)
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__log__log_8hpp.html b/doc/api/html/neg__binomial__2__log__log_8hpp.html new file mode 100644 index 00000000000..856eb14ab35 --- /dev/null +++ b/doc/api/html/neg__binomial__2__log__log_8hpp.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_log_log.hpp File Reference + + + + + + + + + + +
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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+ + +
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+ +
+
neg_binomial_2_log_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_n , typename T_log_location , typename T_precision >
return_type< T_log_location, T_precision >::type stan::math::neg_binomial_2_log_log (const T_n &n, const T_log_location &eta, const T_precision &phi)
 
template<typename T_n , typename T_log_location , typename T_precision >
return_type< T_log_location, T_precision >::type stan::math::neg_binomial_2_log_log (const T_n &n, const T_log_location &eta, const T_precision &phi)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__log__log_8hpp_source.html b/doc/api/html/neg__binomial__2__log__log_8hpp_source.html new file mode 100644 index 00000000000..668ca2e17ac --- /dev/null +++ b/doc/api/html/neg__binomial__2__log__log_8hpp_source.html @@ -0,0 +1,301 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_log_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+ + + + + + +
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+
neg_binomial_2_log_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_LOG_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_LOG_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + +
21 #include <boost/math/special_functions/digamma.hpp>
+
22 #include <boost/random/negative_binomial_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <cmath>
+
25 
+
26 namespace stan {
+
27 
+
28  namespace math {
+
29 
+
30  // NegBinomial(n|eta, phi) [phi > 0; n >= 0]
+
31  template <bool propto,
+
32  typename T_n,
+
33  typename T_log_location, typename T_precision>
+
34  typename return_type<T_log_location, T_precision>::type
+
35  neg_binomial_2_log_log(const T_n& n,
+
36  const T_log_location& eta,
+
37  const T_precision& phi) {
+
38  typedef typename stan::partials_return_type<T_n, T_log_location,
+
39  T_precision>::type
+
40  T_partials_return;
+
41 
+
42  static const char* function("stan::prob::neg_binomial_2_log_log");
+
43 
+ + + + + + +
50 
+
51  // check if any vectors are zero length
+
52  if (!(stan::length(n)
+
53  && stan::length(eta)
+
54  && stan::length(phi)))
+
55  return 0.0;
+
56 
+
57  T_partials_return logp(0.0);
+
58  check_nonnegative(function, "Failures variable", n);
+
59  check_finite(function, "Log location parameter", eta);
+
60  check_positive_finite(function, "Precision parameter", phi);
+
61  check_consistent_sizes(function,
+
62  "Failures variable", n,
+
63  "Log location parameter", eta,
+
64  "Precision parameter", phi);
+
65 
+
66  // check if no variables are involved and prop-to
+ +
68  return 0.0;
+
69 
+ + +
72  using stan::math::digamma;
+
73  using stan::math::lgamma;
+
74  using std::exp;
+
75  using std::log;
+
76 
+
77  // set up template expressions wrapping scalars into vector views
+
78  VectorView<const T_n> n_vec(n);
+ +
80  VectorView<const T_precision> phi_vec(phi);
+
81  size_t size = max_size(n, eta, phi);
+
82 
+ +
84  operands_and_partials(eta, phi);
+
85 
+
86  size_t len_ep = max_size(eta, phi);
+
87  size_t len_np = max_size(n, phi);
+
88 
+ +
90  for (size_t i = 0, size = length(eta); i < size; ++i)
+
91  eta__[i] = value_of(eta_vec[i]);
+
92 
+ +
94  for (size_t i = 0, size = length(phi); i < size; ++i)
+
95  phi__[i] = value_of(phi_vec[i]);
+
96 
+
97 
+ +
99  log_phi(length(phi));
+
100  for (size_t i = 0, size = length(phi); i < size; ++i)
+
101  log_phi[i] = log(phi__[i]);
+
102 
+ +
104  logsumexp_eta_logphi(len_ep);
+
105  for (size_t i = 0; i < len_ep; ++i)
+
106  logsumexp_eta_logphi[i] = log_sum_exp(eta__[i], log_phi[i]);
+
107 
+ +
109  n_plus_phi(len_np);
+
110  for (size_t i = 0; i < len_np; ++i)
+
111  n_plus_phi[i] = n_vec[i] + phi__[i];
+
112 
+
113  for (size_t i = 0; i < size; i++) {
+ +
115  logp -= lgamma(n_vec[i] + 1.0);
+ +
117  logp += multiply_log(phi__[i], phi__[i]) - lgamma(phi__[i]);
+ +
119  logp -= (n_plus_phi[i])*logsumexp_eta_logphi[i];
+ +
121  logp += n_vec[i]*eta__[i];
+ +
123  logp += lgamma(n_plus_phi[i]);
+
124 
+ +
126  operands_and_partials.d_x1[i]
+
127  += n_vec[i] - n_plus_phi[i]
+
128  / (phi__[i]/exp(eta__[i]) + 1.0);
+ +
130  operands_and_partials.d_x2[i]
+
131  += 1.0 - n_plus_phi[i]/(exp(eta__[i]) + phi__[i])
+
132  + log_phi[i] - logsumexp_eta_logphi[i] - digamma(phi__[i])
+
133  + digamma(n_plus_phi[i]);
+
134  }
+
135  return operands_and_partials.value(logp);
+
136  }
+
137 
+
138  template <typename T_n,
+
139  typename T_log_location, typename T_precision>
+
140  inline
+ + +
143  const T_log_location& eta,
+
144  const T_precision& phi) {
+
145  return neg_binomial_2_log_log<false>(n, eta, phi);
+
146  }
+
147  }
+
148 }
+
149 #endif
+
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
return_type< T_log_location, T_precision >::type neg_binomial_2_log_log(const T_n &n, const T_log_location &eta, const T_precision &phi)
+ + +
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/neg__binomial__2__log__rng_8hpp.html b/doc/api/html/neg__binomial__2__log__rng_8hpp.html new file mode 100644 index 00000000000..4459cb41bb9 --- /dev/null +++ b/doc/api/html/neg__binomial__2__log__rng_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_log_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
int stan::math::neg_binomial_2_log_rng (const double eta, const double phi, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__log__rng_8hpp_source.html b/doc/api/html/neg__binomial__2__log__rng_8hpp_source.html new file mode 100644 index 00000000000..1eabe577c0b --- /dev/null +++ b/doc/api/html/neg__binomial__2__log__rng_8hpp_source.html @@ -0,0 +1,200 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_log_rng.hpp Source File + + + + + + + + + + +
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neg_binomial_2_log_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_LOG_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_LOG_RNG_HPP
+
3 
+
4 #include <boost/math/special_functions/digamma.hpp>
+
5 #include <boost/random/negative_binomial_distribution.hpp>
+
6 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <class RNG>
+
27  inline int
+
28  neg_binomial_2_log_rng(const double eta,
+
29  const double phi,
+
30  RNG& rng) {
+
31  using boost::variate_generator;
+
32  using boost::random::negative_binomial_distribution;
+
33  using boost::random::poisson_distribution;
+
34  using boost::gamma_distribution;
+
35 
+
36  static const char* function("stan::math::neg_binomial_2_log_rng");
+
37 
+
38  check_finite(function, "Log-location parameter", eta);
+
39  check_positive_finite(function, "Precision parameter", phi);
+
40 
+
41  double exp_eta_div_phi = std::exp(eta)/phi;
+
42 
+
43  // gamma_rng params must be positive and finite
+
44  check_positive_finite(function,
+
45  "Exponential of the log-location parameter divided by "
+
46  "the precision parameter", exp_eta_div_phi);
+
47 
+
48  double rng_from_gamma =
+
49  variate_generator<RNG&, gamma_distribution<> >
+
50  (rng, gamma_distribution<>(phi, exp_eta_div_phi))();
+
51 
+
52  // same as the constraints for poisson_rng
+
53  check_less(function,
+
54  "Random number that came from gamma distribution",
+
55  rng_from_gamma, POISSON_MAX_RATE);
+
56  check_not_nan(function,
+
57  "Random number that came from gamma distribution",
+
58  rng_from_gamma);
+
59  check_nonnegative(function,
+
60  "Random number that came from gamma distribution",
+
61  rng_from_gamma);
+
62 
+
63  return variate_generator<RNG&, poisson_distribution<> >
+
64  (rng, poisson_distribution<>(rng_from_gamma))();
+
65  }
+
66  }
+
67 }
+
68 #endif
+
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+ + +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + + + + + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
const double POISSON_MAX_RATE
Largest rate parameter allowed in Poisson RNG.
Definition: constants.hpp:72
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
int neg_binomial_2_log_rng(const double eta, const double phi, RNG &rng)
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__rng_8hpp.html b/doc/api/html/neg__binomial__2__rng_8hpp.html new file mode 100644 index 00000000000..6fb5d550414 --- /dev/null +++ b/doc/api/html/neg__binomial__2__rng_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
int stan::math::neg_binomial_2_rng (const double mu, const double phi, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__2__rng_8hpp_source.html b/doc/api/html/neg__binomial__2__rng_8hpp_source.html new file mode 100644 index 00000000000..ef9cd6c0d2b --- /dev/null +++ b/doc/api/html/neg__binomial__2__rng_8hpp_source.html @@ -0,0 +1,198 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_2_rng.hpp Source File + + + + + + + + + + +
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neg_binomial_2_rng.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_2_RNG_HPP
+
3 
+
4 #include <boost/math/special_functions/digamma.hpp>
+
5 #include <boost/random/negative_binomial_distribution.hpp>
+
6 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <class RNG>
+
27  inline int
+
28  neg_binomial_2_rng(const double mu,
+
29  const double phi,
+
30  RNG& rng) {
+
31  using boost::variate_generator;
+
32  using boost::random::negative_binomial_distribution;
+
33  using boost::random::poisson_distribution;
+
34  using boost::gamma_distribution;
+
35 
+
36  static const char* function("stan::math::neg_binomial_2_rng");
+
37 
+
38  check_positive_finite(function, "Location parameter", mu);
+
39  check_positive_finite(function, "Precision parameter", phi);
+
40 
+
41  double mu_div_phi = mu/phi;
+
42 
+
43  // gamma_rng params must be positive and finite
+
44  check_positive_finite(function,
+
45  "Location parameter divided by the precision parameter",
+
46  mu_div_phi);
+
47 
+
48  double rng_from_gamma =
+
49  variate_generator<RNG&, gamma_distribution<> >
+
50  (rng, gamma_distribution<>(phi, mu_div_phi))();
+
51 
+
52  // same as the constraints for poisson_rng
+
53  check_less(function,
+
54  "Random number that came from gamma distribution",
+
55  rng_from_gamma, POISSON_MAX_RATE);
+
56  check_not_nan(function,
+
57  "Random number that came from gamma distribution",
+
58  rng_from_gamma);
+
59  check_nonnegative(function,
+
60  "Random number that came from gamma distribution",
+
61  rng_from_gamma);
+
62 
+
63  return variate_generator<RNG&, poisson_distribution<> >
+
64  (rng, poisson_distribution<>(rng_from_gamma))();
+
65  }
+
66  }
+
67 }
+
68 #endif
+
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+ + +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + + + + + +
int neg_binomial_2_rng(const double mu, const double phi, RNG &rng)
+
const double POISSON_MAX_RATE
Largest rate parameter allowed in Poisson RNG.
Definition: constants.hpp:72
+ + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__ccdf__log_8hpp.html b/doc/api/html/neg__binomial__ccdf__log_8hpp.html new file mode 100644 index 00000000000..4ec15d1336d --- /dev/null +++ b/doc/api/html/neg__binomial__ccdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type stan::math::neg_binomial_ccdf_log (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__ccdf__log_8hpp_source.html b/doc/api/html/neg__binomial__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..dd62ee0f39a --- /dev/null +++ b/doc/api/html/neg__binomial__ccdf__log_8hpp_source.html @@ -0,0 +1,300 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_ccdf_log.hpp Source File + + + + + + + + + + +
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neg_binomial_ccdf_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + +
21 #include <boost/math/special_functions/digamma.hpp>
+
22 #include <boost/random/negative_binomial_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <cmath>
+
25 #include <limits>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_n, typename T_shape,
+
32  typename T_inv_scale>
+
33  typename return_type<T_shape, T_inv_scale>::type
+
34  neg_binomial_ccdf_log(const T_n& n, const T_shape& alpha,
+
35  const T_inv_scale& beta) {
+
36  static const char* function("stan::math::neg_binomial_ccdf_log");
+
37  typedef typename stan::partials_return_type<T_n, T_shape,
+
38  T_inv_scale>::type
+
39  T_partials_return;
+
40 
+ + + + +
45 
+
46  // Ensure non-zero arugment lengths
+
47  if (!(stan::length(n) && stan::length(alpha) && stan::length(beta)))
+
48  return 0.0;
+
49 
+
50  T_partials_return P(0.0);
+
51 
+
52  // Validate arguments
+
53  check_positive_finite(function, "Shape parameter", alpha);
+
54  check_positive_finite(function, "Inverse scale parameter", beta);
+
55  check_consistent_sizes(function,
+
56  "Failures variable", n,
+
57  "Shape parameter", alpha,
+
58  "Inverse scale parameter", beta);
+
59 
+
60  // Wrap arguments in vector views
+
61  VectorView<const T_n> n_vec(n);
+
62  VectorView<const T_shape> alpha_vec(alpha);
+
63  VectorView<const T_inv_scale> beta_vec(beta);
+
64  size_t size = max_size(n, alpha, beta);
+
65 
+
66  // Compute vectorized cdf_log and gradient
+ + +
69  using stan::math::digamma;
+
70  using stan::math::lbeta;
+
71  using std::exp;
+
72  using std::pow;
+
73  using std::log;
+
74  using std::exp;
+
75 
+ +
77  operands_and_partials(alpha, beta);
+
78 
+
79  // Explicit return for extreme values
+
80  // The gradients are technically ill-defined, but treated as zero
+
81  for (size_t i = 0; i < stan::length(n); i++) {
+
82  if (value_of(n_vec[i]) < 0)
+
83  return operands_and_partials.value(0.0);
+
84  }
+
85 
+
86  // Cache a few expensive function calls if alpha is a parameter
+ +
88  T_partials_return, T_shape>
+
89  digammaN_vec(stan::length(alpha));
+ +
91  T_partials_return, T_shape>
+
92  digammaAlpha_vec(stan::length(alpha));
+ +
94  T_partials_return, T_shape>
+
95  digammaSum_vec(stan::length(alpha));
+
96 
+ +
98  for (size_t i = 0; i < stan::length(alpha); i++) {
+
99  const T_partials_return n_dbl = value_of(n_vec[i]);
+
100  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
101 
+
102  digammaN_vec[i] = digamma(n_dbl + 1);
+
103  digammaAlpha_vec[i] = digamma(alpha_dbl);
+
104  digammaSum_vec[i] = digamma(n_dbl + alpha_dbl + 1);
+
105  }
+
106  }
+
107 
+
108  for (size_t i = 0; i < size; i++) {
+
109  // Explicit results for extreme values
+
110  // The gradients are technically ill-defined, but treated as zero
+
111  if (value_of(n_vec[i]) == std::numeric_limits<int>::max())
+
112  return operands_and_partials.value(stan::math::negative_infinity());
+
113 
+
114  const T_partials_return n_dbl = value_of(n_vec[i]);
+
115  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
116  const T_partials_return beta_dbl = value_of(beta_vec[i]);
+
117  const T_partials_return p_dbl = beta_dbl / (1.0 + beta_dbl);
+
118  const T_partials_return d_dbl = 1.0 / ( (1.0 + beta_dbl)
+
119  * (1.0 + beta_dbl) );
+
120  const T_partials_return Pi = 1.0 - inc_beta(alpha_dbl, n_dbl + 1.0,
+
121  p_dbl);
+
122  const T_partials_return beta_func = exp(lbeta(n_dbl + 1, alpha_dbl));
+
123 
+
124  P += log(Pi);
+
125 
+ +
127  T_partials_return g1 = 0;
+
128  T_partials_return g2 = 0;
+
129 
+
130  stan::math::grad_reg_inc_beta(g1, g2, alpha_dbl,
+
131  n_dbl + 1, p_dbl,
+
132  digammaAlpha_vec[i],
+
133  digammaN_vec[i],
+
134  digammaSum_vec[i],
+
135  beta_func);
+
136  operands_and_partials.d_x1[i] -= g1 / Pi;
+
137  }
+ +
139  operands_and_partials.d_x2[i] -= d_dbl * pow(1-p_dbl, n_dbl)
+
140  * pow(p_dbl, alpha_dbl-1) / beta_func / Pi;
+
141  }
+
142 
+
143  return operands_and_partials.value(P);
+
144  }
+
145  }
+
146 }
+
147 #endif
+
VectorView< T_return_type, false, true > d_x2
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
return_type< T_shape, T_inv_scale >::type neg_binomial_ccdf_log(const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__cdf_8hpp.html b/doc/api/html/neg__binomial__cdf_8hpp.html new file mode 100644 index 00000000000..198e85e4980 --- /dev/null +++ b/doc/api/html/neg__binomial__cdf_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+
+ + +
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+ + +
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+ +
+
neg_binomial_cdf.hpp File Reference
+
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+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type stan::math::neg_binomial_cdf (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__cdf_8hpp_source.html b/doc/api/html/neg__binomial__cdf_8hpp_source.html new file mode 100644 index 00000000000..b1b1619b460 --- /dev/null +++ b/doc/api/html/neg__binomial__cdf_8hpp_source.html @@ -0,0 +1,286 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
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+
neg_binomial_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <cmath>
+
20 #include <limits>
+
21 
+
22 namespace stan {
+
23  namespace math {
+
24 
+
25  // Negative Binomial CDF
+
26  template <typename T_n, typename T_shape,
+
27  typename T_inv_scale>
+
28  typename return_type<T_shape, T_inv_scale>::type
+
29  neg_binomial_cdf(const T_n& n, const T_shape& alpha,
+
30  const T_inv_scale& beta) {
+
31  static const char* function("stan::math::neg_binomial_cdf");
+
32  typedef typename stan::partials_return_type<T_n, T_shape,
+
33  T_inv_scale>::type
+
34  T_partials_return;
+
35 
+ + +
38 
+
39  // Ensure non-zero arugment lengths
+
40  if (!(stan::length(n) && stan::length(alpha) && stan::length(beta)))
+
41  return 1.0;
+
42 
+
43  T_partials_return P(1.0);
+
44 
+
45  // Validate arguments
+
46  check_positive_finite(function, "Shape parameter", alpha);
+
47  check_positive_finite(function, "Inverse scale parameter", beta);
+
48  check_consistent_sizes(function,
+
49  "Failures variable", n,
+
50  "Shape parameter", alpha,
+
51  "Inverse scale parameter", beta);
+
52 
+
53  // Wrap arguments in vector views
+
54  VectorView<const T_n> n_vec(n);
+
55  VectorView<const T_shape> alpha_vec(alpha);
+
56  VectorView<const T_inv_scale> beta_vec(beta);
+
57  size_t size = max_size(n, alpha, beta);
+
58 
+
59  // Compute vectorized CDF and gradient
+ + + + +
64  using stan::math::digamma;
+
65 
+ +
67  operands_and_partials(alpha, beta);
+
68 
+
69  // Explicit return for extreme values
+
70  // The gradients are technically ill-defined, but treated as zero
+
71  for (size_t i = 0; i < stan::length(n); i++) {
+
72  if (value_of(n_vec[i]) < 0)
+
73  return operands_and_partials.value(0.0);
+
74  }
+
75 
+
76  // Cache a few expensive function calls if alpha is a parameter
+ +
78  T_partials_return, T_shape>
+
79  digamma_alpha_vec(stan::length(alpha));
+
80 
+ +
82  T_partials_return, T_shape>
+
83  digamma_sum_vec(stan::length(alpha));
+
84 
+ +
86  for (size_t i = 0; i < stan::length(alpha); i++) {
+
87  const T_partials_return n_dbl = value_of(n_vec[i]);
+
88  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
89 
+
90  digamma_alpha_vec[i] = digamma(alpha_dbl);
+
91  digamma_sum_vec[i] = digamma(n_dbl + alpha_dbl + 1);
+
92  }
+
93  }
+
94 
+
95  for (size_t i = 0; i < size; i++) {
+
96  // Explicit results for extreme values
+
97  // The gradients are technically ill-defined, but treated as zero
+
98  if (value_of(n_vec[i]) == std::numeric_limits<int>::max())
+
99  return operands_and_partials.value(1.0);
+
100 
+
101  const T_partials_return n_dbl = value_of(n_vec[i]);
+
102  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
103  const T_partials_return beta_dbl = value_of(beta_vec[i]);
+
104 
+
105  const T_partials_return p_dbl = beta_dbl / (1.0 + beta_dbl);
+
106  const T_partials_return d_dbl = 1.0 / ( (1.0 + beta_dbl)
+
107  * (1.0 + beta_dbl) );
+
108 
+
109  const T_partials_return P_i =
+
110  inc_beta(alpha_dbl, n_dbl + 1.0, p_dbl);
+
111 
+
112  P *= P_i;
+
113 
+ +
115  operands_and_partials.d_x1[i]
+
116  += inc_beta_dda(alpha_dbl, n_dbl + 1, p_dbl,
+
117  digamma_alpha_vec[i],
+
118  digamma_sum_vec[i]) / P_i;
+
119  }
+
120 
+ +
122  operands_and_partials.d_x2[i] +=
+
123  inc_beta_ddz(alpha_dbl, n_dbl + 1.0, p_dbl) * d_dbl / P_i;
+
124  }
+
125 
+ +
127  for (size_t i = 0; i < stan::length(alpha); ++i)
+
128  operands_and_partials.d_x1[i] *= P;
+
129  }
+
130 
+ +
132  for (size_t i = 0; i < stan::length(beta); ++i)
+
133  operands_and_partials.d_x2[i] *= P;
+
134  }
+
135 
+
136  return operands_and_partials.value(P);
+
137  }
+
138 
+
139  } // prob
+
140 } // stan
+
141 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_shape, T_inv_scale >::type neg_binomial_cdf(const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T inc_beta_dda(T a, T b, T z, T digamma_a, T digamma_ab)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to a.
+ + +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T inc_beta_ddz(T a, T b, T z)
Returns the partial derivative of the regularized incomplete beta function, I_{z}(a, b) with respect to z.
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ +
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__cdf__log_8hpp.html b/doc/api/html/neg__binomial__cdf__log_8hpp.html new file mode 100644 index 00000000000..8831d569683 --- /dev/null +++ b/doc/api/html/neg__binomial__cdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
neg_binomial_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type stan::math::neg_binomial_cdf_log (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/neg__binomial__cdf__log_8hpp_source.html b/doc/api/html/neg__binomial__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..0793a8aa294 --- /dev/null +++ b/doc/api/html/neg__binomial__cdf__log_8hpp_source.html @@ -0,0 +1,301 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
neg_binomial_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + +
21 #include <boost/math/special_functions/digamma.hpp>
+
22 #include <boost/random/negative_binomial_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <cmath>
+
25 #include <limits>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_n, typename T_shape,
+
32  typename T_inv_scale>
+
33  typename return_type<T_shape, T_inv_scale>::type
+
34  neg_binomial_cdf_log(const T_n& n, const T_shape& alpha,
+
35  const T_inv_scale& beta) {
+
36  static const char* function("stan::math::neg_binomial_cdf_log");
+
37  typedef typename stan::partials_return_type<T_n, T_shape,
+
38  T_inv_scale>::type
+
39  T_partials_return;
+
40 
+ + + + +
45 
+
46  // Ensure non-zero arugment lengths
+
47  if (!(stan::length(n) && stan::length(alpha) && stan::length(beta)))
+
48  return 0.0;
+
49 
+
50  T_partials_return P(0.0);
+
51 
+
52  // Validate arguments
+
53  check_positive_finite(function, "Shape parameter", alpha);
+
54  check_positive_finite(function, "Inverse scale parameter", beta);
+
55  check_consistent_sizes(function,
+
56  "Failures variable", n,
+
57  "Shape parameter", alpha,
+
58  "Inverse scale parameter", beta);
+
59 
+
60  // Wrap arguments in vector views
+
61  VectorView<const T_n> n_vec(n);
+
62  VectorView<const T_shape> alpha_vec(alpha);
+
63  VectorView<const T_inv_scale> beta_vec(beta);
+
64  size_t size = max_size(n, alpha, beta);
+
65 
+
66  // Compute vectorized cdf_log and gradient
+ + +
69  using stan::math::digamma;
+
70  using stan::math::lbeta;
+
71  using std::exp;
+
72  using std::pow;
+
73  using std::log;
+
74  using std::exp;
+
75 
+
76 
+ +
78  operands_and_partials(alpha, beta);
+
79 
+
80  // Explicit return for extreme values
+
81  // The gradients are technically ill-defined, but treated as zero
+
82  for (size_t i = 0; i < stan::length(n); i++) {
+
83  if (value_of(n_vec[i]) < 0)
+
84  return operands_and_partials.value(stan::math::negative_infinity());
+
85  }
+
86 
+
87  // Cache a few expensive function calls if alpha is a parameter
+ +
89  T_partials_return, T_shape>
+
90  digammaN_vec(stan::length(alpha));
+ +
92  T_partials_return, T_shape>
+
93  digammaAlpha_vec(stan::length(alpha));
+ +
95  T_partials_return, T_shape>
+
96  digammaSum_vec(stan::length(alpha));
+
97 
+ +
99  for (size_t i = 0; i < stan::length(alpha); i++) {
+
100  const T_partials_return n_dbl = value_of(n_vec[i]);
+
101  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
102 
+
103  digammaN_vec[i] = digamma(n_dbl + 1);
+
104  digammaAlpha_vec[i] = digamma(alpha_dbl);
+
105  digammaSum_vec[i] = digamma(n_dbl + alpha_dbl + 1);
+
106  }
+
107  }
+
108 
+
109  for (size_t i = 0; i < size; i++) {
+
110  // Explicit results for extreme values
+
111  // The gradients are technically ill-defined, but treated as zero
+
112  if (value_of(n_vec[i]) == std::numeric_limits<int>::max())
+
113  return operands_and_partials.value(0.0);
+
114 
+
115  const T_partials_return n_dbl = value_of(n_vec[i]);
+
116  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
117  const T_partials_return beta_dbl = value_of(beta_vec[i]);
+
118  const T_partials_return p_dbl = beta_dbl / (1.0 + beta_dbl);
+
119  const T_partials_return d_dbl = 1.0 / ( (1.0 + beta_dbl)
+
120  * (1.0 + beta_dbl) );
+
121  const T_partials_return Pi = inc_beta(alpha_dbl, n_dbl + 1.0, p_dbl);
+
122  const T_partials_return beta_func = exp(lbeta(n_dbl + 1, alpha_dbl));
+
123 
+
124 
+
125  P += log(Pi);
+
126 
+ +
128  T_partials_return g1 = 0;
+
129  T_partials_return g2 = 0;
+
130 
+
131  stan::math::grad_reg_inc_beta(g1, g2, alpha_dbl,
+
132  n_dbl + 1, p_dbl,
+
133  digammaAlpha_vec[i],
+
134  digammaN_vec[i],
+
135  digammaSum_vec[i],
+
136  beta_func);
+
137  operands_and_partials.d_x1[i] += g1 / Pi;
+
138  }
+ +
140  operands_and_partials.d_x2[i] += d_dbl * pow(1-p_dbl, n_dbl)
+
141  * pow(p_dbl, alpha_dbl-1) / beta_func / Pi;
+
142  }
+
143 
+
144  return operands_and_partials.value(P);
+
145  }
+
146  }
+
147 }
+
148 #endif
+
VectorView< T_return_type, false, true > d_x2
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
return_type< T_shape, T_inv_scale >::type neg_binomial_cdf_log(const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
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diff --git a/doc/api/html/neg__binomial__log_8hpp.html b/doc/api/html/neg__binomial__log_8hpp.html new file mode 100644 index 00000000000..ca08f1a3a4c --- /dev/null +++ b/doc/api/html/neg__binomial__log_8hpp.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type stan::math::neg_binomial_log (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
template<typename T_n , typename T_shape , typename T_inv_scale >
return_type< T_shape, T_inv_scale >::type stan::math::neg_binomial_log (const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
 
+
+
+
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diff --git a/doc/api/html/neg__binomial__log_8hpp_source.html b/doc/api/html/neg__binomial__log_8hpp_source.html new file mode 100644 index 00000000000..18de5e1fde0 --- /dev/null +++ b/doc/api/html/neg__binomial__log_8hpp_source.html @@ -0,0 +1,345 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + +
25 #include <boost/math/special_functions/digamma.hpp>
+
26 #include <boost/random/negative_binomial_distribution.hpp>
+
27 #include <boost/random/variate_generator.hpp>
+
28 #include <cmath>
+
29 
+
30 namespace stan {
+
31 
+
32  namespace math {
+
33 
+
34  // NegBinomial(n|alpha, beta) [alpha > 0; beta > 0; n >= 0]
+
35  template <bool propto,
+
36  typename T_n,
+
37  typename T_shape, typename T_inv_scale>
+
38  typename return_type<T_shape, T_inv_scale>::type
+
39  neg_binomial_log(const T_n& n,
+
40  const T_shape& alpha,
+
41  const T_inv_scale& beta) {
+
42  typedef typename stan::partials_return_type<T_n, T_shape,
+
43  T_inv_scale>::type
+
44  T_partials_return;
+
45 
+
46  static const char* function("stan::math::neg_binomial_log");
+
47 
+ + + + + +
53 
+
54  // check if any vectors are zero length
+
55  if (!(stan::length(n)
+
56  && stan::length(alpha)
+
57  && stan::length(beta)))
+
58  return 0.0;
+
59 
+
60  T_partials_return logp(0.0);
+
61  check_nonnegative(function, "Failures variable", n);
+
62  check_positive_finite(function, "Shape parameter", alpha);
+
63  check_positive_finite(function, "Inverse scale parameter", beta);
+
64  check_consistent_sizes(function,
+
65  "Failures variable", n,
+
66  "Shape parameter", alpha,
+
67  "Inverse scale parameter", beta);
+
68 
+
69  // check if no variables are involved and prop-to
+ +
71  return 0.0;
+
72 
+ + +
75  using stan::math::digamma;
+
76  using stan::math::lgamma;
+
77  using std::log;
+
78  using std::log;
+
79 
+
80  // set up template expressions wrapping scalars into vector views
+
81  VectorView<const T_n> n_vec(n);
+
82  VectorView<const T_shape> alpha_vec(alpha);
+
83  VectorView<const T_inv_scale> beta_vec(beta);
+
84  size_t size = max_size(n, alpha, beta);
+
85 
+ +
87  operands_and_partials(alpha, beta);
+
88 
+
89  size_t len_ab = max_size(alpha, beta);
+ +
91  lambda(len_ab);
+
92  for (size_t i = 0; i < len_ab; ++i)
+
93  lambda[i] = value_of(alpha_vec[i]) / value_of(beta_vec[i]);
+
94 
+ +
96  log1p_beta(length(beta));
+
97  for (size_t i = 0; i < length(beta); ++i)
+
98  log1p_beta[i] = log1p(value_of(beta_vec[i]));
+
99 
+ +
101  log_beta_m_log1p_beta(length(beta));
+
102  for (size_t i = 0; i < length(beta); ++i)
+
103  log_beta_m_log1p_beta[i] = log(value_of(beta_vec[i])) - log1p_beta[i];
+
104 
+ +
106  alpha_times_log_beta_over_1p_beta(len_ab);
+
107  for (size_t i = 0; i < len_ab; ++i)
+
108  alpha_times_log_beta_over_1p_beta[i]
+
109  = value_of(alpha_vec[i])
+
110  * log(value_of(beta_vec[i])
+
111  / (1.0 + value_of(beta_vec[i])));
+
112 
+ +
114  T_partials_return, T_shape>
+
115  digamma_alpha(length(alpha));
+ +
117  for (size_t i = 0; i < length(alpha); ++i)
+
118  digamma_alpha[i] = digamma(value_of(alpha_vec[i]));
+
119  }
+
120 
+ +
122  T_partials_return, T_inv_scale> log_beta(length(beta));
+ +
124  for (size_t i = 0; i < length(beta); ++i)
+
125  log_beta[i] = log(value_of(beta_vec[i]));
+
126  }
+
127 
+ +
129  T_partials_return, T_shape, T_inv_scale>
+
130  lambda_m_alpha_over_1p_beta(len_ab);
+ +
132  for (size_t i = 0; i < len_ab; ++i)
+
133  lambda_m_alpha_over_1p_beta[i] =
+
134  lambda[i]
+
135  - (value_of(alpha_vec[i])
+
136  / (1.0 + value_of(beta_vec[i])));
+
137  }
+
138 
+
139  for (size_t i = 0; i < size; i++) {
+
140  if (alpha_vec[i] > 1e10) { // reduces numerically to Poisson
+ +
142  logp -= lgamma(n_vec[i] + 1.0);
+ +
144  logp += multiply_log(n_vec[i], lambda[i]) - lambda[i];
+
145 
+ +
147  operands_and_partials.d_x1[i]
+
148  += n_vec[i] / value_of(alpha_vec[i])
+
149  - 1.0 / value_of(beta_vec[i]);
+ +
151  operands_and_partials.d_x2[i]
+
152  += (lambda[i] - n_vec[i]) / value_of(beta_vec[i]);
+
153  } else { // standard density definition
+ +
155  if (n_vec[i] != 0)
+
156  logp += binomial_coefficient_log(n_vec[i]
+
157  + value_of(alpha_vec[i])
+
158  - 1.0,
+
159  n_vec[i]);
+ +
161  logp +=
+
162  alpha_times_log_beta_over_1p_beta[i]
+
163  - n_vec[i] * log1p_beta[i];
+
164 
+ +
166  operands_and_partials.d_x1[i]
+
167  += digamma(value_of(alpha_vec[i]) + n_vec[i])
+
168  - digamma_alpha[i]
+
169  + log_beta_m_log1p_beta[i];
+ +
171  operands_and_partials.d_x2[i]
+
172  += lambda_m_alpha_over_1p_beta[i]
+
173  - n_vec[i] / (value_of(beta_vec[i]) + 1.0);
+
174  }
+
175  }
+
176  return operands_and_partials.value(logp);
+
177  }
+
178 
+
179  template <typename T_n,
+
180  typename T_shape, typename T_inv_scale>
+
181  inline
+ +
183  neg_binomial_log(const T_n& n,
+
184  const T_shape& alpha,
+
185  const T_inv_scale& beta) {
+
186  return neg_binomial_log<false>(n, alpha, beta);
+
187  }
+
188  }
+
189 }
+
190 #endif
+
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > binomial_coefficient_log(const fvar< T > &x1, const fvar< T > &x2)
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
return_type< T_shape, T_inv_scale >::type neg_binomial_log(const T_n &n, const T_shape &alpha, const T_inv_scale &beta)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/neg__binomial__rng_8hpp.html b/doc/api/html/neg__binomial__rng_8hpp.html new file mode 100644 index 00000000000..f6ba58d8d73 --- /dev/null +++ b/doc/api/html/neg__binomial__rng_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
int stan::math::neg_binomial_rng (const double alpha, const double beta, RNG &rng)
 
+
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diff --git a/doc/api/html/neg__binomial__rng_8hpp_source.html b/doc/api/html/neg__binomial__rng_8hpp_source.html new file mode 100644 index 00000000000..134e169102a --- /dev/null +++ b/doc/api/html/neg__binomial__rng_8hpp_source.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/neg_binomial_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NEG_BINOMIAL_RNG_HPP
+
3 
+
4 #include <boost/math/special_functions/digamma.hpp>
+
5 #include <boost/random/negative_binomial_distribution.hpp>
+
6 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + +
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <class RNG>
+
28  inline int
+
29  neg_binomial_rng(const double alpha,
+
30  const double beta,
+
31  RNG& rng) {
+
32  using boost::variate_generator;
+
33  using boost::random::negative_binomial_distribution;
+
34  using boost::random::poisson_distribution;
+
35  using boost::gamma_distribution;
+
36 
+
37  static const char* function("stan::math::neg_binomial_rng");
+
38 
+
39  // gamma_rng params must be positive and finite
+
40  check_positive_finite(function, "Shape parameter", alpha);
+
41  check_positive_finite(function, "Inverse scale parameter", beta);
+
42 
+
43  double rng_from_gamma =
+
44  variate_generator<RNG&, gamma_distribution<> >
+
45  (rng, gamma_distribution<>(alpha, 1.0 / beta))();
+
46 
+
47  // same as the constraints for poisson_rng
+
48  check_less(function,
+
49  "Random number that came from gamma distribution",
+
50  rng_from_gamma, POISSON_MAX_RATE);
+
51  check_not_nan(function,
+
52  "Random number that came from gamma distribution",
+
53  rng_from_gamma);
+
54  check_nonnegative(function,
+
55  "Random number that came from gamma distribution",
+
56  rng_from_gamma);
+
57 
+
58  return variate_generator<RNG&, poisson_distribution<> >
+
59  (rng, poisson_distribution<>(rng_from_gamma))();
+
60  }
+
61  }
+
62 }
+
63 #endif
+
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+ + +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + +
int neg_binomial_rng(const double alpha, const double beta, RNG &rng)
+ + + + +
const double POISSON_MAX_RATE
Largest rate parameter allowed in Poisson RNG.
Definition: constants.hpp:72
+ + + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
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diff --git a/doc/api/html/nested__size_8hpp.html b/doc/api/html/nested__size_8hpp.html new file mode 100644 index 00000000000..a0fab97507a --- /dev/null +++ b/doc/api/html/nested__size_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/nested_size.hpp File Reference + + + + + + + + + + +
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static size_t stan::math::nested_size ()
 
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diff --git a/doc/api/html/nested__size_8hpp_source.html b/doc/api/html/nested__size_8hpp_source.html new file mode 100644 index 00000000000..7c6503db7c4 --- /dev/null +++ b/doc/api/html/nested__size_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/core/nested_size.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_NESTED_SIZE_HPP
+
2 #define STAN_MATH_REV_CORE_NESTED_SIZE_HPP
+
3 
+ +
5 #include <cstdlib>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  static inline size_t nested_size() {
+
11  return ChainableStack::var_stack_.size()
+ +
13  }
+
14 
+
15  }
+
16 }
+
17 #endif
+ +
static size_t nested_size()
Definition: nested_size.hpp:10
+
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+ +
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+
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diff --git a/doc/api/html/normal__ccdf__log_8hpp.html b/doc/api/html/normal__ccdf__log_8hpp.html new file mode 100644 index 00000000000..4a96a11827e --- /dev/null +++ b/doc/api/html/normal__ccdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::normal_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
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diff --git a/doc/api/html/normal__ccdf__log_8hpp_source.html b/doc/api/html/normal__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..fdd9f5154f6 --- /dev/null +++ b/doc/api/html/normal__ccdf__log_8hpp_source.html @@ -0,0 +1,253 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_ccdf_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NORMAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NORMAL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/normal_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 #include <limits>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <typename T_y, typename T_loc, typename T_scale>
+
25  typename return_type<T_y, T_loc, T_scale>::type
+
26  normal_ccdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
27  static const char* function("stan::math::normal_ccdf_log");
+ +
29  T_partials_return;
+
30 
+ + + + + + +
37  using std::log;
+
38  using std::exp;
+
39 
+
40  T_partials_return ccdf_log(0.0);
+
41  // check if any vectors are zero length
+
42  if (!(stan::length(y)
+
43  && stan::length(mu)
+
44  && stan::length(sigma)))
+
45  return ccdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_finite(function, "Location parameter", mu);
+
49  check_not_nan(function, "Scale parameter", sigma);
+
50  check_positive(function, "Scale parameter", sigma);
+
51  check_consistent_sizes(function,
+
52  "Random variable", y,
+
53  "Location parameter", mu,
+
54  "Scale parameter", sigma);
+
55 
+ +
57  operands_and_partials(y, mu, sigma);
+
58 
+
59  VectorView<const T_y> y_vec(y);
+
60  VectorView<const T_loc> mu_vec(mu);
+
61  VectorView<const T_scale> sigma_vec(sigma);
+
62  size_t N = max_size(y, mu, sigma);
+
63  double log_half = std::log(0.5);
+
64 
+
65  const double SQRT_TWO_OVER_PI = std::sqrt(2.0 / stan::math::pi());
+
66  for (size_t n = 0; n < N; n++) {
+
67  const T_partials_return y_dbl = value_of(y_vec[n]);
+
68  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
69  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
70 
+
71  const T_partials_return scaled_diff = (y_dbl - mu_dbl)
+
72  / (sigma_dbl * SQRT_2);
+
73 
+
74  T_partials_return one_m_erf;
+
75  if (scaled_diff < -37.5 * INV_SQRT_2)
+
76  one_m_erf = 2.0;
+
77  else if (scaled_diff < -5.0 * INV_SQRT_2)
+
78  one_m_erf = 2.0 - erfc(-scaled_diff);
+
79  else if (scaled_diff > 8.25 * INV_SQRT_2)
+
80  one_m_erf = 0.0;
+
81  else
+
82  one_m_erf = 1.0 - erf(scaled_diff);
+
83 
+
84  // log ccdf
+
85  ccdf_log += log_half + log(one_m_erf);
+
86 
+
87  // gradients
+ +
89  const T_partials_return rep_deriv_div_sigma
+
90  = scaled_diff > 8.25 * INV_SQRT_2
+
91  ? std::numeric_limits<double>::infinity()
+
92  : SQRT_TWO_OVER_PI * exp(-scaled_diff * scaled_diff)
+
93  / one_m_erf / sigma_dbl;
+ +
95  operands_and_partials.d_x1[n] -= rep_deriv_div_sigma;
+ +
97  operands_and_partials.d_x2[n] += rep_deriv_div_sigma;
+ +
99  operands_and_partials.d_x3[n] += rep_deriv_div_sigma
+
100  * scaled_diff * stan::math::SQRT_2;
+
101  }
+
102  }
+
103  return operands_and_partials.value(ccdf_log);
+
104  }
+
105  }
+
106 }
+
107 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ +
return_type< T_y, T_loc, T_scale >::type normal_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
const double INV_SQRT_2
The value of 1 over the square root of 2, .
Definition: constants.hpp:27
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/normal__cdf_8hpp.html b/doc/api/html/normal__cdf_8hpp.html new file mode 100644 index 00000000000..f7efe55fe4a --- /dev/null +++ b/doc/api/html/normal__cdf_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
normal_cdf.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::normal_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma)
 Calculates the normal cumulative distribution function for the given variate, location, and scale. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/normal__cdf_8hpp_source.html b/doc/api/html/normal__cdf_8hpp_source.html new file mode 100644 index 00000000000..4467128dd31 --- /dev/null +++ b/doc/api/html/normal__cdf_8hpp_source.html @@ -0,0 +1,263 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
normal_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NORMAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NORMAL_CDF_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/normal_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
38  template <typename T_y, typename T_loc, typename T_scale>
+
39  typename return_type<T_y, T_loc, T_scale>::type
+
40  normal_cdf(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
41  static const char* function("stan::math::normal_cdf");
+ +
43  T_partials_return;
+
44 
+ + + + + + +
51  using std::exp;
+
52 
+
53  T_partials_return cdf(1.0);
+
54 
+
55  // check if any vectors are zero length
+
56  if (!(stan::length(y)
+
57  && stan::length(mu)
+
58  && stan::length(sigma)))
+
59  return cdf;
+
60 
+
61  check_not_nan(function, "Random variable", y);
+
62  check_finite(function, "Location parameter", mu);
+
63  check_not_nan(function, "Scale parameter", sigma);
+
64  check_positive(function, "Scale parameter", sigma);
+
65  check_consistent_sizes(function,
+
66  "Random variable", y,
+
67  "Location parameter", mu,
+
68  "Scale parameter", sigma);
+
69 
+
70 
+ +
72  operands_and_partials(y, mu, sigma);
+
73 
+
74  VectorView<const T_y> y_vec(y);
+
75  VectorView<const T_loc> mu_vec(mu);
+
76  VectorView<const T_scale> sigma_vec(sigma);
+
77  size_t N = max_size(y, mu, sigma);
+
78  const double SQRT_TWO_OVER_PI = std::sqrt(2.0 / stan::math::pi());
+
79 
+
80  for (size_t n = 0; n < N; n++) {
+
81  const T_partials_return y_dbl = value_of(y_vec[n]);
+
82  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
83  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
84  const T_partials_return scaled_diff = (y_dbl - mu_dbl)
+
85  / (sigma_dbl * SQRT_2);
+
86  T_partials_return cdf_;
+
87  if (scaled_diff < -37.5 * INV_SQRT_2)
+
88  cdf_ = 0.0;
+
89  else if (scaled_diff < -5.0 * INV_SQRT_2)
+
90  cdf_ = 0.5 * erfc(-scaled_diff);
+
91  else if (scaled_diff > 8.25 * INV_SQRT_2)
+
92  cdf_ = 1;
+
93  else
+
94  cdf_ = 0.5 * (1.0 + erf(scaled_diff));
+
95 
+
96  // cdf
+
97  cdf *= cdf_;
+
98 
+
99  // gradients
+ +
101  const T_partials_return rep_deriv
+
102  = scaled_diff < -37.5 * INV_SQRT_2
+
103  ? 0.0
+
104  : SQRT_TWO_OVER_PI * 0.5
+
105  * exp(-scaled_diff * scaled_diff) / cdf_ / sigma_dbl;
+ +
107  operands_and_partials.d_x1[n] += rep_deriv;
+ +
109  operands_and_partials.d_x2[n] -= rep_deriv;
+ +
111  operands_and_partials.d_x3[n] -= rep_deriv * scaled_diff * SQRT_2;
+
112  }
+
113  }
+
114 
+ +
116  for (size_t n = 0; n < stan::length(y); ++n)
+
117  operands_and_partials.d_x1[n] *= cdf;
+
118  }
+ +
120  for (size_t n = 0; n < stan::length(mu); ++n)
+
121  operands_and_partials.d_x2[n] *= cdf;
+
122  }
+ +
124  for (size_t n = 0; n < stan::length(sigma); ++n)
+
125  operands_and_partials.d_x3[n] *= cdf;
+
126  }
+
127 
+
128  return operands_and_partials.value(cdf);
+
129  }
+
130  }
+
131 }
+
132 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
const double INV_SQRT_2
The value of 1 over the square root of 2, .
Definition: constants.hpp:27
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
return_type< T_y, T_loc, T_scale >::type normal_cdf(const T_y &y, const T_loc &mu, const T_scale &sigma)
Calculates the normal cumulative distribution function for the given variate, location, and scale.
Definition: normal_cdf.hpp:40
+ +
VectorView< T_return_type, false, true > d_x1
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/normal__cdf__log_8hpp.html b/doc/api/html/normal__cdf__log_8hpp.html new file mode 100644 index 00000000000..52e47b89ca3 --- /dev/null +++ b/doc/api/html/normal__cdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
normal_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::normal_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/normal__cdf__log_8hpp_source.html b/doc/api/html/normal__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..9689f211440 --- /dev/null +++ b/doc/api/html/normal__cdf__log_8hpp_source.html @@ -0,0 +1,253 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
normal_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NORMAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NORMAL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/normal_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 #include <limits>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template <typename T_y, typename T_loc, typename T_scale>
+
25  typename return_type<T_y, T_loc, T_scale>::type
+
26  normal_cdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
27  static const char* function("stan::math::normal_cdf_log");
+ +
29  T_partials_return;
+
30 
+ + + + + + +
37  using std::log;
+
38  using std::exp;
+
39 
+
40  T_partials_return cdf_log(0.0);
+
41  // check if any vectors are zero length
+
42  if (!(stan::length(y)
+
43  && stan::length(mu)
+
44  && stan::length(sigma)))
+
45  return cdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_finite(function, "Location parameter", mu);
+
49  check_not_nan(function, "Scale parameter", sigma);
+
50  check_positive(function, "Scale parameter", sigma);
+
51  check_consistent_sizes(function,
+
52  "Random variable", y,
+
53  "Location parameter", mu,
+
54  "Scale parameter", sigma);
+
55 
+ +
57  operands_and_partials(y, mu, sigma);
+
58 
+
59  VectorView<const T_y> y_vec(y);
+
60  VectorView<const T_loc> mu_vec(mu);
+
61  VectorView<const T_scale> sigma_vec(sigma);
+
62  size_t N = max_size(y, mu, sigma);
+
63 
+
64  const double SQRT_TWO_OVER_PI = std::sqrt(2.0 / stan::math::pi());
+
65  for (size_t n = 0; n < N; n++) {
+
66  const T_partials_return y_dbl = value_of(y_vec[n]);
+
67  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
68  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
69 
+
70  const T_partials_return scaled_diff = (y_dbl - mu_dbl)
+
71  / (sigma_dbl * SQRT_2);
+
72 
+
73  T_partials_return one_p_erf;
+
74  if (scaled_diff < -37.5 * INV_SQRT_2)
+
75  one_p_erf = 0.0;
+
76  else if (scaled_diff < -5.0 * INV_SQRT_2)
+
77  one_p_erf = erfc(-scaled_diff);
+
78  else if (scaled_diff > 8.25 * INV_SQRT_2)
+
79  one_p_erf = 2.0;
+
80  else
+
81  one_p_erf = 1.0 + erf(scaled_diff);
+
82 
+
83  // log cdf
+
84  cdf_log += LOG_HALF + log(one_p_erf);
+
85 
+
86  // gradients
+ +
88  const T_partials_return rep_deriv_div_sigma
+
89  = scaled_diff < -37.5 * INV_SQRT_2
+
90  ? std::numeric_limits<double>::infinity()
+
91  : SQRT_TWO_OVER_PI * exp(-scaled_diff * scaled_diff)
+
92  / sigma_dbl / one_p_erf;
+ +
94  operands_and_partials.d_x1[n] += rep_deriv_div_sigma;
+ +
96  operands_and_partials.d_x2[n] -= rep_deriv_div_sigma;
+ +
98  operands_and_partials.d_x3[n] -= rep_deriv_div_sigma
+
99  * scaled_diff * stan::math::SQRT_2;
+
100  }
+
101  }
+
102  return operands_and_partials.value(cdf_log);
+
103  }
+
104  }
+
105 }
+
106 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
const double LOG_HALF
Definition: constants.hpp:179
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+
const double INV_SQRT_2
The value of 1 over the square root of 2, .
Definition: constants.hpp:27
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
return_type< T_y, T_loc, T_scale >::type normal_cdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+ +
+
+
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diff --git a/doc/api/html/normal__log_8hpp.html b/doc/api/html/normal__log_8hpp.html new file mode 100644 index 00000000000..4cc5ddd9a13 --- /dev/null +++ b/doc/api/html/normal__log_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 The log of the normal density for the specified scalar(s) given the specified mean(s) and deviation(s). More...
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma)
 
+
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diff --git a/doc/api/html/normal__log_8hpp_source.html b/doc/api/html/normal__log_8hpp_source.html new file mode 100644 index 00000000000..903076f6d9b --- /dev/null +++ b/doc/api/html/normal__log_8hpp_source.html @@ -0,0 +1,268 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NORMAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NORMAL_LOG_HPP
+
3 
+ + + + + + + + + + + + +
16 #include <boost/random/normal_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
42  template <bool propto,
+
43  typename T_y, typename T_loc, typename T_scale>
+
44  typename return_type<T_y, T_loc, T_scale>::type
+
45  normal_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
46  static const char* function("stan::math::normal_log");
+ +
48  T_partials_return;
+
49 
+
50  using std::log;
+ + + + + + + +
58  using std::log;
+
59 
+
60  // check if any vectors are zero length
+
61  if (!(stan::length(y)
+
62  && stan::length(mu)
+
63  && stan::length(sigma)))
+
64  return 0.0;
+
65 
+
66  // set up return value accumulator
+
67  T_partials_return logp(0.0);
+
68 
+
69  // validate args (here done over var, which should be OK)
+
70  check_not_nan(function, "Random variable", y);
+
71  check_finite(function, "Location parameter", mu);
+
72  check_positive(function, "Scale parameter", sigma);
+
73  check_consistent_sizes(function,
+
74  "Random variable", y,
+
75  "Location parameter", mu,
+
76  "Scale parameter", sigma);
+
77  // check if no variables are involved and prop-to
+ +
79  return 0.0;
+
80 
+
81  // set up template expressions wrapping scalars into vector views
+ +
83  operands_and_partials(y, mu, sigma);
+
84 
+
85  VectorView<const T_y> y_vec(y);
+
86  VectorView<const T_loc> mu_vec(mu);
+
87  VectorView<const T_scale> sigma_vec(sigma);
+
88  size_t N = max_size(y, mu, sigma);
+
89 
+ + +
92  T_partials_return, T_scale> log_sigma(length(sigma));
+
93  for (size_t i = 0; i < length(sigma); i++) {
+
94  inv_sigma[i] = 1.0 / value_of(sigma_vec[i]);
+ +
96  log_sigma[i] = log(value_of(sigma_vec[i]));
+
97  }
+
98 
+
99  for (size_t n = 0; n < N; n++) {
+
100  // pull out values of arguments
+
101  const T_partials_return y_dbl = value_of(y_vec[n]);
+
102  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
103 
+
104  // reusable subexpression values
+
105  const T_partials_return y_minus_mu_over_sigma
+
106  = (y_dbl - mu_dbl) * inv_sigma[n];
+
107  const T_partials_return y_minus_mu_over_sigma_squared
+
108  = y_minus_mu_over_sigma * y_minus_mu_over_sigma;
+
109 
+
110  static double NEGATIVE_HALF = - 0.5;
+
111 
+
112  // log probability
+ +
114  logp += NEG_LOG_SQRT_TWO_PI;
+ +
116  logp -= log_sigma[n];
+ +
118  logp += NEGATIVE_HALF * y_minus_mu_over_sigma_squared;
+
119 
+
120  // gradients
+
121  T_partials_return scaled_diff = inv_sigma[n] * y_minus_mu_over_sigma;
+ +
123  operands_and_partials.d_x1[n] -= scaled_diff;
+ +
125  operands_and_partials.d_x2[n] += scaled_diff;
+ +
127  operands_and_partials.d_x3[n]
+
128  += -inv_sigma[n] + inv_sigma[n] * y_minus_mu_over_sigma_squared;
+
129  }
+
130 
+
131 
+
132  return operands_and_partials.value(logp);
+
133  }
+
134 
+
135  template <typename T_y, typename T_loc, typename T_scale>
+
136  inline
+ +
138  normal_log(const T_y& y, const T_loc& mu, const T_scale& sigma) {
+
139  return normal_log<false>(y, mu, sigma);
+
140  }
+
141  }
+
142 }
+
143 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
const double NEG_LOG_SQRT_TWO_PI
Definition: constants.hpp:184
+
return_type< T_y, T_loc, T_scale >::type normal_log(const T_y &y, const T_loc &mu, const T_scale &sigma)
The log of the normal density for the specified scalar(s) given the specified mean(s) and deviation(s...
Definition: normal_log.hpp:45
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+ +
+
+
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diff --git a/doc/api/html/normal__rng_8hpp.html b/doc/api/html/normal__rng_8hpp.html new file mode 100644 index 00000000000..4b2f9dd6d60 --- /dev/null +++ b/doc/api/html/normal__rng_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+
normal_rng.hpp File Reference
+
+
+
#include <boost/random/normal_distribution.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+
+

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+ + + + + + + +

+Namespaces

 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<class RNG >
double stan::math::normal_rng (const double mu, const double sigma, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/normal__rng_8hpp_source.html b/doc/api/html/normal__rng_8hpp_source.html new file mode 100644 index 00000000000..4bf2b505360 --- /dev/null +++ b/doc/api/html/normal__rng_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/normal_rng.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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+
normal_rng.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_NORMAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_NORMAL_RNG_HPP
+
3 
+
4 #include <boost/random/normal_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + +
12 
+
13 namespace stan {
+
14 
+
15  namespace math {
+
16 
+
17  template <class RNG>
+
18  inline double
+
19  normal_rng(const double mu,
+
20  const double sigma,
+
21  RNG& rng) {
+
22  using boost::variate_generator;
+
23  using boost::normal_distribution;
+ + + +
27 
+
28  static const char* function("stan::math::normal_rng");
+
29 
+
30  check_finite(function, "Location parameter", mu);
+
31  check_not_nan(function, "Location parameter", mu);
+
32  check_positive(function, "Scale parameter", sigma);
+
33  check_not_nan(function, "Scale parameter", sigma);
+
34 
+
35  variate_generator<RNG&, normal_distribution<> >
+
36  norm_rng(rng, normal_distribution<>(mu, sigma));
+
37  return norm_rng();
+
38  }
+
39  }
+
40 }
+
41 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
double normal_rng(const double mu, const double sigma, RNG &rng)
Definition: normal_rng.hpp:19
+ +
+
+
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diff --git a/doc/api/html/num__elements_8hpp.html b/doc/api/html/num__elements_8hpp.html new file mode 100644 index 00000000000..bfa74648bfe --- /dev/null +++ b/doc/api/html/num__elements_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/num_elements.hpp File Reference + + + + + + + + + + +
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num_elements.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
+

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template<typename T >
int stan::math::num_elements (const T &x)
 Returns 1, the number of elements in a primitive type. More...
 
template<typename T , int R, int C>
int stan::math::num_elements (const Eigen::Matrix< T, R, C > &m)
 Returns the size of the specified matrix. More...
 
template<typename T >
int stan::math::num_elements (const std::vector< T > &v)
 Returns the number of elements in the specified vector. More...
 
+
+
+
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diff --git a/doc/api/html/num__elements_8hpp_source.html b/doc/api/html/num__elements_8hpp_source.html new file mode 100644 index 00000000000..4afdf13ceee --- /dev/null +++ b/doc/api/html/num__elements_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/num_elements.hpp Source File + + + + + + + + + + +
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+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+ + + + + + +
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+
num_elements.hpp
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+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_NUM_ELEMENTS_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_NUM_ELEMENTS_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
17  template <typename T>
+
18  inline int
+
19  num_elements(const T& x) {
+
20  return 1;
+
21  }
+
22 
+
29  template <typename T, int R, int C>
+
30  inline int
+
31  num_elements(const Eigen::Matrix<T, R, C>& m) {
+
32  return m.size();
+
33  }
+
34 
+
43  template <typename T>
+
44  inline int
+
45  num_elements(const std::vector<T>& v) {
+
46  if (v.size() == 0)
+
47  return 0;
+
48  return v.size() * num_elements(v[0]);
+
49  }
+
50 
+
51  }
+
52 }
+
53 #endif
+ + +
int num_elements(const T &x)
Returns 1, the number of elements in a primitive type.
+
+
+
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diff --git a/doc/api/html/ode__system_8hpp.html b/doc/api/html/ode__system_8hpp.html new file mode 100644 index 00000000000..fdcf3217246 --- /dev/null +++ b/doc/api/html/ode__system_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/ode_system.hpp File Reference + + + + + + + + + + +
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ode_system.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/arr/fun/value_of.hpp>
+#include <iostream>
+#include <vector>
+
+

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+Classes

class  stan::math::ode_system< F >
 Internal representation of an ODE model object which provides convenient Jacobian functions to obtain gradients wrt to states and parameters. More...
 
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+Namespaces

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+
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diff --git a/doc/api/html/ode__system_8hpp_source.html b/doc/api/html/ode__system_8hpp_source.html new file mode 100644 index 00000000000..ec8e2562b80 --- /dev/null +++ b/doc/api/html/ode__system_8hpp_source.html @@ -0,0 +1,221 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/ode_system.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + + + + + +
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+ + +
+ +
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+
+
ode_system.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUNCTOR_ODE_SYSTEM_HPP
+
2 #define STAN_MATH_REV_MAT_FUNCTOR_ODE_SYSTEM_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <iostream>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
20  template <typename F>
+
21  class ode_system {
+
22  const F& f_;
+
23  const std::vector<double> theta_;
+
24  const std::vector<double>& x_;
+
25  const std::vector<int>& x_int_;
+
26  std::ostream* msgs_;
+
27 
+
28  public:
+
39  ode_system(const F& f, const std::vector<double> theta,
+
40  const std::vector<double>& x, const std::vector<int>& x_int,
+
41  std::ostream* msgs)
+
42  : f_(f), theta_(theta), x_(x), x_int_(x_int), msgs_(msgs) { }
+
43 
+
51  inline void operator()(const double t, const std::vector<double>& y,
+
52  std::vector<double>& dy_dt) const {
+
53  dy_dt = f_(t, y, theta_, x_, x_int_, msgs_);
+
54  }
+
55 
+
66  template <typename Derived1, typename Derived2>
+
67  void jacobian(const double t, const std::vector<double>& y,
+
68  Eigen::MatrixBase<Derived1>& dy_dt,
+
69  Eigen::MatrixBase<Derived2>& Jy) const {
+
70  using Eigen::Matrix;
+
71  using Eigen::Map;
+
72  using Eigen::RowVectorXd;
+
73  using stan::math::var;
+
74  using std::vector;
+
75  vector<double> grad(y.size());
+
76  Map<RowVectorXd> grad_eig(&grad[0], y.size());
+
77  try {
+
78  start_nested();
+
79  vector<var> y_var(y.begin(), y.end());
+
80  vector<var> dy_dt_var = f_(t, y_var, theta_, x_, x_int_, msgs_);
+
81  for (size_t i = 0; i < dy_dt_var.size(); ++i) {
+
82  dy_dt(i) = dy_dt_var[i].val();
+ +
84  dy_dt_var[i].grad(y_var, grad);
+
85  Jy.row(i) = grad_eig;
+
86  }
+
87  } catch (const std::exception& e) {
+ +
89  throw;
+
90  }
+ +
92  }
+
93 
+
106  template <typename Derived1, typename Derived2>
+
107  void jacobian(const double t, const std::vector<double>& y,
+
108  Eigen::MatrixBase<Derived1>& dy_dt,
+
109  Eigen::MatrixBase<Derived2>& Jy,
+
110  Eigen::MatrixBase<Derived2>& Jtheta) const {
+
111  using Eigen::Dynamic;
+
112  using Eigen::Map;
+
113  using Eigen::Matrix;
+
114  using Eigen::RowVectorXd;
+
115  using stan::math::var;
+
116  using std::vector;
+
117  vector<double> grad(y.size() + theta_.size());
+
118  Map<RowVectorXd> grad_eig(&grad[0], y.size() + theta_.size());
+
119  try {
+
120  start_nested();
+
121  vector<var> y_var(y.begin(), y.end());
+
122  vector<var> theta_var(theta_.begin(), theta_.end());
+
123  vector<var> z_var;
+
124  z_var.reserve(y.size() + theta_.size());
+
125  z_var.insert(z_var.end(), y_var.begin(), y_var.end());
+
126  z_var.insert(z_var.end(), theta_var.begin(), theta_var.end());
+
127  vector<var> dy_dt_var = f_(t, y_var, theta_var, x_, x_int_, msgs_);
+
128  for (size_t i = 0; i < dy_dt_var.size(); ++i) {
+
129  dy_dt(i) = dy_dt_var[i].val();
+ +
131  dy_dt_var[i].grad(z_var, grad);
+
132  Jy.row(i) = grad_eig.leftCols(y.size());
+
133  Jtheta.row(i) = grad_eig.rightCols(theta_.size());
+
134  }
+
135  } catch (const std::exception& e) {
+ +
137  throw;
+
138  }
+ +
140  }
+
141  };
+
142 
+
143  }
+
144 }
+
145 #endif
+ +
void operator()(const double t, const std::vector< double > &y, std::vector< double > &dy_dt) const
Calculate the RHS of the ODE.
Definition: ode_system.hpp:51
+ + +
static void set_zero_all_adjoints_nested()
Reset all adjoint values in the top nested portion of the stack to zero.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
void jacobian(const double t, const std::vector< double > &y, Eigen::MatrixBase< Derived1 > &dy_dt, Eigen::MatrixBase< Derived2 > &Jy) const
Calculate the Jacobian of the ODE RHS wrt to states y.
Definition: ode_system.hpp:67
+
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+
ode_system(const F &f, const std::vector< double > theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
Construct an ODE model with the specified base ODE system, parameters, data, and a message stream...
Definition: ode_system.hpp:39
+
void jacobian(const double t, const std::vector< double > &y, Eigen::MatrixBase< Derived1 > &dy_dt, Eigen::MatrixBase< Derived2 > &Jy, Eigen::MatrixBase< Derived2 > &Jtheta) const
Calculate the Jacobian of the ODE RHS wrt to states y and parameters theta.
Definition: ode_system.hpp:107
+
Internal representation of an ODE model object which provides convenient Jacobian functions to obtain...
Definition: ode_system.hpp:21
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
+
+
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diff --git a/doc/api/html/open.png b/doc/api/html/open.png new file mode 100644 index 0000000000000000000000000000000000000000..30f75c7efe2dd0c9e956e35b69777a02751f048b GIT binary patch literal 123 zcmeAS@N?(olHy`uVBq!ia0vp^oFL4>1|%O$WD@{VPM$7~Ar*{o?;hlAFyLXmaDC0y znK1_#cQqJWPES%4Uujug^TE?jMft$}Eq^WaR~)%f)vSNs&gek&x%A9X9sM + + + + + +Stan Math Library: stan/math/rev/core/operator_divide_equal.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/operator__divide__equal_8hpp_source.html b/doc/api/html/operator__divide__equal_8hpp_source.html new file mode 100644 index 00000000000..cff9e481b2d --- /dev/null +++ b/doc/api/html/operator__divide__equal_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_divide_equal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_DIVIDE_EQUAL_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_DIVIDE_EQUAL_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  inline var& var::operator/=(const var& b) {
+
11  vi_ = new divide_vv_vari(vi_, b.vi_);
+
12  return *this;
+
13  }
+
14 
+
15  inline var& var::operator/=(const double b) {
+
16  if (b == 1.0)
+
17  return *this;
+
18  vi_ = new divide_vd_vari(vi_, b);
+
19  return *this;
+
20  }
+
21 
+
22  }
+
23 }
+
24 #endif
+ +
var & operator/=(const var &b)
The compound divide/assignment operator for variables (C++).
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
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diff --git a/doc/api/html/operator__minus__equal_8hpp.html b/doc/api/html/operator__minus__equal_8hpp.html new file mode 100644 index 00000000000..37952e7b5ad --- /dev/null +++ b/doc/api/html/operator__minus__equal_8hpp.html @@ -0,0 +1,124 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_minus_equal.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/operator__minus__equal_8hpp_source.html b/doc/api/html/operator__minus__equal_8hpp_source.html new file mode 100644 index 00000000000..ef16ce312e9 --- /dev/null +++ b/doc/api/html/operator__minus__equal_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_minus_equal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_MINUS_EQUAL_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_MINUS_EQUAL_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  inline var& var::operator-=(const var& b) {
+
11  vi_ = new subtract_vv_vari(vi_, b.vi_);
+
12  return *this;
+
13  }
+
14 
+
15  inline var& var::operator-=(const double b) {
+
16  if (b == 0.0)
+
17  return *this;
+
18  vi_ = new subtract_vd_vari(vi_, b);
+
19  return *this;
+
20  }
+
21 
+
22  }
+
23 }
+
24 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
var & operator-=(const var &b)
The compound subtract/assignment operator for variables (C++).
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
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diff --git a/doc/api/html/operator__multiply__equal_8hpp.html b/doc/api/html/operator__multiply__equal_8hpp.html new file mode 100644 index 00000000000..9cca715a4e9 --- /dev/null +++ b/doc/api/html/operator__multiply__equal_8hpp.html @@ -0,0 +1,124 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_multiply_equal.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/operator__multiply__equal_8hpp_source.html b/doc/api/html/operator__multiply__equal_8hpp_source.html new file mode 100644 index 00000000000..668c1117ddd --- /dev/null +++ b/doc/api/html/operator__multiply__equal_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_multiply_equal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_MULTIPLY_EQUAL_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_MULTIPLY_EQUAL_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  inline var& var::operator*=(const var& b) {
+
11  vi_ = new multiply_vv_vari(vi_, b.vi_);
+
12  return *this;
+
13  }
+
14 
+
15  inline var& var::operator*=(const double b) {
+
16  if (b == 1.0)
+
17  return *this;
+
18  vi_ = new multiply_vd_vari(vi_, b);
+
19  return *this;
+
20  }
+
21 
+
22  }
+
23 }
+
24 #endif
+
var & operator*=(const var &b)
The compound multiply/assignment operator for variables (C++).
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
+
+
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diff --git a/doc/api/html/operator__plus__equal_8hpp.html b/doc/api/html/operator__plus__equal_8hpp.html new file mode 100644 index 00000000000..d280931df0d --- /dev/null +++ b/doc/api/html/operator__plus__equal_8hpp.html @@ -0,0 +1,124 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_plus_equal.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/operator__plus__equal_8hpp_source.html b/doc/api/html/operator__plus__equal_8hpp_source.html new file mode 100644 index 00000000000..0c8ce91065f --- /dev/null +++ b/doc/api/html/operator__plus__equal_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_plus_equal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_PLUS_EQUAL_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_PLUS_EQUAL_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  inline var& var::operator+=(const var& b) {
+
11  vi_ = new add_vv_vari(vi_, b.vi_);
+
12  return *this;
+
13  }
+
14 
+
15  inline var& var::operator+=(const double b) {
+
16  if (b == 0.0)
+
17  return *this;
+
18  vi_ = new add_vd_vari(vi_, b);
+
19  return *this;
+
20  }
+
21 
+
22  }
+
23 }
+
24 #endif
+
var & operator+=(const var &b)
The compound add/assignment operator for variables (C++).
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
+
+
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diff --git a/doc/api/html/operator__unary__decrement_8hpp.html b/doc/api/html/operator__unary__decrement_8hpp.html new file mode 100644 index 00000000000..f86b326ddbf --- /dev/null +++ b/doc/api/html/operator__unary__decrement_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_decrement.hpp File Reference + + + + + + + + + + +
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#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/v_vari.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
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var & stan::math::operator-- (var &a)
 Prefix decrement operator for variables (C++). More...
 
var stan::math::operator-- (var &a, int)
 Postfix decrement operator for variables (C++). More...
 
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diff --git a/doc/api/html/operator__unary__decrement_8hpp_source.html b/doc/api/html/operator__unary__decrement_8hpp_source.html new file mode 100644 index 00000000000..64eb5399924 --- /dev/null +++ b/doc/api/html/operator__unary__decrement_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_decrement.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_UNARY_DECREMENT_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_UNARY_DECREMENT_HPP
+
3 
+ + +
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <limits>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class decrement_vari : public op_v_vari {
+
14  public:
+
15  explicit decrement_vari(vari* avi) :
+
16  op_v_vari(avi->val_ - 1.0, avi) {
+
17  }
+
18  void chain() {
+
19  if (unlikely(boost::math::isnan(avi_->val_)))
+
20  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
21  else
+
22  avi_->adj_ += adj_;
+
23  }
+
24  };
+
25  }
+
26 
+
40  inline var& operator--(var& a) {
+
41  a.vi_ = new decrement_vari(a.vi_);
+
42  return a;
+
43  }
+
44 
+
56  inline var operator--(var& a, int /*dummy*/) {
+
57  var temp(a);
+
58  a.vi_ = new decrement_vari(a.vi_);
+
59  return temp;
+
60  }
+
61 
+
62  }
+
63 }
+
64 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
var & operator--(var &a)
Prefix decrement operator for variables (C++).
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
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diff --git a/doc/api/html/operator__unary__increment_8hpp.html b/doc/api/html/operator__unary__increment_8hpp.html new file mode 100644 index 00000000000..a4d9cc9c838 --- /dev/null +++ b/doc/api/html/operator__unary__increment_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_increment.hpp File Reference + + + + + + + + + + +
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+
#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/v_vari.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
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var & stan::math::operator++ (var &a)
 Prefix increment operator for variables (C++). More...
 
var stan::math::operator++ (var &a, int)
 Postfix increment operator for variables (C++). More...
 
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diff --git a/doc/api/html/operator__unary__increment_8hpp_source.html b/doc/api/html/operator__unary__increment_8hpp_source.html new file mode 100644 index 00000000000..a36593f8311 --- /dev/null +++ b/doc/api/html/operator__unary__increment_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_increment.hpp Source File + + + + + + + + + + +
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operator_unary_increment.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_UNARY_INCREMENT_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_UNARY_INCREMENT_HPP
+
3 
+ + +
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <limits>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class increment_vari : public op_v_vari {
+
14  public:
+
15  explicit increment_vari(vari* avi) :
+
16  op_v_vari(avi->val_ + 1.0, avi) {
+
17  }
+
18  void chain() {
+
19  if (unlikely(boost::math::isnan(avi_->val_)))
+
20  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
21  else
+
22  avi_->adj_ += adj_;
+
23  }
+
24  };
+
25  }
+
26 
+
36  inline var& operator++(var& a) {
+
37  a.vi_ = new increment_vari(a.vi_);
+
38  return a;
+
39  }
+
40 
+
52  inline var operator++(var& a, int /*dummy*/) {
+
53  var temp(a);
+
54  a.vi_ = new increment_vari(a.vi_);
+
55  return temp;
+
56  }
+
57 
+
58  }
+
59 }
+
60 #endif
+
var & operator++(var &a)
Prefix increment operator for variables (C++).
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/operator__unary__minus_8hpp.html b/doc/api/html/operator__unary__minus_8hpp.html new file mode 100644 index 00000000000..68fedf64d7b --- /dev/null +++ b/doc/api/html/operator__unary__minus_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_unary_minus.hpp File Reference + + + + + + + + + + +
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template<typename T >
fvar< T > stan::math::operator- (const fvar< T > &x)
 
+
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diff --git a/doc/api/html/operator__unary__minus_8hpp_source.html b/doc/api/html/operator__unary__minus_8hpp_source.html new file mode 100644 index 00000000000..b54eda68c54 --- /dev/null +++ b/doc/api/html/operator__unary__minus_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/fwd/core/operator_unary_minus.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_FWD_CORE_OPERATOR_UNARY_MINUS_HPP
+
2 #define STAN_MATH_FWD_CORE_OPERATOR_UNARY_MINUS_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline
+
13  fvar<T>
+
14  operator-(const fvar<T>& x) {
+
15  return fvar<T>(-x.val_, -x.d_);
+
16  }
+
17  }
+
18 }
+
19 #endif
+
fvar< T > operator-(const fvar< T > &x1, const fvar< T > &x2)
+ + + + + +
+
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diff --git a/doc/api/html/operator__unary__negative_8hpp.html b/doc/api/html/operator__unary__negative_8hpp.html new file mode 100644 index 00000000000..ef3220f3f81 --- /dev/null +++ b/doc/api/html/operator__unary__negative_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_negative.hpp File Reference + + + + + + + + + + +
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operator_unary_negative.hpp File Reference
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+
#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/v_vari.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
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var stan::math::operator- (const var &a)
 Unary negation operator for variables (C++). More...
 
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diff --git a/doc/api/html/operator__unary__negative_8hpp_source.html b/doc/api/html/operator__unary__negative_8hpp_source.html new file mode 100644 index 00000000000..40565bc9937 --- /dev/null +++ b/doc/api/html/operator__unary__negative_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_negative.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_UNARY_NEGATIVE_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_UNARY_NEGATIVE_HPP
+
3 
+ + +
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <limits>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class neg_vari : public op_v_vari {
+
14  public:
+
15  explicit neg_vari(vari* avi) :
+
16  op_v_vari(-(avi->val_), avi) {
+
17  }
+
18  void chain() {
+
19  if (unlikely(boost::math::isnan(avi_->val_)))
+
20  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
21  else
+
22  avi_->adj_ -= adj_;
+
23  }
+
24  };
+
25  }
+
26 
+
51  inline var operator-(const var& a) {
+
52  return var(new neg_vari(a.vi_));
+
53  }
+
54 
+
55  }
+
56 }
+
57 #endif
+
fvar< T > operator-(const fvar< T > &x1, const fvar< T > &x2)
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/operator__unary__not_8hpp.html b/doc/api/html/operator__unary__not_8hpp.html new file mode 100644 index 00000000000..686bc4be4fa --- /dev/null +++ b/doc/api/html/operator__unary__not_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_not.hpp File Reference + + + + + + + + + + +
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bool stan::math::operator! (const var &a)
 Prefix logical negation for the value of variables (C++). More...
 
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diff --git a/doc/api/html/operator__unary__not_8hpp_source.html b/doc/api/html/operator__unary__not_8hpp_source.html new file mode 100644 index 00000000000..8133075d874 --- /dev/null +++ b/doc/api/html/operator__unary__not_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_not.hpp Source File + + + + + + + + + + +
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operator_unary_not.hpp
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_UNARY_NOT_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_UNARY_NOT_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
31  inline bool operator!(const var& a) {
+
32  return !a.val();
+
33  }
+
34 
+
35  }
+
36 }
+
37 #endif
+
bool operator!(const var &a)
Prefix logical negation for the value of variables (C++).
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
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diff --git a/doc/api/html/operator__unary__plus_8hpp.html b/doc/api/html/operator__unary__plus_8hpp.html new file mode 100644 index 00000000000..091d34594e9 --- /dev/null +++ b/doc/api/html/operator__unary__plus_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_plus.hpp File Reference + + + + + + + + + + +
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operator_unary_plus.hpp File Reference
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#include <stan/math/rev/core/var.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/rev/core/precomp_v_vari.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+
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var stan::math::operator+ (const var &a)
 Unary plus operator for variables (C++). More...
 
+
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+
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diff --git a/doc/api/html/operator__unary__plus_8hpp_source.html b/doc/api/html/operator__unary__plus_8hpp_source.html new file mode 100644 index 00000000000..d9fa6f92f14 --- /dev/null +++ b/doc/api/html/operator__unary__plus_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_unary_plus.hpp Source File + + + + + + + + + + +
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operator_unary_plus.hpp
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_UNARY_PLUS_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_UNARY_PLUS_HPP
+
3 
+ +
5 #include <boost/math/special_functions/fpclassify.hpp>
+ + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
43  inline var operator+(const var& a) {
+ + +
46  a.vi_,
+ +
48  return a;
+
49  }
+
50 
+
51  }
+
52 }
+
53 #endif
+ +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > operator+(const fvar< T > &x1, const fvar< T > &x2)
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/ordered__constrain_8hpp.html b/doc/api/html/ordered__constrain_8hpp.html new file mode 100644 index 00000000000..896b48d84e6 --- /dev/null +++ b/doc/api/html/ordered__constrain_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/ordered_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 Return an increasing ordered vector derived from the specified free vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &lp)
 Return a positive valued, increasing ordered vector derived from the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
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diff --git a/doc/api/html/ordered__constrain_8hpp_source.html b/doc/api/html/ordered__constrain_8hpp_source.html new file mode 100644 index 00000000000..f35b895b57d --- /dev/null +++ b/doc/api/html/ordered__constrain_8hpp_source.html @@ -0,0 +1,167 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/ordered_constrain.hpp Source File + + + + + + + + + + +
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ordered_constrain.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_ORDERED_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ORDERED_CONSTRAIN_HPP
+
3 
+ + +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
21  template <typename T>
+
22  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
23  ordered_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x) {
+
24  using Eigen::Matrix;
+
25  using Eigen::Dynamic;
+ +
27  using std::exp;
+
28 
+
29  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
30 
+
31  size_type k = x.size();
+
32  Matrix<T, Dynamic, 1> y(k);
+
33  if (k == 0)
+
34  return y;
+
35  y[0] = x[0];
+
36  for (size_type i = 1; i < k; ++i)
+
37  y[i] = y[i-1] + exp(x[i]);
+
38  return y;
+
39  }
+
40 
+
53  template <typename T>
+
54  inline
+
55  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
56  ordered_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x, T& lp) {
+
57  using Eigen::Matrix;
+
58  using Eigen::Dynamic;
+ +
60 
+
61  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
62 
+
63  for (size_type i = 1; i < x.size(); ++i)
+
64  lp += x(i);
+
65  return ordered_constrain(x);
+
66  }
+
67 
+
68  }
+
69 
+
70 }
+
71 
+
72 #endif
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > ordered_constrain(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
Return an increasing ordered vector derived from the specified free vector.
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
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diff --git a/doc/api/html/ordered__free_8hpp.html b/doc/api/html/ordered__free_8hpp.html new file mode 100644 index 00000000000..8ebf2043fa6 --- /dev/null +++ b/doc/api/html/ordered__free_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/ordered_free.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::ordered_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
 Return the vector of unconstrained scalars that transform to the specified positive ordered vector. More...
 
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diff --git a/doc/api/html/ordered__free_8hpp_source.html b/doc/api/html/ordered__free_8hpp_source.html new file mode 100644 index 00000000000..82a76332fe3 --- /dev/null +++ b/doc/api/html/ordered__free_8hpp_source.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/ordered_free.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_ORDERED_FREE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ORDERED_FREE_HPP
+
3 
+ + + +
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
24  template <typename T>
+
25  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
26  ordered_free(const Eigen::Matrix<T, Eigen::Dynamic, 1>& y) {
+
27  stan::math::check_ordered("stan::math::ordered_free",
+
28  "Ordered variable", y);
+
29  using Eigen::Matrix;
+
30  using Eigen::Dynamic;
+ +
32  using std::log;
+
33  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
34 
+
35  size_type k = y.size();
+
36  Matrix<T, Dynamic, 1> x(k);
+
37  if (k == 0)
+
38  return x;
+
39  x[0] = y[0];
+
40  for (size_type i = 1; i < k; ++i)
+
41  x[i] = log(y[i] - y[i-1]);
+
42  return x;
+
43  }
+
44  }
+
45 }
+
46 #endif
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > ordered_free(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
Return the vector of unconstrained scalars that transform to the specified positive ordered vector...
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
bool check_ordered(const char *function, const char *name, const std::vector< T_y > &y)
Return true if the specified vector is sorted into strictly increasing order.
+ + +
+
+
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diff --git a/doc/api/html/ordered__logistic__log_8hpp.html b/doc/api/html/ordered__logistic__log_8hpp.html new file mode 100644 index 00000000000..d0dff317257 --- /dev/null +++ b/doc/api/html/ordered__logistic__log_8hpp.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/ordered_logistic_log.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::log_inv_logit_diff (const T &alpha, const T &beta)
 
template<bool propto, typename T_lambda , typename T_cut >
boost::math::tools::promote_args< T_lambda, T_cut >::type stan::math::ordered_logistic_log (int y, const T_lambda &lambda, const Eigen::Matrix< T_cut, Eigen::Dynamic, 1 > &c)
 Returns the (natural) log probability of the specified integer outcome given the continuous location and specified cutpoints in an ordered logistic model. More...
 
template<typename T_lambda , typename T_cut >
boost::math::tools::promote_args< T_lambda, T_cut >::type stan::math::ordered_logistic_log (int y, const T_lambda &lambda, const Eigen::Matrix< T_cut, Eigen::Dynamic, 1 > &c)
 
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diff --git a/doc/api/html/ordered__logistic__log_8hpp_source.html b/doc/api/html/ordered__logistic__log_8hpp_source.html new file mode 100644 index 00000000000..185efd52b66 --- /dev/null +++ b/doc/api/html/ordered__logistic__log_8hpp_source.html @@ -0,0 +1,229 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/ordered_logistic_log.hpp Source File + + + + + + + + + + +
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ordered_logistic_log.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_ORDERED_LOGISTIC_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_ORDERED_LOGISTIC_LOG_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <typename T>
+
26  inline T log_inv_logit_diff(const T& alpha, const T& beta) {
+
27  using std::exp;
+ + +
30  return beta + log1m_exp(alpha - beta) - log1p_exp(alpha)
+
31  - log1p_exp(beta);
+
32  }
+
33 
+
34  // y in 0, ..., K-1; c.size()==K-2, c increasing, lambda finite
+
59  template <bool propto, typename T_lambda, typename T_cut>
+
60  typename boost::math::tools::promote_args<T_lambda, T_cut>::type
+
61  ordered_logistic_log(int y, const T_lambda& lambda,
+
62  const Eigen::Matrix<T_cut, Eigen::Dynamic, 1>& c) {
+
63  using std::exp;
+
64  using std::log;
+ +
66  using stan::math::log1m;
+ +
68 
+
69  static const char* function("stan::math::ordered_logistic");
+
70 
+ + + + + + + +
78 
+
79  int K = c.size() + 1;
+
80 
+
81  check_bounded(function, "Random variable", y, 1, K);
+
82  check_finite(function, "Location parameter", lambda);
+
83  check_greater(function, "Size of cut points parameter", c.size(), 0);
+
84  for (int i = 1; i < c.size(); ++i)
+
85  check_greater(function, "Cut points parameter", c(i), c(i - 1));
+
86 
+
87  check_finite(function, "Cut points parameter", c(c.size()-1));
+
88  check_finite(function, "Cut points parameter", c(0));
+
89 
+
90  // log(1 - inv_logit(lambda))
+
91  if (y == 1)
+
92  return -log1p_exp(lambda - c(0));
+
93 
+
94  // log(inv_logit(lambda - c(K-3)));
+
95  if (y == K) {
+
96  return -log1p_exp(c(K-2) - lambda);
+
97  }
+
98 
+
99  // if (2 < y < K) { ... }
+
100  // log(inv_logit(lambda - c(y-2)) - inv_logit(lambda - c(y-1)))
+
101  return log_inv_logit_diff(c(y-2) - lambda,
+
102  c(y-1) - lambda);
+
103  }
+
104 
+
105  template <typename T_lambda, typename T_cut>
+
106  typename boost::math::tools::promote_args<T_lambda, T_cut>::type
+
107  ordered_logistic_log(int y, const T_lambda& lambda,
+
108  const Eigen::Matrix<T_cut, Eigen::Dynamic, 1>& c) {
+
109  return ordered_logistic_log<false>(y, lambda, c);
+
110  }
+
111  }
+
112 }
+
113 
+
114 #endif
+
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
T log_inv_logit_diff(const T &alpha, const T &beta)
+ + + + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > log1m_exp(const fvar< T > &x)
Definition: log1m_exp.hpp:16
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
fvar< T > log1p_exp(const fvar< T > &x)
Definition: log1p_exp.hpp:13
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
boost::math::tools::promote_args< T_lambda, T_cut >::type ordered_logistic_log(int y, const T_lambda &lambda, const Eigen::Matrix< T_cut, Eigen::Dynamic, 1 > &c)
Returns the (natural) log probability of the specified integer outcome given the continuous location ...
+
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
+
+
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diff --git a/doc/api/html/ordered__logistic__rng_8hpp.html b/doc/api/html/ordered__logistic__rng_8hpp.html new file mode 100644 index 00000000000..2803047add2 --- /dev/null +++ b/doc/api/html/ordered__logistic__rng_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/ordered_logistic_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
int stan::math::ordered_logistic_rng (const double eta, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &c, RNG &rng)
 
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diff --git a/doc/api/html/ordered__logistic__rng_8hpp_source.html b/doc/api/html/ordered__logistic__rng_8hpp_source.html new file mode 100644 index 00000000000..56efbcca62f --- /dev/null +++ b/doc/api/html/ordered__logistic__rng_8hpp_source.html @@ -0,0 +1,190 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/ordered_logistic_rng.hpp Source File + + + + + + + + + + +
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ordered_logistic_rng.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_ORDERED_LOGISTIC_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_ORDERED_LOGISTIC_RNG_HPP
+
3 
+
4 #include <boost/random/uniform_01.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + +
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  template <class RNG>
+
23  inline int
+
24  ordered_logistic_rng(const double eta,
+
25  const Eigen::Matrix<double, Eigen::Dynamic, 1>& c,
+
26  RNG& rng) {
+
27  using boost::variate_generator;
+ +
29 
+
30  static const char* function("stan::math::ordered_logistic");
+
31 
+ + + + + + + +
39 
+
40  check_finite(function, "Location parameter", eta);
+
41  check_greater(function, "Size of cut points parameter", c.size(), 0);
+
42  for (int i = 1; i < c.size(); ++i) {
+
43  check_greater(function, "Cut points parameter", c(i), c(i - 1));
+
44  }
+
45  check_finite(function, "Cut points parameter", c(c.size()-1));
+
46  check_finite(function, "Cut points parameter", c(0));
+
47 
+
48  Eigen::VectorXd cut(c.rows()+1);
+
49  cut(0) = 1 - inv_logit(eta - c(0));
+
50  for (int j = 1; j < c.rows(); j++)
+
51  cut(j) = inv_logit(eta - c(j - 1)) - inv_logit(eta - c(j));
+
52  cut(c.rows()) = inv_logit(eta - c(c.rows() - 1));
+
53 
+
54  return stan::math::categorical_rng(cut, rng);
+
55  }
+
56  }
+
57 }
+
58 
+
59 #endif
+
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+ + +
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+ + +
int categorical_rng(const Eigen::Matrix< double, Eigen::Dynamic, 1 > &theta, RNG &rng)
+ +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
int ordered_logistic_rng(const double eta, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &c, RNG &rng)
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
+
+
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diff --git a/doc/api/html/out__of__range_8hpp.html b/doc/api/html/out__of__range_8hpp.html new file mode 100644 index 00000000000..771ea1ac35e --- /dev/null +++ b/doc/api/html/out__of__range_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/out_of_range.hpp File Reference + + + + + + + + + + +
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+
#include <stan/math/prim/scal/meta/error_index.hpp>
+#include <typeinfo>
+#include <string>
+#include <sstream>
+#include <stdexcept>
+
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void stan::math::out_of_range (const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
 Throw an out_of_range exception with a consistently formatted message. More...
 
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diff --git a/doc/api/html/out__of__range_8hpp_source.html b/doc/api/html/out__of__range_8hpp_source.html new file mode 100644 index 00000000000..925dd9ad336 --- /dev/null +++ b/doc/api/html/out__of__range_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/err/out_of_range.hpp Source File + + + + + + + + + + +
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out_of_range.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_ERR_OUT_OF_RANGE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_ERR_OUT_OF_RANGE_HPP
+
3 
+ +
5 #include <typeinfo>
+
6 #include <string>
+
7 #include <sstream>
+
8 #include <stdexcept>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
30  inline void out_of_range(const char* function,
+
31  const int max,
+
32  const int index,
+
33  const char* msg1 = "",
+
34  const char* msg2 = "") {
+
35  std::ostringstream message;
+
36 
+
37  message << function << ": accessing element out of range. "
+
38  << "index " << index << " out of range; "
+
39  << "expecting index to be between "
+
40  << stan::error_index::value << " and "
+
41  << stan::error_index::value - 1 + max
+
42  << msg1
+
43  << msg2;
+
44 
+
45  throw std::out_of_range(message.str());
+
46  }
+
47 
+
48  }
+
49 }
+
50 #endif
+ + +
void out_of_range(const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
Throw an out_of_range exception with a consistently formatted message.
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ +
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diff --git a/doc/api/html/pareto__ccdf__log_8hpp.html b/doc/api/html/pareto__ccdf__log_8hpp.html new file mode 100644 index 00000000000..a5ac478227e --- /dev/null +++ b/doc/api/html/pareto__ccdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type stan::math::pareto_ccdf_log (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
+
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diff --git a/doc/api/html/pareto__ccdf__log_8hpp_source.html b/doc/api/html/pareto__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..e789d8785ba --- /dev/null +++ b/doc/api/html/pareto__ccdf__log_8hpp_source.html @@ -0,0 +1,245 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_ccdf_log.hpp Source File + + + + + + + + + + +
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pareto_ccdf_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/exponential_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 #include <limits>
+
19 
+
20 namespace stan {
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_scale, typename T_shape>
+
24  typename return_type<T_y, T_scale, T_shape>::type
+
25  pareto_ccdf_log(const T_y& y, const T_scale& y_min,
+
26  const T_shape& alpha) {
+ +
28  T_partials_return;
+
29 
+
30  // Size checks
+
31  if ( !( stan::length(y) && stan::length(y_min) && stan::length(alpha) ) )
+
32  return 0.0;
+
33 
+
34  // Check errors
+
35  static const char* function("stan::math::pareto_ccdf_log");
+
36 
+ + + + + + +
43  using std::log;
+
44  using std::exp;
+
45 
+
46  T_partials_return P(0.0);
+
47 
+
48  check_not_nan(function, "Random variable", y);
+
49  check_nonnegative(function, "Random variable", y);
+
50  check_positive_finite(function, "Scale parameter", y_min);
+
51  check_positive_finite(function, "Shape parameter", alpha);
+
52  check_consistent_sizes(function,
+
53  "Random variable", y,
+
54  "Scale parameter", y_min,
+
55  "Shape parameter", alpha);
+
56 
+
57  // Wrap arguments in vectors
+
58  VectorView<const T_y> y_vec(y);
+
59  VectorView<const T_scale> y_min_vec(y_min);
+
60  VectorView<const T_shape> alpha_vec(alpha);
+
61  size_t N = max_size(y, y_min, alpha);
+
62 
+ +
64  operands_and_partials(y, y_min, alpha);
+
65 
+
66  // Explicit return for extreme values
+
67  // The gradients are technically ill-defined, but treated as zero
+
68 
+
69  for (size_t i = 0; i < stan::length(y); i++) {
+
70  if (value_of(y_vec[i]) < value_of(y_min_vec[i]))
+
71  return operands_and_partials.value(0.0);
+
72  }
+
73 
+
74  // Compute vectorized cdf_log and its gradients
+
75 
+
76  for (size_t n = 0; n < N; n++) {
+
77  // Explicit results for extreme values
+
78  // The gradients are technically ill-defined, but treated as zero
+
79  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
80  return operands_and_partials.value(stan::math::negative_infinity());
+
81  }
+
82 
+
83  // Pull out values
+
84  const T_partials_return log_dbl = log(value_of(y_min_vec[n])
+
85  / value_of(y_vec[n]));
+
86  const T_partials_return y_min_inv_dbl = 1.0 / value_of(y_min_vec[n]);
+
87  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
88 
+
89  P += alpha_dbl * log_dbl;
+
90 
+ +
92  operands_and_partials.d_x1[n] -= alpha_dbl * y_min_inv_dbl
+
93  * exp(log_dbl);
+ +
95  operands_and_partials.d_x2[n] += alpha_dbl * y_min_inv_dbl;
+ +
97  operands_and_partials.d_x3[n] += log_dbl;
+
98  }
+
99 
+
100  return operands_and_partials.value(P);
+
101  }
+
102  }
+
103 }
+
104 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
return_type< T_y, T_scale, T_shape >::type pareto_ccdf_log(const T_y &y, const T_scale &y_min, const T_shape &alpha)
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
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diff --git a/doc/api/html/pareto__cdf_8hpp.html b/doc/api/html/pareto__cdf_8hpp.html new file mode 100644 index 00000000000..0d0cc3f838c --- /dev/null +++ b/doc/api/html/pareto__cdf_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_cdf.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type stan::math::pareto_cdf (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
+
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diff --git a/doc/api/html/pareto__cdf_8hpp_source.html b/doc/api/html/pareto__cdf_8hpp_source.html new file mode 100644 index 00000000000..d2d15c0e553 --- /dev/null +++ b/doc/api/html/pareto__cdf_8hpp_source.html @@ -0,0 +1,264 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_cdf.hpp Source File + + + + + + + + + + +
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pareto_cdf.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_CDF_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/exponential_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 #include <limits>
+
19 
+
20 
+
21 namespace stan {
+
22  namespace math {
+
23 
+
24  template <typename T_y, typename T_scale, typename T_shape>
+
25  typename return_type<T_y, T_scale, T_shape>::type
+
26  pareto_cdf(const T_y& y, const T_scale& y_min, const T_shape& alpha) {
+ +
28  T_partials_return;
+
29 
+
30  // Check sizes
+
31  // Size checks
+
32  if ( !( stan::length(y) && stan::length(y_min) && stan::length(alpha) ) )
+
33  return 1.0;
+
34 
+
35  // Check errors
+
36  static const char* function("stan::math::pareto_cdf");
+
37 
+ + + + + + +
44  using std::log;
+
45  using std::exp;
+
46 
+
47  T_partials_return P(1.0);
+
48 
+
49  check_not_nan(function, "Random variable", y);
+
50  check_nonnegative(function, "Random variable", y);
+
51  check_positive_finite(function, "Scale parameter", y_min);
+
52  check_positive_finite(function, "Shape parameter", alpha);
+
53  check_consistent_sizes(function,
+
54  "Random variable", y,
+
55  "Scale parameter", y_min,
+
56  "Shape parameter", alpha);
+
57 
+
58  // Wrap arguments in vectors
+
59  VectorView<const T_y> y_vec(y);
+
60  VectorView<const T_scale> y_min_vec(y_min);
+
61  VectorView<const T_shape> alpha_vec(alpha);
+
62  size_t N = max_size(y, y_min, alpha);
+
63 
+ +
65  operands_and_partials(y, y_min, alpha);
+
66 
+
67  // Explicit return for extreme values
+
68  // The gradients are technically ill-defined, but treated as zero
+
69 
+
70  for (size_t i = 0; i < stan::length(y); i++) {
+
71  if (value_of(y_vec[i]) < value_of(y_min_vec[i]))
+
72  return operands_and_partials.value(0.0);
+
73  }
+
74 
+
75  // Compute vectorized CDF and its gradients
+
76 
+
77  for (size_t n = 0; n < N; n++) {
+
78  // Explicit results for extreme values
+
79  // The gradients are technically ill-defined, but treated as zero
+
80  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
81  continue;
+
82  }
+
83 
+
84  // Pull out values
+
85  const T_partials_return log_dbl = log(value_of(y_min_vec[n])
+
86  / value_of(y_vec[n]));
+
87  const T_partials_return y_min_inv_dbl = 1.0 / value_of(y_min_vec[n]);
+
88  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
89 
+
90  // Compute
+
91  const T_partials_return Pn = 1.0 - exp(alpha_dbl * log_dbl);
+
92 
+
93  P *= Pn;
+
94 
+ +
96  operands_and_partials.d_x1[n]
+
97  += alpha_dbl * y_min_inv_dbl * exp((alpha_dbl + 1) * log_dbl)
+
98  / Pn;
+ +
100  operands_and_partials.d_x2[n]
+
101  += - alpha_dbl * y_min_inv_dbl * exp(alpha_dbl * log_dbl) / Pn;
+ +
103  operands_and_partials.d_x3[n]
+
104  += - exp(alpha_dbl * log_dbl) * log_dbl / Pn;
+
105  }
+
106 
+ +
108  for (size_t n = 0; n < stan::length(y); ++n)
+
109  operands_and_partials.d_x1[n] *= P;
+
110  }
+ +
112  for (size_t n = 0; n < stan::length(y_min); ++n)
+
113  operands_and_partials.d_x2[n] *= P;
+
114  }
+ +
116  for (size_t n = 0; n < stan::length(alpha); ++n)
+
117  operands_and_partials.d_x3[n] *= P;
+
118  }
+
119 
+
120  return operands_and_partials.value(P);
+
121  }
+
122  }
+
123 }
+
124 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
return_type< T_y, T_scale, T_shape >::type pareto_cdf(const T_y &y, const T_scale &y_min, const T_shape &alpha)
Definition: pareto_cdf.hpp:26
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__cdf__log_8hpp.html b/doc/api/html/pareto__cdf__log_8hpp.html new file mode 100644 index 00000000000..ceb13e46429 --- /dev/null +++ b/doc/api/html/pareto__cdf__log_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
pareto_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type stan::math::pareto_cdf_log (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__cdf__log_8hpp_source.html b/doc/api/html/pareto__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..02fab31a2ae --- /dev/null +++ b/doc/api/html/pareto__cdf__log_8hpp_source.html @@ -0,0 +1,249 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
pareto_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/exponential_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 #include <limits>
+
19 
+
20 namespace stan {
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_scale, typename T_shape>
+
24  typename return_type<T_y, T_scale, T_shape>::type
+
25  pareto_cdf_log(const T_y& y, const T_scale& y_min, const T_shape& alpha) {
+ +
27  T_partials_return;
+
28 
+
29  // Size checks
+
30  if ( !( stan::length(y) && stan::length(y_min) && stan::length(alpha) ) )
+
31  return 0.0;
+
32 
+
33  // Check errors
+
34  static const char* function("stan::math::pareto_cdf_log");
+
35 
+ + + + + + +
42  using std::log;
+
43  using std::exp;
+
44 
+
45  T_partials_return P(0.0);
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_nonnegative(function, "Random variable", y);
+
49  check_positive_finite(function, "Scale parameter", y_min);
+
50  check_positive_finite(function, "Shape parameter", alpha);
+
51  check_consistent_sizes(function,
+
52  "Random variable", y,
+
53  "Scale parameter", y_min,
+
54  "Shape parameter", alpha);
+
55 
+
56  // Wrap arguments in vectors
+
57  VectorView<const T_y> y_vec(y);
+
58  VectorView<const T_scale> y_min_vec(y_min);
+
59  VectorView<const T_shape> alpha_vec(alpha);
+
60  size_t N = max_size(y, y_min, alpha);
+
61 
+ +
63  operands_and_partials(y, y_min, alpha);
+
64 
+
65  // Explicit return for extreme values
+
66  // The gradients are technically ill-defined, but treated as zero
+
67 
+
68  for (size_t i = 0; i < stan::length(y); i++) {
+
69  if (value_of(y_vec[i]) < value_of(y_min_vec[i]))
+
70  return operands_and_partials.value(stan::math::negative_infinity());
+
71  }
+
72 
+
73  // Compute vectorized cdf_log and its gradients
+
74 
+
75  for (size_t n = 0; n < N; n++) {
+
76  // Explicit results for extreme values
+
77  // The gradients are technically ill-defined, but treated as zero
+
78  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
79  return operands_and_partials.value(0.0);
+
80  }
+
81 
+
82  // Pull out values
+
83  const T_partials_return log_dbl = log(value_of(y_min_vec[n])
+
84  / value_of(y_vec[n]));
+
85  const T_partials_return y_min_inv_dbl = 1.0 / value_of(y_min_vec[n]);
+
86  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
87 
+
88  // Compute
+
89  const T_partials_return Pn = 1.0 - exp(alpha_dbl * log_dbl);
+
90 
+
91  P += log(Pn);
+
92 
+ +
94  operands_and_partials.d_x1[n]
+
95  += alpha_dbl * y_min_inv_dbl * exp((alpha_dbl + 1) * log_dbl) / Pn;
+ +
97  operands_and_partials.d_x2[n]
+
98  -= alpha_dbl * y_min_inv_dbl * exp(alpha_dbl * log_dbl) / Pn;
+ +
100  operands_and_partials.d_x3[n]
+
101  -= exp(alpha_dbl * log_dbl) * log_dbl / Pn;
+
102  }
+
103 
+
104  return operands_and_partials.value(P);
+
105  }
+
106  }
+
107 }
+
108 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
return_type< T_y, T_scale, T_shape >::type pareto_cdf_log(const T_y &y, const T_scale &y_min, const T_shape &alpha)
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__log_8hpp.html b/doc/api/html/pareto__log_8hpp.html new file mode 100644 index 00000000000..b8129550be4 --- /dev/null +++ b/doc/api/html/pareto__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
pareto_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type stan::math::pareto_log (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
template<typename T_y , typename T_scale , typename T_shape >
return_type< T_y, T_scale, T_shape >::type stan::math::pareto_log (const T_y &y, const T_scale &y_min, const T_shape &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__log_8hpp_source.html b/doc/api/html/pareto__log_8hpp_source.html new file mode 100644 index 00000000000..22c74221ad4 --- /dev/null +++ b/doc/api/html/pareto__log_8hpp_source.html @@ -0,0 +1,283 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
pareto_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/random/exponential_distribution.hpp>
+
19 #include <boost/random/variate_generator.hpp>
+
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23  namespace math {
+
24 
+
25  // Pareto(y|y_m, alpha) [y > y_m; y_m > 0; alpha > 0]
+
26  template <bool propto,
+
27  typename T_y, typename T_scale, typename T_shape>
+
28  typename return_type<T_y, T_scale, T_shape>::type
+
29  pareto_log(const T_y& y, const T_scale& y_min, const T_shape& alpha) {
+
30  static const char* function("stan::math::pareto_log");
+ +
32  T_partials_return;
+
33 
+ + + + +
38  using std::log;
+
39 
+
40  // check if any vectors are zero length
+
41  if (!(stan::length(y)
+
42  && stan::length(y_min)
+
43  && stan::length(alpha)))
+
44  return 0.0;
+
45 
+
46  // set up return value accumulator
+
47  T_partials_return logp(0.0);
+
48 
+
49  // validate args (here done over var, which should be OK)
+
50  check_not_nan(function, "Random variable", y);
+
51  check_positive_finite(function, "Scale parameter", y_min);
+
52  check_positive_finite(function, "Shape parameter", alpha);
+
53  check_consistent_sizes(function,
+
54  "Random variable", y,
+
55  "Scale parameter", y_min,
+
56  "Shape parameter", alpha);
+
57 
+
58  // check if no variables are involved and prop-to
+ +
60  return 0.0;
+
61 
+
62  VectorView<const T_y> y_vec(y);
+
63  VectorView<const T_scale> y_min_vec(y_min);
+
64  VectorView<const T_shape> alpha_vec(alpha);
+
65  size_t N = max_size(y, y_min, alpha);
+
66 
+
67  for (size_t n = 0; n < N; n++) {
+
68  if (y_vec[n] < y_min_vec[n])
+
69  return LOG_ZERO;
+
70  }
+
71 
+
72  // set up template expressions wrapping scalars into vector views
+ +
74  operands_and_partials(y, y_min, alpha);
+
75 
+ +
77  T_partials_return, T_y> log_y(length(y));
+ +
79  for (size_t n = 0; n < length(y); n++)
+
80  log_y[n] = log(value_of(y_vec[n]));
+
81  }
+
82 
+ +
84  T_partials_return, T_y> inv_y(length(y));
+ +
86  for (size_t n = 0; n < length(y); n++)
+
87  inv_y[n] = 1 / value_of(y_vec[n]);
+
88  }
+
89 
+ +
91  T_partials_return, T_scale>
+
92  log_y_min(length(y_min));
+ +
94  for (size_t n = 0; n < length(y_min); n++)
+
95  log_y_min[n] = log(value_of(y_min_vec[n]));
+
96  }
+
97 
+ +
99  T_partials_return, T_shape> log_alpha(length(alpha));
+ +
101  for (size_t n = 0; n < length(alpha); n++)
+
102  log_alpha[n] = log(value_of(alpha_vec[n]));
+
103  }
+
104 
+ +
106 
+
107  for (size_t n = 0; n < N; n++) {
+
108  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
109  // log probability
+ +
111  logp += log_alpha[n];
+ +
113  logp += alpha_dbl * log_y_min[n];
+ +
115  logp -= alpha_dbl * log_y[n] + log_y[n];
+
116 
+
117  // gradients
+ +
119  operands_and_partials.d_x1[n] -= alpha_dbl * inv_y[n] + inv_y[n];
+ +
121  operands_and_partials.d_x2[n] += alpha_dbl / value_of(y_min_vec[n]);
+ +
123  operands_and_partials.d_x3[n]
+
124  += 1 / alpha_dbl + log_y_min[n] - log_y[n];
+
125  }
+
126  return operands_and_partials.value(logp);
+
127  }
+
128 
+
129  template <typename T_y, typename T_scale, typename T_shape>
+
130  inline
+ +
132  pareto_log(const T_y& y, const T_scale& y_min, const T_shape& alpha) {
+
133  return pareto_log<false>(y, y_min, alpha);
+
134  }
+
135  }
+
136 }
+
137 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
return_type< T_y, T_scale, T_shape >::type pareto_log(const T_y &y, const T_scale &y_min, const T_shape &alpha)
Definition: pareto_log.hpp:29
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
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diff --git a/doc/api/html/pareto__rng_8hpp.html b/doc/api/html/pareto__rng_8hpp.html new file mode 100644 index 00000000000..6652cdb8c75 --- /dev/null +++ b/doc/api/html/pareto__rng_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::pareto_rng (const double y_min, const double alpha, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__rng_8hpp_source.html b/doc/api/html/pareto__rng_8hpp_source.html new file mode 100644 index 00000000000..dc3c54c2982 --- /dev/null +++ b/doc/api/html/pareto__rng_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_rng.hpp Source File + + + + + + + + + + +
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pareto_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_RNG_HPP
+
3 
+
4 #include <boost/random/exponential_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + +
14 
+
15 
+
16 namespace stan {
+
17  namespace math {
+
18 
+
19  template <class RNG>
+
20  inline double
+
21  pareto_rng(const double y_min,
+
22  const double alpha,
+
23  RNG& rng) {
+
24  using boost::variate_generator;
+
25  using boost::exponential_distribution;
+
26 
+
27  static const char* function("stan::math::pareto_rng");
+
28 
+ +
30 
+
31  check_positive_finite(function, "Scale parameter", y_min);
+
32  check_positive_finite(function, "Shape parameter", alpha);
+
33 
+
34  variate_generator<RNG&, exponential_distribution<> >
+
35  exp_rng(rng, exponential_distribution<>(alpha));
+
36  return y_min * std::exp(exp_rng());
+
37  }
+
38  }
+
39 }
+
40 #endif
+ + + +
double pareto_rng(const double y_min, const double alpha, RNG &rng)
Definition: pareto_rng.hpp:21
+ + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__type__2__ccdf__log_8hpp.html b/doc/api/html/pareto__type__2__ccdf__log_8hpp.html new file mode 100644 index 00000000000..2c7d3231338 --- /dev/null +++ b/doc/api/html/pareto__type__2__ccdf__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::pareto_type_2_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__type__2__ccdf__log_8hpp_source.html b/doc/api/html/pareto__type__2__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..bbc2e410311 --- /dev/null +++ b/doc/api/html/pareto__type__2__ccdf__log_8hpp_source.html @@ -0,0 +1,275 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_ccdf_log.hpp Source File + + + + + + + + + + +
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pareto_type_2_ccdf_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/random/variate_generator.hpp>
+
19 #include <cmath>
+
20 
+
21 namespace stan {
+
22  namespace math {
+
23 
+
24  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
25  typename return_type<T_y, T_loc, T_scale, T_shape>::type
+
26  pareto_type_2_ccdf_log(const T_y& y, const T_loc& mu,
+
27  const T_scale& lambda, const T_shape& alpha) {
+
28  typedef
+ +
30  T_partials_return;
+
31 
+
32  // Check sizes
+
33  // Size checks
+
34  if ( !( stan::length(y)
+
35  && stan::length(mu)
+
36  && stan::length(lambda)
+
37  && stan::length(alpha) ) )
+
38  return 0.0;
+
39 
+
40  // Check errors
+
41  static const char* function("stan::math::pareto_type_2_ccdf_log");
+
42 
+ + + + + + + +
50  using std::log;
+
51 
+
52  T_partials_return P(0.0);
+
53 
+
54  check_greater_or_equal(function, "Random variable", y, mu);
+
55  check_not_nan(function, "Random variable", y);
+
56  check_nonnegative(function, "Random variable", y);
+
57  check_positive_finite(function, "Scale parameter", lambda);
+
58  check_positive_finite(function, "Shape parameter", alpha);
+
59  check_consistent_sizes(function,
+
60  "Random variable", y,
+
61  "Scale parameter", lambda,
+
62  "Shape parameter", alpha);
+
63 
+
64  // Wrap arguments in vectors
+
65  VectorView<const T_y> y_vec(y);
+
66  VectorView<const T_loc> mu_vec(mu);
+
67  VectorView<const T_scale> lambda_vec(lambda);
+
68  VectorView<const T_shape> alpha_vec(alpha);
+
69  size_t N = max_size(y, mu, lambda, alpha);
+
70 
+ +
72  operands_and_partials(y, mu, lambda, alpha);
+
73 
+
74  VectorBuilder<true, T_partials_return,
+
75  T_y, T_loc, T_scale, T_shape>
+
76  ccdf_log(N);
+
77 
+
78  VectorBuilder<contains_nonconstant_struct<T_y, T_loc, T_scale,
+
79  T_shape>::value,
+
80  T_partials_return, T_y, T_loc, T_scale, T_shape>
+
81  a_over_lambda_plus_y(N);
+
82 
+ +
84  T_partials_return, T_y, T_loc, T_scale, T_shape>
+
85  log_1p_y_over_lambda(N);
+
86 
+
87  for (size_t i = 0; i < N; i++) {
+
88  const T_partials_return y_dbl = value_of(y_vec[i]);
+
89  const T_partials_return mu_dbl = value_of(mu_vec[i]);
+
90  const T_partials_return lambda_dbl = value_of(lambda_vec[i]);
+
91  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
92  const T_partials_return temp = 1.0 + (y_dbl - mu_dbl) / lambda_dbl;
+
93  const T_partials_return log_temp = log(temp);
+
94 
+
95  ccdf_log[i] = -alpha_dbl * log_temp;
+
96 
+ +
98  a_over_lambda_plus_y[i] = alpha_dbl / (y_dbl - mu_dbl + lambda_dbl);
+
99 
+ +
101  log_1p_y_over_lambda[i] = log_temp;
+
102  }
+
103 
+
104  // Compute vectorized CDF and its gradients
+
105 
+
106  for (size_t n = 0; n < N; n++) {
+
107  // Pull out values
+
108  const T_partials_return y_dbl = value_of(y_vec[n]);
+
109  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
110  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
+
111 
+
112  // Compute
+
113  P += ccdf_log[n];
+
114 
+ +
116  operands_and_partials.d_x1[n] -= a_over_lambda_plus_y[n];
+ +
118  operands_and_partials.d_x2[n] += a_over_lambda_plus_y[n];
+ +
120  operands_and_partials.d_x3[n] += a_over_lambda_plus_y[n]
+
121  * (y_dbl - mu_dbl) / lambda_dbl;
+ +
123  operands_and_partials.d_x4[n] -= log_1p_y_over_lambda[n];
+
124  }
+
125 
+
126  return operands_and_partials.value(P);
+
127  }
+
128  }
+
129 }
+
130 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
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diff --git a/doc/api/html/pareto__type__2__cdf_8hpp.html b/doc/api/html/pareto__type__2__cdf_8hpp.html new file mode 100644 index 00000000000..f38745c6d9f --- /dev/null +++ b/doc/api/html/pareto__type__2__cdf_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_cdf.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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pareto_type_2_cdf.hpp File Reference
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template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::pareto_type_2_cdf (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__type__2__cdf_8hpp_source.html b/doc/api/html/pareto__type__2__cdf_8hpp_source.html new file mode 100644 index 00000000000..213b55f1751 --- /dev/null +++ b/doc/api/html/pareto__type__2__cdf_8hpp_source.html @@ -0,0 +1,296 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_cdf.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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pareto_type_2_cdf.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/variate_generator.hpp>
+
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23  namespace math {
+
24 
+
25  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
26  typename return_type<T_y, T_loc, T_scale, T_shape>::type
+
27  pareto_type_2_cdf(const T_y& y, const T_loc& mu,
+
28  const T_scale& lambda, const T_shape& alpha) {
+
29  typedef
+ +
31  T_partials_return;
+
32 
+
33  // Check sizes
+
34  // Size checks
+
35  if ( !( stan::length(y)
+
36  && stan::length(mu)
+
37  && stan::length(lambda)
+
38  && stan::length(alpha) ) )
+
39  return 1.0;
+
40 
+
41  // Check errors
+
42  static const char* function("stan::math::pareto_type_2_cdf");
+
43 
+ + + + + + + + +
52  using std::log;
+
53 
+
54  T_partials_return P(1.0);
+
55 
+
56  check_greater_or_equal(function, "Random variable", y, mu);
+
57  check_not_nan(function, "Random variable", y);
+
58  check_nonnegative(function, "Random variable", y);
+
59  check_positive_finite(function, "Scale parameter", lambda);
+
60  check_positive_finite(function, "Shape parameter", alpha);
+
61  check_consistent_sizes(function,
+
62  "Random variable", y,
+
63  "Scale parameter", lambda,
+
64  "Shape parameter", alpha);
+
65 
+
66  // Wrap arguments in vectors
+
67  VectorView<const T_y> y_vec(y);
+
68  VectorView<const T_loc> mu_vec(mu);
+
69  VectorView<const T_scale> lambda_vec(lambda);
+
70  VectorView<const T_shape> alpha_vec(alpha);
+
71  size_t N = max_size(y, mu, lambda, alpha);
+
72 
+ +
74  operands_and_partials(y, mu, lambda, alpha);
+
75 
+
76  VectorBuilder<true, T_partials_return,
+
77  T_y, T_loc, T_scale, T_shape>
+
78  p1_pow_alpha(N);
+
79 
+ +
81  T_partials_return, T_y, T_loc, T_scale, T_shape>
+
82  grad_1_2(N);
+
83 
+ +
85  T_partials_return, T_y, T_loc, T_scale, T_shape>
+
86  grad_3(N);
+
87 
+
88  for (size_t i = 0; i < N; i++) {
+
89  const T_partials_return lambda_dbl = value_of(lambda_vec[i]);
+
90  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
91  const T_partials_return temp = 1 + (value_of(y_vec[i])
+
92  - value_of(mu_vec[i]))
+
93  / lambda_dbl;
+
94  p1_pow_alpha[i] = pow(temp, -alpha_dbl);
+
95 
+ +
97  grad_1_2[i] = p1_pow_alpha[i] / temp * alpha_dbl / lambda_dbl;
+
98 
+ +
100  grad_3[i] = log(temp) * p1_pow_alpha[i];
+
101  }
+
102 
+
103  // Compute vectorized CDF and its gradients
+
104 
+
105  for (size_t n = 0; n < N; n++) {
+
106  // Pull out values
+
107  const T_partials_return y_dbl = value_of(y_vec[n]);
+
108  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
109  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
+
110 
+
111  const T_partials_return Pn = 1.0 - p1_pow_alpha[n];
+
112 
+
113  // Compute
+
114  P *= Pn;
+
115 
+ +
117  operands_and_partials.d_x1[n] += grad_1_2[n] / Pn;
+ +
119  operands_and_partials.d_x2[n] -= grad_1_2[n] / Pn;
+ +
121  operands_and_partials.d_x3[n] += (mu_dbl - y_dbl)
+
122  * grad_1_2[n] / lambda_dbl / Pn;
+ +
124  operands_and_partials.d_x4[n] += grad_3[n] / Pn;
+
125  }
+
126 
+ +
128  for (size_t n = 0; n < stan::length(y); ++n)
+
129  operands_and_partials.d_x1[n] *= P;
+
130  }
+ +
132  for (size_t n = 0; n < stan::length(mu); ++n)
+
133  operands_and_partials.d_x2[n] *= P;
+
134  }
+ +
136  for (size_t n = 0; n < stan::length(lambda); ++n)
+
137  operands_and_partials.d_x3[n] *= P;
+
138  }
+ +
140  for (size_t n = 0; n < stan::length(alpha); ++n)
+
141  operands_and_partials.d_x4[n] *= P;
+
142  }
+
143 
+
144  return operands_and_partials.value(P);
+
145  }
+
146  }
+
147 }
+
148 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_cdf(const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
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diff --git a/doc/api/html/pareto__type__2__cdf__log_8hpp.html b/doc/api/html/pareto__type__2__cdf__log_8hpp.html new file mode 100644 index 00000000000..6fe5343ca3d --- /dev/null +++ b/doc/api/html/pareto__type__2__cdf__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_cdf_log.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
pareto_type_2_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::pareto_type_2_cdf_log (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__type__2__cdf__log_8hpp_source.html b/doc/api/html/pareto__type__2__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..ae510f2ee3a --- /dev/null +++ b/doc/api/html/pareto__type__2__cdf__log_8hpp_source.html @@ -0,0 +1,281 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
+ + +
+ +
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+
+
+
pareto_type_2_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/random/variate_generator.hpp>
+
19 #include <cmath>
+
20 
+
21 
+
22 namespace stan {
+
23  namespace math {
+
24 
+
25  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
26  typename return_type<T_y, T_loc, T_scale, T_shape>::type
+
27  pareto_type_2_cdf_log(const T_y& y, const T_loc& mu,
+
28  const T_scale& lambda, const T_shape& alpha) {
+
29  typedef
+ +
31  T_partials_return;
+
32 
+
33  // Check sizes
+
34  // Size checks
+
35  if ( !( stan::length(y)
+
36  && stan::length(mu)
+
37  && stan::length(lambda)
+
38  && stan::length(alpha) ) )
+
39  return 0.0;
+
40 
+
41  // Check errors
+
42  static const char* function("stan::math::pareto_type_2_cdf_log");
+
43 
+ + + + + + + + +
52  using stan::math::log1m;
+
53  using std::log;
+
54 
+
55  T_partials_return P(0.0);
+
56 
+
57  check_greater_or_equal(function, "Random variable", y, mu);
+
58  check_not_nan(function, "Random variable", y);
+
59  check_nonnegative(function, "Random variable", y);
+
60  check_positive_finite(function, "Scale parameter", lambda);
+
61  check_positive_finite(function, "Shape parameter", alpha);
+
62  check_consistent_sizes(function,
+
63  "Random variable", y,
+
64  "Scale parameter", lambda,
+
65  "Shape parameter", alpha);
+
66 
+
67  // Wrap arguments in vectors
+
68  VectorView<const T_y> y_vec(y);
+
69  VectorView<const T_loc> mu_vec(mu);
+
70  VectorView<const T_scale> lambda_vec(lambda);
+
71  VectorView<const T_shape> alpha_vec(alpha);
+
72  size_t N = max_size(y, mu, lambda, alpha);
+
73 
+ +
75  operands_and_partials(y, mu, lambda, alpha);
+
76 
+
77  VectorBuilder<true, T_partials_return,
+
78  T_y, T_loc, T_scale, T_shape>
+
79  cdf_log(N);
+
80 
+
81  VectorBuilder<true, T_partials_return,
+
82  T_y, T_loc, T_scale, T_shape>
+
83  inv_p1_pow_alpha_minus_one(N);
+
84 
+ +
86  T_partials_return, T_y, T_loc, T_scale, T_shape>
+
87  log_1p_y_over_lambda(N);
+
88 
+
89  for (size_t i = 0; i < N; i++) {
+
90  const T_partials_return temp = 1.0 + (value_of(y_vec[i])
+
91  - value_of(mu_vec[i]))
+
92  / value_of(lambda_vec[i]);
+
93  const T_partials_return p1_pow_alpha
+
94  = pow(temp, value_of(alpha_vec[i]));
+
95  cdf_log[i] = log1m(1.0 / p1_pow_alpha);
+
96 
+
97  inv_p1_pow_alpha_minus_one[i] = 1.0 / (p1_pow_alpha - 1.0);
+
98 
+ +
100  log_1p_y_over_lambda[i] = log(temp);
+
101  }
+
102 
+
103  // Compute vectorized CDF and its gradients
+
104 
+
105  for (size_t n = 0; n < N; n++) {
+
106  // Pull out values
+
107  const T_partials_return y_dbl = value_of(y_vec[n]);
+
108  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
109  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
+
110  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
111 
+
112  const T_partials_return grad_1_2 = alpha_dbl
+
113  * inv_p1_pow_alpha_minus_one[n] / (lambda_dbl - mu_dbl + y_dbl);
+
114 
+
115  // Compute
+
116  P += cdf_log[n];
+
117 
+ +
119  operands_and_partials.d_x1[n] += grad_1_2;
+ +
121  operands_and_partials.d_x2[n] -= grad_1_2;
+ +
123  operands_and_partials.d_x3[n] += (mu_dbl - y_dbl) * grad_1_2
+
124  / lambda_dbl;
+ +
126  operands_and_partials.d_x4[n] += log_1p_y_over_lambda[n]
+
127  * inv_p1_pow_alpha_minus_one[n];
+
128  }
+
129 
+
130  return operands_and_partials.value(P);
+
131  }
+
132  }
+
133 }
+
134 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_cdf_log(const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__type__2__log_8hpp.html b/doc/api/html/pareto__type__2__log_8hpp.html new file mode 100644 index 00000000000..114316084cc --- /dev/null +++ b/doc/api/html/pareto__type__2__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
pareto_type_2_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::pareto_type_2_log (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::pareto_type_2_log (const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__type__2__log_8hpp_source.html b/doc/api/html/pareto__type__2__log_8hpp_source.html new file mode 100644 index 00000000000..5ce1becf8cc --- /dev/null +++ b/doc/api/html/pareto__type__2__log_8hpp_source.html @@ -0,0 +1,304 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
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+
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+
pareto_type_2_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/variate_generator.hpp>
+
20 #include <cmath>
+
21 
+
22 
+
23 namespace stan {
+
24  namespace math {
+
25 
+
26  // pareto_type_2(y|lambda, alpha) [y >= 0; lambda > 0; alpha > 0]
+
27  template <bool propto,
+
28  typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
29  typename return_type<T_y, T_loc, T_scale, T_shape>::type
+
30  pareto_type_2_log(const T_y& y, const T_loc& mu, const T_scale& lambda,
+
31  const T_shape& alpha) {
+
32  static const char* function("stan::math::pareto_type_2_log");
+
33  typedef
+ +
35  T_partials_return;
+
36 
+
37  using std::log;
+ + + + + + + +
45  using std::log;
+
46 
+
47  // check if any vectors are zero length
+
48  if (!(stan::length(y)
+
49  && stan::length(mu)
+
50  && stan::length(lambda)
+
51  && stan::length(alpha)))
+
52  return 0.0;
+
53 
+
54  // set up return value accumulator
+
55  T_partials_return logp(0.0);
+
56 
+
57  // validate args (here done over var, which should be OK)
+
58  check_greater_or_equal(function, "Random variable", y, mu);
+
59  check_not_nan(function, "Random variable", y);
+
60  check_positive_finite(function, "Scale parameter", lambda);
+
61  check_positive_finite(function, "Shape parameter", alpha);
+
62  check_consistent_sizes(function,
+
63  "Random variable", y,
+
64  "Scale parameter", lambda,
+
65  "Shape parameter", alpha);
+
66 
+
67 
+
68  // check if no variables are involved and prop-to
+ +
70  return 0.0;
+
71 
+
72  VectorView<const T_y> y_vec(y);
+
73  VectorView<const T_loc> mu_vec(mu);
+
74  VectorView<const T_scale> lambda_vec(lambda);
+
75  VectorView<const T_shape> alpha_vec(alpha);
+
76  size_t N = max_size(y, mu, lambda, alpha);
+
77 
+
78  // set up template expressions wrapping scalars into vector views
+ +
80  operands_and_partials(y, mu, lambda, alpha);
+
81 
+ +
83  ::value,
+
84  T_partials_return, T_y, T_loc, T_scale>
+
85  log1p_scaled_diff(N);
+ +
87  for (size_t n = 0; n < N; n++)
+
88  log1p_scaled_diff[n] = log1p((value_of(y_vec[n])
+
89  - value_of(mu_vec[n]))
+
90  / value_of(lambda_vec[n]));
+
91  }
+
92 
+ +
94  T_partials_return, T_scale> log_lambda(length(lambda));
+ +
96  for (size_t n = 0; n < length(lambda); n++)
+
97  log_lambda[n] = log(value_of(lambda_vec[n]));
+
98  }
+
99 
+ +
101  T_partials_return, T_shape> log_alpha(length(alpha));
+ +
103  for (size_t n = 0; n < length(alpha); n++)
+
104  log_alpha[n] = log(value_of(alpha_vec[n]));
+
105  }
+
106 
+ +
108  T_partials_return, T_shape> inv_alpha(length(alpha));
+ +
110  for (size_t n = 0; n < length(alpha); n++)
+
111  inv_alpha[n] = 1 / value_of(alpha_vec[n]);
+
112  }
+
113 
+
114  for (size_t n = 0; n < N; n++) {
+
115  const T_partials_return y_dbl = value_of(y_vec[n]);
+
116  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
117  const T_partials_return lambda_dbl = value_of(lambda_vec[n]);
+
118  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
119  const T_partials_return sum_dbl = lambda_dbl + y_dbl - mu_dbl;
+
120  const T_partials_return inv_sum = 1.0 / sum_dbl;
+
121  const T_partials_return alpha_div_sum = alpha_dbl / sum_dbl;
+
122  const T_partials_return deriv_1_2 = inv_sum + alpha_div_sum;
+
123 
+
124  // // log probability
+ +
126  logp += log_alpha[n];
+ +
128  logp -= log_lambda[n];
+ +
130  logp -= (alpha_dbl + 1.0) * log1p_scaled_diff[n];
+
131 
+
132  // gradients
+ +
134  operands_and_partials.d_x1[n] -= deriv_1_2;
+ +
136  operands_and_partials.d_x2[n] += deriv_1_2;
+ +
138  operands_and_partials.d_x3[n] -= alpha_div_sum * (mu_dbl - y_dbl)
+
139  / lambda_dbl + inv_sum;
+ +
141  operands_and_partials.d_x4[n] += inv_alpha[n] - log1p_scaled_diff[n];
+
142  }
+
143  return operands_and_partials.value(logp);
+
144  }
+
145 
+
146  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
147  inline
+ +
149  pareto_type_2_log(const T_y& y, const T_loc& mu,
+
150  const T_scale& lambda, const T_shape& alpha) {
+
151  return pareto_type_2_log<false>(y, mu, lambda, alpha);
+
152  }
+
153  }
+
154 }
+
155 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
return_type< T_y, T_loc, T_scale, T_shape >::type pareto_type_2_log(const T_y &y, const T_loc &mu, const T_scale &lambda, const T_shape &alpha)
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__type__2__rng_8hpp.html b/doc/api/html/pareto__type__2__rng_8hpp.html new file mode 100644 index 00000000000..aa60f564888 --- /dev/null +++ b/doc/api/html/pareto__type__2__rng_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
pareto_type_2_rng.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<class RNG >
double stan::math::pareto_type_2_rng (const double mu, const double lambda, const double alpha, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/pareto__type__2__rng_8hpp_source.html b/doc/api/html/pareto__type__2__rng_8hpp_source.html new file mode 100644 index 00000000000..a35bb9feaeb --- /dev/null +++ b/doc/api/html/pareto__type__2__rng_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/pareto_type_2_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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pareto_type_2_rng.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_PARETO_TYPE_2_RNG_HPP
+
3 
+
4 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + +
15 
+
16 
+
17 namespace stan {
+
18  namespace math {
+
19 
+
20  template <class RNG>
+
21  inline double
+
22  pareto_type_2_rng(const double mu,
+
23  const double lambda,
+
24  const double alpha,
+
25  RNG& rng) {
+
26  static const char* function("stan::math::pareto_type_2_rng");
+
27 
+
28  stan::math::check_positive(function, "scale parameter", lambda);
+
29 
+
30  double uniform_01 = stan::math::uniform_rng(0.0, 1.0, rng);
+
31 
+
32 
+
33  return (std::pow(1.0 - uniform_01, -1.0 / alpha) - 1.0) * lambda + mu;
+
34  }
+
35  }
+
36 }
+
37 #endif
+ + + +
double pareto_type_2_rng(const double mu, const double lambda, const double alpha, RNG &rng)
+ + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
double uniform_rng(const double alpha, const double beta, RNG &rng)
Definition: uniform_rng.hpp:21
+ + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/partial__derivative_8hpp.html b/doc/api/html/partial__derivative_8hpp.html new file mode 100644 index 00000000000..e492301c4f7 --- /dev/null +++ b/doc/api/html/partial__derivative_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/partial_derivative.hpp File Reference + + + + + + + + + + +
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partial_derivative.hpp File Reference
+
+
+
#include <stan/math/fwd/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <vector>
+
+

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 Matrices and templated mathematical functions.
 
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+Functions

template<typename T , typename F >
void stan::math::partial_derivative (const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, int n, T &fx, T &dfx_dxn)
 Return the partial derivative of the specified multiivariate function at the specified argument. More...
 
+
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+
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diff --git a/doc/api/html/partial__derivative_8hpp_source.html b/doc/api/html/partial__derivative_8hpp_source.html new file mode 100644 index 00000000000..dd9fdf720b5 --- /dev/null +++ b/doc/api/html/partial__derivative_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/mix/mat/functor/partial_derivative.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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+ + +
+
+
+
partial_derivative.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_PARTIAL_DERIVATIVE_HPP
+
2 #define STAN_MATH_MIX_MAT_FUNCTOR_PARTIAL_DERIVATIVE_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+ +
6 #include <stan/math/rev/core.hpp>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
25  template <typename T, typename F>
+
26  void
+
27  partial_derivative(const F& f,
+
28  const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
29  int n,
+
30  T& fx,
+
31  T& dfx_dxn) {
+
32  Eigen::Matrix<fvar<T>, Eigen::Dynamic, 1> x_fvar(x.size());
+
33  for (int i = 0; i < x.size(); ++i)
+
34  x_fvar(i) = fvar<T>(x(i), i == n);
+
35  fvar<T> fx_fvar = f(x_fvar);
+
36  fx = fx_fvar.val_;
+
37  dfx_dxn = fx_fvar.d_;
+
38  }
+
39 
+
40  } // namespace math
+
41 } // namespace stan
+
42 #endif
+ + + + + + + +
void partial_derivative(const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, int n, T &fx, T &dfx_dxn)
Return the partial derivative of the specified multiivariate function at the specified argument...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/partials__return__type_8hpp.html b/doc/api/html/partials__return__type_8hpp.html new file mode 100644 index 00000000000..207353e8729 --- /dev/null +++ b/doc/api/html/partials__return__type_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/partials_return_type.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+ +
+
partials_return_type.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/partials_type.hpp>
+#include <stan/math/prim/scal/meta/scalar_type.hpp>
+#include <boost/math/tools/promotion.hpp>
+
+

Go to the source code of this file.

+ + + + +

+Classes

struct  stan::partials_return_type< T1, T2, T3, T4, T5, T6 >
 
+ + + +

+Namespaces

 stan
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/partials__return__type_8hpp_source.html b/doc/api/html/partials__return__type_8hpp_source.html new file mode 100644 index 00000000000..e7a8f209496 --- /dev/null +++ b/doc/api/html/partials__return__type_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/partials_return_type.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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partials_return_type.hpp
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+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_PARTIALS_RETURN_TYPE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_PARTIALS_RETURN_TYPE_HPP
+
3 
+ + +
6 #include <boost/math/tools/promotion.hpp>
+
7 
+
8 namespace stan {
+
9 
+
10  template <typename T1,
+
11  typename T2 = double,
+
12  typename T3 = double,
+
13  typename T4 = double,
+
14  typename T5 = double,
+
15  typename T6 = double>
+ +
17  typedef typename
+
18  boost::math::tools::promote_args
+ + + + + + +
25  ::type
+ +
27  };
+
28 
+
29 
+
30 }
+
31 #endif
+
32 
+ + + + + +
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__ccdf__log_8hpp.html b/doc/api/html/poisson__ccdf__log_8hpp.html new file mode 100644 index 00000000000..02ef67967d5 --- /dev/null +++ b/doc/api/html/poisson__ccdf__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_ccdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+ +
+ + +
+
+ +
+
poisson_ccdf_log.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <stan/math/prim/scal/meta/partials_return_type.hpp>
+#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_less.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/gamma_q.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/poisson_distribution.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+#include <limits>
+
+

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+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_n , typename T_rate >
return_type< T_rate >::type stan::math::poisson_ccdf_log (const T_n &n, const T_rate &lambda)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__ccdf__log_8hpp_source.html b/doc/api/html/poisson__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..38aa36dcce2 --- /dev/null +++ b/doc/api/html/poisson__ccdf__log_8hpp_source.html @@ -0,0 +1,236 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_ccdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
poisson_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_POISSON_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_POISSON_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/math/special_functions/fpclassify.hpp>
+
16 #include <boost/random/poisson_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 #include <limits>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <typename T_n, typename T_rate>
+
26  typename return_type<T_rate>::type
+
27  poisson_ccdf_log(const T_n& n, const T_rate& lambda) {
+
28  static const char* function("stan::math::poisson_ccdf_log");
+ +
30  T_partials_return;
+
31 
+ + + + +
36 
+
37  // Ensure non-zero argument slengths
+
38  if (!(stan::length(n) && stan::length(lambda)))
+
39  return 0.0;
+
40 
+
41  T_partials_return P(0.0);
+
42 
+
43  // Validate arguments
+
44  check_not_nan(function, "Rate parameter", lambda);
+
45  check_nonnegative(function, "Rate parameter", lambda);
+
46  check_consistent_sizes(function,
+
47  "Random variable", n,
+
48  "Rate parameter", lambda);
+
49 
+
50  // Wrap arguments into vector views
+
51  VectorView<const T_n> n_vec(n);
+
52  VectorView<const T_rate> lambda_vec(lambda);
+
53  size_t size = max_size(n, lambda);
+
54 
+
55  // Compute vectorized cdf_log and gradient
+ +
57  using stan::math::gamma_q;
+
58  using boost::math::tgamma;
+
59  using std::exp;
+
60  using std::pow;
+
61  using std::log;
+
62  using std::exp;
+
63 
+
64  OperandsAndPartials<T_rate> operands_and_partials(lambda);
+
65 
+
66  // Explicit return for extreme values
+
67  // The gradients are technically ill-defined, but treated as neg infinity
+
68  for (size_t i = 0; i < stan::length(n); i++) {
+
69  if (value_of(n_vec[i]) < 0)
+
70  return operands_and_partials.value(0.0);
+
71  }
+
72 
+
73  for (size_t i = 0; i < size; i++) {
+
74  // Explicit results for extreme values
+
75  // The gradients are technically ill-defined, but treated as zero
+
76  if (value_of(n_vec[i]) == std::numeric_limits<int>::max())
+
77  return operands_and_partials.value(stan::math::negative_infinity());
+
78 
+
79  const T_partials_return n_dbl = value_of(n_vec[i]);
+
80  const T_partials_return lambda_dbl = value_of(lambda_vec[i]);
+
81  const T_partials_return Pi = 1.0 - gamma_q(n_dbl+1, lambda_dbl);
+
82 
+
83  P += log(Pi);
+
84 
+ +
86  operands_and_partials.d_x1[i] += exp(-lambda_dbl)
+
87  * pow(lambda_dbl, n_dbl) / tgamma(n_dbl+1) / Pi;
+
88  }
+
89 
+
90  return operands_and_partials.value(P);
+
91  }
+
92  }
+
93 }
+
94 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ + + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
return_type< T_rate >::type poisson_ccdf_log(const T_n &n, const T_rate &lambda)
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__cdf_8hpp.html b/doc/api/html/poisson__cdf_8hpp.html new file mode 100644 index 00000000000..a1768f7f43e --- /dev/null +++ b/doc/api/html/poisson__cdf_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
poisson_cdf.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <stan/math/prim/scal/meta/partials_return_type.hpp>
+#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_less.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/gamma_q.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/poisson_distribution.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_n , typename T_rate >
return_type< T_rate >::type stan::math::poisson_cdf (const T_n &n, const T_rate &lambda)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__cdf_8hpp_source.html b/doc/api/html/poisson__cdf_8hpp_source.html new file mode 100644 index 00000000000..d71166bed3f --- /dev/null +++ b/doc/api/html/poisson__cdf_8hpp_source.html @@ -0,0 +1,239 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
poisson_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_POISSON_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_POISSON_CDF_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/math/special_functions/fpclassify.hpp>
+
16 #include <boost/random/poisson_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 #include <limits>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  // Poisson CDF
+
26  template <typename T_n, typename T_rate>
+
27  typename return_type<T_rate>::type
+
28  poisson_cdf(const T_n& n, const T_rate& lambda) {
+
29  static const char* function("stan::math::poisson_cdf");
+ +
31  T_partials_return;
+
32 
+ + + + +
37 
+
38  // Ensure non-zero argument slengths
+
39  if (!(stan::length(n) && stan::length(lambda)))
+
40  return 1.0;
+
41 
+
42  T_partials_return P(1.0);
+
43 
+
44  // Validate arguments
+
45  check_not_nan(function, "Rate parameter", lambda);
+
46  check_nonnegative(function, "Rate parameter", lambda);
+
47  check_consistent_sizes(function,
+
48  "Random variable", n,
+
49  "Rate parameter", lambda);
+
50 
+
51  // Wrap arguments into vector views
+
52  VectorView<const T_n> n_vec(n);
+
53  VectorView<const T_rate> lambda_vec(lambda);
+
54  size_t size = max_size(n, lambda);
+
55 
+
56  // Compute vectorized CDF and gradient
+ +
58  using stan::math::gamma_q;
+
59  using boost::math::tgamma;
+
60  using std::exp;
+
61  using std::pow;
+
62  using std::exp;
+
63 
+
64  OperandsAndPartials<T_rate> operands_and_partials(lambda);
+
65 
+
66  // Explicit return for extreme values
+
67  // The gradients are technically ill-defined, but treated as zero
+
68  for (size_t i = 0; i < stan::length(n); i++) {
+
69  if (value_of(n_vec[i]) < 0)
+
70  return operands_and_partials.value(0.0);
+
71  }
+
72 
+
73  for (size_t i = 0; i < size; i++) {
+
74  // Explicit results for extreme values
+
75  // The gradients are technically ill-defined, but treated as zero
+
76  if (value_of(n_vec[i]) == std::numeric_limits<int>::max())
+
77  continue;
+
78 
+
79  const T_partials_return n_dbl = value_of(n_vec[i]);
+
80  const T_partials_return lambda_dbl = value_of(lambda_vec[i]);
+
81  const T_partials_return Pi = gamma_q(n_dbl+1, lambda_dbl);
+
82 
+
83  P *= Pi;
+
84 
+ +
86  operands_and_partials.d_x1[i] -= exp(-lambda_dbl)
+
87  * pow(lambda_dbl, n_dbl) / tgamma(n_dbl+1) / Pi;
+
88  }
+
89 
+ +
91  for (size_t i = 0; i < stan::length(lambda); ++i)
+
92  operands_and_partials.d_x1[i] *= P;
+
93  }
+
94 
+
95  return operands_and_partials.value(P);
+
96  }
+
97  }
+
98 }
+
99 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
return_type< T_rate >::type poisson_cdf(const T_n &n, const T_rate &lambda)
Definition: poisson_cdf.hpp:28
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ + + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__cdf__log_8hpp.html b/doc/api/html/poisson__cdf__log_8hpp.html new file mode 100644 index 00000000000..5a3b295e09d --- /dev/null +++ b/doc/api/html/poisson__cdf__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+ +
+
poisson_cdf_log.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <stan/math/prim/scal/meta/partials_return_type.hpp>
+#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_less.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/gamma_q.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/poisson_distribution.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+#include <limits>
+
+

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+Functions

template<typename T_n , typename T_rate >
return_type< T_rate >::type stan::math::poisson_cdf_log (const T_n &n, const T_rate &lambda)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__cdf__log_8hpp_source.html b/doc/api/html/poisson__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..4ffae7e3587 --- /dev/null +++ b/doc/api/html/poisson__cdf__log_8hpp_source.html @@ -0,0 +1,236 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
poisson_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_POISSON_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_POISSON_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/math/special_functions/fpclassify.hpp>
+
16 #include <boost/random/poisson_distribution.hpp>
+
17 #include <boost/random/variate_generator.hpp>
+
18 #include <cmath>
+
19 #include <limits>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <typename T_n, typename T_rate>
+
26  typename return_type<T_rate>::type
+
27  poisson_cdf_log(const T_n& n, const T_rate& lambda) {
+
28  static const char* function("stan::math::poisson_cdf_log");
+ +
30  T_partials_return;
+
31 
+ + + + +
36 
+
37  // Ensure non-zero argument slengths
+
38  if (!(stan::length(n) && stan::length(lambda)))
+
39  return 0.0;
+
40 
+
41  T_partials_return P(0.0);
+
42 
+
43  // Validate arguments
+
44  check_not_nan(function, "Rate parameter", lambda);
+
45  check_nonnegative(function, "Rate parameter", lambda);
+
46  check_consistent_sizes(function,
+
47  "Random variable", n,
+
48  "Rate parameter", lambda);
+
49 
+
50  // Wrap arguments into vector views
+
51  VectorView<const T_n> n_vec(n);
+
52  VectorView<const T_rate> lambda_vec(lambda);
+
53  size_t size = max_size(n, lambda);
+
54 
+
55  // Compute vectorized cdf_log and gradient
+ +
57  using stan::math::gamma_q;
+
58  using boost::math::tgamma;
+
59  using std::exp;
+
60  using std::pow;
+
61  using std::log;
+
62  using std::exp;
+
63 
+
64  OperandsAndPartials<T_rate> operands_and_partials(lambda);
+
65 
+
66  // Explicit return for extreme values
+
67  // The gradients are technically ill-defined, but treated as neg infinity
+
68  for (size_t i = 0; i < stan::length(n); i++) {
+
69  if (value_of(n_vec[i]) < 0)
+
70  return operands_and_partials.value(stan::math::negative_infinity());
+
71  }
+
72 
+
73  for (size_t i = 0; i < size; i++) {
+
74  // Explicit results for extreme values
+
75  // The gradients are technically ill-defined, but treated as zero
+
76  if (value_of(n_vec[i]) == std::numeric_limits<int>::max())
+
77  continue;
+
78 
+
79  const T_partials_return n_dbl = value_of(n_vec[i]);
+
80  const T_partials_return lambda_dbl = value_of(lambda_vec[i]);
+
81  const T_partials_return Pi = gamma_q(n_dbl+1, lambda_dbl);
+
82 
+
83  P += log(Pi);
+
84 
+ +
86  operands_and_partials.d_x1[i] -= exp(-lambda_dbl)
+
87  * pow(lambda_dbl, n_dbl) / tgamma(n_dbl+1) / Pi;
+
88  }
+
89 
+
90  return operands_and_partials.value(P);
+
91  }
+
92  }
+
93 }
+
94 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_rate >::type poisson_cdf_log(const T_n &n, const T_rate &lambda)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ + + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__log_8hpp.html b/doc/api/html/poisson__log_8hpp.html new file mode 100644 index 00000000000..58f1efcd787 --- /dev/null +++ b/doc/api/html/poisson__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
poisson_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_n , typename T_rate >
return_type< T_rate >::type stan::math::poisson_log (const T_n &n, const T_rate &lambda)
 
template<typename T_n , typename T_rate >
return_type< T_rate >::type stan::math::poisson_log (const T_n &n, const T_rate &lambda)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__log_8hpp_source.html b/doc/api/html/poisson__log_8hpp_source.html new file mode 100644 index 00000000000..d95baaee36e --- /dev/null +++ b/doc/api/html/poisson__log_8hpp_source.html @@ -0,0 +1,249 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+
+
poisson_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_POISSON_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_POISSON_LOG_HPP
+
3 
+ + + + + + + + + + + + + +
17 #include <boost/math/special_functions/fpclassify.hpp>
+
18 #include <boost/random/poisson_distribution.hpp>
+
19 #include <boost/random/variate_generator.hpp>
+
20 #include <limits>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  // Poisson(n|lambda) [lambda > 0; n >= 0]
+
27  template <bool propto, typename T_n, typename T_rate>
+
28  typename return_type<T_rate>::type
+
29  poisson_log(const T_n& n, const T_rate& lambda) {
+ +
31  T_partials_return;
+
32 
+
33  static const char* function("stan::math::poisson_log");
+
34 
+
35  using boost::math::lgamma;
+ + + + + +
41 
+
42  // check if any vectors are zero length
+
43  if (!(stan::length(n)
+
44  && stan::length(lambda)))
+
45  return 0.0;
+
46 
+
47  // set up return value accumulator
+
48  T_partials_return logp(0.0);
+
49 
+
50  // validate args
+
51  check_nonnegative(function, "Random variable", n);
+
52  check_not_nan(function, "Rate parameter", lambda);
+
53  check_nonnegative(function, "Rate parameter", lambda);
+
54  check_consistent_sizes(function,
+
55  "Random variable", n,
+
56  "Rate parameter", lambda);
+
57 
+
58  // check if no variables are involved and prop-to
+ +
60  return 0.0;
+
61 
+
62  // set up expression templates wrapping scalars/vecs into vector views
+
63  VectorView<const T_n> n_vec(n);
+
64  VectorView<const T_rate> lambda_vec(lambda);
+
65  size_t size = max_size(n, lambda);
+
66 
+
67  for (size_t i = 0; i < size; i++)
+
68  if (boost::math::isinf(lambda_vec[i]))
+
69  return LOG_ZERO;
+
70  for (size_t i = 0; i < size; i++)
+
71  if (lambda_vec[i] == 0 && n_vec[i] != 0)
+
72  return LOG_ZERO;
+
73 
+
74  // return accumulator with gradients
+
75  OperandsAndPartials<T_rate> operands_and_partials(lambda);
+
76 
+ +
78  for (size_t i = 0; i < size; i++) {
+
79  if (!(lambda_vec[i] == 0 && n_vec[i] == 0)) {
+ +
81  logp -= lgamma(n_vec[i] + 1.0);
+ +
83  logp += multiply_log(n_vec[i], value_of(lambda_vec[i]))
+
84  - value_of(lambda_vec[i]);
+
85  }
+
86 
+
87  // gradients
+ +
89  operands_and_partials.d_x1[i]
+
90  += n_vec[i] / value_of(lambda_vec[i]) - 1.0;
+
91  }
+
92 
+
93 
+
94  return operands_and_partials.value(logp);
+
95  }
+
96 
+
97  template <typename T_n,
+
98  typename T_rate>
+
99  inline
+ +
101  poisson_log(const T_n& n, const T_rate& lambda) {
+
102  return poisson_log<false>(n, lambda);
+
103  }
+
104  }
+
105 }
+
106 #endif
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+
This class builds partial derivatives with respect to a set of operands.
+ +
return_type< T_rate >::type poisson_log(const T_n &n, const T_rate &lambda)
Definition: poisson_log.hpp:29
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ + +
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__log__log_8hpp.html b/doc/api/html/poisson__log__log_8hpp.html new file mode 100644 index 00000000000..b519f0f59ea --- /dev/null +++ b/doc/api/html/poisson__log__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_log_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
poisson_log_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_n , typename T_log_rate >
return_type< T_log_rate >::type stan::math::poisson_log_log (const T_n &n, const T_log_rate &alpha)
 
template<typename T_n , typename T_log_rate >
return_type< T_log_rate >::type stan::math::poisson_log_log (const T_n &n, const T_log_rate &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__log__log_8hpp_source.html b/doc/api/html/poisson__log__log_8hpp_source.html new file mode 100644 index 00000000000..4f5f05be843 --- /dev/null +++ b/doc/api/html/poisson__log__log_8hpp_source.html @@ -0,0 +1,262 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_log_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
poisson_log_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_POISSON_LOG_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_POISSON_LOG_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/math/special_functions/fpclassify.hpp>
+
19 #include <boost/random/poisson_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 #include <limits>
+
23 
+
24 namespace stan {
+
25 
+
26  namespace math {
+
27 
+
28  // PoissonLog(n|alpha) [n >= 0] = Poisson(n|exp(alpha))
+
29  template <bool propto,
+
30  typename T_n, typename T_log_rate>
+
31  typename return_type<T_log_rate>::type
+
32  poisson_log_log(const T_n& n, const T_log_rate& alpha) {
+ +
34  T_partials_return;
+
35 
+
36  static const char* function("stan::math::poisson_log_log");
+
37 
+
38  using boost::math::lgamma;
+ + + + + +
44  using std::exp;
+
45  using std::exp;
+
46 
+
47  // check if any vectors are zero length
+
48  if (!(stan::length(n)
+
49  && stan::length(alpha)))
+
50  return 0.0;
+
51 
+
52  // set up return value accumulator
+
53  T_partials_return logp(0.0);
+
54 
+
55  // validate args
+
56  check_nonnegative(function, "Random variable", n);
+
57  check_not_nan(function, "Log rate parameter", alpha);
+
58  check_consistent_sizes(function,
+
59  "Random variable", n,
+
60  "Log rate parameter", alpha);
+
61 
+
62  // check if no variables are involved and prop-to
+ +
64  return 0.0;
+
65 
+
66  // set up expression templates wrapping scalars/vecs into vector views
+
67  VectorView<const T_n> n_vec(n);
+
68  VectorView<const T_log_rate> alpha_vec(alpha);
+
69  size_t size = max_size(n, alpha);
+
70 
+
71  // FIXME: first loop size of alpha_vec, second loop if-ed for size==1
+
72  for (size_t i = 0; i < size; i++)
+
73  if (std::numeric_limits<double>::infinity() == alpha_vec[i])
+
74  return LOG_ZERO;
+
75  for (size_t i = 0; i < size; i++)
+
76  if (-std::numeric_limits<double>::infinity() == alpha_vec[i]
+
77  && n_vec[i] != 0)
+
78  return LOG_ZERO;
+
79 
+
80  // return accumulator with gradients
+
81  OperandsAndPartials<T_log_rate> operands_and_partials(alpha);
+
82 
+
83  // FIXME: cache value_of for alpha_vec? faster if only one?
+ +
85  T_partials_return, T_log_rate>
+
86  exp_alpha(length(alpha));
+
87  for (size_t i = 0; i < length(alpha); i++)
+ +
89  exp_alpha[i] = exp(value_of(alpha_vec[i]));
+
90 
+ +
92  for (size_t i = 0; i < size; i++) {
+
93  if (!(alpha_vec[i] == -std::numeric_limits<double>::infinity()
+
94  && n_vec[i] == 0)) {
+ +
96  logp -= lgamma(n_vec[i] + 1.0);
+ +
98  logp += n_vec[i] * value_of(alpha_vec[i]) - exp_alpha[i];
+
99  }
+
100 
+
101  // gradients
+ +
103  operands_and_partials.d_x1[i] += n_vec[i] - exp_alpha[i];
+
104  }
+
105  return operands_and_partials.value(logp);
+
106  }
+
107 
+
108  template <typename T_n,
+
109  typename T_log_rate>
+
110  inline
+ +
112  poisson_log_log(const T_n& n, const T_log_rate& alpha) {
+
113  return poisson_log_log<false>(n, alpha);
+
114  }
+
115  }
+
116 }
+
117 #endif
+ +
return_type< T_log_rate >::type poisson_log_log(const T_n &n, const T_log_rate &alpha)
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ + +
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/poisson__log__rng_8hpp.html b/doc/api/html/poisson__log__rng_8hpp.html new file mode 100644 index 00000000000..cef58e83d3d --- /dev/null +++ b/doc/api/html/poisson__log__rng_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_log_rng.hpp File Reference + + + + + + + + + + +
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+
#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_less.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/gamma_q.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/poisson_distribution.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <limits>
+
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template<class RNG >
int stan::math::poisson_log_rng (const double alpha, RNG &rng)
 
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diff --git a/doc/api/html/poisson__log__rng_8hpp_source.html b/doc/api/html/poisson__log__rng_8hpp_source.html new file mode 100644 index 00000000000..4434ff3d3b0 --- /dev/null +++ b/doc/api/html/poisson__log__rng_8hpp_source.html @@ -0,0 +1,170 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_log_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_POISSON_LOG_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_POISSON_LOG_RNG_HPP
+
3 
+ + + + + + + + +
12 #include <boost/math/special_functions/fpclassify.hpp>
+
13 #include <boost/random/poisson_distribution.hpp>
+
14 #include <boost/random/variate_generator.hpp>
+
15 #include <limits>
+
16 
+
17 namespace stan {
+
18 
+
19  namespace math {
+
20 
+
21  template <class RNG>
+
22  inline int
+
23  poisson_log_rng(const double alpha,
+
24  RNG& rng) {
+
25  using boost::variate_generator;
+
26  using boost::random::poisson_distribution;
+
27 
+
28  static const char* function("stan::math::poisson_log_rng");
+
29  static const double POISSON_MAX_LOG_RATE = 30 * std::log(2);
+
30 
+ + + +
34  using std::exp;
+
35 
+
36  check_not_nan(function, "Log rate parameter", alpha);
+
37  check_less(function, "Log rate parameter", alpha, POISSON_MAX_LOG_RATE);
+
38 
+
39  variate_generator<RNG&, poisson_distribution<> >
+
40  poisson_rng(rng, poisson_distribution<>(exp(alpha)));
+
41  return poisson_rng();
+
42  }
+
43  }
+
44 }
+
45 #endif
+ +
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ + + +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
int poisson_log_rng(const double alpha, RNG &rng)
+ +
int poisson_rng(const double lambda, RNG &rng)
Definition: poisson_rng.hpp:24
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
+
+
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diff --git a/doc/api/html/poisson__rng_8hpp.html b/doc/api/html/poisson__rng_8hpp.html new file mode 100644 index 00000000000..cb9e224d566 --- /dev/null +++ b/doc/api/html/poisson__rng_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_rng.hpp File Reference + + + + + + + + + + +
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+
+
+
#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_less.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/gamma_q.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/random/poisson_distribution.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <cmath>
+#include <limits>
+
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template<class RNG >
int stan::math::poisson_rng (const double lambda, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/poisson__rng_8hpp_source.html b/doc/api/html/poisson__rng_8hpp_source.html new file mode 100644 index 00000000000..bda4c983517 --- /dev/null +++ b/doc/api/html/poisson__rng_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/poisson_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_POISSON_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_POISSON_RNG_HPP
+
3 
+ + + + + + + + +
12 #include <boost/math/special_functions/fpclassify.hpp>
+
13 #include <boost/random/poisson_distribution.hpp>
+
14 #include <boost/random/variate_generator.hpp>
+
15 #include <cmath>
+
16 #include <limits>
+
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  template <class RNG>
+
23  inline int
+
24  poisson_rng(const double lambda,
+
25  RNG& rng) {
+
26  using boost::variate_generator;
+
27  using boost::random::poisson_distribution;
+
28 
+
29  static const char* function("stan::math::poisson_rng");
+
30 
+
31  check_not_nan(function, "Rate parameter", lambda);
+
32  check_nonnegative(function, "Rate parameter", lambda);
+
33  check_less(function, "Rate parameter", lambda, POISSON_MAX_RATE);
+
34 
+
35  variate_generator<RNG&, poisson_distribution<> >
+
36  poisson_rng(rng, poisson_distribution<>(lambda));
+
37  return poisson_rng();
+
38  }
+
39  }
+
40 }
+
41 #endif
+ +
bool check_less(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is strictly less than high.
Definition: check_less.hpp:81
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + + + +
const double POISSON_MAX_RATE
Largest rate parameter allowed in Poisson RNG.
Definition: constants.hpp:72
+ +
int poisson_rng(const double lambda, RNG &rng)
Definition: poisson_rng.hpp:24
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/positive__constrain_8hpp.html b/doc/api/html/positive__constrain_8hpp.html new file mode 100644 index 00000000000..2dbfb305493 --- /dev/null +++ b/doc/api/html/positive__constrain_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/positive_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::positive_constrain (const T x)
 Return the positive value for the specified unconstrained input. More...
 
template<typename T >
stan::math::positive_constrain (const T x, T &lp)
 Return the positive value for the specified unconstrained input, incrementing the scalar reference with the log absolute Jacobian determinant. More...
 
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diff --git a/doc/api/html/positive__constrain_8hpp_source.html b/doc/api/html/positive__constrain_8hpp_source.html new file mode 100644 index 00000000000..c15f8b168b4 --- /dev/null +++ b/doc/api/html/positive__constrain_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/positive_constrain.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_POSITIVE_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_POSITIVE_CONSTRAIN_HPP
+
3 
+
4 #include <cmath>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
20  template <typename T>
+
21  inline
+
22  T positive_constrain(const T x) {
+
23  return exp(x);
+
24  }
+
25 
+
42  template <typename T>
+
43  inline
+
44  T positive_constrain(const T x, T& lp) {
+
45  lp += x;
+
46  return exp(x);
+
47  }
+
48 
+
49 
+
50  }
+
51 
+
52 }
+
53 
+
54 #endif
+
T positive_constrain(const T x)
Return the positive value for the specified unconstrained input.
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
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diff --git a/doc/api/html/positive__free_8hpp.html b/doc/api/html/positive__free_8hpp.html new file mode 100644 index 00000000000..3e691b13104 --- /dev/null +++ b/doc/api/html/positive__free_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/positive_free.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::positive_free (const T y)
 Return the unconstrained value corresponding to the specified positive-constrained value. More...
 
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diff --git a/doc/api/html/positive__free_8hpp_source.html b/doc/api/html/positive__free_8hpp_source.html new file mode 100644 index 00000000000..4adada2f243 --- /dev/null +++ b/doc/api/html/positive__free_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/positive_free.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_POSITIVE_FREE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_POSITIVE_FREE_HPP
+
3 
+ +
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
27  template <typename T>
+
28  inline
+
29  T positive_free(const T y) {
+
30  stan::math::check_positive("stan::math::positive_free",
+
31  "Positive variable", y);
+
32  return log(y);
+
33  }
+
34 
+
35  }
+
36 
+
37 }
+
38 
+
39 #endif
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T positive_free(const T y)
Return the unconstrained value corresponding to the specified positive-constrained value...
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
+
+
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diff --git a/doc/api/html/positive__ordered__constrain_8hpp.html b/doc/api/html/positive__ordered__constrain_8hpp.html new file mode 100644 index 00000000000..b8418c86df2 --- /dev/null +++ b/doc/api/html/positive__ordered__constrain_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/positive_ordered_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::positive_ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 Return an increasing positive ordered vector derived from the specified free vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::positive_ordered_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &lp)
 Return a positive valued, increasing positive ordered vector derived from the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
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diff --git a/doc/api/html/positive__ordered__constrain_8hpp_source.html b/doc/api/html/positive__ordered__constrain_8hpp_source.html new file mode 100644 index 00000000000..a2461b075e6 --- /dev/null +++ b/doc/api/html/positive__ordered__constrain_8hpp_source.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/positive_ordered_constrain.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
positive_ordered_constrain.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_POSITIVE_ORDERED_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_POSITIVE_ORDERED_CONSTRAIN_HPP
+
3 
+ + +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
21  template <typename T>
+
22  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
23  positive_ordered_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x) {
+
24  using Eigen::Matrix;
+
25  using Eigen::Dynamic;
+ +
27  using std::exp;
+
28  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
29 
+
30  size_type k = x.size();
+
31  Matrix<T, Dynamic, 1> y(k);
+
32  if (k == 0)
+
33  return y;
+
34  y[0] = exp(x[0]);
+
35  for (size_type i = 1; i < k; ++i)
+
36  y[i] = y[i-1] + exp(x[i]);
+
37  return y;
+
38  }
+
39 
+
52  template <typename T>
+
53  inline
+
54  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
55  positive_ordered_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
56  T& lp) {
+
57  using Eigen::Matrix;
+
58  using Eigen::Dynamic;
+ +
60  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
61 
+
62  for (size_type i = 0; i < x.size(); ++i)
+
63  lp += x(i);
+ +
65  }
+
66 
+
67  }
+
68 
+
69 }
+
70 
+
71 #endif
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > positive_ordered_constrain(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
Return an increasing positive ordered vector derived from the specified free vector.
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/positive__ordered__free_8hpp.html b/doc/api/html/positive__ordered__free_8hpp.html new file mode 100644 index 00000000000..c8f60d38f4b --- /dev/null +++ b/doc/api/html/positive__ordered__free_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/positive_ordered_free.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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positive_ordered_free.hpp File Reference
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+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::positive_ordered_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
 Return the vector of unconstrained scalars that transform to the specified positive ordered vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/positive__ordered__free_8hpp_source.html b/doc/api/html/positive__ordered__free_8hpp_source.html new file mode 100644 index 00000000000..e5194eee156 --- /dev/null +++ b/doc/api/html/positive__ordered__free_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/positive_ordered_free.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
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positive_ordered_free.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_POSITIVE_ORDERED_FREE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_POSITIVE_ORDERED_FREE_HPP
+
3 
+ + + +
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
24  template <typename T>
+
25  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
26  positive_ordered_free(const Eigen::Matrix<T, Eigen::Dynamic, 1>& y) {
+
27  using Eigen::Matrix;
+
28  using Eigen::Dynamic;
+ +
30  using std::log;
+
31  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
32 
+
33  stan::math::check_positive_ordered("stan::math::positive_ordered_free",
+
34  "Positive ordered variable",
+
35  y);
+
36  size_type k = y.size();
+
37  Matrix<T, Dynamic, 1> x(k);
+
38  if (k == 0)
+
39  return x;
+
40  x[0] = log(y[0]);
+
41  for (size_type i = 1; i < k; ++i)
+
42  x[i] = log(y[i] - y[i-1]);
+
43  return x;
+
44  }
+
45  }
+
46 }
+
47 #endif
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > positive_ordered_free(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
Return the vector of unconstrained scalars that transform to the specified positive ordered vector...
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
bool check_positive_ordered(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, 1 > &y)
Return true if the specified vector contains non-negative values and is sorted into strictly increasi...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/precomp__v__vari_8hpp.html b/doc/api/html/precomp__v__vari_8hpp.html new file mode 100644 index 00000000000..01ed82474f7 --- /dev/null +++ b/doc/api/html/precomp__v__vari_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/precomp_v_vari.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
+ +
+
precomp_v_vari.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::precomp_v_vari
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/precomp__v__vari_8hpp_source.html b/doc/api/html/precomp__v__vari_8hpp_source.html new file mode 100644 index 00000000000..6c491339b69 --- /dev/null +++ b/doc/api/html/precomp__v__vari_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/rev/core/precomp_v_vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+
precomp_v_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_PRECOMP_V_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_PRECOMP_V_VARI_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  // use for single precomputed partials
+
11  class precomp_v_vari : public op_v_vari {
+
12  protected:
+
13  double da_;
+
14  public:
+
15  precomp_v_vari(double val, vari* avi, double da)
+
16  : op_v_vari(val, avi),
+
17  da_(da) {
+
18  }
+
19  void chain() {
+
20  avi_->adj_ += adj_ * da_;
+
21  }
+
22  };
+
23 
+
24  }
+
25 }
+
26 #endif
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+ + + + + +
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
+
precomp_v_vari(double val, vari *avi, double da)
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/precomp__vv__vari_8hpp.html b/doc/api/html/precomp__vv__vari_8hpp.html new file mode 100644 index 00000000000..c6c5f1ea899 --- /dev/null +++ b/doc/api/html/precomp__vv__vari_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/precomp_vv_vari.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+ +
+
precomp_vv_vari.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::precomp_vv_vari
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/precomp__vv__vari_8hpp_source.html b/doc/api/html/precomp__vv__vari_8hpp_source.html new file mode 100644 index 00000000000..7322e369b13 --- /dev/null +++ b/doc/api/html/precomp__vv__vari_8hpp_source.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/rev/core/precomp_vv_vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+
+
precomp_vv_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_PRECOMP_VV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_PRECOMP_VV_VARI_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  // use for single precomputed partials
+
11  class precomp_vv_vari : public op_vv_vari {
+
12  protected:
+
13  double da_;
+
14  double db_;
+
15  public:
+
16  precomp_vv_vari(double val,
+
17  vari* avi, vari* bvi,
+
18  double da, double db)
+
19  : op_vv_vari(val, avi, bvi),
+
20  da_(da),
+
21  db_(db) {
+
22  }
+
23  void chain() {
+
24  avi_->adj_ += adj_ * da_;
+
25  bvi_->adj_ += adj_ * db_;
+
26  }
+
27  };
+
28 
+
29  }
+
30 }
+
31 #endif
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
+ + + + +
precomp_vv_vari(double val, vari *avi, vari *bvi, double da, double db)
+ +
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/precomp__vvv__vari_8hpp.html b/doc/api/html/precomp__vvv__vari_8hpp.html new file mode 100644 index 00000000000..39358a29ebd --- /dev/null +++ b/doc/api/html/precomp__vvv__vari_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/precomp_vvv_vari.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
precomp_vvv_vari.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::precomp_vvv_vari
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/precomp__vvv__vari_8hpp_source.html b/doc/api/html/precomp__vvv__vari_8hpp_source.html new file mode 100644 index 00000000000..3afb9ca9718 --- /dev/null +++ b/doc/api/html/precomp__vvv__vari_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/rev/core/precomp_vvv_vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
precomp_vvv_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_PRECOMP_VVV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_PRECOMP_VVV_VARI_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  // use for single precomputed partials
+
11  class precomp_vvv_vari : public op_vvv_vari {
+
12  protected:
+
13  double da_;
+
14  double db_;
+
15  double dc_;
+
16  public:
+
17  precomp_vvv_vari(double val,
+
18  vari* avi, vari* bvi, vari* cvi,
+
19  double da, double db, double dc)
+
20  : op_vvv_vari(val, avi, bvi, cvi),
+
21  da_(da),
+
22  db_(db),
+
23  dc_(dc) {
+
24  }
+
25  void chain() {
+
26  avi_->adj_ += adj_ * da_;
+
27  bvi_->adj_ += adj_ * db_;
+
28  cvi_->adj_ += adj_ * dc_;
+
29  }
+
30  };
+
31 
+
32  }
+
33 }
+
34 #endif
+
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
+ + + + + + + + +
The variable implementation base class.
Definition: vari.hpp:30
+
precomp_vvv_vari(double val, vari *avi, vari *bvi, vari *cvi, double da, double db, double dc)
+ + + +
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/precomputed__gradients_8hpp.html b/doc/api/html/precomputed__gradients_8hpp.html new file mode 100644 index 00000000000..e7fb5c612f7 --- /dev/null +++ b/doc/api/html/precomputed__gradients_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/core/precomputed_gradients.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
precomputed_gradients.hpp File Reference
+
+
+
#include <stan/math/rev/core/vari.hpp>
+#include <stan/math/rev/core/var.hpp>
+#include <algorithm>
+#include <stdexcept>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

class  stan::math::precomputed_gradients_vari
 A variable implementation taking a sequence of operands and partial derivatives with respect to the operands. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

var stan::math::precomputed_gradients (const double value, const std::vector< var > &operands, const std::vector< double > &gradients)
 This function returns a var for an expression that has the specified value, vector of operands, and vector of partial derivatives of value with respect to the operands. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/precomputed__gradients_8hpp_source.html b/doc/api/html/precomputed__gradients_8hpp_source.html new file mode 100644 index 00000000000..8e474006082 --- /dev/null +++ b/doc/api/html/precomputed__gradients_8hpp_source.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan/math/rev/core/precomputed_gradients.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
precomputed_gradients.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_PRECOMPUTED_GRADIENTS_HPP
+
2 #define STAN_MATH_REV_CORE_PRECOMPUTED_GRADIENTS_HPP
+
3 
+ + +
6 #include <algorithm>
+
7 #include <stdexcept>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+ +
22  protected:
+
23  const size_t size_;
+ +
25  double* gradients_;
+
26 
+
27  public:
+ +
38  size_t size,
+
39  vari** varis,
+
40  double* gradients)
+
41  : vari(val),
+
42  size_(size),
+
43  varis_(varis),
+
44  gradients_(gradients) {
+
45  }
+
46 
+ +
59  const std::vector<var>& vars,
+
60  const std::vector<double>& gradients)
+
61  : vari(val),
+
62  size_(vars.size()),
+
63  varis_(ChainableStack::memalloc_
+
64  .alloc_array<vari*>(vars.size())),
+
65  gradients_(ChainableStack::memalloc_
+
66  .alloc_array<double>(vars.size())) {
+
67  if (vars.size() != gradients.size())
+
68  throw std::invalid_argument("sizes of vars and gradients"
+
69  " do not match");
+
70  for (size_t i = 0; i < vars.size(); ++i)
+
71  varis_[i] = vars[i].vi_;
+
72  std::copy(gradients.begin(), gradients.end(), gradients_);
+
73  }
+
74 
+
79  void chain() {
+
80  for (size_t i = 0; i < size_; ++i)
+
81  varis_[i]->adj_ += adj_ * gradients_[i];
+
82  }
+
83  };
+
84 
+
85 
+
98  var precomputed_gradients(const double value,
+
99  const std::vector<var>& operands,
+
100  const std::vector<double>& gradients) {
+
101  return var(new precomputed_gradients_vari(value, operands, gradients));
+
102  }
+
103  }
+
104 }
+
105 #endif
+
var precomputed_gradients(const double value, const std::vector< var > &operands, const std::vector< double > &gradients)
This function returns a var for an expression that has the specified value, vector of operands...
+ + + + +
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
A variable implementation taking a sequence of operands and partial derivatives with respect to the o...
+
precomputed_gradients_vari(double val, const std::vector< var > &vars, const std::vector< double > &gradients)
Construct a precomputed vari with the specified value, operands, and gradients.
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
+ +
void chain()
Implements the chain rule for this variable, using the prestored operands and gradient.
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+
precomputed_gradients_vari(double val, size_t size, vari **varis, double *gradients)
Construct a precomputed vari with the specified value, operands, and gradients.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2arr_2fun_2dot__self_8hpp.html b/doc/api/html/prim_2arr_2fun_2dot__self_8hpp.html new file mode 100644 index 00000000000..0eecbaa2d24 --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2dot__self_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/dot_self.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+ +
+
dot_self.hpp File Reference
+
+
+
#include <vector>
+#include <cstddef>
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double stan::math::dot_self (const std::vector< double > &x)
 
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diff --git a/doc/api/html/prim_2arr_2fun_2dot__self_8hpp_source.html b/doc/api/html/prim_2arr_2fun_2dot__self_8hpp_source.html new file mode 100644 index 00000000000..aed70d3d3c6 --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2dot__self_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/dot_self.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_DOT_SELF_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_DOT_SELF_HPP
+
3 
+
4 #include <vector>
+
5 #include <cstddef>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  // x' * x
+
11  inline double dot_self(const std::vector<double>& x) {
+
12  double sum = 0.0;
+
13  for (size_t i = 0; i < x.size(); ++i)
+
14  sum += x[i] * x[i];
+
15  return sum;
+
16  }
+
17 
+
18  }
+
19 }
+
20 
+
21 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
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diff --git a/doc/api/html/prim_2arr_2fun_2log__sum__exp_8hpp.html b/doc/api/html/prim_2arr_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..6fd1d24ea42 --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
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#include <cmath>
+#include <cstdlib>
+#include <limits>
+#include <vector>
+
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double stan::math::log_sum_exp (const std::vector< double > &x)
 Return the log of the sum of the exponentiated values of the specified sequence of values. More...
 
+
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diff --git a/doc/api/html/prim_2arr_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/prim_2arr_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..f3ff08df692 --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_LOG_SUM_EXP_HPP
+
3 
+
4 #include <cmath>
+
5 #include <cstdlib>
+
6 #include <limits>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
24  double log_sum_exp(const std::vector<double>& x) {
+
25  using std::numeric_limits;
+
26  using std::log;
+
27  using std::exp;
+
28  double max = -numeric_limits<double>::infinity();
+
29  for (size_t ii = 0; ii < x.size(); ii++)
+
30  if (x[ii] > max)
+
31  max = x[ii];
+
32 
+
33  double sum = 0.0;
+
34  for (size_t ii = 0; ii < x.size(); ii++)
+
35  if (x[ii] != -numeric_limits<double>::infinity())
+
36  sum += exp(x[ii] - max);
+
37 
+
38  return max + log(sum);
+
39  }
+
40 
+
41  }
+
42 }
+
43 
+
44 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+
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diff --git a/doc/api/html/prim_2arr_2fun_2sum_8hpp.html b/doc/api/html/prim_2arr_2fun_2sum_8hpp.html new file mode 100644 index 00000000000..878818bdd83 --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2sum_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/sum.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::sum (const std::vector< T > &xs)
 Return the sum of the values in the specified standard vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2arr_2fun_2sum_8hpp_source.html b/doc/api/html/prim_2arr_2fun_2sum_8hpp_source.html new file mode 100644 index 00000000000..23a58eb89ff --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2sum_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/sum.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_SUM_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_SUM_HPP
+
3 
+
4 #include <cstddef>
+
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
17  template <typename T>
+
18  inline T sum(const std::vector<T>& xs) {
+
19  if (xs.size() == 0) return 0;
+
20  T sum(xs[0]);
+
21  for (size_t i = 1; i < xs.size(); ++i)
+
22  sum += xs[i];
+
23  return sum;
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
+
+
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diff --git a/doc/api/html/prim_2arr_2fun_2value__of_8hpp.html b/doc/api/html/prim_2arr_2fun_2value__of_8hpp.html new file mode 100644 index 00000000000..574195295f7 --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2value__of_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/value_of.hpp File Reference + + + + + + + + + + +
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value_of.hpp File Reference
+
+
+
#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <stan/math/prim/scal/meta/child_type.hpp>
+#include <vector>
+#include <cstddef>
+
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template<typename T >
std::vector< typename child_type< T >::type > stan::math::value_of (const std::vector< T > &x)
 Convert a std::vector of type T to a std::vector of child_type<T>::type. More...
 
template<>
std::vector< double > stan::math::value_of (const std::vector< double > &x)
 Return the specified argument. More...
 
+
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diff --git a/doc/api/html/prim_2arr_2fun_2value__of_8hpp_source.html b/doc/api/html/prim_2arr_2fun_2value__of_8hpp_source.html new file mode 100644 index 00000000000..db3d4f72ae2 --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2value__of_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/value_of.hpp Source File + + + + + + + + + + +
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value_of.hpp
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_VALUE_OF_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_VALUE_OF_HPP
+
3 
+ + +
6 #include <vector>
+
7 #include <cstddef>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
20  template <typename T>
+
21  inline std::vector<typename child_type<T>::type>
+
22  value_of(const std::vector<T>& x) {
+
23  size_t size = x.size();
+
24  std::vector<typename child_type<T>::type> result(size);
+
25  for (size_t i=0; i < size; i++)
+
26  result[i] = value_of(x[i]);
+
27  return result;
+
28  }
+
29 
+
41  template <>
+
42  inline std::vector<double> value_of(const std::vector<double>& x) {
+
43  return x;
+
44  }
+
45 
+
46  }
+
47 }
+
48 
+
49 #endif
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2arr_2fun_2value__of__rec_8hpp.html b/doc/api/html/prim_2arr_2fun_2value__of__rec_8hpp.html new file mode 100644 index 00000000000..33f06041910 --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2value__of__rec_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/value_of_rec.hpp File Reference + + + + + + + + + + +
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value_of_rec.hpp File Reference
+
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+
#include <stan/math/prim/scal/fun/value_of_rec.hpp>
+#include <vector>
+#include <cstddef>
+
+

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 Matrices and templated mathematical functions.
 
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+Functions

template<typename T >
std::vector< double > stan::math::value_of_rec (const std::vector< T > &x)
 Convert a std::vector of type T to a std::vector of doubles. More...
 
template<>
std::vector< double > stan::math::value_of_rec (const std::vector< double > &x)
 Return the specified argument. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2arr_2fun_2value__of__rec_8hpp_source.html b/doc/api/html/prim_2arr_2fun_2value__of__rec_8hpp_source.html new file mode 100644 index 00000000000..582560a7d4d --- /dev/null +++ b/doc/api/html/prim_2arr_2fun_2value__of__rec_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/value_of_rec.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_VALUE_OF_REC_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_VALUE_OF_REC_HPP
+
3 
+ +
5 #include <vector>
+
6 #include <cstddef>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
21  template <typename T>
+
22  inline std::vector<double>
+
23  value_of_rec(const std::vector<T>& x) {
+
24  size_t size = x.size();
+
25  std::vector<double> result(size);
+
26  for (size_t i=0; i < size; i++)
+
27  result[i] = value_of_rec(x[i]);
+
28  return result;
+
29  }
+
30 
+
42  template <>
+
43  inline std::vector<double> value_of_rec(const std::vector<double>& x) {
+
44  return x;
+
45  }
+
46 
+
47  }
+
48 }
+
49 
+
50 #endif
+ +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2arr_2functor_2coupled__ode__system_8hpp.html b/doc/api/html/prim_2arr_2functor_2coupled__ode__system_8hpp.html new file mode 100644 index 00000000000..c4df3dc2fc2 --- /dev/null +++ b/doc/api/html/prim_2arr_2functor_2coupled__ode__system_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/functor/coupled_ode_system.hpp File Reference + + + + + + + + + + +
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coupled_ode_system.hpp File Reference
+
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+
#include <stan/math/prim/scal/err/check_size_match.hpp>
+#include <ostream>
+#include <vector>
+
+

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+ + + + + + + + +

+Classes

struct  stan::math::coupled_ode_system< F, T1, T2 >
 Base template class for a coupled ordinary differential equation system, which adds sensitivities to the base system. More...
 
class  stan::math::coupled_ode_system< F, double, double >
 The coupled ode system for known initial values and known parameters. More...
 
+ + + + + + +

+Namespaces

 stan
 
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 Matrices and templated mathematical functions.
 
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diff --git a/doc/api/html/prim_2arr_2functor_2coupled__ode__system_8hpp_source.html b/doc/api/html/prim_2arr_2functor_2coupled__ode__system_8hpp_source.html new file mode 100644 index 00000000000..dc01a9cd645 --- /dev/null +++ b/doc/api/html/prim_2arr_2functor_2coupled__ode__system_8hpp_source.html @@ -0,0 +1,203 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/functor/coupled_ode_system.hpp Source File + + + + + + + + + + +
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coupled_ode_system.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_ARR_FUNCTOR_COUPLED_ODE_SYSTEM_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUNCTOR_COUPLED_ODE_SYSTEM_HPP
+
3 
+ +
5 #include <ostream>
+
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
24  template <typename F, typename T1, typename T2>
+ +
26  };
+
27 
+
38  template <typename F>
+
39  class coupled_ode_system<F, double, double> {
+
40  public:
+
41  const F& f_;
+
42  const std::vector<double>& y0_dbl_;
+
43  const std::vector<double>& theta_dbl_;
+
44  const std::vector<double>& x_;
+
45  const std::vector<int>& x_int_;
+
46  const size_t N_;
+
47  const size_t M_;
+
48  const size_t size_;
+
49  std::ostream* msgs_;
+
50 
+
63  coupled_ode_system(const F& f,
+
64  const std::vector<double>& y0,
+
65  const std::vector<double>& theta,
+
66  const std::vector<double>& x,
+
67  const std::vector<int>& x_int,
+
68  std::ostream* msgs)
+
69  : f_(f),
+
70  y0_dbl_(y0),
+
71  theta_dbl_(theta),
+
72  x_(x),
+
73  x_int_(x_int),
+
74  N_(y0.size()),
+
75  M_(theta.size()),
+
76  size_(N_),
+
77  msgs_(msgs) {
+
78  }
+
79 
+
95  void operator()(const std::vector<double>& y,
+
96  std::vector<double>& dy_dt,
+
97  double t) {
+
98  dy_dt = f_(t, y, theta_dbl_, x_, x_int_, msgs_);
+
99  stan::math::check_size_match("coupled_ode_system",
+
100  "y", y.size(),
+
101  "dy_dt", dy_dt.size());
+
102  }
+
103 
+
109  int size() const {
+
110  return size_;
+
111  }
+
112 
+
125  std::vector<double> initial_state() {
+
126  std::vector<double> state(size_, 0.0);
+
127  for (size_t n = 0; n < N_; n++)
+
128  state[n] = y0_dbl_[n];
+
129  return state;
+
130  }
+
131 
+
142  std::vector<std::vector<double> >
+
143  decouple_states(const std::vector<std::vector<double> >& y) {
+
144  return y;
+
145  }
+
146  };
+
147  } // math
+
148 } // stan
+
149 
+
150 #endif
+ +
void operator()(const std::vector< double > &y, std::vector< double > &dy_dt, double t)
Calculates the derivative of the coupled ode system with respect to the specified state at the specif...
+ +
coupled_ode_system(const F &f, const std::vector< double > &y0, const std::vector< double > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
Construct the coupled ODE system from the base system function, initial state, parameters, data and a stream for messages.
+ + + + + + +
size_t size_
Definition: dot_self.hpp:18
+
std::vector< double > initial_state()
Returns the initial state of the coupled system, which is identical to the base ODE original state in...
+ +
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ +
std::vector< std::vector< double > > decouple_states(const std::vector< std::vector< double > > &y)
Returns the base portion of the coupled state.
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
Base template class for a coupled ordinary differential equation system, which adds sensitivities to ...
+
int N_
+
int size() const
Returns the size of the coupled system.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2arr_8hpp.html b/doc/api/html/prim_2arr_8hpp.html new file mode 100644 index 00000000000..64c68907ae1 --- /dev/null +++ b/doc/api/html/prim_2arr_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/arr.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/prim_2arr_8hpp_source.html b/doc/api/html/prim_2arr_8hpp_source.html new file mode 100644 index 00000000000..8343094c072 --- /dev/null +++ b/doc/api/html/prim_2arr_8hpp_source.html @@ -0,0 +1,174 @@ + + + + + + +Stan Math Library: stan/math/prim/arr.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_HPP
+
2 #define STAN_MATH_PRIM_ARR_HPP
+
3 
+ + + + + + + + + +
13 
+ + +
16 
+ + + + + + + + + + + + + +
30 
+ + + +
34 
+
35 #include <stan/math/prim/scal.hpp>
+
36 
+
37 #endif
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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diff --git a/doc/api/html/prim_2mat_2fun_2_l_d_l_t__factor_8hpp.html b/doc/api/html/prim_2mat_2fun_2_l_d_l_t__factor_8hpp.html new file mode 100644 index 00000000000..5c7d58b7d16 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2_l_d_l_t__factor_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/LDLT_factor.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <boost/shared_ptr.hpp>
+#include <stan/math/prim/mat/err/check_square.hpp>
+#include <stan/math/prim/scal/fun/is_nan.hpp>
+
+

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+ + + + + + + +

+Classes

class  stan::math::LDLT_factor< T, R, C >
 
class  stan::math::LDLT_factor< T, R, C >
 LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodiff of things like log determinants and solutions to linear systems. More...
 
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+Namespaces

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diff --git a/doc/api/html/prim_2mat_2fun_2_l_d_l_t__factor_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2_l_d_l_t__factor_8hpp_source.html new file mode 100644 index 00000000000..bc962382297 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2_l_d_l_t__factor_8hpp_source.html @@ -0,0 +1,232 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/LDLT_factor.hpp Source File + + + + + + + + + + +
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LDLT_factor.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_LDLT_FACTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_LDLT_FACTOR_HPP
+
3 
+ +
5 #include <boost/shared_ptr.hpp>
+ + +
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  // This class is conceptually similar to the corresponding Eigen class
+
14  // Any spd matrix A can be decomposed as LDL' where L is unit
+
15  // lower-triangular and D is diagonal with positive diagonal elements
+
16 
+
17  template<typename T, int R, int C>
+
18  class LDLT_factor;
+
19 
+
57  template<int R, int C, typename T>
+
58  class LDLT_factor<T, R, C> {
+
59  public:
+ +
61  : N_(0), _ldltP(new Eigen::LDLT< Eigen::Matrix<T, R, C> >()) {}
+
62 
+
63  explicit LDLT_factor(const Eigen::Matrix<T, R, C> &A)
+
64  : N_(0), _ldltP(new Eigen::LDLT< Eigen::Matrix<T, R, C> >()) {
+
65  compute(A);
+
66  }
+
67 
+
68  inline void compute(const Eigen::Matrix<T, R, C> &A) {
+
69  stan::math::check_square("LDLT_factor", "A", A);
+
70  N_ = A.rows();
+
71  _ldltP->compute(A);
+
72  }
+
73 
+
74  inline bool success() const {
+
75  using stan::math::is_nan;
+
76  // bool ret;
+
77  // ret = _ldltP->info() == Eigen::Success;
+
78  // ret = ret && _ldltP->isPositive();
+
79  // ret = ret && (_ldltP->vectorD().array() > 0).all();
+
80  // return ret;
+
81 
+
82  if (_ldltP->info() != Eigen::Success)
+
83  return false;
+
84  if (!(_ldltP->isPositive()))
+
85  return false;
+
86  Eigen::Matrix<T, Eigen::Dynamic, 1> ldltP_diag(_ldltP->vectorD());
+
87  for (int i = 0; i < ldltP_diag.size(); ++i)
+
88  if (ldltP_diag(i) <= 0 || is_nan(ldltP_diag(i)))
+
89  return false;
+
90  return true;
+
91  }
+
92 
+
93  inline T log_abs_det() const {
+
94  return _ldltP->vectorD().array().log().sum();
+
95  }
+
96 
+
97  inline void inverse(Eigen::Matrix<T, R, C> &invA) const {
+
98  invA.setIdentity(N_);
+
99  _ldltP->solveInPlace(invA);
+
100  }
+
101 
+
102  template<typename Rhs>
+
103  inline const
+
104  Eigen::internal::solve_retval<Eigen::LDLT< Eigen::Matrix<T, R, C> >, Rhs>
+
105  solve(const Eigen::MatrixBase<Rhs>& b) const {
+
106  return _ldltP->solve(b);
+
107  }
+
108 
+
109  inline Eigen::Matrix<T, R, C>
+
110  solveRight(const Eigen::Matrix<T, R, C> &B) const {
+
111  return _ldltP->solve(B.transpose()).transpose();
+
112  }
+
113 
+
114  inline Eigen::Matrix<T, Eigen::Dynamic, 1> vectorD() const {
+
115  return _ldltP->vectorD();
+
116  }
+
117 
+
118  inline Eigen::LDLT<Eigen::Matrix<T, R, C> > matrixLDLT() const {
+
119  return _ldltP->matrixLDLT();
+
120  }
+
121 
+
122  inline size_t rows() const { return N_; }
+
123  inline size_t cols() const { return N_; }
+
124 
+
125  typedef size_t size_type;
+
126  typedef double value_type;
+
127 
+
128  size_t N_;
+
129  boost::shared_ptr< Eigen::LDLT< Eigen::Matrix<T, R, C> > > _ldltP;
+
130  };
+
131  }
+
132 }
+
133 #endif
+
void inverse(Eigen::Matrix< T, R, C > &invA) const
Definition: LDLT_factor.hpp:97
+
const Eigen::internal::solve_retval< Eigen::LDLT< Eigen::Matrix< T, R, C > >, Rhs > solve(const Eigen::MatrixBase< Rhs > &b) const
+ + + +
boost::shared_ptr< Eigen::LDLT< Eigen::Matrix< T, R, C > > > _ldltP
+ +
LDLT_factor(const Eigen::Matrix< T, R, C > &A)
Definition: LDLT_factor.hpp:63
+
Eigen::Matrix< T, R, C > solveRight(const Eigen::Matrix< T, R, C > &B) const
+
(Expert) Numerical traits for algorithmic differentiation variables.
+ + +
Eigen::LDLT< Eigen::Matrix< T, R, C > > matrixLDLT() const
+
boost::shared_ptr< Eigen::LDLT< Eigen::Matrix< double, R1, C1 > > > _ldltP
This share_ptr is used to prevent copying the LDLT factorizations for mdivide_left_ldlt(ldltA, b) when ldltA is a LDLT_factor.
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > vectorD() const
+ + + + + +
void compute(const Eigen::Matrix< T, R, C > &A)
Definition: LDLT_factor.hpp:68
+
int is_nan(const fvar< T > &x)
Returns 1 if the input's value is NaN and 0 otherwise.
Definition: is_nan.hpp:22
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
int N_
+ +
+
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diff --git a/doc/api/html/prim_2mat_2fun_2cholesky__decompose_8hpp.html b/doc/api/html/prim_2mat_2fun_2cholesky__decompose_8hpp.html new file mode 100644 index 00000000000..53df541f1e3 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2cholesky__decompose_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_decompose.hpp File Reference + + + + + + + + + + +
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+Functions

template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::cholesky_decompose (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Return the lower-triangular Cholesky factor (i.e., matrix square root) of the specified square, symmetric matrix. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2cholesky__decompose_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2cholesky__decompose_8hpp_source.html new file mode 100644 index 00000000000..710c621a90a --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2cholesky__decompose_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/cholesky_decompose.hpp Source File + + + + + + + + + + +
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cholesky_decompose.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_CHOLESKY_DECOMPOSE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CHOLESKY_DECOMPOSE_HPP
+
3 
+ + + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
23  template <typename T>
+
24  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
25  cholesky_decompose(const Eigen::Matrix
+
26  <T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
27  stan::math::check_square("cholesky_decompose", "m", m);
+
28  stan::math::check_symmetric("cholesky_decompose", "m", m);
+
29  Eigen::LLT<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
+
30  llt(m.rows());
+
31  llt.compute(m);
+
32  stan::math::check_pos_definite("cholesky_decompose", "m", llt);
+
33  return llt.matrixL();
+
34  }
+
35 
+
36  }
+
37 }
+
38 #endif
+ + + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_decompose(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Return the lower-triangular Cholesky factor (i.e., matrix square root) of the specified square...
+
bool check_pos_definite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified square, symmetric matrix is positive definite.
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
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diff --git a/doc/api/html/prim_2mat_2fun_2columns__dot__product_8hpp.html b/doc/api/html/prim_2mat_2fun_2columns__dot__product_8hpp.html new file mode 100644 index 00000000000..99045a373e9 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2columns__dot__product_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/columns_dot_product.hpp File Reference + + + + + + + + + + +
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template<int R1, int C1, int R2, int C2>
Eigen::Matrix< double, 1, C1 > stan::math::columns_dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 Returns the dot product of the specified vectors. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2columns__dot__product_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2columns__dot__product_8hpp_source.html new file mode 100644 index 00000000000..75891ec4d85 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2columns__dot__product_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/columns_dot_product.hpp Source File + + + + + + + + + + +
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columns_dot_product.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_COLUMNS_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COLUMNS_DOT_PRODUCT_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
20  template<int R1, int C1, int R2, int C2>
+
21  inline Eigen::Matrix<double, 1, C1>
+
22  columns_dot_product(const Eigen::Matrix<double, R1, C1>& v1,
+
23  const Eigen::Matrix<double, R2, C2>& v2) {
+
24  stan::math::check_matching_sizes("columns_dot_product",
+
25  "v1", v1,
+
26  "v2", v2);
+
27  Eigen::Matrix<double, 1, C1> ret(1, v1.cols());
+
28  for (size_type j = 0; j < v1.cols(); ++j) {
+
29  ret(j) = v1.col(j).dot(v2.col(j));
+
30  }
+
31  return ret;
+
32  }
+
33 
+
34  }
+
35 }
+
36 #endif
+
Eigen::Matrix< fvar< T >, 1, C1 > columns_dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
+ + +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ + +
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diff --git a/doc/api/html/prim_2mat_2fun_2columns__dot__self_8hpp.html b/doc/api/html/prim_2mat_2fun_2columns__dot__self_8hpp.html new file mode 100644 index 00000000000..76e457ece2a --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2columns__dot__self_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/columns_dot_self.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< T, 1, C > stan::math::columns_dot_self (const Eigen::Matrix< T, R, C > &x)
 Returns the dot product of each column of a matrix with itself. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2columns__dot__self_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2columns__dot__self_8hpp_source.html new file mode 100644 index 00000000000..652563ffb9d --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2columns__dot__self_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/columns_dot_self.hpp Source File + + + + + + + + + + +
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columns_dot_self.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_COLUMNS_DOT_SELF_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_COLUMNS_DOT_SELF_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
14  template<typename T, int R, int C>
+
15  inline Eigen::Matrix<T, 1, C>
+
16  columns_dot_self(const Eigen::Matrix<T, R, C>& x) {
+
17  return x.colwise().squaredNorm();
+
18  }
+
19 
+
20  }
+
21 }
+
22 #endif
+ + +
Eigen::Matrix< fvar< T >, 1, C > columns_dot_self(const Eigen::Matrix< fvar< T >, R, C > &x)
+
+
+
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diff --git a/doc/api/html/prim_2mat_2fun_2crossprod_8hpp.html b/doc/api/html/prim_2mat_2fun_2crossprod_8hpp.html new file mode 100644 index 00000000000..c3f992e6efa --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2crossprod_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/crossprod.hpp File Reference + + + + + + + + + + +
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matrix_d stan::math::crossprod (const matrix_d &M)
 Returns the result of pre-multiplying a matrix by its own transpose. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2crossprod_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2crossprod_8hpp_source.html new file mode 100644 index 00000000000..f6a92bbb391 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2crossprod_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/crossprod.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_CROSSPROD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_CROSSPROD_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
16  inline matrix_d
+
17  crossprod(const matrix_d& M) {
+
18  return tcrossprod(static_cast<matrix_d>(M.transpose()));
+
19  }
+
20 
+
21  }
+
22 }
+
23 #endif
+ + +
Eigen::Matrix< fvar< T >, R, R > tcrossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: tcrossprod.hpp:17
+
Eigen::Matrix< fvar< T >, C, C > crossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: crossprod.hpp:17
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > matrix_d
Type for matrix of double values.
Definition: typedefs.hpp:23
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2determinant_8hpp.html b/doc/api/html/prim_2mat_2fun_2determinant_8hpp.html new file mode 100644 index 00000000000..6be7a95f488 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2determinant_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/determinant.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
stan::math::determinant (const Eigen::Matrix< T, R, C > &m)
 Returns the determinant of the specified square matrix. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2determinant_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2determinant_8hpp_source.html new file mode 100644 index 00000000000..04da402b295 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2determinant_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/determinant.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DETERMINANT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DETERMINANT_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
17  template <typename T, int R, int C>
+
18  inline T determinant(const Eigen::Matrix<T, R, C>& m) {
+
19  stan::math::check_square("determinant", "m", m);
+
20  return m.determinant();
+
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ +
fvar< T > determinant(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: determinant.hpp:21
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2divide_8hpp.html b/doc/api/html/prim_2mat_2fun_2divide_8hpp.html new file mode 100644 index 00000000000..74d5e8213b4 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2divide_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/divide.hpp File Reference + + + + + + + + + + +
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#include <boost/type_traits/is_arithmetic.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+
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template<int R, int C, typename T >
boost::enable_if_c< boost::is_arithmetic< T >::value, Eigen::Matrix< double, R, C > >::type stan::math::divide (const Eigen::Matrix< double, R, C > &m, T c)
 Return specified matrix divided by specified scalar. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2divide_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2divide_8hpp_source.html new file mode 100644 index 00000000000..147f847bdaf --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2divide_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/divide.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DIVIDE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DIVIDE_HPP
+
3 
+
4 #include <boost/type_traits/is_arithmetic.hpp>
+
5 #include <boost/utility/enable_if.hpp>
+ +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
19  template <int R, int C, typename T>
+
20  inline
+
21  typename boost::enable_if_c<boost::is_arithmetic<T>::value,
+
22  Eigen::Matrix<double, R, C> >::type
+
23  divide(const Eigen::Matrix<double, R, C>& m,
+
24  T c) {
+
25  return m / c;
+
26  }
+
27 
+
28  }
+
29 }
+
30 #endif
+ +
Eigen::Matrix< fvar< T >, R, C > divide(const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
Definition: divide.hpp:16
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diff --git a/doc/api/html/prim_2mat_2fun_2dot__product_8hpp.html b/doc/api/html/prim_2mat_2fun_2dot__product_8hpp.html new file mode 100644 index 00000000000..a8c6c0571ab --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2dot__product_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/dot_product.hpp File Reference + + + + + + + + + + +
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template<int R1, int C1, int R2, int C2>
double stan::math::dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 Returns the dot product of the specified vectors. More...
 
double stan::math::dot_product (const double *v1, const double *v2, size_t length)
 Returns the dot product of the specified arrays of doubles. More...
 
double stan::math::dot_product (const std::vector< double > &v1, const std::vector< double > &v2)
 Returns the dot product of the specified arrays of doubles. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2dot__product_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2dot__product_8hpp_source.html new file mode 100644 index 00000000000..4b720150048 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2dot__product_8hpp_source.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/dot_product.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DOT_PRODUCT_HPP
+
3 
+ + + +
7 #include <vector>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
21  template<int R1, int C1, int R2, int C2>
+
22  inline double dot_product(const Eigen::Matrix<double, R1, C1>& v1,
+
23  const Eigen::Matrix<double, R2, C2>& v2) {
+
24  stan::math::check_vector("dot_product", "v1", v1);
+
25  stan::math::check_vector("dot_product", "v2", v2);
+ +
27  "v1", v1,
+
28  "v2", v2);
+
29  return v1.dot(v2);
+
30  }
+
37  inline double dot_product(const double* v1, const double* v2,
+
38  size_t length) {
+
39  double result = 0;
+
40  for (size_t i = 0; i < length; i++)
+
41  result += v1[i] * v2[i];
+
42  return result;
+
43  }
+
50  inline double dot_product(const std::vector<double>& v1,
+
51  const std::vector<double>& v2) {
+ +
53  "v1", v1,
+
54  "v2", v2);
+
55  return dot_product(&v1[0], &v2[0], v1.size());
+
56  }
+
57 
+
58  }
+
59 }
+
60 #endif
+
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
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diff --git a/doc/api/html/prim_2mat_2fun_2dot__self_8hpp.html b/doc/api/html/prim_2mat_2fun_2dot__self_8hpp.html new file mode 100644 index 00000000000..233732102ad --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2dot__self_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/dot_self.hpp File Reference + + + + + + + + + + +
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template<int R, int C>
double stan::math::dot_self (const Eigen::Matrix< double, R, C > &v)
 Returns the dot product of the specified vector with itself. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2dot__self_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2dot__self_8hpp_source.html new file mode 100644 index 00000000000..eb63415ca84 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2dot__self_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/dot_self.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_DOT_SELF_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_DOT_SELF_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
17  template <int R, int C>
+
18  inline double dot_self(const Eigen::Matrix<double, R, C>& v) {
+
19  stan::math::check_vector("dot_self", "v", v);
+
20  return v.squaredNorm();
+
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ +
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+ + +
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diff --git a/doc/api/html/prim_2mat_2fun_2exp_8hpp.html b/doc/api/html/prim_2mat_2fun_2exp_8hpp.html new file mode 100644 index 00000000000..ece58ab9b4d --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2exp_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/exp.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
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template<typename T , int Rows, int Cols>
Eigen::Matrix< T, Rows, Cols > stan::math::exp (const Eigen::Matrix< T, Rows, Cols > &m)
 Return the element-wise exponentiation of the matrix or vector. More...
 
template<int Rows, int Cols>
Eigen::Matrix< double, Rows, Cols > stan::math::exp (const Eigen::Matrix< double, Rows, Cols > &m)
 
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diff --git a/doc/api/html/prim_2mat_2fun_2exp_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2exp_8hpp_source.html new file mode 100644 index 00000000000..c93db248768 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2exp_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_EXP_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_EXP_HPP
+
3 
+ +
5 #include <boost/math/special_functions/fpclassify.hpp>
+
6 #include <limits>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
17  template<typename T, int Rows, int Cols>
+
18  inline Eigen::Matrix<T, Rows, Cols>
+
19  exp(const Eigen::Matrix<T, Rows, Cols>& m) {
+
20  return m.array().exp().matrix();
+
21  }
+
22 
+
23  // FIXME:
+
24  // specialization not needed once Eigen fixes issue:
+
25  // http:// eigen.tuxfamily.org/bz/show_bug.cgi?id=859
+
26  template<int Rows, int Cols>
+
27  inline Eigen::Matrix<double, Rows, Cols>
+
28  exp(const Eigen::Matrix<double, Rows, Cols>& m) {
+
29  Eigen::Matrix<double, Rows, Cols> mat = m.array().exp().matrix();
+
30  for (int i = 0, size_ = mat.size(); i < size_; i++)
+
31  if (boost::math::isnan(m(i)))
+
32  mat(i) = std::numeric_limits<double>::quiet_NaN();
+
33  return mat;
+
34  }
+
35 
+
36  }
+
37 }
+
38 #endif
+ +
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
size_t size_
Definition: dot_self.hpp:18
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diff --git a/doc/api/html/prim_2mat_2fun_2inverse_8hpp.html b/doc/api/html/prim_2mat_2fun_2inverse_8hpp.html new file mode 100644 index 00000000000..58de260f8ee --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2inverse_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/inverse.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< T, R, C > stan::math::inverse (const Eigen::Matrix< T, R, C > &m)
 Returns the inverse of the specified matrix. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2inverse_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2inverse_8hpp_source.html new file mode 100644 index 00000000000..1f9b308b43b --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2inverse_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/inverse.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_INVERSE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_INVERSE_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
15  template <typename T, int R, int C>
+
16  inline
+
17  Eigen::Matrix<T, R, C>
+
18  inverse(const Eigen::Matrix<T, R, C>& m) {
+
19  stan::math::check_square("inverse", "m", m);
+
20  return m.inverse();
+
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ +
Eigen::Matrix< fvar< T >, R, C > inverse(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: inverse.hpp:20
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2log_8hpp.html b/doc/api/html/prim_2mat_2fun_2log_8hpp.html new file mode 100644 index 00000000000..838ddfb476a --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log.hpp File Reference + + + + + + + + + + +
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template<typename T , int Rows, int Cols>
Eigen::Matrix< T, Rows, Cols > stan::math::log (const Eigen::Matrix< T, Rows, Cols > &m)
 Return the element-wise logarithm of the matrix or vector. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2log_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2log_8hpp_source.html new file mode 100644 index 00000000000..11937825d1e --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_LOG_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
15  template<typename T, int Rows, int Cols>
+
16  inline Eigen::Matrix<T, Rows, Cols>
+
17  log(const Eigen::Matrix<T, Rows, Cols>& m) {
+
18  return m.array().log().matrix();
+
19  }
+
20 
+
21 
+
22  }
+
23 }
+
24 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2log__determinant_8hpp.html b/doc/api/html/prim_2mat_2fun_2log__determinant_8hpp.html new file mode 100644 index 00000000000..eb06cd06b31 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__determinant_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_determinant.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
stan::math::log_determinant (const Eigen::Matrix< T, R, C > &m)
 Returns the log absolute determinant of the specified square matrix. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2log__determinant_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2log__determinant_8hpp_source.html new file mode 100644 index 00000000000..cbbfc068ac2 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__determinant_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_determinant.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_LOG_DETERMINANT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_LOG_DETERMINANT_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
17  template <typename T, int R, int C>
+
18  inline T log_determinant(const Eigen::Matrix<T, R, C>& m) {
+
19  stan::math::check_square("log_determinant", "m", m);
+
20  return m.colPivHouseholderQr().logAbsDeterminant();
+
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ +
fvar< T > log_determinant(const Eigen::Matrix< fvar< T >, R, C > &m)
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2log__determinant__ldlt_8hpp.html b/doc/api/html/prim_2mat_2fun_2log__determinant__ldlt_8hpp.html new file mode 100644 index 00000000000..57111f5bc66 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__determinant__ldlt_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_determinant_ldlt.hpp File Reference + + + + + + + + + + +
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template<int R, int C, typename T >
stan::math::log_determinant_ldlt (stan::math::LDLT_factor< T, R, C > &A)
 
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diff --git a/doc/api/html/prim_2mat_2fun_2log__determinant__ldlt_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2log__determinant__ldlt_8hpp_source.html new file mode 100644 index 00000000000..f19f1cebcbf --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__determinant__ldlt_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_determinant_ldlt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_LOG_DETERMINANT_LDLT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_LOG_DETERMINANT_LDLT_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  // Returns log(abs(det(A))) given a LDLT_factor of A
+
10  template<int R, int C, typename T>
+
11  inline T
+ +
13  return A.log_abs_det();
+
14  }
+
15 
+
16  }
+
17 }
+
18 #endif
+ + + +
LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodi...
Definition: LDLT_factor.hpp:58
+
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+
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diff --git a/doc/api/html/prim_2mat_2fun_2log__determinant__spd_8hpp.html b/doc/api/html/prim_2mat_2fun_2log__determinant__spd_8hpp.html new file mode 100644 index 00000000000..4efe04c16b2 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__determinant__spd_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_determinant_spd.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
stan::math::log_determinant_spd (const Eigen::Matrix< T, R, C > &m)
 Returns the log absolute determinant of the specified square matrix. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2log__determinant__spd_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2log__determinant__spd_8hpp_source.html new file mode 100644 index 00000000000..8a8677c1771 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__determinant__spd_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_determinant_spd.hpp Source File + + + + + + + + + + +
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log_determinant_spd.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_LOG_DETERMINANT_SPD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_LOG_DETERMINANT_SPD_HPP
+
3 
+ + +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
18  template <typename T, int R, int C>
+
19  inline T log_determinant_spd(const Eigen::Matrix<T, R, C>& m) {
+
20  using std::log;
+
21  stan::math::check_square("log_determinant_spd", "m", m);
+
22  // Eigen::TriangularView< Eigen::Matrix<T, R, C>, Eigen::Lower >
+
23  // L(m.llt().matrixL());
+
24  // T ret(0.0);
+
25  // for (size_t i = 0; i < L.rows(); i++)
+
26  // ret += log(L(i, i));
+
27  // return 2*ret;
+
28  return m.ldlt().vectorD().array().log().sum();
+
29  }
+
30 
+
31  }
+
32 }
+
33 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
T log_determinant_spd(const Eigen::Matrix< T, R, C > &m)
Returns the log absolute determinant of the specified square matrix.
+ +
+
+
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diff --git a/doc/api/html/prim_2mat_2fun_2log__softmax_8hpp.html b/doc/api/html/prim_2mat_2fun_2log__softmax_8hpp.html new file mode 100644 index 00000000000..03541145052 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__softmax_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_softmax.hpp File Reference + + + + + + + + + + +
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+
#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/log_sum_exp.hpp>
+#include <cmath>
+#include <sstream>
+#include <stdexcept>
+
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::log_softmax (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v)
 Return the natural logarithm of the softmax of the specified vector. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2log__softmax_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2log__softmax_8hpp_source.html new file mode 100644 index 00000000000..2d6c3279bdf --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__softmax_8hpp_source.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_softmax.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_LOG_SOFTMAX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_LOG_SOFTMAX_HPP
+
3 
+ + + +
7 #include <cmath>
+
8 #include <sstream>
+
9 #include <stdexcept>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
42  template <typename T>
+
43  inline Eigen::Matrix<T, Eigen::Dynamic, 1>
+
44  log_softmax(const Eigen::Matrix<T, Eigen::Dynamic, 1>& v) {
+
45  using std::exp;
+
46  using std::log;
+ +
48  stan::math::check_nonzero_size("log_softmax", "v", v);
+
49  Eigen::Matrix<T, Eigen::Dynamic, 1> theta(v.size());
+
50  T z = log_sum_exp(v);
+
51  for (int i = 0; i < v.size(); ++i)
+
52  theta(i) = v(i) - z;
+
53  return theta;
+
54  // T sum(0.0);
+
55  // T max_v = v.maxCoeff();
+
56  // for (int i = 0; i < v.size(); ++i)
+
57  // sum += exp(v(i) - max_v); // log_sum_exp trick
+
58  // T log_sum = log(sum);
+
59  // for (int i = 0; i < v.size(); ++i)
+
60  // theta(i) = (v(i) - max_v) - log_sum;
+
61  // return theta;
+
62  }
+
63 
+
64  }
+
65 }
+
66 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > log_softmax(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
Definition: log_softmax.hpp:16
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + + +
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diff --git a/doc/api/html/prim_2mat_2fun_2log__sum__exp_8hpp.html b/doc/api/html/prim_2mat_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..1dcbff50376 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
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log_sum_exp.hpp File Reference
+
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+
#include <stan/math/prim/scal/fun/log1p.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <limits>
+#include <vector>
+
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template<int R, int C>
double stan::math::log_sum_exp (const Eigen::Matrix< double, R, C > &x)
 Return the log of the sum of the exponentiated values of the specified matrix of values. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..43b765de467 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_LOG_SUM_EXP_HPP
+
3 
+ + +
6 #include <boost/math/tools/promotion.hpp>
+
7 #include <limits>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
27  template <int R, int C>
+
28  double log_sum_exp(const Eigen::Matrix<double, R, C>& x) {
+
29  using std::numeric_limits;
+
30  using std::log;
+
31  using std::exp;
+
32  double max = -numeric_limits<double>::infinity();
+
33  for (int i = 0; i < x.size(); i++)
+
34  if (x(i) > max)
+
35  max = x(i);
+
36 
+
37  double sum = 0.0;
+
38  for (int i = 0; i < x.size(); i++)
+
39  if (x(i) != -numeric_limits<double>::infinity())
+
40  sum += exp(x(i) - max);
+
41 
+
42  return max + log(sum);
+
43  }
+
44 
+
45  }
+
46 }
+
47 
+
48 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left_8hpp.html b/doc/api/html/prim_2mat_2fun_2mdivide__left_8hpp.html new file mode 100644 index 00000000000..56b7c4aa244 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_left (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 Returns the solution of the system Ax=b. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2mdivide__left_8hpp_source.html new file mode 100644 index 00000000000..352e2fca89b --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left.hpp Source File + + + + + + + + + + +
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mdivide_left.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + + +
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
21  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
22  inline
+
23  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
24  R1, C2>
+
25  mdivide_left(const Eigen::Matrix<T1, R1, C1> &A,
+
26  const Eigen::Matrix<T2, R2, C2> &b) {
+
27  stan::math::check_square("mdivide_left", "A", A);
+
28  stan::math::check_multiplicable("mdivide_left",
+
29  "A", A,
+
30  "b", b);
+
31  return promote_common<Eigen::Matrix<T1, R1, C1>,
+
32  Eigen::Matrix<T2, R1, C1> >(A)
+
33  .lu()
+
34  .solve(promote_common<Eigen::Matrix<T1, R2, C2>,
+
35  Eigen::Matrix<T2, R2, C2> >(b));
+
36  }
+
37 
+
38  }
+
39 }
+
40 #endif
+
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_left(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ + + +
common_type< T1, T2 >::type promote_common(const F &u)
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left__ldlt_8hpp.html b/doc/api/html/prim_2mat_2fun_2mdivide__left__ldlt_8hpp.html new file mode 100644 index 00000000000..3f56a1939d9 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left__ldlt_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left_ldlt.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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mdivide_left_ldlt.hpp File Reference
+
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+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/LDLT_factor.hpp>
+#include <stan/math/prim/mat/err/check_multiplicable.hpp>
+#include <stan/math/prim/mat/fun/promote_common.hpp>
+#include <boost/type_traits/is_same.hpp>
+
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template<int R1, int C1, int R2, int C2, typename T1 , typename T2 >
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html new file mode 100644 index 00000000000..305841c415e --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left_ldlt.hpp Source File + + + + + + + + + + +
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mdivide_left_ldlt.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_LDLT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_LDLT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + + +
9 #include <boost/type_traits/is_same.hpp>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
22  template <int R1, int C1, int R2, int C2, typename T1, typename T2>
+
23  inline Eigen::Matrix<typename
+
24  boost::math::tools::promote_args<T1, T2>::type,
+
25  R1, C2>
+ +
27  const Eigen::Matrix<T2, R2, C2> &b) {
+
28  stan::math::check_multiplicable("mdivide_left_ldlt",
+
29  "A", A,
+
30  "b", b);
+
31 
+
32  return A.solve(promote_common<Eigen::Matrix<T1, R2, C2>,
+
33  Eigen::Matrix<T2, R2, C2> >(b));
+
34  }
+
35 
+
36  }
+
37 }
+
38 #endif
+ + + +
common_type< T1, T2 >::type promote_common(const F &u)
+ + +
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt(const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
Returns the solution of the system Ax=b given an LDLT_factor of A.
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left__spd_8hpp.html b/doc/api/html/prim_2mat_2fun_2mdivide__left__spd_8hpp.html new file mode 100644 index 00000000000..5afe3e06b2f --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left__spd_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left_spd.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_left_spd (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 Returns the solution of the system Ax=b where A is symmetric positive definite. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left__spd_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2mdivide__left__spd_8hpp_source.html new file mode 100644 index 00000000000..e9a06537822 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left__spd_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left_spd.hpp Source File + + + + + + + + + + +
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mdivide_left_spd.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_SPD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_SPD_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + + + + +
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
24  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
25  inline
+
26  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
27  R1, C2>
+
28  mdivide_left_spd(const Eigen::Matrix<T1, R1, C1> &A,
+
29  const Eigen::Matrix<T2, R2, C2> &b) {
+
30  stan::math::check_symmetric("mdivide_left_spd", "A", A);
+
31  stan::math::check_pos_definite("mdivide_left_spd", "A", A);
+
32  stan::math::check_square("mdivide_left_spd", "A", A);
+
33  stan::math::check_multiplicable("mdivide_left_spd",
+
34  "A", A,
+
35  "b", b);
+
36  return promote_common<Eigen::Matrix<T1, R1, C1>,
+
37  Eigen::Matrix<T2, R1, C1> >(A)
+
38  .llt()
+
39  .solve(promote_common<Eigen::Matrix<T1, R2, C2>,
+
40  Eigen::Matrix<T2, R2, C2> >(b));
+
41  }
+
42 
+
43  }
+
44 }
+
45 #endif
+ + + + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_spd(const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
Returns the solution of the system Ax=b where A is symmetric positive definite.
+
common_type< T1, T2 >::type promote_common(const F &u)
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
bool check_pos_definite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified square, symmetric matrix is positive definite.
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
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+
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left__tri_8hpp.html b/doc/api/html/prim_2mat_2fun_2mdivide__left__tri_8hpp.html new file mode 100644 index 00000000000..1c3bf2954bf --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left__tri_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left_tri.hpp File Reference + + + + + + + + + + +
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template<int TriView, typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_left_tri (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 Returns the solution of the system Ax=b when A is triangular. More...
 
template<int TriView, typename T , int R1, int C1>
Eigen::Matrix< T, R1, C1 > stan::math::mdivide_left_tri (const Eigen::Matrix< T, R1, C1 > &A)
 Returns the solution of the system Ax=b when A is triangular and b=I. More...
 
+
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left__tri_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2mdivide__left__tri_8hpp_source.html new file mode 100644 index 00000000000..66bbe50f145 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left__tri_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left_tri.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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mdivide_left_tri.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_TRI_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_TRI_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + + +
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
22  template <int TriView, typename T1, typename T2,
+
23  int R1, int C1, int R2, int C2>
+
24  inline
+
25  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
26  R1, C2>
+
27  mdivide_left_tri(const Eigen::Matrix<T1, R1, C1> &A,
+
28  const Eigen::Matrix<T2, R2, C2> &b) {
+
29  stan::math::check_square("mdivide_left_tri", "A", A);
+
30  stan::math::check_multiplicable("mdivide_left_tri",
+
31  "A", A,
+
32  "b", b);
+
33  return promote_common<Eigen::Matrix<T1, R1, C1>,
+
34  Eigen::Matrix<T2, R1, C1> >(A)
+
35  .template triangularView<TriView>()
+
36  .solve(promote_common<Eigen::Matrix<T1, R2, C2>,
+
37  Eigen::Matrix<T2, R2, C2> >(b));
+
38  }
+
39 
+
47  template<int TriView, typename T, int R1, int C1>
+
48  inline
+
49  Eigen::Matrix<T, R1, C1>
+
50  mdivide_left_tri(const Eigen::Matrix<T, R1, C1> &A) {
+
51  stan::math::check_square("mdivide_left_tri", "A", A);
+
52  int n = A.rows();
+
53  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> b;
+
54  b.setIdentity(n, n);
+
55  A.template triangularView<TriView>().solveInPlace(b);
+
56  return b;
+
57  }
+
58 
+
59  }
+
60 }
+
61 #endif
+ + + +
common_type< T1, T2 >::type promote_common(const F &u)
+
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_tri(const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
Returns the solution of the system Ax=b when A is triangular.
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left__tri__low_8hpp.html b/doc/api/html/prim_2mat_2fun_2mdivide__left__tri__low_8hpp.html new file mode 100644 index 00000000000..6138c49c9cd --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left__tri__low_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left_tri_low.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_left_tri_low (const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
 
template<typename T , int R1, int C1>
Eigen::Matrix< T, R1, C1 > stan::math::mdivide_left_tri_low (const Eigen::Matrix< T, R1, C1 > &A)
 
+
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__left__tri__low_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2mdivide__left__tri__low_8hpp_source.html new file mode 100644 index 00000000000..4ab2a2b1681 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__left__tri__low_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_left_tri_low.hpp Source File + + + + + + + + + + +
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mdivide_left_tri_low.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_TRI_LOW_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_LEFT_TRI_LOW_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + + +
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
13  inline
+
14  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
15  R1, C2>
+
16  mdivide_left_tri_low(const Eigen::Matrix<T1, R1, C1> &A,
+
17  const Eigen::Matrix<T2, R2, C2> &b) {
+
18  stan::math::check_square("mdivide_left_tri_low", "A", A);
+
19  stan::math::check_multiplicable("mdivide_left_tri_low",
+
20  "A", A,
+
21  "b", b);
+
22  // return promote_common<Eigen::Matrix<T1, R1, C1>,
+
23  // Eigen::Matrix<T2, R1, C1> >(A)
+
24  // .template triangularView<Eigen::Lower>()
+
25  // .solve( promote_common<Eigen::Matrix<T1, R2, C2>,
+
26  // Eigen::Matrix<T2, R2, C2> >(b) );
+
27  return mdivide_left_tri<Eigen::Lower, T1, T2, R1, C1, R2, C2>(A, b);
+
28  }
+
29  template <typename T, int R1, int C1>
+
30  inline
+
31  Eigen::Matrix<T, R1, C1>
+
32  mdivide_left_tri_low(const Eigen::Matrix<T, R1, C1> &A) {
+
33  stan::math::check_square("mdivide_left_tri_low", "A", A);
+
34  // int n = A.rows();
+
35  // Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> b;
+
36  // b.setIdentity(n, n);
+
37  // A.template triangularView<Eigen::Lower>().solveInPlace(b);
+
38  // return b;
+
39  return mdivide_left_tri<Eigen::Lower, T, R1, C1>(A);
+
40  }
+
41 
+
42  }
+
43 }
+
44 #endif
+ + + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_left_tri_low(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__right_8hpp.html b/doc/api/html/prim_2mat_2fun_2mdivide__right_8hpp.html new file mode 100644 index 00000000000..92deafacb68 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__right_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_right (const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
 Returns the solution of the system Ax=b. More...
 
+
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__right_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2mdivide__right_8hpp_source.html new file mode 100644 index 00000000000..d28c00cdf70 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__right_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + + + +
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
22  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
23  inline
+
24  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
25  R1, C2>
+
26  mdivide_right(const Eigen::Matrix<T1, R1, C1> &b,
+
27  const Eigen::Matrix<T2, R2, C2> &A) {
+
28  stan::math::check_square("mdivide_right", "A", A);
+
29  stan::math::check_multiplicable("mdivide_right",
+
30  "b", b,
+
31  "A", A);
+
32  // FIXME: This is nice and general but likely slow.
+
33  return transpose(mdivide_left(transpose(A), transpose(b)));
+
34 // return promote_common<Eigen::Matrix<T1, R2, C2>,
+
35 // Eigen::Matrix<T2, R2, C2> >(A)
+
36 // .transpose()
+
37 // .lu()
+
38 // .solve(promote_common<Eigen::Matrix<T1, R1, C1>,
+
39 // Eigen::Matrix<T2, R1, C1> >(b)
+
40 // .transpose())
+
41 // .transpose();
+
42  }
+
43 
+
44  }
+
45 }
+
46 #endif
+
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_left(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+ + + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_right(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__right__tri__low_8hpp.html b/doc/api/html/prim_2mat_2fun_2mdivide__right__tri__low_8hpp.html new file mode 100644 index 00000000000..c633d647219 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__right__tri__low_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right_tri_low.hpp File Reference + + + + + + + + + + +
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mdivide_right_tri_low.hpp File Reference
+
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+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/mdivide_right_tri.hpp>
+#include <stan/math/prim/mat/fun/promote_common.hpp>
+
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template<typename T1 , typename T2 , int R1, int C1, int R2, int C2>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > stan::math::mdivide_right_tri_low (const Eigen::Matrix< T1, R1, C1 > &b, const Eigen::Matrix< T2, R2, C2 > &A)
 Returns the solution of the system tri(A)x=b when tri(A) is a lower triangular view of the matrix A. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2mdivide__right__tri__low_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2mdivide__right__tri__low_8hpp_source.html new file mode 100644 index 00000000000..9179ba77654 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2mdivide__right__tri__low_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/mdivide_right_tri_low.hpp Source File + + + + + + + + + + +
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mdivide_right_tri_low.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_TRI_LOW_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MDIVIDE_RIGHT_TRI_LOW_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
21  template <typename T1, typename T2, int R1, int C1, int R2, int C2>
+
22  inline
+
23  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
24  R1, C2>
+
25  mdivide_right_tri_low(const Eigen::Matrix<T1, R1, C1> &b,
+
26  const Eigen::Matrix<T2, R2, C2> &A) {
+
27  return mdivide_right_tri<Eigen::Lower>
+
28  (promote_common<Eigen::Matrix<T1, R1, C1>,
+
29  Eigen::Matrix<T2, R1, C1> >(b),
+
30  promote_common<Eigen::Matrix<T1, R2, C2>,
+
31  Eigen::Matrix<T2, R2, C2> >(A));
+
32  }
+
33 
+
34  }
+
35 }
+
36 #endif
+ + + +
common_type< T1, T2 >::type promote_common(const F &u)
+ +
Eigen::Matrix< fvar< T >, R1, C1 > mdivide_right_tri_low(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
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diff --git a/doc/api/html/prim_2mat_2fun_2multiply_8hpp.html b/doc/api/html/prim_2mat_2fun_2multiply_8hpp.html new file mode 100644 index 00000000000..8fb66644471 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2multiply_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/multiply.hpp File Reference + + + + + + + + + + +
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multiply.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/err/check_matching_sizes.hpp>
+#include <stan/math/prim/mat/err/check_multiplicable.hpp>
+#include <boost/type_traits/is_arithmetic.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <stdexcept>
+
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template<int R, int C, typename T >
boost::enable_if_c< boost::is_arithmetic< T >::value, Eigen::Matrix< double, R, C > >::type stan::math::multiply (const Eigen::Matrix< double, R, C > &m, T c)
 Return specified matrix multiplied by specified scalar. More...
 
template<int R, int C, typename T >
boost::enable_if_c< boost::is_arithmetic< T >::value, Eigen::Matrix< double, R, C > >::type stan::math::multiply (T c, const Eigen::Matrix< double, R, C > &m)
 Return specified scalar multiplied by specified matrix. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< double, R1, C2 > stan::math::multiply (const Eigen::Matrix< double, R1, C1 > &m1, const Eigen::Matrix< double, R2, C2 > &m2)
 Return the product of the specified matrices. More...
 
template<int C1, int R2>
double stan::math::multiply (const Eigen::Matrix< double, 1, C1 > &rv, const Eigen::Matrix< double, R2, 1 > &v)
 Return the scalar product of the specified row vector and specified column vector. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2multiply_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2multiply_8hpp_source.html new file mode 100644 index 00000000000..918a0c438f5 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2multiply_8hpp_source.html @@ -0,0 +1,175 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/multiply.hpp Source File + + + + + + + + + + +
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multiply.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_MULTIPLY_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MULTIPLY_HPP
+
3 
+ + + +
7 #include <boost/type_traits/is_arithmetic.hpp>
+
8 #include <boost/utility/enable_if.hpp>
+
9 #include <stdexcept>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
22  template <int R, int C, typename T>
+
23  inline
+
24  typename boost::enable_if_c<boost::is_arithmetic<T>::value,
+
25  Eigen::Matrix<double, R, C> >::type
+
26  multiply(const Eigen::Matrix<double, R, C>& m,
+
27  T c) {
+
28  return c * m;
+
29  }
+
30 
+
31  // FIXME: apply above pattern everywhere below to remove
+
32  // extra defs, etc.
+
33 
+
42  template <int R, int C, typename T>
+
43  inline
+
44  typename boost::enable_if_c<boost::is_arithmetic<T>::value,
+
45  Eigen::Matrix<double, R, C> >::type
+
46  multiply(T c,
+
47  const Eigen::Matrix<double, R, C>& m) {
+
48  return c * m;
+
49  }
+
50 
+
61  template<int R1, int C1, int R2, int C2>
+
62  inline Eigen::Matrix<double, R1, C2>
+
63  multiply(const Eigen::Matrix<double, R1, C1>& m1,
+
64  const Eigen::Matrix<double, R2, C2>& m2) {
+ +
66  "m1", m1,
+
67  "m2", m2);
+
68  return m1*m2;
+
69  }
+
70 
+
80  template<int C1, int R2>
+
81  inline double multiply(const Eigen::Matrix<double, 1, C1>& rv,
+
82  const Eigen::Matrix<double, R2, 1>& v) {
+ +
84  "rv", rv,
+
85  "v", v);
+
86  if (rv.size() != v.size())
+
87  throw std::domain_error("rv.size() != v.size()");
+
88  return rv.dot(v);
+
89  }
+
90 
+
91  }
+
92 }
+
93 #endif
+ + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html b/doc/api/html/prim_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html new file mode 100644 index 00000000000..bef663bbd89 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/multiply_lower_tri_self_transpose.hpp File Reference + + + + + + + + + + +
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multiply_lower_tri_self_transpose.hpp File Reference
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matrix_d stan::math::multiply_lower_tri_self_transpose (const matrix_d &L)
 Returns the result of multiplying the lower triangular portion of the input matrix by its own transpose. More...
 
+
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diff --git a/doc/api/html/prim_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html new file mode 100644 index 00000000000..02b9e9073f9 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/multiply_lower_tri_self_transpose.hpp Source File + + + + + + + + + + +
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multiply_lower_tri_self_transpose.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_MULTIPLY_LOWER_TRI_SELF_TRANSPOSE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_MULTIPLY_LOWER_TRI_SELF_TRANSPOSE_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
17  inline matrix_d
+ +
19  int K = L.rows();
+
20  int J = L.cols();
+
21  int k;
+
22  matrix_d LLt(K, K);
+
23  matrix_d Lt = L.transpose();
+
24 
+
25  if (K == 0)
+
26  return matrix_d(0, 0);
+
27  if (K == 1) {
+
28  matrix_d result(1, 1);
+
29  result(0, 0) = L(0, 0) * L(0, 0);
+
30  return result;
+
31  }
+
32 
+
33  for (int m = 0; m < K; ++m) {
+
34  k = (J < m + 1) ? J : m + 1;
+
35  LLt(m, m) = Lt.col(m).head(k).squaredNorm();
+
36  for (int n = (m + 1); n < K; ++n) {
+
37  LLt(n, m) = LLt(m, n) = Lt.col(m).head(k).dot(Lt.col(n).head(k));
+
38  }
+
39  }
+
40  return LLt;
+
41  }
+
42 
+
43  }
+
44 }
+
45 #endif
+ +
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose(const Eigen::Matrix< fvar< T >, R, C > &m)
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > matrix_d
Type for matrix of double values.
Definition: typedefs.hpp:23
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2qr___q_8hpp.html b/doc/api/html/prim_2mat_2fun_2qr___q_8hpp.html new file mode 100644 index 00000000000..af691d09588 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2qr___q_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/qr_Q.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::qr_Q (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 
+
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diff --git a/doc/api/html/prim_2mat_2fun_2qr___q_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2qr___q_8hpp_source.html new file mode 100644 index 00000000000..b6bbd86e977 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2qr___q_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/qr_Q.hpp Source File + + + + + + + + + + +
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qr_Q.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_QR_Q_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_QR_Q_HPP
+
3 
+ + + +
7 #include <Eigen/QR>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
14  qr_Q(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
15  typedef Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrix_t;
+
16  stan::math::check_nonzero_size("qr_Q", "m", m);
+
17  stan::math::check_greater_or_equal("qr_Q", "m.rows()",
+
18  static_cast<size_t>(m.rows()),
+
19  static_cast<size_t>(m.cols()));
+
20 
+
21  Eigen::HouseholderQR<matrix_t> qr(m.rows(), m.cols());
+
22  qr.compute(m);
+
23  matrix_t Q = qr.householderQ();
+
24  for (int i = 0; i < m.cols(); i++)
+
25  if (qr.matrixQR().coeff(i, i) < 0)
+
26  Q.col(i) *= -1.0;
+
27  return Q;
+
28  }
+
29 
+
30  }
+
31 }
+
32 #endif
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+ +
Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > qr_Q(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > &m)
Definition: qr_Q.hpp:15
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+ + + +
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diff --git a/doc/api/html/prim_2mat_2fun_2qr___r_8hpp.html b/doc/api/html/prim_2mat_2fun_2qr___r_8hpp.html new file mode 100644 index 00000000000..4ffe8c4ae86 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2qr___r_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/qr_R.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::qr_R (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 
+
+
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diff --git a/doc/api/html/prim_2mat_2fun_2qr___r_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2qr___r_8hpp_source.html new file mode 100644 index 00000000000..74e30b63437 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2qr___r_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/qr_R.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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qr_R.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_QR_R_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_QR_R_HPP
+
3 
+ + + +
7 #include <Eigen/QR>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
14  qr_R(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
15  typedef Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> matrix_t;
+
16  stan::math::check_nonzero_size("qr_R", "m", m);
+ +
18  "m.rows()",
+
19  static_cast<size_t>(m.rows()),
+
20  static_cast<size_t>(m.cols()));
+
21  Eigen::HouseholderQR<matrix_t> qr(m.rows(), m.cols());
+
22  qr.compute(m);
+
23  matrix_t R = qr.matrixQR();
+
24  if (m.rows() > m.cols())
+
25  R.bottomRows(m.rows() - m.cols()).setZero();
+
26  for (int i = 0; i < R.cols(); i++) {
+
27  for (int j = 0; j < i; j++)
+
28  R.coeffRef(i, j) = 0.0;
+
29  if (R(i, i) < 0)
+
30  R.row(i) *= -1.0;
+
31  }
+
32  return R;
+
33  }
+
34  }
+
35 }
+
36 #endif
+
bool check_greater_or_equal(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is greater or equal than low.
+
Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > qr_R(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, Eigen::Dynamic > &m)
Definition: qr_R.hpp:15
+ +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+ + + +
+
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diff --git a/doc/api/html/prim_2mat_2fun_2quad__form_8hpp.html b/doc/api/html/prim_2mat_2fun_2quad__form_8hpp.html new file mode 100644 index 00000000000..6983d843fce --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2quad__form_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/quad_form.hpp File Reference + + + + + + + + + + +
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template<int RA, int CA, int RB, int CB, typename T >
Eigen::Matrix< T, CB, CB > stan::math::quad_form (const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, CB > &B)
 Compute B^T A B. More...
 
template<int RA, int CA, int RB, typename T >
stan::math::quad_form (const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, 1 > &B)
 
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diff --git a/doc/api/html/prim_2mat_2fun_2quad__form_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2quad__form_8hpp_source.html new file mode 100644 index 00000000000..24a42d84242 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2quad__form_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/quad_form.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_QUAD_FORM_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_QUAD_FORM_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits.hpp>
+ + + + + + + +
13 
+
14 namespace stan {
+
15  namespace math {
+
19  template<int RA, int CA, int RB, int CB, typename T>
+
20  inline Eigen::Matrix<T, CB, CB>
+
21  quad_form(const Eigen::Matrix<T, RA, CA>& A,
+
22  const Eigen::Matrix<T, RB, CB>& B) {
+ +
24  stan::math::check_square("quad_form", "A", A);
+ +
26  "A", A,
+
27  "B", B);
+
28  return multiply(stan::math::transpose(B), multiply(A, B));
+
29  }
+
30 
+
31  template<int RA, int CA, int RB, typename T>
+
32  inline T
+
33  quad_form(const Eigen::Matrix<T, RA, CA>& A,
+
34  const Eigen::Matrix<T, RB, 1>& B) {
+ + +
37 
+
38  stan::math::check_square("quad_form", "A", A);
+ +
40  "A", A,
+
41  "B", B);
+
42  return dot_product(B, multiply(A, B));
+
43  }
+
44 
+
45  }
+
46 }
+
47 
+
48 #endif
+
49 
+ + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ + +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
Eigen::Matrix< T, CB, CB > quad_form(const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, CB > &B)
Compute B^T A B.
Definition: quad_form.hpp:21
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diff --git a/doc/api/html/prim_2mat_2fun_2quad__form__sym_8hpp.html b/doc/api/html/prim_2mat_2fun_2quad__form__sym_8hpp.html new file mode 100644 index 00000000000..e25b98fd050 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2quad__form__sym_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/quad_form_sym.hpp File Reference + + + + + + + + + + +
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template<int RA, int CA, int RB, int CB, typename T >
Eigen::Matrix< T, CB, CB > stan::math::quad_form_sym (const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, CB > &B)
 
template<int RA, int CA, int RB, typename T >
stan::math::quad_form_sym (const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, 1 > &B)
 
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diff --git a/doc/api/html/prim_2mat_2fun_2quad__form__sym_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2quad__form__sym_8hpp_source.html new file mode 100644 index 00000000000..ddb3d115051 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2quad__form__sym_8hpp_source.html @@ -0,0 +1,174 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/quad_form_sym.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_QUAD_FORM_SYM_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_QUAD_FORM_SYM_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits.hpp>
+ + + + + + + +
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  template<int RA, int CA, int RB, int CB, typename T>
+
18  inline Eigen::Matrix<T, CB, CB>
+
19  quad_form_sym(const Eigen::Matrix<T, RA, CA>& A,
+
20  const Eigen::Matrix<T, RB, CB>& B) {
+ +
22 
+
23  stan::math::check_square("quad_form_sym", "A", A);
+
24  stan::math::check_multiplicable("quad_form_sym",
+
25  "A", A,
+
26  "B", B);
+
27  stan::math::check_symmetric("quad_form_sym", "A", A);
+
28  Eigen::Matrix<T, CB, CB> ret(multiply(transpose(B), multiply(A, B)));
+
29  return T(0.5) * (ret + transpose(ret));
+
30  }
+
31 
+
32  template<int RA, int CA, int RB, typename T>
+
33  inline T
+
34  quad_form_sym(const Eigen::Matrix<T, RA, CA>& A,
+
35  const Eigen::Matrix<T, RB, 1>& B) {
+ + +
38 
+
39  stan::math::check_square("quad_form_sym", "A", A);
+
40  stan::math::check_multiplicable("quad_form_sym",
+
41  "A", A,
+
42  "B", B);
+
43  stan::math::check_symmetric("quad_form_sym", "A", A);
+
44  return dot_product(B, multiply(A, B));
+
45  }
+
46  }
+
47 }
+
48 
+
49 #endif
+
50 
+ + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ + +
Eigen::Matrix< fvar< T >, CB, CB > quad_form_sym(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
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diff --git a/doc/api/html/prim_2mat_2fun_2rows__dot__product_8hpp.html b/doc/api/html/prim_2mat_2fun_2rows__dot__product_8hpp.html new file mode 100644 index 00000000000..4f0035a9655 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2rows__dot__product_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rows_dot_product.hpp File Reference + + + + + + + + + + +
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template<int R1, int C1, int R2, int C2>
Eigen::Matrix< double, R1, 1 > stan::math::rows_dot_product (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 Returns the dot product of the specified vectors. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2rows__dot__product_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2rows__dot__product_8hpp_source.html new file mode 100644 index 00000000000..d2b9c765752 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2rows__dot__product_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rows_dot_product.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_ROWS_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ROWS_DOT_PRODUCT_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
20  template<int R1, int C1, int R2, int C2>
+
21  inline Eigen::Matrix<double, R1, 1>
+
22  rows_dot_product(const Eigen::Matrix<double, R1, C1>& v1,
+
23  const Eigen::Matrix<double, R2, C2>& v2) {
+
24  stan::math::check_matching_sizes("rows_dot_product",
+
25  "v1", v1,
+
26  "v2", v2);
+
27  Eigen::Matrix<double, R1, 1> ret(v1.rows(), 1);
+
28  for (size_type j = 0; j < v1.rows(); ++j) {
+
29  ret(j) = v1.row(j).dot(v2.row(j));
+
30  }
+
31  return ret;
+
32  }
+
33 
+
34  }
+
35 }
+
36 #endif
+ + +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ +
Eigen::Matrix< fvar< T >, R1, 1 > rows_dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
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diff --git a/doc/api/html/prim_2mat_2fun_2rows__dot__self_8hpp.html b/doc/api/html/prim_2mat_2fun_2rows__dot__self_8hpp.html new file mode 100644 index 00000000000..b7d973e87ab --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2rows__dot__self_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rows_dot_self.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< T, R, 1 > stan::math::rows_dot_self (const Eigen::Matrix< T, R, C > &x)
 Returns the dot product of each row of a matrix with itself. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2rows__dot__self_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2rows__dot__self_8hpp_source.html new file mode 100644 index 00000000000..54c4efa9137 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2rows__dot__self_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rows_dot_self.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_ROWS_DOT_SELF_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ROWS_DOT_SELF_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
14  template<typename T, int R, int C>
+
15  inline Eigen::Matrix<T, R, 1>
+
16  rows_dot_self(const Eigen::Matrix<T, R, C>& x) {
+
17  return x.rowwise().squaredNorm();
+
18  }
+
19 
+
20  }
+
21 }
+
22 #endif
+ +
Eigen::Matrix< fvar< T >, R, 1 > rows_dot_self(const Eigen::Matrix< fvar< T >, R, C > &x)
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2sd_8hpp.html b/doc/api/html/prim_2mat_2fun_2sd_8hpp.html new file mode 100644 index 00000000000..afc85ba3b75 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2sd_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sd.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/variance.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <vector>
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::sd (const std::vector< T > &v)
 Returns the unbiased sample standard deviation of the coefficients in the specified column vector. More...
 
template<typename T , int R, int C>
boost::math::tools::promote_args< T >::type stan::math::sd (const Eigen::Matrix< T, R, C > &m)
 Returns the unbiased sample standard deviation of the coefficients in the specified vector, row vector, or matrix. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2sd_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2sd_8hpp_source.html new file mode 100644 index 00000000000..3985a9d6d9f --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2sd_8hpp_source.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sd.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SD_HPP
+
3 
+ + + +
7 #include <boost/math/tools/promotion.hpp>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
19  template <typename T>
+
20  inline
+
21  typename boost::math::tools::promote_args<T>::type
+
22  sd(const std::vector<T>& v) {
+
23  stan::math::check_nonzero_size("sd", "v", v);
+
24  if (v.size() == 1) return 0.0;
+
25  return sqrt(variance(v));
+
26  }
+
27 
+
34  template <typename T, int R, int C>
+
35  inline
+
36  typename boost::math::tools::promote_args<T>::type
+
37  sd(const Eigen::Matrix<T, R, C>& m) {
+
38  // FIXME: redundant with test in variance; second line saves sqrt
+
39  stan::math::check_nonzero_size("sd", "m", m);
+
40  if (m.size() == 1) return 0.0;
+
41  return sqrt(variance(m));
+
42  }
+
43 
+
44  }
+
45 }
+
46 #endif
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
boost::math::tools::promote_args< T >::type sd(const std::vector< T > &v)
Returns the unbiased sample standard deviation of the coefficients in the specified column vector...
Definition: sd.hpp:22
+
boost::math::tools::promote_args< T >::type variance(const std::vector< T > &v)
Returns the sample variance (divide by length - 1) of the coefficients in the specified standard vect...
Definition: variance.hpp:24
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diff --git a/doc/api/html/prim_2mat_2fun_2softmax_8hpp.html b/doc/api/html/prim_2mat_2fun_2softmax_8hpp.html new file mode 100644 index 00000000000..b2c87b607c0 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2softmax_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/softmax.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::softmax (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v)
 Return the softmax of the specified vector. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2softmax_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2softmax_8hpp_source.html new file mode 100644 index 00000000000..f2f39c3d13c --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2softmax_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/softmax.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SOFTMAX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SOFTMAX_HPP
+
3 
+ + +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
44  template <typename T>
+
45  inline Eigen::Matrix<T, Eigen::Dynamic, 1>
+
46  softmax(const Eigen::Matrix<T, Eigen::Dynamic, 1>& v) {
+
47  using std::exp;
+
48  stan::math::check_nonzero_size("softmax", "v", v);
+
49  Eigen::Matrix<T, Eigen::Dynamic, 1> theta(v.size());
+
50  T sum(0.0);
+
51  T max_v = v.maxCoeff();
+
52  for (int i = 0; i < v.size(); ++i) {
+
53  theta(i) = exp(v(i) - max_v); // extra work for (v[i] == max_v)
+
54  sum += theta(i); // extra work vs. sum() w. auto-diff
+
55  }
+
56  for (int i = 0; i < v.size(); ++i)
+
57  theta(i) /= sum;
+
58  return theta;
+
59  }
+
60 
+
61  }
+
62 }
+
63 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > softmax(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
Definition: softmax.hpp:14
+ +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + +
+
+
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diff --git a/doc/api/html/prim_2mat_2fun_2squared__distance_8hpp.html b/doc/api/html/prim_2mat_2fun_2squared__distance_8hpp.html new file mode 100644 index 00000000000..743b04f9adf --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2squared__distance_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/squared_distance.hpp File Reference + + + + + + + + + + +
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template<int R1, int C1, int R2, int C2, typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::squared_distance (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 Returns the squared distance between the specified vectors. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2squared__distance_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2squared__distance_8hpp_source.html new file mode 100644 index 00000000000..65da1cfc2b1 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2squared__distance_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/squared_distance.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SQUARED_DISTANCE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SQUARED_DISTANCE_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
20  template<int R1, int C1, int R2, int C2, typename T1, typename T2>
+
21  inline typename boost::math::tools::promote_args<T1, T2>::type
+
22  squared_distance(const Eigen::Matrix<T1, R1, C1>& v1,
+
23  const Eigen::Matrix<T2, R2, C2>& v2) {
+
24  stan::math::check_vector("squared_distance", "v1", v1);
+
25  stan::math::check_vector("squared_distance", "v2", v2);
+
26  stan::math::check_matching_sizes("squared_distance",
+
27  "v1", v1,
+
28  "v2", v2);
+
29  if (v1.rows() != v2.rows())
+
30  return (v1.transpose()-v2).squaredNorm();
+
31  else
+
32  return (v1-v2).squaredNorm();
+
33  }
+
34  }
+
35 }
+
36 #endif
+
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ +
boost::math::tools::promote_args< T1, T2 >::type squared_distance(const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
Returns the squared distance between the specified vectors.
+ +
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ + +
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+
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diff --git a/doc/api/html/prim_2mat_2fun_2stan__print_8hpp.html b/doc/api/html/prim_2mat_2fun_2stan__print_8hpp.html new file mode 100644 index 00000000000..11eb1af28fc --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2stan__print_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/stan_print.hpp File Reference + + + + + + + + + + +
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template<typename T >
void stan::math::stan_print (std::ostream *o, const T &x)
 
template<typename T >
void stan::math::stan_print (std::ostream *o, const std::vector< T > &x)
 
template<typename T >
void stan::math::stan_print (std::ostream *o, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 
template<typename T >
void stan::math::stan_print (std::ostream *o, const Eigen::Matrix< T, 1, Eigen::Dynamic > &x)
 
template<typename T >
void stan::math::stan_print (std::ostream *o, const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &x)
 
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diff --git a/doc/api/html/prim_2mat_2fun_2stan__print_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2stan__print_8hpp_source.html new file mode 100644 index 00000000000..47a8c7b7fcc --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2stan__print_8hpp_source.html @@ -0,0 +1,178 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/stan_print.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_STAN_PRINT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_STAN_PRINT_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9  // prints used in generator for print() statements in modeling language
+
10 
+
11  template <typename T>
+
12  void stan_print(std::ostream* o, const T& x) {
+
13  *o << x;
+
14  }
+
15 
+
16  template <typename T>
+
17  void stan_print(std::ostream* o, const std::vector<T>& x) {
+
18  *o << '[';
+
19  for (size_t i = 0; i < x.size(); ++i) {
+
20  if (i > 0) *o << ',';
+
21  stan_print(o, x[i]);
+
22  }
+
23  *o << ']';
+
24  }
+
25 
+
26  template <typename T>
+
27  void stan_print(std::ostream* o,
+
28  const Eigen::Matrix<T, Eigen::Dynamic, 1>& x) {
+
29  *o << '[';
+
30  for (int i = 0; i < x.size(); ++i) {
+
31  if (i > 0) *o << ',';
+
32  stan_print(o, x(i));
+
33  }
+
34  *o << ']';
+
35  }
+
36 
+
37  template <typename T>
+
38  void stan_print(std::ostream* o,
+
39  const Eigen::Matrix<T, 1, Eigen::Dynamic>& x) {
+
40  *o << '[';
+
41  for (int i = 0; i < x.size(); ++i) {
+
42  if (i > 0) *o << ',';
+
43  stan_print(o, x(i));
+
44  }
+
45  *o << ']';
+
46  }
+
47 
+
48  template <typename T>
+
49  void stan_print(std::ostream* o,
+
50  const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& x) {
+
51  *o << '[';
+
52  for (int i = 0; i < x.rows(); ++i) {
+
53  if (i > 0) *o << ',';
+
54  *o << '[';
+
55  for (int j = 0; j < x.row(i).size(); ++j) {
+
56  if (j > 0) *o << ',';
+
57  stan_print(o, x.row(i)(j));
+
58  }
+
59  *o << ']';
+
60  }
+
61  *o << ']';
+
62  }
+
63 
+
64  }
+
65 }
+
66 #endif
+ + +
void stan_print(std::ostream *o, const T &x)
Definition: stan_print.hpp:12
+
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diff --git a/doc/api/html/prim_2mat_2fun_2sum_8hpp.html b/doc/api/html/prim_2mat_2fun_2sum_8hpp.html new file mode 100644 index 00000000000..e6fdf98c164 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2sum_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sum.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/arr/fun/sum.hpp>
+#include <vector>
+
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template<typename T , int R, int C>
double stan::math::sum (const Eigen::Matrix< T, R, C > &v)
 Returns the sum of the coefficients of the specified column vector. More...
 
+
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diff --git a/doc/api/html/prim_2mat_2fun_2sum_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2sum_8hpp_source.html new file mode 100644 index 00000000000..2ce62ce3a4f --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2sum_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sum.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SUM_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SUM_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
21  template <typename T, int R, int C>
+
22  inline double sum(const Eigen::Matrix<T, R, C>& v) {
+
23  return v.sum();
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + + +
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diff --git a/doc/api/html/prim_2mat_2fun_2tcrossprod_8hpp.html b/doc/api/html/prim_2mat_2fun_2tcrossprod_8hpp.html new file mode 100644 index 00000000000..23f0ab0e766 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2tcrossprod_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/tcrossprod.hpp File Reference + + + + + + + + + + +
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matrix_d stan::math::tcrossprod (const matrix_d &M)
 Returns the result of post-multiplying a matrix by its own transpose. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2tcrossprod_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2tcrossprod_8hpp_source.html new file mode 100644 index 00000000000..315a1293caa --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2tcrossprod_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/tcrossprod.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TCROSSPROD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TCROSSPROD_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
16  inline matrix_d
+
17  tcrossprod(const matrix_d& M) {
+
18  if (M.rows() == 0)
+
19  return matrix_d(0, 0);
+
20  if (M.rows() == 1)
+
21  return M * M.transpose();
+
22  matrix_d result(M.rows(), M.rows());
+
23  return result
+
24  .setZero()
+
25  .selfadjointView<Eigen::Upper>()
+
26  .rankUpdate(M);
+
27  }
+
28 
+
29  }
+
30 }
+
31 #endif
+ +
Eigen::Matrix< fvar< T >, R, R > tcrossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: tcrossprod.hpp:17
+ +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > matrix_d
Type for matrix of double values.
Definition: typedefs.hpp:23
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp.html b/doc/api/html/prim_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp.html new file mode 100644 index 00000000000..5846c79f62a --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace_gen_inv_quad_form_ldlt.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , typename T3 , int R1, int C1, int R2, int C2, int R3, int C3>
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value &&!stan::is_var< T3 >::value, typename boost::math::tools::promote_args< T1, T2, T3 >::type >::type stan::math::trace_gen_inv_quad_form_ldlt (const Eigen::Matrix< T1, R1, C1 > &D, const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
 
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diff --git a/doc/api/html/prim_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp_source.html new file mode 100644 index 00000000000..ab88fb4d09d --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp_source.html @@ -0,0 +1,175 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace_gen_inv_quad_form_ldlt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TRACE_GEN_INV_QUAD_FORM_LDLT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TRACE_GEN_INV_QUAD_FORM_LDLT_HPP
+
3 
+ + + + + + + + + +
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  /*
+
18  * Compute the trace of an inverse quadratic form. I.E., this computes
+
19  * trace(D B^T A^-1 B)
+
20  * where D is a square matrix and the LDLT_factor of A is provided.
+
21  */
+
22  template <typename T1, typename T2, typename T3,
+
23  int R1, int C1, int R2, int C2, int R3, int C3>
+
24  inline typename
+
25  boost::enable_if_c<!stan::is_var<T1>::value &&
+ + +
28  typename
+
29  boost::math::tools::promote_args<T1, T2, T3>::type>::type
+
30  trace_gen_inv_quad_form_ldlt(const Eigen::Matrix<T1, R1, C1> &D,
+ +
32  const Eigen::Matrix<T3, R3, C3> &B) {
+
33  stan::math::check_square("trace_gen_inv_quad_form_ldlt", "D", D);
+
34  stan::math::check_multiplicable("trace_gen_inv_quad_form_ldlt",
+
35  "A", A,
+
36  "B", B);
+
37  stan::math::check_multiplicable("trace_gen_inv_quad_form_ldlt",
+
38  "B", B,
+
39  "D", D);
+
40 
+
41  return trace(multiply(multiply(D, transpose(B)),
+
42  mdivide_left_ldlt(A, B)));
+
43  }
+
44 
+
45  }
+
46 }
+
47 #endif
+ + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value &&!stan::is_var< T3 >::value, typename boost::math::tools::promote_args< T1, T2, T3 >::type >::type trace_gen_inv_quad_form_ldlt(const Eigen::Matrix< T1, R1, C1 > &D, const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
+ + + + + +
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt(const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
Returns the solution of the system Ax=b given an LDLT_factor of A.
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+ +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
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diff --git a/doc/api/html/prim_2mat_2fun_2trace__gen__quad__form_8hpp.html b/doc/api/html/prim_2mat_2fun_2trace__gen__quad__form_8hpp.html new file mode 100644 index 00000000000..6179cabae39 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2trace__gen__quad__form_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace_gen_quad_form.hpp File Reference + + + + + + + + + + +
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#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/err/check_multiplicable.hpp>
+#include <stan/math/prim/mat/err/check_square.hpp>
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template<int RD, int CD, int RA, int CA, int RB, int CB>
double stan::math::trace_gen_quad_form (const Eigen::Matrix< double, RD, CD > &D, const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
 Compute trace(D B^T A B). More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2trace__gen__quad__form_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2trace__gen__quad__form_8hpp_source.html new file mode 100644 index 00000000000..bbf586239fb --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2trace__gen__quad__form_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace_gen_quad_form.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TRACE_GEN_QUAD_FORM_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TRACE_GEN_QUAD_FORM_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits.hpp>
+ + + +
9 
+
10 namespace stan {
+
11  namespace math {
+
15  template<int RD, int CD, int RA, int CA, int RB, int CB>
+
16  inline double
+
17  trace_gen_quad_form(const Eigen::Matrix<double, RD, CD> &D,
+
18  const Eigen::Matrix<double, RA, CA> &A,
+
19  const Eigen::Matrix<double, RB, CB> &B) {
+
20  stan::math::check_square("trace_gen_quad_form", "A", A);
+
21  stan::math::check_square("trace_gen_quad_form", "D", D);
+
22  stan::math::check_multiplicable("trace_gen_quad_form",
+
23  "A", A,
+
24  "B", B);
+
25  stan::math::check_multiplicable("trace_gen_quad_form",
+
26  "B", B,
+
27  "D", D);
+
28  return (D*B.transpose()*A*B).trace();
+
29  }
+
30  }
+
31 }
+
32 
+
33 #endif
+
34 
+ + +
fvar< T > trace_gen_quad_form(const Eigen::Matrix< fvar< T >, RD, CD > &D, const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp.html b/doc/api/html/prim_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp.html new file mode 100644 index 00000000000..577f3e0a2a0 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace_inv_quad_form_ldlt.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , int R2, int C2, int R3, int C3>
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value, typename boost::math::tools::promote_args< T1, T2 >::type >::type stan::math::trace_inv_quad_form_ldlt (const stan::math::LDLT_factor< T1, R2, C2 > &A, const Eigen::Matrix< T2, R3, C3 > &B)
 
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diff --git a/doc/api/html/prim_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp_source.html new file mode 100644 index 00000000000..249e8b0965d --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace_inv_quad_form_ldlt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TRACE_INV_QUAD_FORM_LDLT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TRACE_INV_QUAD_FORM_LDLT_HPP
+
3 
+ + + + + + + + +
12 
+
13 namespace stan {
+
14  namespace math {
+
15 
+
16  /*
+
17  * Compute the trace of an inverse quadratic form. I.E., this computes
+
18  * trace(B^T A^-1 B)
+
19  * where the LDLT_factor of A is provided.
+
20  */
+
21  template <typename T1, typename T2, int R2, int C2, int R3, int C3>
+
22  inline typename
+
23  boost::enable_if_c<!stan::is_var<T1>::value &&
+ +
25  typename
+
26  boost::math::tools::promote_args<T1, T2>::type>::type
+ +
28  const Eigen::Matrix<T2, R3, C3> &B) {
+
29  stan::math::check_multiplicable("trace_inv_quad_form_ldlt",
+
30  "A", A,
+
31  "B", B);
+
32 
+
33  return trace(multiply(transpose(B), mdivide_left_ldlt(A, B)));
+
34  }
+
35  }
+
36 }
+
37 
+
38 #endif
+ + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value, typename boost::math::tools::promote_args< T1, T2 >::type >::type trace_inv_quad_form_ldlt(const stan::math::LDLT_factor< T1, R2, C2 > &A, const Eigen::Matrix< T2, R3, C3 > &B)
+ + + + + +
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt(const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
Returns the solution of the system Ax=b given an LDLT_factor of A.
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+ +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
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diff --git a/doc/api/html/prim_2mat_2fun_2trace__quad__form_8hpp.html b/doc/api/html/prim_2mat_2fun_2trace__quad__form_8hpp.html new file mode 100644 index 00000000000..b9eff2f3728 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2trace__quad__form_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace_quad_form.hpp File Reference + + + + + + + + + + +
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#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/err/check_multiplicable.hpp>
+#include <stan/math/prim/mat/err/check_square.hpp>
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template<int RA, int CA, int RB, int CB>
double stan::math::trace_quad_form (const Eigen::Matrix< double, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
 Compute trace(B^T A B). More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2trace__quad__form_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2trace__quad__form_8hpp_source.html new file mode 100644 index 00000000000..e33a81372df --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2trace__quad__form_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace_quad_form.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TRACE_QUAD_FORM_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TRACE_QUAD_FORM_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits.hpp>
+ + + +
9 
+
10 namespace stan {
+
11  namespace math {
+
15  template<int RA, int CA, int RB, int CB>
+
16  inline double
+
17  trace_quad_form(const Eigen::Matrix<double, RA, CA> &A,
+
18  const Eigen::Matrix<double, RB, CB> &B) {
+
19  stan::math::check_square("trace_quad_form", "A", A);
+
20  stan::math::check_multiplicable("trace_quad_form",
+
21  "A", A,
+
22  "B", B);
+
23 
+
24  return (B.transpose()*A*B).trace();
+
25  }
+
26 
+
27  }
+
28 }
+
29 
+
30 #endif
+
31 
+ +
fvar< T > trace_quad_form(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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diff --git a/doc/api/html/prim_2mat_2fun_2typedefs_8hpp.html b/doc/api/html/prim_2mat_2fun_2typedefs_8hpp.html new file mode 100644 index 00000000000..4e6373add77 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2typedefs_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/typedefs.hpp File Reference + + + + + + + + + + +
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typedef Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > stan::math::matrix_d
 Type for matrix of double values. More...
 
typedef Eigen::Matrix< double, Eigen::Dynamic, 1 > stan::math::vector_d
 Type for (column) vector of double values. More...
 
typedef Eigen::Matrix< double, 1, Eigen::Dynamic > stan::math::row_vector_d
 Type for (row) vector of double values. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2typedefs_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2typedefs_8hpp_source.html new file mode 100644 index 00000000000..b9bb8011f31 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2typedefs_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/typedefs.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TYPEDEFS_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TYPEDEFS_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
14  typedef
+
15  index_type<Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> >::type
+
16  size_type;
+
17 
+
21  typedef
+
22  Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>
+ +
24 
+
28  typedef
+
29  Eigen::Matrix<double, Eigen::Dynamic, 1>
+ +
31 
+
35  typedef
+
36  Eigen::Matrix<double, 1, Eigen::Dynamic>
+ +
38 
+
39  }
+
40 }
+
41 
+
42 #endif
+
Eigen::Matrix< double, Eigen::Dynamic, 1 > vector_d
Type for (column) vector of double values.
Definition: typedefs.hpp:30
+ +
Eigen::Matrix< double, 1, Eigen::Dynamic > row_vector_d
Type for (row) vector of double values.
Definition: typedefs.hpp:37
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ + +
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > matrix_d
Type for matrix of double values.
Definition: typedefs.hpp:23
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diff --git a/doc/api/html/prim_2mat_2fun_2unit__vector__constrain_8hpp.html b/doc/api/html/prim_2mat_2fun_2unit__vector__constrain_8hpp.html new file mode 100644 index 00000000000..a405b409dce --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2unit__vector__constrain_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/unit_vector_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< T, R, C > stan::math::unit_vector_constrain (const Eigen::Matrix< T, R, C > &y)
 Return the unit length vector corresponding to the free vector y. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > stan::math::unit_vector_constrain (const Eigen::Matrix< T, R, C > &y, T &lp)
 Return the unit length vector corresponding to the free vector y. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2unit__vector__constrain_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2unit__vector__constrain_8hpp_source.html new file mode 100644 index 00000000000..bc5b7c68e9e --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2unit__vector__constrain_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/unit_vector_constrain.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_UNIT_VECTOR_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_UNIT_VECTOR_CONSTRAIN_HPP
+
3 
+ + + + + + +
10 #include <cmath>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
23  template <typename T, int R, int C>
+
24  Eigen::Matrix<T, R, C>
+
25  unit_vector_constrain(const Eigen::Matrix<T, R, C>& y) {
+
26  using std::sqrt;
+
27  check_vector("unit_vector_constrain", "y", y);
+
28  check_nonzero_size("unit_vector_constrain", "y", y);
+
29  const T SN = dot_self(y);
+
30  check_positive_finite("unit_vector_constrain", "norm", SN);
+
31  return y / sqrt(SN);
+
32  }
+
33 
+
43  template <typename T, int R, int C>
+
44  Eigen::Matrix<T, R, C>
+
45  unit_vector_constrain(const Eigen::Matrix<T, R, C>& y, T& lp) {
+
46  using std::sqrt;
+
47  check_vector("unit_vector_constrain", "y", y);
+
48  check_nonzero_size("unit_vector_constrain", "y", y);
+
49  const T SN = dot_self(y);
+
50  check_positive_finite("unit_vector_constrain", "norm", SN);
+
51  lp -= 0.5 * SN;
+
52  return y / sqrt(SN);
+
53  }
+
54 
+
55  }
+
56 
+
57 }
+
58 
+
59 #endif
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ + + +
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
Eigen::Matrix< fvar< T >, R, C > unit_vector_constrain(const Eigen::Matrix< fvar< T >, R, C > &y)
+ + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
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diff --git a/doc/api/html/prim_2mat_2fun_2value__of_8hpp.html b/doc/api/html/prim_2mat_2fun_2value__of_8hpp.html new file mode 100644 index 00000000000..ef9c6b8a23d --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2value__of_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/value_of.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
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 Convert a matrix of type T to a matrix of doubles. More...
 
template<int R, int C>
Eigen::Matrix< double, R, C > stan::math::value_of (const Eigen::Matrix< double, R, C > &x)
 Return the specified argument. More...
 
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diff --git a/doc/api/html/prim_2mat_2fun_2value__of_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2value__of_8hpp_source.html new file mode 100644 index 00000000000..69bcb6d8aa3 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2value__of_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/value_of.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
value_of.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_VALUE_OF_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_VALUE_OF_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
23  template <typename T, int R, int C>
+
24  inline Eigen::Matrix<typename child_type<T>::type, R, C>
+
25  value_of(const Eigen::Matrix<T, R, C>& M) {
+ +
27  Eigen::Matrix<typename child_type<T>::type, R, C> Md(M.rows(), M.cols());
+
28  for (int j = 0; j < M.cols(); j++)
+
29  for (int i = 0; i < M.rows(); i++)
+
30  Md(i, j) = value_of(M(i, j));
+
31  return Md;
+
32  }
+
33 
+
45  template <int R, int C>
+
46  inline typename Eigen::Matrix<double, R, C>
+
47  value_of(const Eigen::Matrix<double, R, C>& x) {
+
48  return x;
+
49  }
+
50  }
+
51 }
+
52 
+
53 #endif
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_2fun_2value__of__rec_8hpp.html b/doc/api/html/prim_2mat_2fun_2value__of__rec_8hpp.html new file mode 100644 index 00000000000..508f86960c0 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2value__of__rec_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/value_of_rec.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
value_of_rec.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + +

+Functions

template<typename T , int R, int C>
Eigen::Matrix< double, R, C > stan::math::value_of_rec (const Eigen::Matrix< T, R, C > &M)
 Convert a matrix of type T to a matrix of doubles. More...
 
template<int R, int C>
Eigen::Matrix< double, R, C > stan::math::value_of_rec (const Eigen::Matrix< double, R, C > &x)
 Return the specified argument. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_2fun_2value__of__rec_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2value__of__rec_8hpp_source.html new file mode 100644 index 00000000000..fba21f43b24 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2value__of__rec_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/value_of_rec.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
value_of_rec.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_VALUE_OF_REC_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_VALUE_OF_REC_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
22  template <typename T, int R, int C>
+
23  inline Eigen::Matrix<double, R, C>
+
24  value_of_rec(const Eigen::Matrix<T, R, C>& M) {
+ +
26  Eigen::Matrix<double, R, C> Md(M.rows(), M.cols());
+
27  for (int j = 0; j < M.cols(); j++)
+
28  for (int i = 0; i < M.rows(); i++)
+
29  Md(i, j) = value_of_rec(M(i, j));
+
30  return Md;
+
31  }
+
32 
+
44  template <int R, int C>
+
45  inline typename Eigen::Matrix<double, R, C>
+
46  value_of_rec(const Eigen::Matrix<double, R, C>& x) {
+
47  return x;
+
48  }
+
49  }
+
50 }
+
51 
+
52 #endif
+ +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_2fun_2variance_8hpp.html b/doc/api/html/prim_2mat_2fun_2variance_8hpp.html new file mode 100644 index 00000000000..49fd9d3ff18 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2variance_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/variance.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
variance.hpp File Reference
+
+
+
#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/mean.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + +

+Functions

template<typename T >
boost::math::tools::promote_args< T >::type stan::math::variance (const std::vector< T > &v)
 Returns the sample variance (divide by length - 1) of the coefficients in the specified standard vector. More...
 
template<typename T , int R, int C>
boost::math::tools::promote_args< T >::type stan::math::variance (const Eigen::Matrix< T, R, C > &m)
 Returns the sample variance (divide by length - 1) of the coefficients in the specified column vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_2fun_2variance_8hpp_source.html b/doc/api/html/prim_2mat_2fun_2variance_8hpp_source.html new file mode 100644 index 00000000000..b789a0cf016 --- /dev/null +++ b/doc/api/html/prim_2mat_2fun_2variance_8hpp_source.html @@ -0,0 +1,167 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/variance.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
variance.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_VARIANCE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_VARIANCE_HPP
+
3 
+ + + +
7 #include <boost/math/tools/promotion.hpp>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
21  template <typename T>
+
22  inline
+
23  typename boost::math::tools::promote_args<T>::type
+
24  variance(const std::vector<T>& v) {
+
25  stan::math::check_nonzero_size("variance", "v", v);
+
26  if (v.size() == 1)
+
27  return 0.0;
+
28  T v_mean(mean(v));
+
29  T sum_sq_diff(0);
+
30  for (size_t i = 0; i < v.size(); ++i) {
+
31  T diff = v[i] - v_mean;
+
32  sum_sq_diff += diff * diff;
+
33  }
+
34  return sum_sq_diff / (v.size() - 1);
+
35  }
+
36 
+
43  template <typename T, int R, int C>
+
44  inline
+
45  typename boost::math::tools::promote_args<T>::type
+
46  variance(const Eigen::Matrix<T, R, C>& m) {
+
47  stan::math::check_nonzero_size("variance", "m", m);
+
48 
+
49  if (m.size() == 1)
+
50  return 0.0;
+
51  typename boost::math::tools::promote_args<T>::type
+
52  mn(mean(m));
+
53  typename boost::math::tools::promote_args<T>::type
+
54  sum_sq_diff(0);
+
55  for (int i = 0; i < m.size(); ++i) {
+
56  typename boost::math::tools::promote_args<T>::type
+
57  diff = m(i) - mn;
+
58  sum_sq_diff += diff * diff;
+
59  }
+
60  return sum_sq_diff / (m.size() - 1);
+
61  }
+
62 
+
63  }
+
64 }
+
65 #endif
+ +
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
boost::math::tools::promote_args< T >::type variance(const std::vector< T > &v)
Returns the sample variance (divide by length - 1) of the coefficients in the specified standard vect...
Definition: variance.hpp:24
+ +
boost::math::tools::promote_args< T >::type mean(const std::vector< T > &v)
Returns the sample mean (i.e., average) of the coefficients in the specified standard vector...
Definition: mean.hpp:23
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_2vectorize_2apply__scalar__unary_8hpp.html b/doc/api/html/prim_2mat_2vectorize_2apply__scalar__unary_8hpp.html new file mode 100644 index 00000000000..4426140331e --- /dev/null +++ b/doc/api/html/prim_2mat_2vectorize_2apply__scalar__unary_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/vectorize/apply_scalar_unary.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
apply_scalar_unary.hpp File Reference
+
+
+
#include <Eigen/Dense>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + + + + + + + + +

+Classes

struct  stan::math::apply_scalar_unary< F, T >
 Base template class for vectorization of unary scalar functions defined by a template class F to a scalar, standard library vector, or Eigen dense matrix expression template. More...
 
struct  stan::math::apply_scalar_unary< F, double >
 Template specialization for vectorized functions applying to double arguments. More...
 
struct  stan::math::apply_scalar_unary< F, int >
 Template specialization for vectorized functions applying to integer arguments. More...
 
struct  stan::math::apply_scalar_unary< F, std::vector< T > >
 Template specialization for vectorized functions applying to standard vector containers. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html b/doc/api/html/prim_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html new file mode 100644 index 00000000000..bc77cb49e87 --- /dev/null +++ b/doc/api/html/prim_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/vectorize/apply_scalar_unary.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
apply_scalar_unary.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_VECTORIZE_APPLY_UNARY_SCALAR_HPP
+
2 #define STAN_MATH_PRIM_MAT_VECTORIZE_APPLY_UNARY_SCALAR_HPP
+
3 
+
4 #include <Eigen/Dense>
+
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
35  template <typename F, typename T>
+ +
40  typedef typename Eigen::internal::traits<T>::Scalar scalar_t;
+
41 
+
46  typedef Eigen::Matrix<scalar_t, T::RowsAtCompileTime,
+
47  T::ColsAtCompileTime>
+ +
49 
+
58  static inline return_t apply(const T& x) {
+
59  return_t result(x.rows(), x.cols());
+
60  for (int j = 0; j < x.cols(); ++j)
+
61  for (int i = 0; i < x.rows(); ++i)
+
62  result(i, j) = apply_scalar_unary<F, scalar_t>::apply(x(i, j));
+
63  return result;
+
64  }
+
65  };
+
66 
+
73  template <typename F>
+
74  struct apply_scalar_unary<F, double> {
+
78  typedef double return_t;
+
79 
+
89  static inline return_t apply(double x) {
+
90  return F::fun(x);
+
91  }
+
92  };
+
93 
+
102  template <typename F>
+
103  struct apply_scalar_unary<F, int> {
+
107  typedef double return_t;
+
108 
+
118  static inline return_t apply(int x) {
+
119  return F::fun(static_cast<double>(x));
+
120  }
+
121  };
+
122 
+
132  template <typename F, typename T>
+
133  struct apply_scalar_unary<F, std::vector<T> > {
+
138  typedef typename std::vector<typename apply_scalar_unary<F, T>::return_t>
+ +
140 
+
150  static inline return_t apply(const std::vector<T>& x) {
+
151  return_t fx(x.size());
+
152  for (size_t i = 0; i < x.size(); ++i)
+
153  fx[i] = apply_scalar_unary<F, T>::apply(x[i]);
+
154  return fx;
+
155  }
+
156  };
+
157 
+
158  }
+
159 }
+
160 #endif
+
static return_t apply(double x)
Apply the function specified by F to the specified argument.
+ + +
Eigen::Matrix< scalar_t, T::RowsAtCompileTime, T::ColsAtCompileTime > return_t
Return type for applying the function elementwise to a matrix expression template of type T...
+
static return_t apply(const std::vector< T > &x)
Apply the function specified by F elementwise to the specified argument.
+
static return_t apply(int x)
Apply the function specified by F to the specified argument.
+
double return_t
The return type, double.
+
std::vector< typename apply_scalar_unary< F, T >::return_t > return_t
Return type, which is calculated recursively as a standard vector of the return type of the contained...
+
Eigen::internal::traits< T >::Scalar scalar_t
Type of underlying scalar for the matrix type T.
+
Base template class for vectorization of unary scalar functions defined by a template class F to a sc...
+
double return_t
The return type, double.
+
static return_t apply(const T &x)
Return the result of applying the function defined by the template parameter F to the specified matri...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2mat_8hpp.html b/doc/api/html/prim_2mat_8hpp.html new file mode 100644 index 00000000000..c611f4e9f65 --- /dev/null +++ b/doc/api/html/prim_2mat_8hpp.html @@ -0,0 +1,334 @@ + + + + + + +Stan Math Library: stan/math/prim/mat.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
mat.hpp File Reference
+
+
+
#include <stan/math/prim/arr/meta/get.hpp>
+#include <stan/math/prim/arr/meta/index_type.hpp>
+#include <stan/math/prim/arr/meta/is_vector.hpp>
+#include <stan/math/prim/arr/meta/length.hpp>
+#include <stan/math/prim/mat/meta/container_view.hpp>
+#include <stan/math/prim/mat/meta/get.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stan/math/prim/mat/meta/is_constant_struct.hpp>
+#include <stan/math/prim/mat/meta/is_vector.hpp>
+#include <stan/math/prim/mat/meta/is_vector_like.hpp>
+#include <stan/math/prim/mat/meta/length.hpp>
+#include <stan/math/prim/mat/meta/length_mvt.hpp>
+#include <stan/math/prim/mat/meta/seq_view.hpp>
+#include <stan/math/prim/mat/meta/scalar_type.hpp>
+#include <stan/math/prim/mat/meta/value_type.hpp>
+#include <stan/math/prim/mat/meta/VectorView.hpp>
+#include <stan/math/prim/mat/meta/VectorViewMvt.hpp>
+#include <stan/math/prim/mat/err/check_cholesky_factor.hpp>
+#include <stan/math/prim/mat/err/check_cholesky_factor_corr.hpp>
+#include <stan/math/prim/mat/err/check_column_index.hpp>
+#include <stan/math/prim/mat/err/check_corr_matrix.hpp>
+#include <stan/math/prim/mat/err/check_cov_matrix.hpp>
+#include <stan/math/prim/mat/err/check_ldlt_factor.hpp>
+#include <stan/math/prim/mat/err/check_lower_triangular.hpp>
+#include <stan/math/prim/mat/err/check_matching_dims.hpp>
+#include <stan/math/prim/mat/err/check_matching_sizes.hpp>
+#include <stan/math/prim/mat/err/check_multiplicable.hpp>
+#include <stan/math/prim/mat/err/check_ordered.hpp>
+#include <stan/math/prim/mat/err/check_pos_definite.hpp>
+#include <stan/math/prim/mat/err/check_pos_semidefinite.hpp>
+#include <stan/math/prim/mat/err/check_positive_ordered.hpp>
+#include <stan/math/prim/mat/err/check_range.hpp>
+#include <stan/math/prim/mat/err/check_row_index.hpp>
+#include <stan/math/prim/mat/err/check_simplex.hpp>
+#include <stan/math/prim/mat/err/check_spsd_matrix.hpp>
+#include <stan/math/prim/mat/err/check_square.hpp>
+#include <stan/math/prim/mat/err/check_std_vector_index.hpp>
+#include <stan/math/prim/mat/err/check_symmetric.hpp>
+#include <stan/math/prim/mat/err/check_unit_vector.hpp>
+#include <stan/math/prim/mat/err/check_vector.hpp>
+#include <stan/math/prim/mat/err/constraint_tolerance.hpp>
+#include <stan/math/prim/mat/err/validate_non_negative_index.hpp>
+#include <stan/math/prim/mat/fun/accumulator.hpp>
+#include <stan/math/prim/mat/fun/add.hpp>
+#include <stan/math/prim/mat/fun/append_col.hpp>
+#include <stan/math/prim/mat/fun/append_row.hpp>
+#include <stan/math/prim/mat/fun/array_builder.hpp>
+#include <stan/math/prim/mat/fun/assign.hpp>
+#include <stan/math/prim/mat/fun/autocorrelation.hpp>
+#include <stan/math/prim/mat/fun/autocovariance.hpp>
+#include <stan/math/prim/mat/fun/block.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_corr_free.hpp>
+#include <stan/math/prim/mat/fun/cholesky_decompose.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_constrain.hpp>
+#include <stan/math/prim/mat/fun/cholesky_factor_free.hpp>
+#include <stan/math/prim/mat/fun/col.hpp>
+#include <stan/math/prim/mat/fun/cols.hpp>
+#include <stan/math/prim/mat/fun/columns_dot_product.hpp>
+#include <stan/math/prim/mat/fun/columns_dot_self.hpp>
+#include <stan/math/prim/mat/fun/common_type.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/corr_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_constrain_lkj.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free.hpp>
+#include <stan/math/prim/mat/fun/cov_matrix_free_lkj.hpp>
+#include <stan/math/prim/mat/fun/crossprod.hpp>
+#include <stan/math/prim/mat/fun/cumulative_sum.hpp>
+#include <stan/math/prim/mat/fun/determinant.hpp>
+#include <stan/math/prim/mat/fun/diag_matrix.hpp>
+#include <stan/math/prim/mat/fun/diag_post_multiply.hpp>
+#include <stan/math/prim/mat/fun/diag_pre_multiply.hpp>
+#include <stan/math/prim/mat/fun/diagonal.hpp>
+#include <stan/math/prim/mat/fun/dims.hpp>
+#include <stan/math/prim/mat/fun/distance.hpp>
+#include <stan/math/prim/mat/fun/divide.hpp>
+#include <stan/math/prim/mat/fun/dot_product.hpp>
+#include <stan/math/prim/mat/fun/dot_self.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/eigenvalues_sym.hpp>
+#include <stan/math/prim/mat/fun/eigenvectors_sym.hpp>
+#include <stan/math/prim/mat/fun/elt_divide.hpp>
+#include <stan/math/prim/mat/fun/elt_multiply.hpp>
+#include <stan/math/prim/mat/fun/exp.hpp>
+#include <stan/math/prim/mat/fun/factor_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/factor_U.hpp>
+#include <stan/math/prim/mat/fun/fill.hpp>
+#include <stan/math/prim/mat/fun/get_base1.hpp>
+#include <stan/math/prim/mat/fun/get_base1_lhs.hpp>
+#include <stan/math/prim/mat/fun/get_lp.hpp>
+#include <stan/math/prim/mat/fun/head.hpp>
+#include <stan/math/prim/mat/fun/initialize.hpp>
+#include <stan/math/prim/mat/fun/inverse.hpp>
+#include <stan/math/prim/mat/fun/inverse_spd.hpp>
+#include <stan/math/prim/mat/fun/LDLT_factor.hpp>
+#include <stan/math/prim/mat/fun/log.hpp>
+#include <stan/math/prim/mat/fun/log_determinant.hpp>
+#include <stan/math/prim/mat/fun/log_determinant_ldlt.hpp>
+#include <stan/math/prim/mat/fun/log_determinant_spd.hpp>
+#include <stan/math/prim/mat/fun/log_softmax.hpp>
+#include <stan/math/prim/mat/fun/log_sum_exp.hpp>
+#include <stan/math/prim/mat/fun/make_nu.hpp>
+#include <stan/math/prim/mat/fun/max.hpp>
+#include <stan/math/prim/mat/fun/mdivide_left.hpp>
+#include <stan/math/prim/mat/fun/mdivide_left_ldlt.hpp>
+#include <stan/math/prim/mat/fun/mdivide_left_spd.hpp>
+#include <stan/math/prim/mat/fun/mdivide_left_tri.hpp>
+#include <stan/math/prim/mat/fun/mdivide_left_tri_low.hpp>
+#include <stan/math/prim/mat/fun/mdivide_right.hpp>
+#include <stan/math/prim/mat/fun/mdivide_right_ldlt.hpp>
+#include <stan/math/prim/mat/fun/mdivide_right_spd.hpp>
+#include <stan/math/prim/mat/fun/mdivide_right_tri.hpp>
+#include <stan/math/prim/mat/fun/mdivide_right_tri_low.hpp>
+#include <stan/math/prim/mat/fun/mean.hpp>
+#include <stan/math/prim/mat/fun/min.hpp>
+#include <stan/math/prim/mat/fun/minus.hpp>
+#include <stan/math/prim/mat/fun/multiply.hpp>
+#include <stan/math/prim/mat/fun/multiply_lower_tri_self_transpose.hpp>
+#include <stan/math/prim/mat/fun/num_elements.hpp>
+#include <stan/math/prim/mat/fun/ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/ordered_free.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_constrain.hpp>
+#include <stan/math/prim/mat/fun/positive_ordered_free.hpp>
+#include <stan/math/prim/mat/fun/prod.hpp>
+#include <stan/math/prim/mat/fun/promote_common.hpp>
+#include <stan/math/prim/mat/fun/promote_scalar.hpp>
+#include <stan/math/prim/mat/fun/promote_scalar_type.hpp>
+#include <stan/math/prim/mat/fun/promoter.hpp>
+#include <stan/math/prim/mat/fun/qr_Q.hpp>
+#include <stan/math/prim/mat/fun/qr_R.hpp>
+#include <stan/math/prim/mat/fun/quad_form.hpp>
+#include <stan/math/prim/mat/fun/quad_form_diag.hpp>
+#include <stan/math/prim/mat/fun/quad_form_sym.hpp>
+#include <stan/math/prim/mat/fun/rank.hpp>
+#include <stan/math/prim/mat/fun/read_corr_L.hpp>
+#include <stan/math/prim/mat/fun/read_corr_matrix.hpp>
+#include <stan/math/prim/mat/fun/read_cov_L.hpp>
+#include <stan/math/prim/mat/fun/read_cov_matrix.hpp>
+#include <stan/math/prim/mat/fun/rep_matrix.hpp>
+#include <stan/math/prim/mat/fun/rep_row_vector.hpp>
+#include <stan/math/prim/mat/fun/rep_vector.hpp>
+#include <stan/math/prim/mat/fun/resize.hpp>
+#include <stan/math/prim/mat/fun/row.hpp>
+#include <stan/math/prim/mat/fun/rows.hpp>
+#include <stan/math/prim/mat/fun/rows_dot_product.hpp>
+#include <stan/math/prim/mat/fun/rows_dot_self.hpp>
+#include <stan/math/prim/mat/fun/sd.hpp>
+#include <stan/math/prim/mat/fun/segment.hpp>
+#include <stan/math/prim/mat/fun/simplex_constrain.hpp>
+#include <stan/math/prim/mat/fun/simplex_free.hpp>
+#include <stan/math/prim/mat/fun/singular_values.hpp>
+#include <stan/math/prim/mat/fun/size.hpp>
+#include <stan/math/prim/mat/fun/softmax.hpp>
+#include <stan/math/prim/mat/fun/sort.hpp>
+#include <stan/math/prim/mat/fun/sort_indices.hpp>
+#include <stan/math/prim/mat/fun/sort_indices_asc.hpp>
+#include <stan/math/prim/mat/fun/sort_indices_desc.hpp>
+#include <stan/math/prim/mat/fun/csr_extract_w.hpp>
+#include <stan/math/prim/mat/fun/csr_extract_v.hpp>
+#include <stan/math/prim/mat/fun/csr_extract_u.hpp>
+#include <stan/math/prim/mat/fun/csr_matrix_times_vector.hpp>
+#include <stan/math/prim/mat/fun/csr_to_dense_matrix.hpp>
+#include <stan/math/prim/mat/fun/csr_u_to_z.hpp>
+#include <stan/math/prim/mat/fun/squared_distance.hpp>
+#include <stan/math/prim/mat/fun/stan_print.hpp>
+#include <stan/math/prim/mat/fun/sub_col.hpp>
+#include <stan/math/prim/mat/fun/sub_row.hpp>
+#include <stan/math/prim/mat/fun/subtract.hpp>
+#include <stan/math/prim/mat/fun/sum.hpp>
+#include <stan/math/prim/mat/fun/tail.hpp>
+#include <stan/math/prim/mat/fun/tcrossprod.hpp>
+#include <stan/math/prim/mat/fun/to_array_1d.hpp>
+#include <stan/math/prim/mat/fun/to_array_2d.hpp>
+#include <stan/math/prim/mat/fun/to_matrix.hpp>
+#include <stan/math/prim/mat/fun/to_row_vector.hpp>
+#include <stan/math/prim/mat/fun/to_vector.hpp>
+#include <stan/math/prim/mat/fun/trace.hpp>
+#include <stan/math/prim/mat/fun/trace_gen_inv_quad_form_ldlt.hpp>
+#include <stan/math/prim/mat/fun/trace_gen_quad_form.hpp>
+#include <stan/math/prim/mat/fun/trace_inv_quad_form_ldlt.hpp>
+#include <stan/math/prim/mat/fun/trace_quad_form.hpp>
+#include <stan/math/prim/mat/fun/transpose.hpp>
+#include <stan/math/prim/mat/fun/typedefs.hpp>
+#include <stan/math/prim/mat/fun/unit_vector_constrain.hpp>
+#include <stan/math/prim/mat/fun/unit_vector_free.hpp>
+#include <stan/math/prim/mat/fun/value_of.hpp>
+#include <stan/math/prim/mat/fun/value_of_rec.hpp>
+#include <stan/math/prim/mat/fun/variance.hpp>
+#include <stan/math/prim/mat/fun/welford_covar_estimator.hpp>
+#include <stan/math/prim/mat/fun/welford_var_estimator.hpp>
+#include <stan/math/prim/mat/functor/finite_diff_gradient.hpp>
+#include <stan/math/prim/mat/functor/finite_diff_hessian.hpp>
+#include <stan/math/prim/mat/prob/categorical_log.hpp>
+#include <stan/math/prim/mat/prob/categorical_logit_log.hpp>
+#include <stan/math/prim/mat/prob/categorical_rng.hpp>
+#include <stan/math/prim/mat/prob/dirichlet_log.hpp>
+#include <stan/math/prim/mat/prob/dirichlet_rng.hpp>
+#include <stan/math/prim/mat/prob/gaussian_dlm_obs_log.hpp>
+#include <stan/math/prim/mat/prob/inv_wishart_log.hpp>
+#include <stan/math/prim/mat/prob/inv_wishart_rng.hpp>
+#include <stan/math/prim/mat/prob/lkj_corr_cholesky_log.hpp>
+#include <stan/math/prim/mat/prob/lkj_corr_cholesky_rng.hpp>
+#include <stan/math/prim/mat/prob/lkj_corr_log.hpp>
+#include <stan/math/prim/mat/prob/lkj_corr_rng.hpp>
+#include <stan/math/prim/mat/prob/lkj_cov_log.hpp>
+#include <stan/math/prim/mat/prob/matrix_normal_prec_log.hpp>
+#include <stan/math/prim/mat/prob/multi_gp_cholesky_log.hpp>
+#include <stan/math/prim/mat/prob/multi_gp_log.hpp>
+#include <stan/math/prim/mat/prob/multi_normal_cholesky_log.hpp>
+#include <stan/math/prim/mat/prob/multi_normal_cholesky_rng.hpp>
+#include <stan/math/prim/mat/prob/multi_normal_log.hpp>
+#include <stan/math/prim/mat/prob/multi_normal_prec_log.hpp>
+#include <stan/math/prim/mat/prob/multi_normal_rng.hpp>
+#include <stan/math/prim/mat/prob/multi_student_t_log.hpp>
+#include <stan/math/prim/mat/prob/multi_student_t_rng.hpp>
+#include <stan/math/prim/mat/prob/multinomial_log.hpp>
+#include <stan/math/prim/mat/prob/multinomial_rng.hpp>
+#include <stan/math/prim/mat/prob/ordered_logistic_log.hpp>
+#include <stan/math/prim/mat/prob/ordered_logistic_rng.hpp>
+#include <stan/math/prim/mat/prob/wishart_log.hpp>
+#include <stan/math/prim/mat/prob/wishart_rng.hpp>
+#include <stan/math/prim/arr.hpp>
+
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diff --git a/doc/api/html/prim_2mat_8hpp_source.html b/doc/api/html/prim_2mat_8hpp_source.html new file mode 100644 index 00000000000..aea7bdf0b8b --- /dev/null +++ b/doc/api/html/prim_2mat_8hpp_source.html @@ -0,0 +1,566 @@ + + + + + + +Stan Math Library: stan/math/prim/mat.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_HPP
+
2 #define STAN_MATH_PRIM_MAT_HPP
+
3 
+ + + + +
8 
+ + + + + + + + + + + + + +
22 
+ + + + + + + + + + + + + + + + + + + + + + + + + +
48 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
198 
+ + +
201 
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231 
+
232 #include <stan/math/prim/arr.hpp>
+
233 
+
234 #endif
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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diff --git a/doc/api/html/prim_2scal_2fun_2_phi_8hpp.html b/doc/api/html/prim_2scal_2fun_2_phi_8hpp.html new file mode 100644 index 00000000000..c81a739026b --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2_phi_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/Phi.hpp File Reference + + + + + + + + + + +
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Phi.hpp File Reference
+
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+
#include <boost/math/tools/promotion.hpp>
+#include <boost/math/special_functions/erf.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::Phi (const T x)
 The unit normal cumulative distribution function. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2_phi_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2_phi_8hpp_source.html new file mode 100644 index 00000000000..9b9f213cd86 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2_phi_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/Phi.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_PHI_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_PHI_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 #include <boost/math/special_functions/erf.hpp>
+ + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
29  template <typename T>
+
30  inline typename boost::math::tools::promote_args<T>::type
+
31  Phi(const T x) {
+
32  // overridden in fvar and var, so can hard-code boost versions
+
33  // here for scalars only
+ +
35 
+
36  check_not_nan("Phi", "x", x);
+
37  if (x < -37.5)
+
38  return 0;
+
39  else if (x < -5.0)
+
40  return 0.5 * boost::math::erfc(-INV_SQRT_2 * x);
+
41  else if (x > 8.25)
+
42  return 1;
+
43  else
+
44  return 0.5 * (1.0 + boost::math::erf(INV_SQRT_2 * x));
+
45  }
+
46 
+
47  }
+
48 }
+
49 
+
50 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+
const double INV_SQRT_2
The value of 1 over the square root of 2, .
Definition: constants.hpp:27
+
fvar< T > Phi(const fvar< T > &x)
Definition: Phi.hpp:14
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2_phi__approx_8hpp.html b/doc/api/html/prim_2scal_2fun_2_phi__approx_8hpp.html new file mode 100644 index 00000000000..2ed0cd7173b --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2_phi__approx_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/Phi_approx.hpp File Reference + + + + + + + + + + +
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Phi_approx.hpp File Reference
+
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+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/fun/inv_logit.hpp>
+
+

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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::Phi_approx (T x)
 Approximation of the unit normal CDF. More...
 
+
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2_phi__approx_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2_phi__approx_8hpp_source.html new file mode 100644 index 00000000000..2fc324de465 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2_phi__approx_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/Phi_approx.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_PHI_APPROX_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_PHI_APPROX_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
21  template <typename T>
+
22  inline typename boost::math::tools::promote_args<T>::type
+
23  Phi_approx(T x) {
+
24  using std::pow;
+
25  return inv_logit(0.07056 * pow(x, 3.0) + 1.5976 * x);
+
26  }
+
27 
+
28  }
+
29 }
+
30 
+
31 #endif
+ +
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
boost::math::tools::promote_args< T >::type Phi_approx(T x)
Approximation of the unit normal CDF.
Definition: Phi_approx.hpp:23
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2abs_8hpp.html b/doc/api/html/prim_2scal_2fun_2abs_8hpp.html new file mode 100644 index 00000000000..920fb31b59b --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2abs_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/abs.hpp File Reference + + + + + + + + + + +
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double stan::math::abs (double x)
 Return floating-point absolute value. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2abs_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2abs_8hpp_source.html new file mode 100644 index 00000000000..858661b1886 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2abs_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/abs.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_ABS_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_ABS_HPP
+
3 
+
4 #include <cmath>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
19  double abs(double x) {
+
20  return std::fabs(x);
+
21  }
+
22 
+
23  }
+
24 }
+
25 
+
26 #endif
+
fvar< T > abs(const fvar< T > &x)
Definition: abs.hpp:15
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
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diff --git a/doc/api/html/prim_2scal_2fun_2as__bool_8hpp.html b/doc/api/html/prim_2scal_2fun_2as__bool_8hpp.html new file mode 100644 index 00000000000..b436f75f36a --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2as__bool_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/as_bool.hpp File Reference + + + + + + + + + + +
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template<typename T >
bool stan::math::as_bool (const T x)
 Return 1 if the argument is unequal to zero and 0 otherwise. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2as__bool_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2as__bool_8hpp_source.html new file mode 100644 index 00000000000..b53da549c4c --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2as__bool_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/as_bool.hpp Source File + + + + + + + + + + +
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as_bool.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_AS_BOOL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_AS_BOOL_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
13  template <typename T>
+
14  inline bool as_bool(const T x) {
+
15  return x != 0;
+
16  }
+
17 
+
18  }
+
19 }
+
20 
+
21 #endif
+
bool as_bool(const T x)
Return 1 if the argument is unequal to zero and 0 otherwise.
Definition: as_bool.hpp:14
+ +
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diff --git a/doc/api/html/prim_2scal_2fun_2bessel__first__kind_8hpp.html b/doc/api/html/prim_2scal_2fun_2bessel__first__kind_8hpp.html new file mode 100644 index 00000000000..c057d997a5f --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2bessel__first__kind_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/bessel_first_kind.hpp File Reference + + + + + + + + + + +
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bessel_first_kind.hpp File Reference
+
+
+
#include <boost/math/special_functions/bessel.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+
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template<typename T2 >
T2 stan::math::bessel_first_kind (const int v, const T2 z)
 

+\[ \mbox{bessel\_first\_kind}(v, x) = \begin{cases} J_v(x) & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{error} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2bessel__first__kind_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2bessel__first__kind_8hpp_source.html new file mode 100644 index 00000000000..5ffab856128 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2bessel__first__kind_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/bessel_first_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_BESSEL_FIRST_KIND_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_BESSEL_FIRST_KIND_HPP
+
3 
+
4 #include <boost/math/special_functions/bessel.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
38  template<typename T2>
+
39  inline T2
+
40  bessel_first_kind(const int v, const T2 z) {
+ +
42 
+
43  check_not_nan("bessel_first_kind", "z", z);
+
44  return boost::math::cyl_bessel_j(v, z);
+
45  }
+
46 
+
47  }
+
48 }
+
49 
+
50 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+
fvar< T > bessel_first_kind(int v, const fvar< T > &z)
+ +
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diff --git a/doc/api/html/prim_2scal_2fun_2bessel__second__kind_8hpp.html b/doc/api/html/prim_2scal_2fun_2bessel__second__kind_8hpp.html new file mode 100644 index 00000000000..4bc739c2ece --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2bessel__second__kind_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/bessel_second_kind.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/bessel.hpp>
+
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template<typename T2 >
T2 stan::math::bessel_second_kind (const int v, const T2 z)
 

+\[ \mbox{bessel\_second\_kind}(v, x) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0 \\ Y_v(x) & \mbox{if } x > 0 \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2bessel__second__kind_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2bessel__second__kind_8hpp_source.html new file mode 100644 index 00000000000..fd126830021 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2bessel__second__kind_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/bessel_second_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_BESSEL_SECOND_KIND_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_BESSEL_SECOND_KIND_HPP
+
3 
+
4 #include <boost/math/special_functions/bessel.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
38  template <typename T2>
+
39  inline T2
+
40  bessel_second_kind(const int v, const T2 z) {
+
41  return boost::math::cyl_neumann(v, z);
+
42  }
+
43 
+
44  }
+
45 }
+
46 
+
47 #endif
+ +
fvar< T > bessel_second_kind(int v, const fvar< T > &z)
+
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2binary__log__loss_8hpp.html b/doc/api/html/prim_2scal_2fun_2binary__log__loss_8hpp.html new file mode 100644 index 00000000000..2894759e5b8 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2binary__log__loss_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/binary_log_loss.hpp File Reference + + + + + + + + + + +
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#include <boost/math/tools/promotion.hpp>
+
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::binary_log_loss (const int y, const T y_hat)
 Returns the log loss function for binary classification with specified reference and response values. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2binary__log__loss_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2binary__log__loss_8hpp_source.html new file mode 100644 index 00000000000..957fc440c58 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2binary__log__loss_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/binary_log_loss.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_BINARY_LOG_LOSS_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_BINARY_LOG_LOSS_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
24  template <typename T>
+
25  inline typename boost::math::tools::promote_args<T>::type
+
26  binary_log_loss(const int y, const T y_hat) {
+
27  using std::log;
+
28  return -log(y ? y_hat : (1.0 - y_hat));
+
29  }
+
30 
+
31  }
+
32 }
+
33 
+
34 #endif
+ +
fvar< T > binary_log_loss(const int y, const fvar< T > &y_hat)
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
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diff --git a/doc/api/html/prim_2scal_2fun_2binomial__coefficient__log_8hpp.html b/doc/api/html/prim_2scal_2fun_2binomial__coefficient__log_8hpp.html new file mode 100644 index 00000000000..4aadfad230c --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2binomial__coefficient__log_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/binomial_coefficient_log.hpp File Reference + + + + + + + + + + +
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binomial_coefficient_log.hpp File Reference
+
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#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/tools/promotion.hpp>
+
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template<typename T_N , typename T_n >
boost::math::tools::promote_args< T_N, T_n >::type stan::math::binomial_coefficient_log (const T_N N, const T_n n)
 Return the log of the binomial coefficient for the specified arguments. More...
 
+
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diff --git a/doc/api/html/prim_2scal_2fun_2binomial__coefficient__log_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2binomial__coefficient__log_8hpp_source.html new file mode 100644 index 00000000000..791a07b52ce --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2binomial__coefficient__log_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/binomial_coefficient_log.hpp Source File + + + + + + + + + + +
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binomial_coefficient_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_BINOMIAL_COEFFICIENT_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_BINOMIAL_COEFFICIENT_LOG_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 #include <boost/math/tools/promotion.hpp>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
60  template <typename T_N, typename T_n>
+
61  inline typename boost::math::tools::promote_args<T_N, T_n>::type
+
62  binomial_coefficient_log(const T_N N, const T_n n) {
+
63  using std::log;
+
64  using boost::math::lgamma;
+
65  const double CUTOFF = 1000;
+
66  if (N - n < CUTOFF) {
+
67  T_N N_plus_1 = N + 1;
+
68  return lgamma(N_plus_1) - lgamma(n + 1) - lgamma(N_plus_1 - n);
+
69  } else {
+
70  typename boost::math::tools::promote_args<T_N, T_n>::type N_minus_n
+
71  = N - n;
+
72  double one_twelfth = 1.0 / 12;
+
73  return n * log(N_minus_n)
+
74  + (N + 0.5) * log(N / N_minus_n)
+
75  + one_twelfth / N
+
76  - n
+
77  - one_twelfth / N_minus_n
+
78  - lgamma(n + 1);
+
79  }
+
80  }
+
81 
+
82  }
+
83 }
+
84 #endif
+
fvar< T > binomial_coefficient_log(const fvar< T > &x1, const fvar< T > &x2)
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
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diff --git a/doc/api/html/prim_2scal_2fun_2digamma_8hpp.html b/doc/api/html/prim_2scal_2fun_2digamma_8hpp.html new file mode 100644 index 00000000000..9904d158d25 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2digamma_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/digamma.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/digamma.hpp>
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double stan::math::digamma (double x)
 

+\[ \mbox{digamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

+ More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2digamma_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2digamma_8hpp_source.html new file mode 100644 index 00000000000..88df4c0ddb7 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2digamma_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/digamma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_DIGAMMA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_DIGAMMA_HPP
+
3 
+
4 #include <boost/math/special_functions/digamma.hpp>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
39  double digamma(double x) {
+
40  return boost::math::digamma(x);
+
41  }
+
42 
+
43  }
+
44 }
+
45 
+
46 #endif
+ +
var digamma(const stan::math::var &a)
Definition: digamma.hpp:24
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2divide_8hpp.html b/doc/api/html/prim_2scal_2fun_2divide_8hpp.html new file mode 100644 index 00000000000..b03135d15b8 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2divide_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/divide.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/meta/return_type.hpp>
+#include <cstddef>
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template<typename T1 , typename T2 >
stan::return_type< T1, T2 >::type stan::math::divide (const T1 &x, const T2 &y)
 Return the division of the first scalar by the second scalar. More...
 
int stan::math::divide (const int x, const int y)
 
+
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diff --git a/doc/api/html/prim_2scal_2fun_2divide_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2divide_8hpp_source.html new file mode 100644 index 00000000000..662ac235fa0 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2divide_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/divide.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_DIVIDE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_DIVIDE_HPP
+
3 
+ +
5 #include <cstddef>
+
6 #include <cstdlib>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
18  template<typename T1, typename T2>
+
19  inline typename stan::return_type<T1, T2>::type
+
20  divide(const T1& x, const T2& y) {
+
21  return x / y;
+
22  }
+
23 
+
24  inline int divide(const int x, const int y) {
+
25  return std::div(x, y).quot;
+
26  }
+
27 
+
28 
+
29  }
+
30 }
+
31 
+
32 #endif
+ + +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
Eigen::Matrix< fvar< T >, R, C > divide(const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
Definition: divide.hpp:16
+
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diff --git a/doc/api/html/prim_2scal_2fun_2exp2_8hpp.html b/doc/api/html/prim_2scal_2fun_2exp2_8hpp.html new file mode 100644 index 00000000000..dc3093ff78d --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2exp2_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/exp2.hpp File Reference + + + + + + + + + + +
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#include <boost/math/tools/promotion.hpp>
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+
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::exp2 (const T y)
 Return the exponent base 2 of the specified argument (C99). More...
 
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+
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diff --git a/doc/api/html/prim_2scal_2fun_2exp2_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2exp2_8hpp_source.html new file mode 100644 index 00000000000..6626d22398e --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2exp2_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/exp2.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_EXP2_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_EXP2_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
21  template <typename T>
+
22  inline typename boost::math::tools::promote_args<T>::type
+
23  exp2(const T y) {
+
24  using std::pow;
+
25  return pow(2.0, y);
+
26  }
+
27 
+
28  }
+
29 }
+
30 #endif
+ +
fvar< T > exp2(const fvar< T > &x)
Definition: exp2.hpp:14
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
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diff --git a/doc/api/html/prim_2scal_2fun_2falling__factorial_8hpp.html b/doc/api/html/prim_2scal_2fun_2falling__factorial_8hpp.html new file mode 100644 index 00000000000..8d052be9d66 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2falling__factorial_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/falling_factorial.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::falling_factorial (const T1 x, const T2 n)
 

+\[ \mbox{falling\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ (x)_n & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2falling__factorial_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2falling__factorial_8hpp_source.html new file mode 100644 index 00000000000..d2f90a79e41 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2falling__factorial_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/falling_factorial.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_FALLING_FACTORIAL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_FALLING_FACTORIAL_HPP
+
3 
+ +
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
52  template<typename T1, typename T2>
+
53  inline typename boost::math::tools::promote_args<T1, T2>::type
+
54  falling_factorial(const T1 x, const T2 n) {
+
55  using std::exp;
+
56  return exp(log_falling_factorial(x, n));
+
57  }
+
58 
+
59  }
+
60 }
+
61 
+
62 #endif
+
fvar< T > log_falling_factorial(const fvar< T > &x, const fvar< T > &n)
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > falling_factorial(const fvar< T > &x, const fvar< T > &n)
+ +
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diff --git a/doc/api/html/prim_2scal_2fun_2fdim_8hpp.html b/doc/api/html/prim_2scal_2fun_2fdim_8hpp.html new file mode 100644 index 00000000000..edd19fb1211 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2fdim_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/fdim.hpp File Reference + + + + + + + + + + +
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#include <math.h>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <cmath>
+#include <limits>
+
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template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::fdim (T1 a, T2 b)
 The positive difference function (C99). More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2fdim_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2fdim_8hpp_source.html new file mode 100644 index 00000000000..493eb112952 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2fdim_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/fdim.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_FDIM_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_FDIM_HPP
+
3 
+
4 #include <math.h>
+
5 #include <boost/math/special_functions/fpclassify.hpp>
+
6 #include <boost/math/tools/promotion.hpp>
+
7 #include <cmath>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
24  template <typename T1, typename T2>
+
25  inline typename boost::math::tools::promote_args<T1, T2>::type
+
26  fdim(T1 a, T2 b) {
+ +
28  using std::numeric_limits;
+
29  using boost::math::tools::promote_args;
+ +
31  return numeric_limits<typename promote_args<T1, T2>::type>::quiet_NaN();
+
32  return fdim(a, b);
+
33  }
+
34  }
+
35 }
+
36 
+
37 #endif
+ +
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
fvar< T > fdim(const fvar< T > &x1, const fvar< T > &x2)
Definition: fdim.hpp:11
+
var fdim(const stan::math::var &a, const double &b)
Return the positive difference between the first variable's value and the second value (C99)...
Definition: fdim.hpp:158
+
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diff --git a/doc/api/html/prim_2scal_2fun_2gamma__p_8hpp.html b/doc/api/html/prim_2scal_2fun_2gamma__p_8hpp.html new file mode 100644 index 00000000000..bed5be878e9 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2gamma__p_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/gamma_p.hpp File Reference + + + + + + + + + + +
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double stan::math::gamma_p (double x, double a)
 

+\[ \mbox{gamma\_p}(a, z) = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ P(a, z) & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2gamma__p_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2gamma__p_8hpp_source.html new file mode 100644 index 00000000000..1ee01a56140 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2gamma__p_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/gamma_p.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_GAMMA_P_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_GAMMA_P_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
52  // throws domain_error if x is at pole
+
53  double gamma_p(double x, double a) {
+
54  return boost::math::gamma_p(x, a);
+
55  }
+
56 
+
57  }
+
58 }
+
59 
+
60 #endif
+ +
var gamma_p(const double &a, const stan::math::var &b)
Definition: gamma_p.hpp:114
+
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+
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diff --git a/doc/api/html/prim_2scal_2fun_2gamma__q_8hpp.html b/doc/api/html/prim_2scal_2fun_2gamma__q_8hpp.html new file mode 100644 index 00000000000..3a40d59b3dd --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2gamma__q_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/gamma_q.hpp File Reference + + + + + + + + + + +
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double stan::math::gamma_q (double x, double a)
 

+\[ \mbox{gamma\_q}(a, z) = \begin{cases} \textrm{error} & \mbox{if } a\leq 0 \textrm{ or } z < 0\\ Q(a, z) & \mbox{if } a > 0, z \geq 0 \\[6pt] \textrm{NaN} & \mbox{if } a = \textrm{NaN or } z = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2gamma__q_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2gamma__q_8hpp_source.html new file mode 100644 index 00000000000..4a8862c5f3c --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2gamma__q_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/gamma_q.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_GAMMA_Q_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_GAMMA_Q_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
52  // throws domain_error if x is at pole
+
53  double gamma_q(double x, double a) {
+
54  return boost::math::gamma_q(x, a);
+
55  }
+
56 
+
57  }
+
58 }
+
59 
+
60 #endif
+ +
var gamma_q(const double &a, const stan::math::var &b)
Definition: gamma_q.hpp:68
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+
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diff --git a/doc/api/html/prim_2scal_2fun_2grad__inc__beta_8hpp.html b/doc/api/html/prim_2scal_2fun_2grad__inc__beta_8hpp.html new file mode 100644 index 00000000000..a1fbcae2511 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2grad__inc__beta_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_inc_beta.hpp File Reference + + + + + + + + + + +
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void stan::math::grad_inc_beta (double &g1, double &g2, double a, double b, double z)
 
+
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diff --git a/doc/api/html/prim_2scal_2fun_2grad__inc__beta_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2grad__inc__beta_8hpp_source.html new file mode 100644 index 00000000000..5d3682a8224 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2grad__inc__beta_8hpp_source.html @@ -0,0 +1,159 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/grad_inc_beta.hpp Source File + + + + + + + + + + +
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grad_inc_beta.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_GRAD_INC_BETA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_GRAD_INC_BETA_HPP
+
3 
+ + + + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  // Gradient of the incomplete beta function beta(a, b, z)
+
14  // with respect to the first two arguments, using the
+
15  // equivalence to a hypergeometric function.
+
16  // See http://dlmf.nist.gov/8.17#ii
+
17  void grad_inc_beta(double& g1, double& g2, double a, double b, double z) {
+
18  using stan::math::lbeta;
+ +
20  using stan::math::log1m;
+ +
22  using std::exp;
+
23  using std::log;
+
24 
+
25  double c1 = log(z);
+
26  double c2 = log1m(z);
+
27  double c3 = exp(lbeta(a, b)) * inc_beta(a, b, z);
+
28  double C = exp(a * c1 + b * c2) / a;
+
29  double dF1 = 0;
+
30  double dF2 = 0;
+
31  if (C) grad_2F1(dF1, dF2, a + b, 1.0, a + 1, z);
+
32  g1 = (c1 - 1.0 / a) * c3 + C * (dF1 + dF2);
+
33  g2 = c2 * c3 + C * dF1;
+
34  }
+
35 
+
36  }
+
37 }
+
38 #endif
+ +
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
void grad_inc_beta(stan::math::fvar< T > &g1, stan::math::fvar< T > &g2, stan::math::fvar< T > a, stan::math::fvar< T > b, stan::math::fvar< T > z)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + + + +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
void grad_2F1(T &gradA, T &gradC, T a, T b, T c, T z, T precision=1e-6)
Definition: grad_2F1.hpp:13
+
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diff --git a/doc/api/html/prim_2scal_2fun_2ibeta_8hpp.html b/doc/api/html/prim_2scal_2fun_2ibeta_8hpp.html new file mode 100644 index 00000000000..3d2b96924a8 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2ibeta_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/ibeta.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/beta.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+
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double stan::math::ibeta (const double a, const double b, const double x)
 The normalized incomplete beta function of a, b, and x. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2ibeta_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2ibeta_8hpp_source.html new file mode 100644 index 00000000000..bacc74d19a4 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2ibeta_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/ibeta.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_IBETA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_IBETA_HPP
+
3 
+
4 #include <boost/math/special_functions/beta.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
23  inline double ibeta(const double a,
+
24  const double b,
+
25  const double x) {
+ +
27 
+
28  check_not_nan("ibeta", "a", a);
+
29  check_not_nan("ibeta", "b", b);
+
30  check_not_nan("ibeta", "x", x);
+
31  return boost::math::ibeta(a, b, x);
+
32  }
+
33 
+
34  }
+
35 }
+
36 
+
37 #endif
+ +
double ibeta(const double a, const double b, const double x)
The normalized incomplete beta function of a, b, and x.
Definition: ibeta.hpp:23
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
var ibeta(const var &a, const var &b, const var &x)
The normalized incomplete beta function of a, b, and x.
Definition: ibeta.hpp:238
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2if__else_8hpp.html b/doc/api/html/prim_2scal_2fun_2if__else_8hpp.html new file mode 100644 index 00000000000..09b829ce542 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2if__else_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/if_else.hpp File Reference + + + + + + + + + + +
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template<typename T_true , typename T_false >
boost::math::tools::promote_args< T_true, T_false >::type stan::math::if_else (const bool c, const T_true y_true, const T_false y_false)
 Return the second argument if the first argument is true and otherwise return the second argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2if__else_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2if__else_8hpp_source.html new file mode 100644 index 00000000000..36b8ac174d9 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2if__else_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/if_else.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_IF_ELSE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_IF_ELSE_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
23  template <typename T_true, typename T_false>
+
24  inline typename boost::math::tools::promote_args<T_true, T_false>::type
+
25  if_else(const bool c, const T_true y_true, const T_false y_false) {
+
26  return c ? y_true : y_false;
+
27  }
+
28 
+
29  }
+
30 }
+
31 
+
32 #endif
+ +
boost::math::tools::promote_args< T_true, T_false >::type if_else(const bool c, const T_true y_true, const T_false y_false)
Return the second argument if the first argument is true and otherwise return the second argument...
Definition: if_else.hpp:25
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diff --git a/doc/api/html/prim_2scal_2fun_2inc__beta_8hpp.html b/doc/api/html/prim_2scal_2fun_2inc__beta_8hpp.html new file mode 100644 index 00000000000..a34ab9ba2c4 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inc__beta_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inc_beta.hpp File Reference + + + + + + + + + + +
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double stan::math::inc_beta (const double &a, const double &b, const double &x)
 
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diff --git a/doc/api/html/prim_2scal_2fun_2inc__beta_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2inc__beta_8hpp_source.html new file mode 100644 index 00000000000..29aa3325051 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inc__beta_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inc_beta.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INC_BETA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INC_BETA_HPP
+
3 
+
4 #include <boost/math/special_functions/beta.hpp>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
10  inline double inc_beta(const double& a,
+
11  const double& b,
+
12  const double& x) {
+
13  using boost::math::ibeta;
+
14  return ibeta(a, b, x);
+
15  }
+
16  }
+
17 }
+
18 #endif
+
double ibeta(const double a, const double b, const double x)
The normalized incomplete beta function of a, b, and x.
Definition: ibeta.hpp:23
+ +
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
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diff --git a/doc/api/html/prim_2scal_2fun_2inv_8hpp.html b/doc/api/html/prim_2scal_2fun_2inv_8hpp.html new file mode 100644 index 00000000000..56b8ba3db17 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv.hpp File Reference + + + + + + + + + + +
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::inv (const T x)
 
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diff --git a/doc/api/html/prim_2scal_2fun_2inv_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2inv_8hpp_source.html new file mode 100644 index 00000000000..e2ee034e6ef --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INV_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INV_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  template <typename T>
+
10  inline
+
11  typename boost::math::tools::promote_args<T>::type
+
12  inv(const T x) {
+
13  return 1.0 / x;
+
14  }
+
15 
+
16  }
+
17 }
+
18 
+
19 #endif
+ +
fvar< T > inv(const fvar< T > &x)
Definition: inv.hpp:15
+
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diff --git a/doc/api/html/prim_2scal_2fun_2inv___phi_8hpp.html b/doc/api/html/prim_2scal_2fun_2inv___phi_8hpp.html new file mode 100644 index 00000000000..ea98a80ce0d --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv___phi_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_Phi.hpp File Reference + + + + + + + + + + +
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double stan::math::inv_Phi (double p)
 The inverse of the unit normal cumulative distribution function. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2inv___phi_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2inv___phi_8hpp_source.html new file mode 100644 index 00000000000..b1d5d815665 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv___phi_8hpp_source.html @@ -0,0 +1,195 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_Phi.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INV_PHI_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INV_PHI_HPP
+
3 
+ + + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
26  inline double inv_Phi(double p) {
+
27  stan::math::check_bounded<double, double, double>("inv_Phi",
+
28  "Probability variable", p, 0, 1);
+
29 
+
30  if (p < 8e-311)
+
31  return NEGATIVE_INFTY;
+
32  if (p == 1)
+
33  return INFTY;
+
34 
+
35  static const double a[6] = {
+
36  -3.969683028665376e+01, 2.209460984245205e+02,
+
37  -2.759285104469687e+02, 1.383577518672690e+02,
+
38  -3.066479806614716e+01, 2.506628277459239e+00
+
39  };
+
40  static const double b[5] = {
+
41  -5.447609879822406e+01, 1.615858368580409e+02,
+
42  -1.556989798598866e+02, 6.680131188771972e+01,
+
43  -1.328068155288572e+01
+
44  };
+
45  static const double c[6] = {
+
46  -7.784894002430293e-03, -3.223964580411365e-01,
+
47  -2.400758277161838e+00, -2.549732539343734e+00,
+
48  4.374664141464968e+00, 2.938163982698783e+00
+
49  };
+
50  static const double d[4] = {
+
51  7.784695709041462e-03, 3.224671290700398e-01,
+
52  2.445134137142996e+00, 3.754408661907416e+00
+
53  };
+
54 
+
55  static const double p_low = 0.02425;
+
56  static const double p_high = 0.97575;
+
57 
+
58  double x;
+
59  if ((p_low <= p) && (p <= p_high)) {
+
60  double q = p - 0.5;
+
61  double r = q * q;
+
62  x = (((((a[0]*r + a[1])*r + a[2])*r + a[3])*r + a[4])*r + a[5])*q
+
63  / (((((b[0]*r + b[1])*r + b[2])*r + b[3])*r + b[4])*r + 1.0);
+
64  } else if (p < p_low) {
+
65  double q = std::sqrt(-2.0*std::log(p));
+
66  x = (((((c[0]*q + c[1])*q + c[2])*q + c[3])*q + c[4])*q + c[5])
+
67  / ((((d[0]*q + d[1])*q + d[2])*q + d[3])*q + 1.0);
+
68  } else {
+
69  double q = std::sqrt(-2.0 * stan::math::log1m(p));
+
70  x = -(((((c[0]*q + c[1])*q + c[2])*q + c[3])*q + c[4])*q + c[5])
+
71  / ((((d[0]*q + d[1])*q + d[2])*q + d[3])*q + 1.0);
+
72  }
+
73 
+
74  if (x < 37.6) { // gradient blows up past here
+
75  double e = stan::math::Phi(x) - p;
+
76  double u = e * SQRT_2_TIMES_SQRT_PI * std::exp(0.5 * x * x);
+
77  x -= u / (1.0 + 0.5 * x * u);
+
78  }
+
79 
+
80  return x;
+
81  }
+
82 
+
83  }
+
84 }
+
85 #endif
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
fvar< T > inv_Phi(const fvar< T > &p)
Definition: inv_Phi.hpp:15
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
const double SQRT_2_TIMES_SQRT_PI
Definition: constants.hpp:158
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > Phi(const fvar< T > &x)
Definition: Phi.hpp:14
+ + +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+ +
const double INFTY
Positive infinity.
Definition: constants.hpp:44
+
const double NEGATIVE_INFTY
Negative infinity.
Definition: constants.hpp:50
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
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diff --git a/doc/api/html/prim_2scal_2fun_2inv__cloglog_8hpp.html b/doc/api/html/prim_2scal_2fun_2inv__cloglog_8hpp.html new file mode 100644 index 00000000000..a62d63d46d5 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv__cloglog_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_cloglog.hpp File Reference + + + + + + + + + + +
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template<typename T >
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 The inverse complementary log-log function. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2inv__cloglog_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2inv__cloglog_8hpp_source.html new file mode 100644 index 00000000000..4d2d0bd73d8 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv__cloglog_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_cloglog.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INV_CLOGLOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INV_CLOGLOG_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
47  template <typename T>
+
48  inline typename boost::math::tools::promote_args<T>::type
+
49  inv_cloglog(T x) {
+
50  using std::exp;
+
51  return 1 - exp(-exp(x));
+
52  }
+
53 
+
54  }
+
55 }
+
56 
+
57 #endif
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > inv_cloglog(const fvar< T > &x)
Definition: inv_cloglog.hpp:15
+
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diff --git a/doc/api/html/prim_2scal_2fun_2inv__logit_8hpp.html b/doc/api/html/prim_2scal_2fun_2inv__logit_8hpp.html new file mode 100644 index 00000000000..f5180aa043e --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv__logit_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_logit.hpp File Reference + + + + + + + + + + +
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 Returns the inverse logit function applied to the argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2inv__logit_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2inv__logit_8hpp_source.html new file mode 100644 index 00000000000..f56d8791a7c --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv__logit_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_logit.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INV_LOGIT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INV_LOGIT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
50  template <typename T>
+
51  inline typename boost::math::tools::promote_args<T>::type
+
52  inv_logit(const T a) {
+
53  using std::exp;
+
54  return 1.0 / (1.0 + exp(-a));
+
55  }
+
56 
+
57  }
+
58 }
+
59 
+
60 #endif
+
61 
+ +
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2inv__sqrt_8hpp.html b/doc/api/html/prim_2scal_2fun_2inv__sqrt_8hpp.html new file mode 100644 index 00000000000..034671f70c3 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv__sqrt_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_sqrt.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/prim_2scal_2fun_2inv__sqrt_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2inv__sqrt_8hpp_source.html new file mode 100644 index 00000000000..abd625ac05f --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv__sqrt_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_sqrt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INV_SQRT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INV_SQRT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  template <typename T>
+
10  inline
+
11  typename boost::math::tools::promote_args<T>::type
+
12  inv_sqrt(const T x) {
+
13  using std::sqrt;
+
14 
+
15  return 1.0 / sqrt(x);
+
16  }
+
17 
+
18  }
+
19 }
+
20 
+
21 #endif
+
fvar< T > inv_sqrt(const fvar< T > &x)
Definition: inv_sqrt.hpp:15
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
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diff --git a/doc/api/html/prim_2scal_2fun_2inv__square_8hpp.html b/doc/api/html/prim_2scal_2fun_2inv__square_8hpp.html new file mode 100644 index 00000000000..7f8ba4ae9c6 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv__square_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_square.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/prim_2scal_2fun_2inv__square_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2inv__square_8hpp_source.html new file mode 100644 index 00000000000..d2dc5e73712 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2inv__square_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/inv_square.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_INV_SQUARE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_INV_SQUARE_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  template <typename T>
+
10  inline
+
11  typename boost::math::tools::promote_args<T>::type
+
12  inv_square(const T x) {
+
13  return 1.0 / (x * x);
+
14  }
+
15  }
+
16 }
+
17 
+
18 #endif
+ +
fvar< T > inv_square(const fvar< T > &x)
Definition: inv_square.hpp:15
+
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diff --git a/doc/api/html/prim_2scal_2fun_2is__inf_8hpp.html b/doc/api/html/prim_2scal_2fun_2is__inf_8hpp.html new file mode 100644 index 00000000000..8708408ba06 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2is__inf_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/is_inf.hpp File Reference + + + + + + + + + + +
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 Returns 1 if the input is infinite and 0 otherwise. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2is__inf_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2is__inf_8hpp_source.html new file mode 100644 index 00000000000..7786c343d75 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2is__inf_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/is_inf.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_IS_INF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_IS_INF_HPP
+
3 
+
4 #include <boost/math/special_functions/fpclassify.hpp>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
18  inline int
+
19  is_inf(const double x) {
+
20  return boost::math::isinf(x);
+
21  }
+
22 
+
23  }
+
24 }
+
25 
+
26 #endif
+ +
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+
int is_inf(const fvar< T > &x)
Returns 1 if the input's value is infinite and 0 otherwise.
Definition: is_inf.hpp:22
+
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diff --git a/doc/api/html/prim_2scal_2fun_2is__nan_8hpp.html b/doc/api/html/prim_2scal_2fun_2is__nan_8hpp.html new file mode 100644 index 00000000000..8c5f9605884 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2is__nan_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/is_nan.hpp File Reference + + + + + + + + + + +
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bool stan::math::is_nan (double x)
 Returns 1 if the input is NaN and 0 otherwise. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2is__nan_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2is__nan_8hpp_source.html new file mode 100644 index 00000000000..7428747ae9a --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2is__nan_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/is_nan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_IS_NAN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_IS_NAN_HPP
+
3 
+
4 #include <boost/math/special_functions/fpclassify.hpp>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
18  inline bool is_nan(double x) {
+
19  return boost::math::isnan(x);
+
20  }
+
21 
+
22  }
+
23 }
+
24 
+
25 #endif
+ +
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
int is_nan(const fvar< T > &x)
Returns 1 if the input's value is NaN and 0 otherwise.
Definition: is_nan.hpp:22
+
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diff --git a/doc/api/html/prim_2scal_2fun_2is__uninitialized_8hpp.html b/doc/api/html/prim_2scal_2fun_2is__uninitialized_8hpp.html new file mode 100644 index 00000000000..3fa50519cc5 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2is__uninitialized_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/is_uninitialized.hpp File Reference + + + + + + + + + + +
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bool stan::math::is_uninitialized (T x)
 Returns true if the specified variable is uninitialized. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2is__uninitialized_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2is__uninitialized_8hpp_source.html new file mode 100644 index 00000000000..b5a2326ae57 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2is__uninitialized_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/is_uninitialized.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_IS_UNINITIALIZED_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_IS_UNINITIALIZED_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  namespace math {
+
7 
+
18  template <typename T>
+
19  inline bool is_uninitialized(T x) {
+
20  return false;
+
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ +
bool is_uninitialized(T x)
Returns true if the specified variable is uninitialized.
+
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diff --git a/doc/api/html/prim_2scal_2fun_2lbeta_8hpp.html b/doc/api/html/prim_2scal_2fun_2lbeta_8hpp.html new file mode 100644 index 00000000000..98cdb8a9792 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2lbeta_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lbeta.hpp File Reference + + + + + + + + + + +
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+
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template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::lbeta (const T1 a, const T2 b)
 Return the log of the beta function applied to the specified arguments. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2lbeta_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2lbeta_8hpp_source.html new file mode 100644 index 00000000000..586a882715e --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2lbeta_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lbeta.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LBETA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LBETA_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 #include <boost/math/special_functions/gamma.hpp>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
57  template <typename T1, typename T2>
+
58  inline typename boost::math::tools::promote_args<T1, T2>::type
+
59  lbeta(const T1 a, const T2 b) {
+
60  using boost::math::lgamma;
+
61  return lgamma(a)
+
62  + lgamma(b)
+
63  - lgamma(a + b);
+
64  }
+
65 
+
66  }
+
67 }
+
68 
+
69 #endif
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+
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diff --git a/doc/api/html/prim_2scal_2fun_2lgamma_8hpp.html b/doc/api/html/prim_2scal_2fun_2lgamma_8hpp.html new file mode 100644 index 00000000000..823123ca3f7 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2lgamma_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lgamma.hpp File Reference + + + + + + + + + + +
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double stan::math::lgamma (double x)
 

+\[ \mbox{lgamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \ln\Gamma(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2lgamma_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2lgamma_8hpp_source.html new file mode 100644 index 00000000000..d52ef7f0a29 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2lgamma_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lgamma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LGAMMA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LGAMMA_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
30  // throws domain_error if x is at pole
+
31  double lgamma(double x) {
+
32  return boost::math::lgamma(x);
+
33  }
+
34 
+
35  }
+
36 }
+
37 
+
38 #endif
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
var lgamma(const stan::math::var &a)
The log gamma function for variables (C99).
Definition: lgamma.hpp:35
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2lmgamma_8hpp.html b/doc/api/html/prim_2scal_2fun_2lmgamma_8hpp.html new file mode 100644 index 00000000000..cb6f28e0c95 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2lmgamma_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lmgamma.hpp File Reference + + + + + + + + + + +
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#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+
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template<typename T >
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 Return the natural logarithm of the multivariate gamma function with the speciifed dimensions and argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2lmgamma_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2lmgamma_8hpp_source.html new file mode 100644 index 00000000000..ba42fc64def --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2lmgamma_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/lmgamma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LMGAMMA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LMGAMMA_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ +
6 #include <boost/math/special_functions/gamma.hpp>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
55  template <typename T>
+
56  inline typename boost::math::tools::promote_args<T>::type
+
57  lmgamma(const int k, T x) {
+
58  using boost::math::lgamma;
+
59  typename boost::math::tools::promote_args<T>::type result
+
60  = k * (k - 1) * LOG_PI_OVER_FOUR;
+
61 
+
62  for (int j = 1; j <= k; ++j)
+
63  result += lgamma(x + (1.0 - j) / 2.0);
+
64  return result;
+
65  }
+
66 
+
67  }
+
68 }
+
69 #endif
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
const double LOG_PI_OVER_FOUR
Log pi divided by 4 .
Definition: constants.hpp:79
+ +
fvar< typename stan::return_type< T, int >::type > lmgamma(int x1, const fvar< T > &x2)
Definition: lmgamma.hpp:16
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2log1m_8hpp.html b/doc/api/html/prim_2scal_2fun_2log1m_8hpp.html new file mode 100644 index 00000000000..cb265cfef9e --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1m_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1m.hpp File Reference + + + + + + + + + + +
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#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/fun/log1p.hpp>
+
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::log1m (T x)
 Return the natural logarithm of one minus the specified value. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log1m_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log1m_8hpp_source.html new file mode 100644 index 00000000000..24f2889b649 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1m_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1m.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG1M_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG1M_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
38  template <typename T>
+
39  inline typename boost::math::tools::promote_args<T>::type
+
40  log1m(T x) {
+
41  return log1p(-x);
+
42  }
+
43 
+
44  }
+
45 }
+
46 
+
47 #endif
+ +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
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diff --git a/doc/api/html/prim_2scal_2fun_2log1m__exp_8hpp.html b/doc/api/html/prim_2scal_2fun_2log1m__exp_8hpp.html new file mode 100644 index 00000000000..9fc3478b511 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1m__exp_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1m_exp.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/fun/log1m.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <boost/throw_exception.hpp>
+#include <cmath>
+#include <limits>
+#include <stdexcept>
+
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::log1m_exp (const T a)
 Calculates the log of 1 minus the exponential of the specified value without overflow log1m_exp(x) = log(1-exp(x)). More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log1m__exp_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log1m__exp_8hpp_source.html new file mode 100644 index 00000000000..95a033ed2c4 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1m__exp_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1m_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG1M_EXP_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG1M_EXP_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+
6 #include <boost/throw_exception.hpp>
+
7 #include <cmath>
+
8 #include <limits>
+
9 #include <stdexcept>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
39  template <typename T>
+
40  inline typename boost::math::tools::promote_args<T>::type
+
41  log1m_exp(const T a) {
+
42  using std::log;
+
43  using std::exp;
+ +
45 
+
46  if (a >= 0)
+
47  return std::numeric_limits<double>::quiet_NaN();
+
48  else if (a > -0.693147)
+
49  return log(-expm1(a)); // 0.693147 ~= log(2)
+
50  else
+
51  return log1m(exp(a));
+
52  }
+
53 
+
54  }
+
55 }
+
56 
+
57 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > expm1(const fvar< T > &x)
Definition: expm1.hpp:12
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > log1m_exp(const fvar< T > &x)
Definition: log1m_exp.hpp:16
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
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diff --git a/doc/api/html/prim_2scal_2fun_2log1m__inv__logit_8hpp.html b/doc/api/html/prim_2scal_2fun_2log1m__inv__logit_8hpp.html new file mode 100644 index 00000000000..ea4032b6851 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1m__inv__logit_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1m_inv_logit.hpp File Reference + + + + + + + + + + +
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::log1m_inv_logit (const T u)
 Returns the natural logarithm of 1 minus the inverse logit of the specified argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log1m__inv__logit_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log1m__inv__logit_8hpp_source.html new file mode 100644 index 00000000000..aef6bcd1a9a --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1m__inv__logit_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1m_inv_logit.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG1M_INV_LOGIT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG1M_INV_LOGIT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
34  template <typename T>
+
35  inline typename boost::math::tools::promote_args<T>::type
+
36  log1m_inv_logit(const T u) {
+
37  using std::exp;
+
38  if (u > 0.0)
+
39  return -u - log1p(exp(-u)); // prevent underflow
+
40  return -log1p(exp(u));
+
41  }
+
42 
+
43  }
+
44 }
+
45 
+
46 #endif
+
fvar< T > log1m_inv_logit(const fvar< T > &x)
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
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diff --git a/doc/api/html/prim_2scal_2fun_2log1p_8hpp.html b/doc/api/html/prim_2scal_2fun_2log1p_8hpp.html new file mode 100644 index 00000000000..4ae6bf1b8c8 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1p_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1p.hpp File Reference + + + + + + + + + + +
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::log1p (const T x)
 Return the natural logarithm of one plus the specified value. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log1p_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log1p_8hpp_source.html new file mode 100644 index 00000000000..a4b3da4eedc --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1p_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1p.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG1P_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG1P_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 #include <limits>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
37  template <typename T>
+
38  inline typename boost::math::tools::promote_args<T>::type
+
39  log1p(const T x) {
+
40  using std::log;
+
41  if (!(x >= -1.0))
+
42  return std::numeric_limits<double>::quiet_NaN();
+
43 
+
44  if (x > 1e-9 || x < -1e-9)
+
45  return log(1.0 + x); // direct, if distant from 1
+
46  else if (x > 1e-16 || x < -1e-16)
+
47  return x - 0.5 * x * x; // 2nd order Taylor, if close to 1
+
48  else
+
49  return x; // 1st order Taylor, if very close to 1
+
50  }
+
51 
+
52  }
+
53 }
+
54 
+
55 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
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diff --git a/doc/api/html/prim_2scal_2fun_2log1p__exp_8hpp.html b/doc/api/html/prim_2scal_2fun_2log1p__exp_8hpp.html new file mode 100644 index 00000000000..baf3eaa91cc --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1p__exp_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1p_exp.hpp File Reference + + + + + + + + + + +
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#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/fun/log1p.hpp>
+
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::log1p_exp (const T a)
 Calculates the log of 1 plus the exponential of the specified value without overflow. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log1p__exp_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log1p__exp_8hpp_source.html new file mode 100644 index 00000000000..70b7902ba65 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log1p__exp_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log1p_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG1P_EXP_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG1P_EXP_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
42  template <typename T>
+
43  inline typename boost::math::tools::promote_args<T>::type
+
44  log1p_exp(const T a) {
+
45  using std::exp;
+
46  // like log_sum_exp below with b=0.0; prevents underflow
+
47  if (a > 0.0)
+
48  return a + log1p(exp(-a));
+
49  return log1p(exp(a));
+
50  }
+
51 
+
52  }
+
53 }
+
54 
+
55 #endif
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > log1p_exp(const fvar< T > &x)
Definition: log1p_exp.hpp:13
+
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
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diff --git a/doc/api/html/prim_2scal_2fun_2log2_8hpp.html b/doc/api/html/prim_2scal_2fun_2log2_8hpp.html new file mode 100644 index 00000000000..76fbda7c719 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log2_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log2.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/fun/constants.hpp>
+#include <boost/math/tools/promotion.hpp>
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::log2 (const T a)
 Returns the base 2 logarithm of the argument (C99). More...
 
double stan::math::log2 ()
 Return natural logarithm of two. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log2_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log2_8hpp_source.html new file mode 100644 index 00000000000..666c5f62e9d --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log2_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log2.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG2_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG2_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+
6 #include <stdexcept>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
23  template <typename T>
+
24  inline typename boost::math::tools::promote_args<T>::type
+
25  log2(const T a) {
+
26  using std::log;
+
27  return log(a) / LOG_2;
+
28  }
+
29 
+
35  inline double log2() {
+
36  return LOG_2;
+
37  }
+
38 
+
39  }
+
40 }
+
41 
+
42 #endif
+
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:33
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
fvar< T > log2(const fvar< T > &x)
Definition: log2.hpp:17
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diff --git a/doc/api/html/prim_2scal_2fun_2log__diff__exp_8hpp.html b/doc/api/html/prim_2scal_2fun_2log__diff__exp_8hpp.html new file mode 100644 index 00000000000..276ea82e7b6 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__diff__exp_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_diff_exp.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/fun/log1m_exp.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <boost/throw_exception.hpp>
+#include <limits>
+#include <stdexcept>
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template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::log_diff_exp (const T1 x, const T2 y)
 The natural logarithm of the difference of the natural exponentiation of x1 and the natural exponentiation of x2. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log__diff__exp_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log__diff__exp_8hpp_source.html new file mode 100644 index 00000000000..a5140a1c083 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__diff__exp_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_diff_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG_DIFF_EXP_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG_DIFF_EXP_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+
6 #include <boost/throw_exception.hpp>
+
7 #include <limits>
+
8 #include <stdexcept>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
48  template <typename T1, typename T2>
+
49  inline typename boost::math::tools::promote_args<T1, T2>::type
+
50  log_diff_exp(const T1 x, const T2 y) {
+
51  if (x <= y)
+
52  return std::numeric_limits<double>::quiet_NaN();
+
53  return x + log1m_exp(y - x);
+
54  }
+
55 
+
56  }
+
57 }
+
58 
+
59 #endif
+ +
fvar< T > log_diff_exp(const fvar< T > &x1, const fvar< T > &x2)
+
fvar< T > log1m_exp(const fvar< T > &x)
Definition: log1m_exp.hpp:16
+ +
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diff --git a/doc/api/html/prim_2scal_2fun_2log__falling__factorial_8hpp.html b/doc/api/html/prim_2scal_2fun_2log__falling__factorial_8hpp.html new file mode 100644 index 00000000000..df161affed9 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__falling__factorial_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_falling_factorial.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::log_falling_factorial (const T1 x, const T2 n)
 

+\[ \mbox{log\_falling\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \ln (x)_n & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2log__falling__factorial_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log__falling__factorial_8hpp_source.html new file mode 100644 index 00000000000..606a5ed5d78 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__falling__factorial_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_falling_factorial.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG_FALLING_FACTORIAL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG_FALLING_FACTORIAL_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
39  template<typename T1, typename T2>
+
40  inline typename boost::math::tools::promote_args<T1, T2>::type
+
41  log_falling_factorial(const T1 x, const T2 n) {
+
42  return lgamma(x + 1) - lgamma(x - n + 1);
+
43  }
+
44 
+
45  }
+
46 }
+
47 
+
48 #endif
+ +
fvar< T > log_falling_factorial(const fvar< T > &x, const fvar< T > &n)
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
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diff --git a/doc/api/html/prim_2scal_2fun_2log__inv__logit_8hpp.html b/doc/api/html/prim_2scal_2fun_2log__inv__logit_8hpp.html new file mode 100644 index 00000000000..754119fbe6d --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__inv__logit_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_inv_logit.hpp File Reference + + + + + + + + + + +
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::log_inv_logit (const T &u)
 Returns the natural logarithm of the inverse logit of the specified argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log__inv__logit_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log__inv__logit_8hpp_source.html new file mode 100644 index 00000000000..c89a6e4aa98 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__inv__logit_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_inv_logit.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG_INV_LOGIT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG_INV_LOGIT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
34  template <typename T>
+
35  inline typename boost::math::tools::promote_args<T>::type
+
36  log_inv_logit(const T& u) {
+
37  using std::exp;
+
38  if (u < 0.0)
+
39  return u - log1p(exp(u)); // prevent underflow
+
40  return -log1p(exp(-u));
+
41  }
+
42 
+
43  }
+
44 }
+
45 
+
46 #endif
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+
fvar< T > log_inv_logit(const fvar< T > &x)
+
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diff --git a/doc/api/html/prim_2scal_2fun_2log__mix_8hpp.html b/doc/api/html/prim_2scal_2fun_2log__mix_8hpp.html new file mode 100644 index 00000000000..ce093a7d19a --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__mix_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_mix.hpp File Reference + + + + + + + + + + +
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double stan::math::log_mix (double theta, double lambda1, double lambda2)
 Return the log mixture density with specified mixing proportion and log densities. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log__mix_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log__mix_8hpp_source.html new file mode 100644 index 00000000000..1e46313f147 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__mix_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_mix.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG_MIX_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG_MIX_HPP
+
3 
+ + + + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
46  double log_mix(double theta,
+
47  double lambda1,
+
48  double lambda2) {
+
49  using std::log;
+
50  stan::math::check_not_nan("log_mix", "lambda1", lambda1);
+
51  stan::math::check_not_nan("log_mix", "lambda2", lambda2);
+
52  stan::math::check_bounded("log_mix", "theta", theta, 0, 1);
+
53  return log_sum_exp(log(theta) + lambda1,
+
54  log1m(theta) + lambda2);
+
55  }
+
56 
+
57  }
+
58 
+
59 }
+
60 
+
61 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+ + + +
fvar< T > log_mix(const fvar< T > &theta, const fvar< T > &lambda1, const fvar< T > &lambda2)
Return the log mixture density with specified mixing proportion and log densities and its derivative ...
Definition: log_mix.hpp:117
+
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
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diff --git a/doc/api/html/prim_2scal_2fun_2log__rising__factorial_8hpp.html b/doc/api/html/prim_2scal_2fun_2log__rising__factorial_8hpp.html new file mode 100644 index 00000000000..f11321d2dea --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__rising__factorial_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_rising_factorial.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/gamma.hpp>
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template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::log_rising_factorial (const T1 x, const T2 n)
 

+\[ \mbox{log\_rising\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ \ln x^{(n)} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2log__rising__factorial_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log__rising__factorial_8hpp_source.html new file mode 100644 index 00000000000..e8077aa7745 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__rising__factorial_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_rising_factorial.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG_RISING_FACTORIAL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG_RISING_FACTORIAL_HPP
+
3 
+
4 #include <boost/math/special_functions/gamma.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
39  template<typename T1, typename T2>
+
40  inline typename boost::math::tools::promote_args<T1, T2>::type
+
41  log_rising_factorial(const T1 x, const T2 n) {
+
42  using boost::math::lgamma;
+
43  return lgamma(x + n) - lgamma(x);
+
44  }
+
45 
+
46  }
+
47 }
+
48 
+
49 #endif
+
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
fvar< T > log_rising_factorial(const fvar< T > &x, const fvar< T > &n)
+
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diff --git a/doc/api/html/prim_2scal_2fun_2log__sum__exp_8hpp.html b/doc/api/html/prim_2scal_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..f480907d4dd --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/fun/log1p_exp.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <limits>
+
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template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::log_sum_exp (const T2 &a, const T1 &b)
 Calculates the log sum of exponetials without overflow. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..de0f179f138 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOG_SUM_EXP_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+
6 #include <limits>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
46  template <typename T1, typename T2>
+
47  inline typename boost::math::tools::promote_args<T1, T2>::type
+
48  log_sum_exp(const T2& a, const T1& b) {
+
49  using std::exp;
+
50  if (a > b)
+
51  return a + log1p_exp(b - a);
+
52  return b + log1p_exp(a - b);
+
53  }
+
54 
+
55  }
+
56 }
+
57 
+
58 #endif
+ +
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
fvar< T > log1p_exp(const fvar< T > &x)
Definition: log1p_exp.hpp:13
+
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diff --git a/doc/api/html/prim_2scal_2fun_2logit_8hpp.html b/doc/api/html/prim_2scal_2fun_2logit_8hpp.html new file mode 100644 index 00000000000..9796e3b5526 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2logit_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logit.hpp File Reference + + + + + + + + + + +
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template<typename T >
boost::math::tools::promote_args< T >::type stan::math::logit (const T a)
 Returns the logit function applied to the argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2logit_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2logit_8hpp_source.html new file mode 100644 index 00000000000..4bd05a14707 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2logit_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/logit.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_LOGIT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_LOGIT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
42  template <typename T>
+
43  inline typename boost::math::tools::promote_args<T>::type
+
44  logit(const T a) {
+
45  using std::log;
+
46  return log(a / (1.0 - a));
+
47  }
+
48 
+
49  }
+
50 }
+
51 
+
52 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > logit(const fvar< T > &x)
Definition: logit.hpp:17
+
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diff --git a/doc/api/html/prim_2scal_2fun_2modified__bessel__first__kind_8hpp.html b/doc/api/html/prim_2scal_2fun_2modified__bessel__first__kind_8hpp.html new file mode 100644 index 00000000000..232d9b6bee1 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2modified__bessel__first__kind_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/modified_bessel_first_kind.hpp File Reference + + + + + + + + + + +
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#include <boost/math/special_functions/bessel.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+
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template<typename T2 >
T2 stan::math::modified_bessel_first_kind (const int v, const T2 z)
 

+\[ \mbox{modified\_bessel\_first\_kind}(v, z) = \begin{cases} I_v(z) & \mbox{if } -\infty\leq z \leq \infty \\[6pt] \textrm{error} & \mbox{if } z = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html new file mode 100644 index 00000000000..3b5896ece17 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/modified_bessel_first_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_MODIFIED_BESSEL_FIRST_KIND_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_MODIFIED_BESSEL_FIRST_KIND_HPP
+
3 
+
4 #include <boost/math/special_functions/bessel.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
37  template<typename T2>
+
38  inline T2
+
39  modified_bessel_first_kind(const int v, const T2 z) {
+ +
41  check_not_nan("modified_bessel_first_kind", "z", z);
+
42 
+
43  return boost::math::cyl_bessel_i(v, z);
+
44  }
+
45 
+
46  }
+
47 }
+
48 
+
49 #endif
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
fvar< T > modified_bessel_first_kind(int v, const fvar< T > &z)
+
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2modified__bessel__second__kind_8hpp.html b/doc/api/html/prim_2scal_2fun_2modified__bessel__second__kind_8hpp.html new file mode 100644 index 00000000000..395664886fc --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2modified__bessel__second__kind_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/modified_bessel_second_kind.hpp File Reference + + + + + + + + + + +
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template<typename T2 >
T2 stan::math::modified_bessel_second_kind (const int v, const T2 z)
 

+\[ \mbox{modified\_bessel\_second\_kind}(v, z) = \begin{cases} \textrm{error} & \mbox{if } z \leq 0 \\ K_v(z) & \mbox{if } z > 0 \\[6pt] \textrm{NaN} & \mbox{if } z = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html new file mode 100644 index 00000000000..e7f51e3d6e6 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/modified_bessel_second_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_MODIFIED_BESSEL_SECOND_KIND_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_MODIFIED_BESSEL_SECOND_KIND_HPP
+
3 
+
4 #include <boost/math/special_functions/bessel.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
40  template<typename T2>
+
41  inline T2
+
42  modified_bessel_second_kind(const int v, const T2 z) {
+
43  return boost::math::cyl_bessel_k(v, z);
+
44  }
+
45 
+
46  }
+
47 }
+
48 
+
49 #endif
+
fvar< T > modified_bessel_second_kind(int v, const fvar< T > &z)
+ +
+
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diff --git a/doc/api/html/prim_2scal_2fun_2multiply__log_8hpp.html b/doc/api/html/prim_2scal_2fun_2multiply__log_8hpp.html new file mode 100644 index 00000000000..d4bfc529ecb --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2multiply__log_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/multiply_log.hpp File Reference + + + + + + + + + + +
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template<typename T_a , typename T_b >
boost::math::tools::promote_args< T_a, T_b >::type stan::math::multiply_log (const T_a a, const T_b b)
 Calculated the value of the first argument times log of the second argument while behaving properly with 0 inputs. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2multiply__log_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2multiply__log_8hpp_source.html new file mode 100644 index 00000000000..75a24da9125 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2multiply__log_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/multiply_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_MULTIPLY_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_MULTIPLY_LOG_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
49  template <typename T_a, typename T_b>
+
50  inline typename boost::math::tools::promote_args<T_a, T_b>::type
+
51  multiply_log(const T_a a, const T_b b) {
+
52  using std::log;
+
53  if (b == 0.0 && a == 0.0)
+
54  return 0.0;
+
55  return a * log(b);
+
56  }
+
57 
+
58  }
+
59 }
+
60 
+
61 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
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diff --git a/doc/api/html/prim_2scal_2fun_2owens__t_8hpp.html b/doc/api/html/prim_2scal_2fun_2owens__t_8hpp.html new file mode 100644 index 00000000000..d7cf2b5f08f --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2owens__t_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/owens_t.hpp File Reference + + + + + + + + + + +
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double stan::math::owens_t (const double h, const double a)
 The Owen's T function of h and a. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2owens__t_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2owens__t_8hpp_source.html new file mode 100644 index 00000000000..d8319dfb40b --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2owens__t_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/owens_t.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_OWENS_T_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_OWENS_T_HPP
+
3 
+
4 #include <boost/math/special_functions/owens_t.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9 
+
61  inline
+
62  double owens_t(const double h, const double a) {
+
63  return boost::math::owens_t(h, a);
+
64  }
+
65  }
+
66 }
+
67 
+
68 #endif
+ +
fvar< T > owens_t(const fvar< T > &x1, const fvar< T > &x2)
Definition: owens_t.hpp:14
+
var owens_t(double h, const var &a)
The Owen's T function of h and a.
Definition: owens_t.hpp:99
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diff --git a/doc/api/html/prim_2scal_2fun_2primitive__value_8hpp.html b/doc/api/html/prim_2scal_2fun_2primitive__value_8hpp.html new file mode 100644 index 00000000000..476f8654996 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2primitive__value_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/primitive_value.hpp File Reference + + + + + + + + + + +
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#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits/is_arithmetic.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+
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template<typename T >
boost::enable_if< boost::is_arithmetic< T >, T >::type stan::math::primitive_value (T x)
 Return the value of the specified arithmetic argument unmodified with its own declared type. More...
 
template<typename T >
boost::disable_if< boost::is_arithmetic< T >, double >::type stan::math::primitive_value (const T &x)
 Return the primitive value of the specified argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2primitive__value_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2primitive__value_8hpp_source.html new file mode 100644 index 00000000000..ca663dd4e16 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2primitive__value_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/primitive_value.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_PRIMITIVE_VALUE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_PRIMITIVE_VALUE_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits/is_arithmetic.hpp>
+ +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
27  template <typename T>
+
28  inline
+
29  typename boost::enable_if<boost::is_arithmetic<T>, T>::type
+ +
31  return x;
+
32  }
+
33 
+
44  template <typename T>
+
45  inline
+
46  typename boost::disable_if<boost::is_arithmetic<T>, double>::type
+
47  primitive_value(const T& x) {
+ +
49  return value_of(x);
+
50  }
+
51 
+
52  }
+
53 
+
54 }
+
55 
+
56 #endif
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
double primitive_value(const fvar< T > &v)
Return the primitive value of the specified forward-mode autodiff variable.
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diff --git a/doc/api/html/prim_2scal_2fun_2rising__factorial_8hpp.html b/doc/api/html/prim_2scal_2fun_2rising__factorial_8hpp.html new file mode 100644 index 00000000000..df219d21e54 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2rising__factorial_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/rising_factorial.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 >
boost::math::tools::promote_args< T1, T2 >::type stan::math::rising_factorial (const T1 x, const T2 n)
 

+\[ \mbox{rising\_factorial}(x, n) = \begin{cases} \textrm{error} & \mbox{if } x \leq 0\\ x^{(n)} & \mbox{if } x > 0 \textrm{ and } -\infty \leq n \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN or } n = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/prim_2scal_2fun_2rising__factorial_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2rising__factorial_8hpp_source.html new file mode 100644 index 00000000000..b23bc485745 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2rising__factorial_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/rising_factorial.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_RISING_FACTORIAL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_RISING_FACTORIAL_HPP
+
3 
+ +
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
52  template<typename T1, typename T2>
+
53  inline typename boost::math::tools::promote_args<T1, T2>::type
+
54  rising_factorial(const T1 x, const T2 n) {
+
55  using std::exp;
+ +
57  }
+
58 
+
59  }
+
60 }
+
61 
+
62 #endif
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
fvar< T > log_rising_factorial(const fvar< T > &x, const fvar< T > &n)
+
fvar< T > rising_factorial(const fvar< T > &x, const fvar< T > &n)
+
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diff --git a/doc/api/html/prim_2scal_2fun_2square_8hpp.html b/doc/api/html/prim_2scal_2fun_2square_8hpp.html new file mode 100644 index 00000000000..0cdeb9b7d17 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2square_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/square.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::square (const T x)
 Return the square of the specified argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2square_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2square_8hpp_source.html new file mode 100644 index 00000000000..2aed87a0006 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2square_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/square.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_SQUARE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_SQUARE_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
21  template <typename T>
+
22  inline T square(const T x) {
+
23  return x * x;
+
24  }
+
25 
+
26  }
+
27 }
+
28 
+
29 #endif
+ +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
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diff --git a/doc/api/html/prim_2scal_2fun_2step_8hpp.html b/doc/api/html/prim_2scal_2fun_2step_8hpp.html new file mode 100644 index 00000000000..a0fcd6462a7 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2step_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/step.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/prim_2scal_2fun_2step_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2step_8hpp_source.html new file mode 100644 index 00000000000..6ee2b849171 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2step_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/step.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_STEP_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_STEP_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
28  template <typename T>
+
29  inline int step(const T y) {
+
30  return y < 0.0 ? 0 : 1;
+
31  }
+
32 
+
33  }
+
34 }
+
35 
+
36 #endif
+ +
int step(const T y)
The step, or Heaviside, function.
Definition: step.hpp:29
+
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diff --git a/doc/api/html/prim_2scal_2fun_2value__of_8hpp.html b/doc/api/html/prim_2scal_2fun_2value__of_8hpp.html new file mode 100644 index 00000000000..fa62f2d44ac --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2value__of_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/value_of.hpp File Reference + + + + + + + + + + +
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template<typename T >
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 Return the value of the specified scalar argument converted to a double value. More...
 
template<>
double stan::math::value_of< double > (const double x)
 Return the specified argument. More...
 
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diff --git a/doc/api/html/prim_2scal_2fun_2value__of_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2value__of_8hpp_source.html new file mode 100644 index 00000000000..34f4f0cb7e1 --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2value__of_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/value_of.hpp Source File + + + + + + + + + + +
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+
+
value_of.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_VALUE_OF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_VALUE_OF_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  namespace math {
+
7 
+
23  template <typename T>
+
24  inline double value_of(const T x) {
+
25  return static_cast<double>(x);
+
26  }
+
27 
+
39  template <>
+
40  inline double value_of<double>(const double x) {
+
41  return x;
+
42  }
+
43 
+
44  }
+
45 }
+
46 
+
47 #endif
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
double value_of< double >(const double x)
Return the specified argument.
Definition: value_of.hpp:40
+
+
+
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diff --git a/doc/api/html/prim_2scal_2fun_2value__of__rec_8hpp.html b/doc/api/html/prim_2scal_2fun_2value__of__rec_8hpp.html new file mode 100644 index 00000000000..36b4ae6834e --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2value__of__rec_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/value_of_rec.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
+ + + + + + + + + +

+Functions

template<typename T >
double stan::math::value_of_rec (const T x)
 Return the value of the specified scalar argument converted to a double value. More...
 
template<>
double stan::math::value_of_rec< double > (const double x)
 Return the specified argument. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2scal_2fun_2value__of__rec_8hpp_source.html b/doc/api/html/prim_2scal_2fun_2value__of__rec_8hpp_source.html new file mode 100644 index 00000000000..bd5b9ac6d3c --- /dev/null +++ b/doc/api/html/prim_2scal_2fun_2value__of__rec_8hpp_source.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/value_of_rec.hpp Source File + + + + + + + + + + +
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value_of_rec.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_VALUE_OF_REC_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_VALUE_OF_REC_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  namespace math {
+
7 
+
23  template <typename T>
+
24  inline double value_of_rec(const T x) {
+
25  return static_cast<double>(x);
+
26  }
+
27 
+
39  template <>
+
40  inline double value_of_rec<double>(const double x) {
+
41  return x;
+
42  }
+
43 
+
44  }
+
45 }
+
46 
+
47 #endif
+ +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+
double value_of_rec< double >(const double x)
Return the specified argument.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2scal_2meta_2_operands_and_partials_8hpp.html b/doc/api/html/prim_2scal_2meta_2_operands_and_partials_8hpp.html new file mode 100644 index 00000000000..5bc1f00f047 --- /dev/null +++ b/doc/api/html/prim_2scal_2meta_2_operands_and_partials_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/OperandsAndPartials.hpp File Reference + + + + + + + + + + +
+
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OperandsAndPartials.hpp File Reference
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+ + + + + +

+Classes

struct  stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >
 This class builds partial derivatives with respect to a set of operands. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
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diff --git a/doc/api/html/prim_2scal_2meta_2_operands_and_partials_8hpp_source.html b/doc/api/html/prim_2scal_2meta_2_operands_and_partials_8hpp_source.html new file mode 100644 index 00000000000..723dcb91243 --- /dev/null +++ b/doc/api/html/prim_2scal_2meta_2_operands_and_partials_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/OperandsAndPartials.hpp Source File + + + + + + + + + + +
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OperandsAndPartials.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_OPERANDSANDPARTIALS_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_OPERANDSANDPARTIALS_HPP
+
3 
+ + +
6 
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
34  template<typename T1 = double, typename T2 = double, typename T3 = double,
+
35  typename T4 = double, typename T5 = double, typename T6 = double,
+
36  typename T_return_type
+ + + + + + + + +
45 
+
56  OperandsAndPartials(const T1& x1 = 0, const T2& x2 = 0,
+
57  const T3& x3 = 0, const T4& x4 = 0,
+
58  const T5& x5 = 0, const T6& x6 = 0) { }
+
59 
+
67  T_return_type
+
68  value(double value) {
+
69  return value;
+
70  }
+
71  };
+
72 
+
73  }
+
74 }
+
75 #endif
+
VectorView< T_return_type, false, true > d_x2
+
OperandsAndPartials(const T1 &x1=0, const T2 &x2=0, const T3 &x3=0, const T4 &x4=0, const T5 &x5=0, const T6 &x6=0)
Constructor.
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
VectorView< T_return_type, false, true > d_x6
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+ +
VectorView< T_return_type, false, true > d_x5
+
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2scal_2meta_2is__fvar_8hpp.html b/doc/api/html/prim_2scal_2meta_2is__fvar_8hpp.html new file mode 100644 index 00000000000..79b8797e288 --- /dev/null +++ b/doc/api/html/prim_2scal_2meta_2is__fvar_8hpp.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_fvar.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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+
is_fvar.hpp File Reference
+
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+Classes

struct  stan::is_fvar< T >
 
+ + + +

+Namespaces

 stan
 
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diff --git a/doc/api/html/prim_2scal_2meta_2is__fvar_8hpp_source.html b/doc/api/html/prim_2scal_2meta_2is__fvar_8hpp_source.html new file mode 100644 index 00000000000..3202dc5f90d --- /dev/null +++ b/doc/api/html/prim_2scal_2meta_2is__fvar_8hpp_source.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_fvar.hpp Source File + + + + + + + + + + +
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+
is_fvar.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_IS_FVAR_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_IS_FVAR_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  template <typename T>
+
7  struct is_fvar {
+
8  enum { value = false };
+
9  };
+
10 
+
11 }
+
12 #endif
+
13 
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2scal_2meta_2is__var_8hpp.html b/doc/api/html/prim_2scal_2meta_2is__var_8hpp.html new file mode 100644 index 00000000000..aeafd791b65 --- /dev/null +++ b/doc/api/html/prim_2scal_2meta_2is__var_8hpp.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_var.hpp File Reference + + + + + + + + + + +
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is_var.hpp File Reference
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+ + + + +

+Classes

struct  stan::is_var< T >
 
+ + + +

+Namespaces

 stan
 
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diff --git a/doc/api/html/prim_2scal_2meta_2is__var_8hpp_source.html b/doc/api/html/prim_2scal_2meta_2is__var_8hpp_source.html new file mode 100644 index 00000000000..a57c6cdcae3 --- /dev/null +++ b/doc/api/html/prim_2scal_2meta_2is__var_8hpp_source.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_var.hpp Source File + + + + + + + + + + +
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is_var.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_META_IS_VAR_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_IS_VAR_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  template <typename T>
+
7  struct is_var {
+
8  enum { value = false };
+
9  };
+
10 
+
11 }
+
12 #endif
+
13 
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2scal_2meta_2partials__type_8hpp.html b/doc/api/html/prim_2scal_2meta_2partials__type_8hpp.html new file mode 100644 index 00000000000..39721995f37 --- /dev/null +++ b/doc/api/html/prim_2scal_2meta_2partials__type_8hpp.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/partials_type.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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partials_type.hpp File Reference
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+Classes

struct  stan::partials_type< T >
 
+ + + +

+Namespaces

 stan
 
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diff --git a/doc/api/html/prim_2scal_2meta_2partials__type_8hpp_source.html b/doc/api/html/prim_2scal_2meta_2partials__type_8hpp_source.html new file mode 100644 index 00000000000..7492480cda3 --- /dev/null +++ b/doc/api/html/prim_2scal_2meta_2partials__type_8hpp_source.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/partials_type.hpp Source File + + + + + + + + + + +
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partials_type.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_PARTIALS_TYPE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_PARTIALS_TYPE_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  template <typename T>
+
7  struct partials_type {
+
8  typedef T type;
+
9  };
+
10 
+
11 }
+
12 #endif
+
13 
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prim_2scal_8hpp.html b/doc/api/html/prim_2scal_8hpp.html new file mode 100644 index 00000000000..2b829b4896c --- /dev/null +++ b/doc/api/html/prim_2scal_8hpp.html @@ -0,0 +1,406 @@ + + + + + + +Stan Math Library: stan/math/prim/scal.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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+
+
scal.hpp File Reference
+
+
+
#include <stan/math/version.hpp>
+#include <stan/math/prim/scal/meta/child_type.hpp>
+#include <stan/math/prim/scal/meta/container_view.hpp>
+#include <stan/math/prim/scal/meta/contains_fvar.hpp>
+#include <stan/math/prim/scal/meta/contains_nonconstant_struct.hpp>
+#include <stan/math/prim/scal/meta/contains_vector.hpp>
+#include <stan/math/prim/scal/meta/error_index.hpp>
+#include <stan/math/prim/scal/meta/get.hpp>
+#include <stan/math/prim/scal/meta/include_summand.hpp>
+#include <stan/math/prim/scal/meta/index_type.hpp>
+#include <stan/math/prim/scal/meta/is_constant.hpp>
+#include <stan/math/prim/scal/meta/is_constant_struct.hpp>
+#include <stan/math/prim/scal/meta/is_fvar.hpp>
+#include <stan/math/prim/scal/meta/is_var.hpp>
+#include <stan/math/prim/scal/meta/is_var_or_arithmetic.hpp>
+#include <stan/math/prim/scal/meta/is_vector.hpp>
+#include <stan/math/prim/scal/meta/is_vector_like.hpp>
+#include <stan/math/prim/scal/meta/length.hpp>
+#include <stan/math/prim/scal/meta/length_mvt.hpp>
+#include <stan/math/prim/scal/meta/likely.hpp>
+#include <stan/math/prim/scal/meta/max_size.hpp>
+#include <stan/math/prim/scal/meta/max_size_mvt.hpp>
+#include <stan/math/prim/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal/meta/partials_return_type.hpp>
+#include <stan/math/prim/scal/meta/partials_type.hpp>
+#include <stan/math/prim/scal/meta/return_type.hpp>
+#include <stan/math/prim/scal/meta/scalar_type.hpp>
+#include <stan/math/prim/scal/meta/scalar_type_pre.hpp>
+#include <stan/math/prim/scal/meta/size_of.hpp>
+#include <stan/math/prim/scal/meta/value_type.hpp>
+#include <stan/math/prim/scal/meta/VectorBuilder.hpp>
+#include <stan/math/prim/scal/meta/VectorView.hpp>
+#include <stan/math/prim/scal/err/check_bounded.hpp>
+#include <stan/math/prim/scal/err/check_consistent_size.hpp>
+#include <stan/math/prim/scal/err/check_consistent_sizes.hpp>
+#include <stan/math/prim/scal/err/check_equal.hpp>
+#include <stan/math/prim/scal/err/check_finite.hpp>
+#include <stan/math/prim/scal/err/check_greater.hpp>
+#include <stan/math/prim/scal/err/check_greater_or_equal.hpp>
+#include <stan/math/prim/scal/err/check_less.hpp>
+#include <stan/math/prim/scal/err/check_less_or_equal.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/scal/err/check_not_nan.hpp>
+#include <stan/math/prim/scal/err/check_positive.hpp>
+#include <stan/math/prim/scal/err/check_positive_finite.hpp>
+#include <stan/math/prim/scal/err/check_positive_size.hpp>
+#include <stan/math/prim/scal/err/check_size_match.hpp>
+#include <stan/math/prim/scal/err/domain_error.hpp>
+#include <stan/math/prim/scal/err/domain_error_vec.hpp>
+#include <stan/math/prim/scal/err/invalid_argument.hpp>
+#include <stan/math/prim/scal/err/invalid_argument_vec.hpp>
+#include <stan/math/prim/scal/err/out_of_range.hpp>
+#include <stan/math/prim/scal/fun/abs.hpp>
+#include <stan/math/prim/scal/fun/as_bool.hpp>
+#include <stan/math/prim/scal/fun/bessel_first_kind.hpp>
+#include <stan/math/prim/scal/fun/bessel_second_kind.hpp>
+#include <stan/math/prim/scal/fun/binary_log_loss.hpp>
+#include <stan/math/prim/scal/fun/binomial_coefficient_log.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/corr_constrain.hpp>
+#include <stan/math/prim/scal/fun/corr_free.hpp>
+#include <stan/math/prim/scal/fun/digamma.hpp>
+#include <stan/math/prim/scal/fun/divide.hpp>
+#include <stan/math/prim/scal/fun/exp2.hpp>
+#include <stan/math/prim/scal/fun/F32.hpp>
+#include <stan/math/prim/scal/fun/falling_factorial.hpp>
+#include <stan/math/prim/scal/fun/fdim.hpp>
+#include <stan/math/prim/scal/fun/fill.hpp>
+#include <stan/math/prim/scal/fun/gamma_p.hpp>
+#include <stan/math/prim/scal/fun/gamma_q.hpp>
+#include <stan/math/prim/scal/fun/grad_2F1.hpp>
+#include <stan/math/prim/scal/fun/grad_F32.hpp>
+#include <stan/math/prim/scal/fun/grad_inc_beta.hpp>
+#include <stan/math/prim/scal/fun/grad_reg_inc_beta.hpp>
+#include <stan/math/prim/scal/fun/grad_reg_inc_gamma.hpp>
+#include <stan/math/prim/scal/fun/ibeta.hpp>
+#include <stan/math/prim/scal/fun/identity_constrain.hpp>
+#include <stan/math/prim/scal/fun/identity_free.hpp>
+#include <stan/math/prim/scal/fun/if_else.hpp>
+#include <stan/math/prim/scal/fun/inc_beta.hpp>
+#include <stan/math/prim/scal/fun/int_step.hpp>
+#include <stan/math/prim/scal/fun/inv.hpp>
+#include <stan/math/prim/scal/fun/inv_cloglog.hpp>
+#include <stan/math/prim/scal/fun/inv_logit.hpp>
+#include <stan/math/prim/scal/fun/inv_Phi.hpp>
+#include <stan/math/prim/scal/fun/inv_sqrt.hpp>
+#include <stan/math/prim/scal/fun/inv_square.hpp>
+#include <stan/math/prim/scal/fun/inverse_softmax.hpp>
+#include <stan/math/prim/scal/fun/is_inf.hpp>
+#include <stan/math/prim/scal/fun/is_nan.hpp>
+#include <stan/math/prim/scal/fun/is_uninitialized.hpp>
+#include <stan/math/prim/scal/fun/lb_constrain.hpp>
+#include <stan/math/prim/scal/fun/lb_free.hpp>
+#include <stan/math/prim/scal/fun/lbeta.hpp>
+#include <stan/math/prim/scal/fun/lgamma.hpp>
+#include <stan/math/prim/scal/fun/lmgamma.hpp>
+#include <stan/math/prim/scal/fun/log1m.hpp>
+#include <stan/math/prim/scal/fun/log1m_exp.hpp>
+#include <stan/math/prim/scal/fun/log1m_inv_logit.hpp>
+#include <stan/math/prim/scal/fun/log1p.hpp>
+#include <stan/math/prim/scal/fun/log1p_exp.hpp>
+#include <stan/math/prim/scal/fun/log2.hpp>
+#include <stan/math/prim/scal/fun/log_diff_exp.hpp>
+#include <stan/math/prim/scal/fun/log_falling_factorial.hpp>
+#include <stan/math/prim/scal/fun/log_inv_logit.hpp>
+#include <stan/math/prim/scal/fun/log_mix.hpp>
+#include <stan/math/prim/scal/fun/log_rising_factorial.hpp>
+#include <stan/math/prim/scal/fun/log_sum_exp.hpp>
+#include <stan/math/prim/scal/fun/logical_and.hpp>
+#include <stan/math/prim/scal/fun/logical_eq.hpp>
+#include <stan/math/prim/scal/fun/logical_gt.hpp>
+#include <stan/math/prim/scal/fun/logical_gte.hpp>
+#include <stan/math/prim/scal/fun/logical_lt.hpp>
+#include <stan/math/prim/scal/fun/logical_lte.hpp>
+#include <stan/math/prim/scal/fun/logical_negation.hpp>
+#include <stan/math/prim/scal/fun/logical_neq.hpp>
+#include <stan/math/prim/scal/fun/logical_or.hpp>
+#include <stan/math/prim/scal/fun/logit.hpp>
+#include <stan/math/prim/scal/fun/lub_constrain.hpp>
+#include <stan/math/prim/scal/fun/lub_free.hpp>
+#include <stan/math/prim/scal/fun/modified_bessel_first_kind.hpp>
+#include <stan/math/prim/scal/fun/modified_bessel_second_kind.hpp>
+#include <stan/math/prim/scal/fun/modulus.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <stan/math/prim/scal/fun/owens_t.hpp>
+#include <stan/math/prim/scal/fun/Phi.hpp>
+#include <stan/math/prim/scal/fun/Phi_approx.hpp>
+#include <stan/math/prim/scal/fun/positive_constrain.hpp>
+#include <stan/math/prim/scal/fun/positive_free.hpp>
+#include <stan/math/prim/scal/fun/primitive_value.hpp>
+#include <stan/math/prim/scal/fun/prob_constrain.hpp>
+#include <stan/math/prim/scal/fun/prob_free.hpp>
+#include <stan/math/prim/scal/fun/promote_scalar.hpp>
+#include <stan/math/prim/scal/fun/promote_scalar_type.hpp>
+#include <stan/math/prim/scal/fun/rising_factorial.hpp>
+#include <stan/math/prim/scal/fun/sign.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <stan/math/prim/scal/fun/step.hpp>
+#include <stan/math/prim/scal/fun/trigamma.hpp>
+#include <stan/math/prim/scal/fun/ub_constrain.hpp>
+#include <stan/math/prim/scal/fun/ub_free.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <stan/math/prim/scal/fun/value_of_rec.hpp>
+#include <stan/math/prim/scal/prob/bernoulli_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/bernoulli_cdf.hpp>
+#include <stan/math/prim/scal/prob/bernoulli_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/bernoulli_log.hpp>
+#include <stan/math/prim/scal/prob/bernoulli_logit_log.hpp>
+#include <stan/math/prim/scal/prob/bernoulli_rng.hpp>
+#include <stan/math/prim/scal/prob/beta_binomial_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/beta_binomial_cdf.hpp>
+#include <stan/math/prim/scal/prob/beta_binomial_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/beta_binomial_log.hpp>
+#include <stan/math/prim/scal/prob/beta_binomial_rng.hpp>
+#include <stan/math/prim/scal/prob/beta_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/beta_cdf.hpp>
+#include <stan/math/prim/scal/prob/beta_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/beta_log.hpp>
+#include <stan/math/prim/scal/prob/beta_rng.hpp>
+#include <stan/math/prim/scal/prob/binomial_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/binomial_cdf.hpp>
+#include <stan/math/prim/scal/prob/binomial_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/binomial_log.hpp>
+#include <stan/math/prim/scal/prob/binomial_logit_log.hpp>
+#include <stan/math/prim/scal/prob/binomial_rng.hpp>
+#include <stan/math/prim/scal/prob/cauchy_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/cauchy_cdf.hpp>
+#include <stan/math/prim/scal/prob/cauchy_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/cauchy_log.hpp>
+#include <stan/math/prim/scal/prob/cauchy_rng.hpp>
+#include <stan/math/prim/scal/prob/chi_square_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/chi_square_cdf.hpp>
+#include <stan/math/prim/scal/prob/chi_square_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/chi_square_log.hpp>
+#include <stan/math/prim/scal/prob/chi_square_rng.hpp>
+#include <stan/math/prim/scal/prob/double_exponential_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/double_exponential_cdf.hpp>
+#include <stan/math/prim/scal/prob/double_exponential_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/double_exponential_log.hpp>
+#include <stan/math/prim/scal/prob/double_exponential_rng.hpp>
+#include <stan/math/prim/scal/prob/exp_mod_normal_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/exp_mod_normal_cdf.hpp>
+#include <stan/math/prim/scal/prob/exp_mod_normal_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/exp_mod_normal_log.hpp>
+#include <stan/math/prim/scal/prob/exp_mod_normal_rng.hpp>
+#include <stan/math/prim/scal/prob/exponential_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/exponential_cdf.hpp>
+#include <stan/math/prim/scal/prob/exponential_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/exponential_log.hpp>
+#include <stan/math/prim/scal/prob/exponential_rng.hpp>
+#include <stan/math/prim/scal/prob/frechet_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/frechet_cdf.hpp>
+#include <stan/math/prim/scal/prob/frechet_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/frechet_log.hpp>
+#include <stan/math/prim/scal/prob/frechet_rng.hpp>
+#include <stan/math/prim/scal/prob/gamma_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/gamma_cdf.hpp>
+#include <stan/math/prim/scal/prob/gamma_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/gamma_log.hpp>
+#include <stan/math/prim/scal/prob/gamma_rng.hpp>
+#include <stan/math/prim/scal/prob/gumbel_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/gumbel_cdf.hpp>
+#include <stan/math/prim/scal/prob/gumbel_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/gumbel_log.hpp>
+#include <stan/math/prim/scal/prob/gumbel_rng.hpp>
+#include <stan/math/prim/scal/prob/hypergeometric_log.hpp>
+#include <stan/math/prim/scal/prob/hypergeometric_rng.hpp>
+#include <stan/math/prim/scal/prob/inv_chi_square_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/inv_chi_square_cdf.hpp>
+#include <stan/math/prim/scal/prob/inv_chi_square_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/inv_chi_square_log.hpp>
+#include <stan/math/prim/scal/prob/inv_chi_square_rng.hpp>
+#include <stan/math/prim/scal/prob/inv_gamma_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/inv_gamma_cdf.hpp>
+#include <stan/math/prim/scal/prob/inv_gamma_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/inv_gamma_log.hpp>
+#include <stan/math/prim/scal/prob/inv_gamma_rng.hpp>
+#include <stan/math/prim/scal/prob/logistic_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/logistic_cdf.hpp>
+#include <stan/math/prim/scal/prob/logistic_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/logistic_log.hpp>
+#include <stan/math/prim/scal/prob/logistic_rng.hpp>
+#include <stan/math/prim/scal/prob/lognormal_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/lognormal_cdf.hpp>
+#include <stan/math/prim/scal/prob/lognormal_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/lognormal_log.hpp>
+#include <stan/math/prim/scal/prob/lognormal_rng.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_2_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_2_cdf.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_2_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_2_log.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_2_log_log.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_2_log_rng.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_2_rng.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_cdf.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_log.hpp>
+#include <stan/math/prim/scal/prob/neg_binomial_rng.hpp>
+#include <stan/math/prim/scal/prob/normal_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/normal_cdf.hpp>
+#include <stan/math/prim/scal/prob/normal_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/normal_log.hpp>
+#include <stan/math/prim/scal/prob/normal_rng.hpp>
+#include <stan/math/prim/scal/prob/pareto_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/pareto_cdf.hpp>
+#include <stan/math/prim/scal/prob/pareto_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/pareto_log.hpp>
+#include <stan/math/prim/scal/prob/pareto_rng.hpp>
+#include <stan/math/prim/scal/prob/pareto_type_2_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/pareto_type_2_cdf.hpp>
+#include <stan/math/prim/scal/prob/pareto_type_2_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/pareto_type_2_log.hpp>
+#include <stan/math/prim/scal/prob/pareto_type_2_rng.hpp>
+#include <stan/math/prim/scal/prob/poisson_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/poisson_cdf.hpp>
+#include <stan/math/prim/scal/prob/poisson_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/poisson_log.hpp>
+#include <stan/math/prim/scal/prob/poisson_log_log.hpp>
+#include <stan/math/prim/scal/prob/poisson_log_rng.hpp>
+#include <stan/math/prim/scal/prob/poisson_rng.hpp>
+#include <stan/math/prim/scal/prob/rayleigh_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/rayleigh_cdf.hpp>
+#include <stan/math/prim/scal/prob/rayleigh_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/rayleigh_log.hpp>
+#include <stan/math/prim/scal/prob/rayleigh_rng.hpp>
+#include <stan/math/prim/scal/prob/scaled_inv_chi_square_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/scaled_inv_chi_square_cdf.hpp>
+#include <stan/math/prim/scal/prob/scaled_inv_chi_square_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/scaled_inv_chi_square_log.hpp>
+#include <stan/math/prim/scal/prob/scaled_inv_chi_square_rng.hpp>
+#include <stan/math/prim/scal/prob/skew_normal_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/skew_normal_cdf.hpp>
+#include <stan/math/prim/scal/prob/skew_normal_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/skew_normal_log.hpp>
+#include <stan/math/prim/scal/prob/skew_normal_rng.hpp>
+#include <stan/math/prim/scal/prob/student_t_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/student_t_cdf.hpp>
+#include <stan/math/prim/scal/prob/student_t_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/student_t_log.hpp>
+#include <stan/math/prim/scal/prob/student_t_rng.hpp>
+#include <stan/math/prim/scal/prob/uniform_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/uniform_cdf.hpp>
+#include <stan/math/prim/scal/prob/uniform_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/uniform_log.hpp>
+#include <stan/math/prim/scal/prob/uniform_rng.hpp>
+#include <stan/math/prim/scal/prob/von_mises_log.hpp>
+#include <stan/math/prim/scal/prob/von_mises_rng.hpp>
+#include <stan/math/prim/scal/prob/weibull_ccdf_log.hpp>
+#include <stan/math/prim/scal/prob/weibull_cdf.hpp>
+#include <stan/math/prim/scal/prob/weibull_cdf_log.hpp>
+#include <stan/math/prim/scal/prob/weibull_log.hpp>
+#include <stan/math/prim/scal/prob/weibull_rng.hpp>
+#include <stan/math/prim/scal/prob/wiener_log.hpp>
+#include <cmath>
+
+

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diff --git a/doc/api/html/prim_2scal_8hpp_source.html b/doc/api/html/prim_2scal_8hpp_source.html new file mode 100644 index 00000000000..90efdfb11ce --- /dev/null +++ b/doc/api/html/prim_2scal_8hpp_source.html @@ -0,0 +1,708 @@ + + + + + + +Stan Math Library: stan/math/prim/scal.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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scal.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_HPP
+
3 
+
4 #include <stan/math/version.hpp>
+
5 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
37 
+ + + + + + + + + + + + + + + + + + + + +
58 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
150 
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302 
+
303 #include <cmath>
+
304 
+
305 #endif
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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diff --git a/doc/api/html/print__stack_8hpp.html b/doc/api/html/print__stack_8hpp.html new file mode 100644 index 00000000000..5f6e18026bd --- /dev/null +++ b/doc/api/html/print__stack_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/core/print_stack.hpp File Reference + + + + + + + + + + +
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print_stack.hpp File Reference
+
+
+
#include <stan/math/rev/core/chainablestack.hpp>
+#include <stan/math/rev/core/vari.hpp>
+#include <ostream>
+
+

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+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

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void stan::math::print_stack (std::ostream &o)
 Prints the auto-dif variable stack. More...
 
+
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diff --git a/doc/api/html/print__stack_8hpp_source.html b/doc/api/html/print__stack_8hpp_source.html new file mode 100644 index 00000000000..b585e94103d --- /dev/null +++ b/doc/api/html/print__stack_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/core/print_stack.hpp Source File + + + + + + + + + + +
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print_stack.hpp
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1 #ifndef STAN_MATH_REV_CORE_PRINT_STACK_HPP
+
2 #define STAN_MATH_REV_CORE_PRINT_STACK_HPP
+
3 
+ + +
6 #include <ostream>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
20  inline void print_stack(std::ostream& o) {
+
21  o << "STACK, size=" << ChainableStack::var_stack_.size() << std::endl;
+
22  // TODO(carpenter): this shouldn't need to be cast any more
+
23  for (size_t i = 0; i < ChainableStack::var_stack_.size(); ++i)
+
24  o << i
+
25  << " " << ChainableStack::var_stack_[i]
+
26  << " " << (static_cast<vari*>(ChainableStack::var_stack_[i]))->val_
+
27  << " : " << (static_cast<vari*>(ChainableStack::var_stack_[i]))->adj_
+
28  << std::endl;
+
29  }
+
30 
+
31  }
+
32 }
+
33 #endif
+ + +
void print_stack(std::ostream &o)
Prints the auto-dif variable stack.
Definition: print_stack.hpp:20
+ +
static std::vector< ChainableT * > var_stack_
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/prob__constrain_8hpp.html b/doc/api/html/prob__constrain_8hpp.html new file mode 100644 index 00000000000..b88dec7dbb6 --- /dev/null +++ b/doc/api/html/prob__constrain_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/prob_constrain.hpp File Reference + + + + + + + + + + +
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prob_constrain.hpp File Reference
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 stan::math
 Matrices and templated mathematical functions.
 
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+Functions

template<typename T >
stan::math::prob_constrain (const T x)
 Return a probability value constrained to fall between 0 and 1 (inclusive) for the specified free scalar. More...
 
template<typename T >
stan::math::prob_constrain (const T x, T &lp)
 Return a probability value constrained to fall between 0 and 1 (inclusive) for the specified free scalar and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
+
+
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diff --git a/doc/api/html/prob__constrain_8hpp_source.html b/doc/api/html/prob__constrain_8hpp_source.html new file mode 100644 index 00000000000..39737d143ee --- /dev/null +++ b/doc/api/html/prob__constrain_8hpp_source.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/prob_constrain.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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prob_constrain.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_FUN_PROB_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_PROB_CONSTRAIN_HPP
+
3 
+ + +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
25  template <typename T>
+
26  inline
+
27  T prob_constrain(const T x) {
+ +
29  return inv_logit(x);
+
30  }
+
31 
+
53  template <typename T>
+
54  inline
+
55  T prob_constrain(const T x, T& lp) {
+ +
57  using stan::math::log1m;
+
58  using std::log;
+
59  T inv_logit_x = inv_logit(x);
+
60  lp += log(inv_logit_x) + log1m(inv_logit_x);
+
61  return inv_logit_x;
+
62  }
+
63 
+
64 
+
65  }
+
66 
+
67 }
+
68 
+
69 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+ + +
T prob_constrain(const T x)
Return a probability value constrained to fall between 0 and 1 (inclusive) for the specified free sca...
+
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
+
+
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diff --git a/doc/api/html/prob__free_8hpp.html b/doc/api/html/prob__free_8hpp.html new file mode 100644 index 00000000000..72e33cf1142 --- /dev/null +++ b/doc/api/html/prob__free_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/prob_free.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
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template<typename T >
stan::math::prob_free (const T y)
 Return the free scalar that when transformed to a probability produces the specified scalar. More...
 
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diff --git a/doc/api/html/prob__free_8hpp_source.html b/doc/api/html/prob__free_8hpp_source.html new file mode 100644 index 00000000000..090fc6831c4 --- /dev/null +++ b/doc/api/html/prob__free_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/prob_free.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_PROB_FREE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_PROB_FREE_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
25  template <typename T>
+
26  inline
+
27  T prob_free(const T y) {
+
28  using stan::math::logit;
+
29  stan::math::check_bounded<T, double, double>
+
30  ("stan::math::prob_free", "Probability variable",
+
31  y, 0, 1);
+
32  return logit(y);
+
33  }
+
34 
+
35  }
+
36 
+
37 }
+
38 
+
39 #endif
+ + +
fvar< T > logit(const fvar< T > &x)
Definition: logit.hpp:17
+
T prob_free(const T y)
Return the free scalar that when transformed to a probability produces the specified scalar...
Definition: prob_free.hpp:27
+ +
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diff --git a/doc/api/html/prod_8hpp.html b/doc/api/html/prod_8hpp.html new file mode 100644 index 00000000000..109cf12f3fc --- /dev/null +++ b/doc/api/html/prod_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/prod.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
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template<typename T >
stan::math::prod (const std::vector< T > &v)
 Returns the product of the coefficients of the specified standard vector. More...
 
template<typename T , int R, int C>
stan::math::prod (const Eigen::Matrix< T, R, C > &v)
 Returns the product of the coefficients of the specified column vector. More...
 
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diff --git a/doc/api/html/prod_8hpp_source.html b/doc/api/html/prod_8hpp_source.html new file mode 100644 index 00000000000..e715ea7cd22 --- /dev/null +++ b/doc/api/html/prod_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/prod.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_PROD_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_PROD_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
16  template <typename T>
+
17  inline T prod(const std::vector<T>& v) {
+
18  if (v.size() == 0) return 1;
+
19  T product = v[0];
+
20  for (size_t i = 1; i < v.size(); ++i)
+
21  product *= v[i];
+
22  return product;
+
23  }
+
24 
+
31  template <typename T, int R, int C>
+
32  inline T prod(const Eigen::Matrix<T, R, C>& v) {
+
33  if (v.size() == 0) return 1.0;
+
34  return v.prod();
+
35  }
+
36 
+
37  }
+
38 }
+
39 #endif
+ +
T prod(const std::vector< T > &v)
Returns the product of the coefficients of the specified standard vector.
Definition: prod.hpp:17
+ +
+
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diff --git a/doc/api/html/promote__common_8hpp.html b/doc/api/html/promote__common_8hpp.html new file mode 100644 index 00000000000..da68e7c6368 --- /dev/null +++ b/doc/api/html/promote__common_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/promote_common.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , typename F >
common_type< T1, T2 >::type stan::math::promote_common (const F &u)
 
+
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diff --git a/doc/api/html/promote__common_8hpp_source.html b/doc/api/html/promote__common_8hpp_source.html new file mode 100644 index 00000000000..416ab467c7c --- /dev/null +++ b/doc/api/html/promote__common_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/promote_common.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_PROMOTE_COMMON_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_PROMOTE_COMMON_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T1, typename T2, typename F>
+
12  inline
+
13  typename common_type<T1, T2>::type
+
14  promote_common(const F& u) {
+ +
16  ::promote_to(u);
+
17  }
+
18 
+
19  }
+
20 }
+
21 
+
22 
+
23 #endif
+ + +
common_type< T1, T2 >::type promote_common(const F &u)
+ + +
+
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diff --git a/doc/api/html/promoter_8hpp.html b/doc/api/html/promoter_8hpp.html new file mode 100644 index 00000000000..2e4e5ae7037 --- /dev/null +++ b/doc/api/html/promoter_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/promoter.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/promoter_8hpp_source.html b/doc/api/html/promoter_8hpp_source.html new file mode 100644 index 00000000000..42f4ac0c3b5 --- /dev/null +++ b/doc/api/html/promoter_8hpp_source.html @@ -0,0 +1,221 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/promoter.hpp Source File + + + + + + + + + + +
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promoter.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_PROMOTER_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_PROMOTER_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10  // from input type F to output type T
+
11 
+
12  // scalar, F != T (base template)
+
13  template <typename F, typename T>
+
14  struct promoter {
+
15  inline static void promote(const F& u, T& t) {
+
16  t = u;
+
17  }
+
18  inline static T promote_to(const F& u) {
+
19  return u;
+
20  }
+
21  };
+
22  // scalar, F == T
+
23  template <typename T>
+
24  struct promoter<T, T> {
+
25  inline static void promote(const T& u, T& t) {
+
26  t = u;
+
27  }
+
28  inline static T promote_to(const T& u) {
+
29  return u;
+
30  }
+
31  };
+
32 
+
33  // std::vector, F != T
+
34  template <typename F, typename T>
+
35  struct promoter<std::vector<F>, std::vector<T> > {
+
36  inline static void promote(const std::vector<F>& u,
+
37  std::vector<T>& t) {
+
38  t.resize(u.size());
+
39  for (size_t i = 0; i < u.size(); ++i)
+
40  promoter<F, T>::promote(u[i], t[i]);
+
41  }
+
42  inline static std::vector<T>
+
43  promote_to(const std::vector<F>& u) {
+
44  std::vector<T> t;
+
45  promoter<std::vector<F>, std::vector<T> >::promote(u, t);
+
46  return t;
+
47  }
+
48  };
+
49  // std::vector, F == T
+
50  template <typename T>
+
51  struct promoter<std::vector<T>, std::vector<T> > {
+
52  inline static void promote(const std::vector<T>& u,
+
53  std::vector<T>& t) {
+
54  t = u;
+
55  }
+
56  inline static std::vector<T> promote_to(const std::vector<T>& u) {
+
57  return u;
+
58  }
+
59  };
+
60 
+
61  // Eigen::Matrix, F != T
+
62  template <typename F, typename T, int R, int C>
+
63  struct promoter<Eigen::Matrix<F, R, C>, Eigen::Matrix<T, R, C> > {
+
64  inline static void promote(const Eigen::Matrix<F, R, C>& u,
+
65  Eigen::Matrix<T, R, C>& t) {
+
66  t.resize(u.rows(), u.cols());
+
67  for (int i = 0; i < u.size(); ++i)
+
68  promoter<F, T>::promote(u(i), t(i));
+
69  }
+
70  inline static Eigen::Matrix<T, R, C>
+
71  promote_to(const Eigen::Matrix<F, R, C>& u) {
+
72  Eigen::Matrix<T, R, C> t;
+ +
74  Eigen::Matrix<T, R, C> >::promote(u, t);
+
75  return t;
+
76  }
+
77  };
+
78  // Eigen::Matrix, F == T
+
79  template <typename T, int R, int C>
+
80  struct promoter<Eigen::Matrix<T, R, C>, Eigen::Matrix<T, R, C> > {
+
81  inline static void promote(const Eigen::Matrix<T, R, C>& u,
+
82  Eigen::Matrix<T, R, C>& t) {
+
83  t = u;
+
84  }
+
85  inline static Eigen::Matrix<T, R, C>
+
86  promote_to(const Eigen::Matrix<T, R, C>& u) {
+
87  return u;
+
88  }
+
89  };
+
90 
+
91  }
+
92 }
+
93 
+
94 
+
95 #endif
+
static void promote(const T &u, T &t)
Definition: promoter.hpp:25
+
static void promote(const std::vector< T > &u, std::vector< T > &t)
Definition: promoter.hpp:52
+ +
static void promote(const Eigen::Matrix< F, R, C > &u, Eigen::Matrix< T, R, C > &t)
Definition: promoter.hpp:64
+ +
(Expert) Numerical traits for algorithmic differentiation variables.
+
static void promote(const std::vector< F > &u, std::vector< T > &t)
Definition: promoter.hpp:36
+
static T promote_to(const T &u)
Definition: promoter.hpp:28
+
static void promote(const Eigen::Matrix< T, R, C > &u, Eigen::Matrix< T, R, C > &t)
Definition: promoter.hpp:81
+
static Eigen::Matrix< T, R, C > promote_to(const Eigen::Matrix< T, R, C > &u)
Definition: promoter.hpp:86
+ +
static void promote(const F &u, T &t)
Definition: promoter.hpp:15
+
static T promote_to(const F &u)
Definition: promoter.hpp:18
+
static std::vector< T > promote_to(const std::vector< F > &u)
Definition: promoter.hpp:43
+ +
static std::vector< T > promote_to(const std::vector< T > &u)
Definition: promoter.hpp:56
+
static Eigen::Matrix< T, R, C > promote_to(const Eigen::Matrix< F, R, C > &u)
Definition: promoter.hpp:71
+
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diff --git a/doc/api/html/quad__form__diag_8hpp.html b/doc/api/html/quad__form__diag_8hpp.html new file mode 100644 index 00000000000..c17295889d7 --- /dev/null +++ b/doc/api/html/quad__form__diag_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/quad_form_diag.hpp File Reference + + + + + + + + + + +
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template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > stan::math::quad_form_diag (const Eigen::Matrix< T1, Eigen::Dynamic, Eigen::Dynamic > &mat, const Eigen::Matrix< T2, R, C > &vec)
 
+
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diff --git a/doc/api/html/quad__form__diag_8hpp_source.html b/doc/api/html/quad__form__diag_8hpp_source.html new file mode 100644 index 00000000000..14dd89bd33f --- /dev/null +++ b/doc/api/html/quad__form__diag_8hpp_source.html @@ -0,0 +1,159 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/quad_form_diag.hpp Source File + + + + + + + + + + +
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quad_form_diag.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_QUAD_FORM_DIAG_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_QUAD_FORM_DIAG_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+ + + +
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  template <typename T1, typename T2, int R, int C>
+
14  inline Eigen::Matrix <
+
15  typename boost::math::tools::promote_args<T1, T2>::type,
+
16  Eigen::Dynamic, Eigen::Dynamic>
+
17  quad_form_diag(const Eigen::Matrix<T1, Eigen::Dynamic, Eigen::Dynamic>& mat,
+
18  const Eigen::Matrix<T2, R, C>& vec) {
+
19  using boost::math::tools::promote_args;
+
20  stan::math::check_vector("quad_form_diag", "vec", vec);
+
21  stan::math::check_square("quad_form_diag", "mat", mat);
+
22  int size = vec.size();
+
23  stan::math::check_equal("quad_form_diag", "matrix size", mat.rows(),
+
24  size);
+
25  Eigen::Matrix<typename promote_args<T1, T2>::type,
+
26  Eigen::Dynamic, Eigen::Dynamic> result(size, size);
+
27  for (int i = 0; i < size; i++) {
+
28  result(i, i) = vec(i)*vec(i)*mat(i, i);
+
29  for (int j = i+1; j < size; ++j) {
+
30  typename promote_args<T1, T2>::type temp = vec(i)*vec(j);
+
31  result(j, i) = temp*mat(j, i);
+
32  result(i, j) = temp*mat(i, j);
+
33  }
+
34  }
+
35  return result;
+
36  }
+
37 
+
38  }
+
39 }
+
40 #endif
+
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ + +
bool check_equal(const char *function, const char *name, const T_y &y, const T_eq &eq)
Return true if y is equal to eq.
Definition: check_equal.hpp:90
+ + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, Eigen::Dynamic, Eigen::Dynamic > quad_form_diag(const Eigen::Matrix< T1, Eigen::Dynamic, Eigen::Dynamic > &mat, const Eigen::Matrix< T2, R, C > &vec)
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
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diff --git a/doc/api/html/rank_8hpp.html b/doc/api/html/rank_8hpp.html new file mode 100644 index 00000000000..5a29f615624 --- /dev/null +++ b/doc/api/html/rank_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rank.hpp File Reference + + + + + + + + + + +
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template<typename T >
int stan::math::rank (const std::vector< T > &v, int s)
 Return the number of components of v less than v[s]. More...
 
template<typename T , int R, int C>
int stan::math::rank (const Eigen::Matrix< T, R, C > &v, int s)
 Return the number of components of v less than v[s]. More...
 
+
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diff --git a/doc/api/html/rank_8hpp_source.html b/doc/api/html/rank_8hpp_source.html new file mode 100644 index 00000000000..32686440981 --- /dev/null +++ b/doc/api/html/rank_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rank.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_RANK_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_RANK_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
19  template <typename T>
+
20  inline int rank(const std::vector<T> & v, int s) {
+ +
22  int size = static_cast<int>(v.size());
+
23  check_range("rank", "v", size, s);
+
24  --s;
+
25  int count(0);
+
26  T compare(v[s]);
+
27  for (int i = 0; i < size; ++i)
+
28  if (v[i] < compare)
+
29  ++count;
+
30  return count;
+
31  }
+
32 
+
41  template <typename T, int R, int C>
+
42  inline int rank(const Eigen::Matrix<T, R, C> & v, int s) {
+ +
44  int size = v.size();
+
45  check_range("rank", "v", size, s);
+
46  --s;
+
47  const T * vv = v.data();
+
48  int count(0);
+
49  T compare(vv[s]);
+
50  for (int i = 0; i < size; ++i)
+
51  if (vv[i] < compare)
+
52  ++count;
+
53  return count;
+
54  }
+
55 
+
56  }
+
57 }
+
58 #endif
+ +
bool check_range(const char *function, const char *name, const int max, const int index, const int nested_level, const char *error_msg)
Return true if specified index is within range.
Definition: check_range.hpp:29
+
int rank(const std::vector< T > &v, int s)
Return the number of components of v less than v[s].
Definition: rank.hpp:20
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
+
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diff --git a/doc/api/html/rayleigh__ccdf__log_8hpp.html b/doc/api/html/rayleigh__ccdf__log_8hpp.html new file mode 100644 index 00000000000..cdde1168316 --- /dev/null +++ b/doc/api/html/rayleigh__ccdf__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_scale >
return_type< T_y, T_scale >::type stan::math::rayleigh_ccdf_log (const T_y &y, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rayleigh__ccdf__log_8hpp_source.html b/doc/api/html/rayleigh__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..b0c27f66474 --- /dev/null +++ b/doc/api/html/rayleigh__ccdf__log_8hpp_source.html @@ -0,0 +1,229 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_ccdf_log.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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rayleigh_ccdf_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <boost/random/uniform_real_distribution.hpp>
+
19 #include <boost/random/variate_generator.hpp>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <typename T_y, typename T_scale>
+
26  typename return_type<T_y, T_scale>::type
+
27  rayleigh_ccdf_log(const T_y& y, const T_scale& sigma) {
+
28  static const char* function("stan::math::rayleigh_ccdf_log");
+ +
30  T_partials_return;
+
31 
+ + + + + + +
38  using stan::math::square;
+ +
40 
+
41  T_partials_return ccdf_log(0.0);
+
42 
+
43  // check if any vectors are zero length
+
44  if (!(stan::length(y) && stan::length(sigma)))
+
45  return ccdf_log;
+
46 
+
47  check_not_nan(function, "Random variable", y);
+
48  check_nonnegative(function, "Random variable", y);
+
49  check_not_nan(function, "Scale parameter", sigma);
+
50  check_positive(function, "Scale parameter", sigma);
+
51  check_consistent_sizes(function,
+
52  "Random variable", y,
+
53  "Scale parameter", sigma);
+
54 
+
55 
+
56  // set up template expressions wrapping scalars into vector views
+
57  OperandsAndPartials<T_y, T_scale> operands_and_partials(y, sigma);
+
58 
+
59  VectorView<const T_y> y_vec(y);
+
60  VectorView<const T_scale> sigma_vec(sigma);
+
61  size_t N = max_size(y, sigma);
+
62 
+ +
64  for (size_t i = 0; i < length(sigma); i++) {
+
65  inv_sigma[i] = 1.0 / value_of(sigma_vec[i]);
+
66  }
+
67 
+
68  for (size_t n = 0; n < N; n++) {
+
69  const T_partials_return y_dbl = value_of(y_vec[n]);
+
70  const T_partials_return y_sqr = y_dbl * y_dbl;
+
71  const T_partials_return inv_sigma_sqr = inv_sigma[n] * inv_sigma[n];
+
72 
+ +
74  ccdf_log += -0.5 * y_sqr * inv_sigma_sqr;
+
75 
+ +
77  operands_and_partials.d_x1[n] -= y_dbl * inv_sigma_sqr;
+ +
79  operands_and_partials.d_x2[n] += y_sqr * inv_sigma_sqr
+
80  * inv_sigma[n];
+
81  }
+
82 
+
83  return operands_and_partials.value(ccdf_log);
+
84  }
+
85  }
+
86 }
+
87 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_scale >::type rayleigh_ccdf_log(const T_y &y, const T_scale &sigma)
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rayleigh__cdf_8hpp.html b/doc/api/html/rayleigh__cdf_8hpp.html new file mode 100644 index 00000000000..b1e1bdf04aa --- /dev/null +++ b/doc/api/html/rayleigh__cdf_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_cdf.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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template<typename T_y , typename T_scale >
return_type< T_y, T_scale >::type stan::math::rayleigh_cdf (const T_y &y, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rayleigh__cdf_8hpp_source.html b/doc/api/html/rayleigh__cdf_8hpp_source.html new file mode 100644 index 00000000000..99ad46fa9b1 --- /dev/null +++ b/doc/api/html/rayleigh__cdf_8hpp_source.html @@ -0,0 +1,243 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_cdf.hpp Source File + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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rayleigh_cdf.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_CDF_HPP
+
3 
+
4 #include <boost/random/uniform_real_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <typename T_y, typename T_scale>
+
27  typename return_type<T_y, T_scale>::type
+
28  rayleigh_cdf(const T_y& y, const T_scale& sigma) {
+
29  static const char* function("stan::math::rayleigh_cdf");
+ +
31  T_partials_return;
+
32 
+ + + + + + +
39  using stan::math::square;
+ +
41  using std::exp;
+
42 
+
43  T_partials_return cdf(1.0);
+
44 
+
45  // check if any vectors are zero length
+
46  if (!(stan::length(y) && stan::length(sigma)))
+
47  return cdf;
+
48 
+
49  check_not_nan(function, "Random variable", y);
+
50  check_nonnegative(function, "Random variable", y);
+
51  check_not_nan(function, "Scale parameter", sigma);
+
52  check_positive(function, "Scale parameter", sigma);
+
53  check_consistent_sizes(function,
+
54  "Random variable", y,
+
55  "Scale parameter", sigma);
+
56 
+
57 
+
58  // set up template expressions wrapping scalars into vector views
+
59  OperandsAndPartials<T_y, T_scale> operands_and_partials(y, sigma);
+
60 
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_scale> sigma_vec(sigma);
+
63  size_t N = max_size(y, sigma);
+
64 
+ +
66  for (size_t i = 0; i < length(sigma); i++) {
+
67  inv_sigma[i] = 1.0 / value_of(sigma_vec[i]);
+
68  }
+
69 
+
70  for (size_t n = 0; n < N; n++) {
+
71  const T_partials_return y_dbl = value_of(y_vec[n]);
+
72  const T_partials_return y_sqr = y_dbl * y_dbl;
+
73  const T_partials_return inv_sigma_sqr = inv_sigma[n] * inv_sigma[n];
+
74  const T_partials_return exp_val = exp(-0.5 * y_sqr * inv_sigma_sqr);
+
75 
+ +
77  cdf *= (1.0 - exp_val);
+
78  }
+
79 
+
80  // gradients
+
81  for (size_t n = 0; n < N; n++) {
+
82  const T_partials_return y_dbl = value_of(y_vec[n]);
+
83  const T_partials_return y_sqr = square(y_dbl);
+
84  const T_partials_return inv_sigma_sqr = square(inv_sigma[n]);
+
85  const T_partials_return exp_val = exp(-0.5 * y_sqr * inv_sigma_sqr);
+
86  const T_partials_return exp_div_1m_exp = exp_val / (1.0 - exp_val);
+
87 
+ +
89  operands_and_partials.d_x1[n] += y_dbl * inv_sigma_sqr
+
90  * exp_div_1m_exp * cdf;
+ +
92  operands_and_partials.d_x2[n] -= y_sqr * inv_sigma_sqr
+
93  * inv_sigma[n] * exp_div_1m_exp * cdf;
+
94  }
+
95 
+
96  return operands_and_partials.value(cdf);
+
97  }
+
98  }
+
99 }
+
100 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
return_type< T_y, T_scale >::type rayleigh_cdf(const T_y &y, const T_scale &sigma)
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rayleigh__cdf__log_8hpp.html b/doc/api/html/rayleigh__cdf__log_8hpp.html new file mode 100644 index 00000000000..50348925445 --- /dev/null +++ b/doc/api/html/rayleigh__cdf__log_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + + + + + +
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+
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+ + + + + + + +

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+ + + + +

+Functions

template<typename T_y , typename T_scale >
return_type< T_y, T_scale >::type stan::math::rayleigh_cdf_log (const T_y &y, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rayleigh__cdf__log_8hpp_source.html b/doc/api/html/rayleigh__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..cb086f11186 --- /dev/null +++ b/doc/api/html/rayleigh__cdf__log_8hpp_source.html @@ -0,0 +1,236 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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rayleigh_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_CDF_LOG_HPP
+
3 
+
4 #include <boost/random/uniform_real_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <typename T_y, typename T_scale>
+
27  typename return_type<T_y, T_scale>::type
+
28  rayleigh_cdf_log(const T_y& y, const T_scale& sigma) {
+
29  static const char* function("stan::math::rayleigh_cdf_log");
+ +
31  T_partials_return;
+
32 
+ + + + + + +
39  using stan::math::square;
+ +
41  using stan::math::log1m;
+
42  using std::exp;
+
43 
+
44  T_partials_return cdf_log(0.0);
+
45 
+
46  // check if any vectors are zero length
+
47  if (!(stan::length(y) && stan::length(sigma)))
+
48  return cdf_log;
+
49 
+
50  check_not_nan(function, "Random variable", y);
+
51  check_nonnegative(function, "Random variable", y);
+
52  check_not_nan(function, "Scale parameter", sigma);
+
53  check_positive(function, "Scale parameter", sigma);
+
54  check_consistent_sizes(function,
+
55  "Random variable", y,
+
56  "Scale parameter", sigma);
+
57 
+
58  // set up template expressions wrapping scalars into vector views
+
59  OperandsAndPartials<T_y, T_scale> operands_and_partials(y, sigma);
+
60 
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_scale> sigma_vec(sigma);
+
63  size_t N = max_size(y, sigma);
+
64 
+ +
66  for (size_t i = 0; i < length(sigma); i++) {
+
67  inv_sigma[i] = 1.0 / value_of(sigma_vec[i]);
+
68  }
+
69 
+
70  for (size_t n = 0; n < N; n++) {
+
71  const T_partials_return y_dbl = value_of(y_vec[n]);
+
72  const T_partials_return y_sqr = y_dbl * y_dbl;
+
73  const T_partials_return inv_sigma_sqr = inv_sigma[n] * inv_sigma[n];
+
74  const T_partials_return exp_val = exp(-0.5 * y_sqr * inv_sigma_sqr);
+
75  const T_partials_return exp_div_1m_exp = exp_val / (1.0 - exp_val);
+
76 
+ +
78  cdf_log += log1m(exp_val);
+
79 
+ +
81  operands_and_partials.d_x1[n] += y_dbl * inv_sigma_sqr
+
82  * exp_div_1m_exp;
+ +
84  operands_and_partials.d_x2[n] -= y_sqr * inv_sigma_sqr
+
85  * inv_sigma[n] * exp_div_1m_exp;
+
86  }
+
87 
+
88  return operands_and_partials.value(cdf_log);
+
89  }
+
90  }
+
91 }
+
92 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
return_type< T_y, T_scale >::type rayleigh_cdf_log(const T_y &y, const T_scale &sigma)
+ + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rayleigh__log_8hpp.html b/doc/api/html/rayleigh__log_8hpp.html new file mode 100644 index 00000000000..adf1395f0ee --- /dev/null +++ b/doc/api/html/rayleigh__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
rayleigh_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_scale >
return_type< T_y, T_scale >::type stan::math::rayleigh_log (const T_y &y, const T_scale &sigma)
 
template<typename T_y , typename T_scale >
return_type< T_y, T_scale >::type stan::math::rayleigh_log (const T_y &y, const T_scale &sigma)
 
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diff --git a/doc/api/html/rayleigh__log_8hpp_source.html b/doc/api/html/rayleigh__log_8hpp_source.html new file mode 100644 index 00000000000..45eb3df602e --- /dev/null +++ b/doc/api/html/rayleigh__log_8hpp_source.html @@ -0,0 +1,256 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_log.hpp Source File + + + + + + + + + + +
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rayleigh_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_LOG_HPP
+
3 
+
4 #include <boost/random/uniform_real_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + +
20 #include <cmath>
+
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <bool propto,
+
27  typename T_y, typename T_scale>
+
28  typename return_type<T_y, T_scale>::type
+
29  rayleigh_log(const T_y& y, const T_scale& sigma) {
+
30  static const char* function("stan::math::rayleigh_log");
+ +
32  T_partials_return;
+
33 
+
34  using std::log;
+ + + + + + +
41  using std::log;
+
42 
+
43  // check if any vectors are zero length
+
44  if (!(stan::length(y) && stan::length(sigma)))
+
45  return 0.0;
+
46 
+
47  // set up return value accumulator
+
48  T_partials_return logp(0.0);
+
49 
+
50  // validate args (here done over var, which should be OK)
+
51  check_not_nan(function, "Random variable", y);
+
52  check_positive(function, "Scale parameter", sigma);
+
53  check_positive(function, "Random variable", y);
+
54  check_consistent_sizes(function,
+
55  "Random variable", y,
+
56  "Scale parameter", sigma);
+
57 
+
58  // check if no variables are involved and prop-to
+ +
60  return 0.0;
+
61 
+
62  // set up template expressions wrapping scalars into vector views
+
63  OperandsAndPartials<T_y, T_scale> operands_and_partials(y, sigma);
+
64 
+
65  VectorView<const T_y> y_vec(y);
+
66  VectorView<const T_scale> sigma_vec(sigma);
+
67  size_t N = max_size(y, sigma);
+
68 
+ + +
71  T_partials_return, T_scale> log_sigma(length(sigma));
+
72  for (size_t i = 0; i < length(sigma); i++) {
+
73  inv_sigma[i] = 1.0 / value_of(sigma_vec[i]);
+ +
75  log_sigma[i] = log(value_of(sigma_vec[i]));
+
76  }
+
77 
+
78  for (size_t n = 0; n < N; n++) {
+
79  // pull out values of arguments
+
80  const T_partials_return y_dbl = value_of(y_vec[n]);
+
81 
+
82  // reusable subexpression values
+
83  const T_partials_return y_over_sigma = y_dbl * inv_sigma[n];
+
84 
+
85  static double NEGATIVE_HALF = -0.5;
+
86 
+
87  // log probability
+ +
89  logp -= 2.0 * log_sigma[n];
+ +
91  logp += log(y_dbl);
+
92  // if (include_summand<propto, T_y, T_scale>::value)
+
93  logp += NEGATIVE_HALF * y_over_sigma * y_over_sigma;
+
94 
+
95  // gradients
+
96  T_partials_return scaled_diff = inv_sigma[n] * y_over_sigma;
+ +
98  operands_and_partials.d_x1[n] += 1.0 / y_dbl - scaled_diff;
+ +
100  operands_and_partials.d_x2[n]
+
101  += y_over_sigma * scaled_diff - 2.0 * inv_sigma[n];
+
102  }
+
103  return operands_and_partials.value(logp);
+
104  }
+
105 
+
106  template <typename T_y, typename T_scale>
+
107  inline
+ +
109  rayleigh_log(const T_y& y, const T_scale& sigma) {
+
110  return rayleigh_log<false>(y, sigma);
+
111  }
+
112  }
+
113 }
+
114 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_y, T_scale >::type rayleigh_log(const T_y &y, const T_scale &sigma)
+
This class builds partial derivatives with respect to a set of operands.
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/rayleigh__rng_8hpp.html b/doc/api/html/rayleigh__rng_8hpp.html new file mode 100644 index 00000000000..8dea607d897 --- /dev/null +++ b/doc/api/html/rayleigh__rng_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::rayleigh_rng (const double sigma, RNG &rng)
 
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diff --git a/doc/api/html/rayleigh__rng_8hpp_source.html b/doc/api/html/rayleigh__rng_8hpp_source.html new file mode 100644 index 00000000000..77ccc878ae0 --- /dev/null +++ b/doc/api/html/rayleigh__rng_8hpp_source.html @@ -0,0 +1,167 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/rayleigh_rng.hpp Source File + + + + + + + + + + +
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rayleigh_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_RAYLEIGH_RNG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/uniform_real_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  template <class RNG>
+
23  inline double
+
24  rayleigh_rng(const double sigma,
+
25  RNG& rng) {
+
26  using boost::variate_generator;
+
27  using boost::random::uniform_real_distribution;
+
28 
+
29  static const char* function("stan::math::rayleigh_rng");
+
30 
+ +
32 
+
33  check_positive(function, "Scale parameter", sigma);
+
34 
+
35  variate_generator<RNG&, uniform_real_distribution<> >
+
36  uniform_rng(rng, uniform_real_distribution<>(0.0, 1.0));
+
37  return sigma * std::sqrt(-2.0 * std::log(uniform_rng()));
+
38  }
+
39  }
+
40 }
+
41 #endif
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
double rayleigh_rng(const double sigma, RNG &rng)
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ + + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
double uniform_rng(const double alpha, const double beta, RNG &rng)
Definition: uniform_rng.hpp:21
+ + + + + + +
+
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diff --git a/doc/api/html/read__corr___l_8hpp.html b/doc/api/html/read__corr___l_8hpp.html new file mode 100644 index 00000000000..3c241c7bfd7 --- /dev/null +++ b/doc/api/html/read__corr___l_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/read_corr_L.hpp File Reference + + + + + + + + + + +
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read_corr_L.hpp File Reference
+
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+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/scal/fun/log1m.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <stan/math/prim/mat/fun/sum.hpp>
+#include <cstddef>
+#include <iostream>
+
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::read_corr_L (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
 Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::read_corr_L (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K, T &log_prob)
 Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations, incrementing the specified scalar reference with the log absolute determinant of the Jacobian of the transformation. More...
 
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diff --git a/doc/api/html/read__corr___l_8hpp_source.html b/doc/api/html/read__corr___l_8hpp_source.html new file mode 100644 index 00000000000..17ea028647c --- /dev/null +++ b/doc/api/html/read__corr___l_8hpp_source.html @@ -0,0 +1,195 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/read_corr_L.hpp Source File + + + + + + + + + + +
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read_corr_L.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_READ_CORR_L_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_READ_CORR_L_HPP
+
3 
+ + + + +
8 #include <cstddef>
+
9 #include <iostream>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15 
+
16  // MATRIX TRANSFORMS +/- JACOBIANS
+
17 
+
39  template <typename T>
+
40  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
41  read_corr_L(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs, // on (-1, 1)
+
42  const size_t K) {
+
43  Eigen::Array<T, Eigen::Dynamic, 1> temp;
+
44  Eigen::Array<T, Eigen::Dynamic, 1> acc(K-1);
+
45  acc.setOnes();
+
46  // Cholesky factor of correlation matrix
+
47  Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic> L(K, K);
+
48  L.setZero();
+
49 
+
50  size_t position = 0;
+
51  size_t pull = K - 1;
+
52 
+
53  L(0, 0) = 1.0;
+
54  L.col(0).tail(pull) = temp = CPCs.head(pull);
+
55  acc.tail(pull) = T(1.0) - temp.square();
+
56  for (size_t i = 1; i < (K - 1); i++) {
+
57  position += pull;
+
58  pull--;
+
59  temp = CPCs.segment(position, pull);
+
60  L(i, i) = sqrt(acc(i-1));
+
61  L.col(i).tail(pull) = temp * acc.tail(pull).sqrt();
+
62  acc.tail(pull) *= T(1.0) - temp.square();
+
63  }
+
64  L(K-1, K-1) = sqrt(acc(K-2));
+
65  return L.matrix();
+
66  }
+
67 
+
68 
+
93  template <typename T>
+
94  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
95  read_corr_L(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
+
96  const size_t K,
+
97  T& log_prob) {
+
98  using stan::math::log1m;
+
99  using stan::math::square;
+
100  using stan::math::sum;
+
101 
+
102  Eigen::Matrix<T, Eigen::Dynamic, 1> values(CPCs.rows() - 1);
+
103  size_t pos = 0;
+
104  // no need to abs() because this Jacobian determinant
+
105  // is strictly positive (and triangular)
+
106  // see inverse of Jacobian in equation 11 of LKJ paper
+
107  for (size_t k = 1; k <= (K - 2); k++)
+
108  for (size_t i = k + 1; i <= K; i++) {
+
109  values(pos) = (K - k - 1) * log1m(square(CPCs(pos)));
+
110  pos++;
+
111  }
+
112 
+
113  log_prob += 0.5 * sum(values);
+
114  return read_corr_L(CPCs, K);
+
115  }
+
116 
+
117  }
+
118 
+
119 }
+
120 
+
121 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_L(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to...
Definition: read_corr_L.hpp:41
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/read__corr__matrix_8hpp.html b/doc/api/html/read__corr__matrix_8hpp.html new file mode 100644 index 00000000000..6fd9ddb83fe --- /dev/null +++ b/doc/api/html/read__corr__matrix_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/read_corr_matrix.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::read_corr_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
 Return the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::read_corr_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K, T &log_prob)
 Return the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations, incrementing the specified scalar reference with the log absolute determinant of the Jacobian of the transformation. More...
 
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diff --git a/doc/api/html/read__corr__matrix_8hpp_source.html b/doc/api/html/read__corr__matrix_8hpp_source.html new file mode 100644 index 00000000000..f6579a337bc --- /dev/null +++ b/doc/api/html/read__corr__matrix_8hpp_source.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/read_corr_matrix.hpp Source File + + + + + + + + + + +
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read_corr_matrix.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_READ_CORR_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_READ_CORR_MATRIX_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12 
+
26  template <typename T>
+
27  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
28  read_corr_matrix(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
+
29  const size_t K) {
+
30  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> L
+
31  = read_corr_L(CPCs, K);
+ + +
34  }
+
35 
+
54  template <typename T>
+
55  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
56  read_corr_matrix(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
+
57  const size_t K,
+
58  T& log_prob) {
+
59  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> L
+
60  = read_corr_L(CPCs, K, log_prob);
+ + +
63  }
+
64 
+
65  }
+
66 
+
67 }
+
68 
+
69 #endif
+ +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_matrix(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
Return the correlation matrix of the specified dimensionality corresponding to the specified canonica...
+ +
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose(const Eigen::Matrix< fvar< T >, R, C > &m)
+ +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_L(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to...
Definition: read_corr_L.hpp:41
+ +
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diff --git a/doc/api/html/read__cov___l_8hpp.html b/doc/api/html/read__cov___l_8hpp.html new file mode 100644 index 00000000000..15dadad6ddb --- /dev/null +++ b/doc/api/html/read__cov___l_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/read_cov_L.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::read_cov_L (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds, T &log_prob)
 This is the function that should be called prior to evaluating the density of any elliptical distribution. More...
 
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diff --git a/doc/api/html/read__cov___l_8hpp_source.html b/doc/api/html/read__cov___l_8hpp_source.html new file mode 100644 index 00000000000..7253ef1d9b9 --- /dev/null +++ b/doc/api/html/read__cov___l_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/read_cov_L.hpp Source File + + + + + + + + + + +
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read_cov_L.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_READ_COV_L_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_READ_COV_L_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
21  template <typename T>
+
22  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
23  read_cov_L(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
+
24  const Eigen::Array<T, Eigen::Dynamic, 1>& sds,
+
25  T& log_prob) {
+
26  size_t K = sds.rows();
+
27  // adjust due to transformation from correlations to covariances
+
28  log_prob += (sds.log().sum() + stan::math::LOG_2) * K;
+
29  return sds.matrix().asDiagonal() * read_corr_L(CPCs, K, log_prob);
+
30  }
+
31 
+
32 
+
33  }
+
34 
+
35 }
+
36 
+
37 #endif
+
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:33
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_cov_L(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds, T &log_prob)
This is the function that should be called prior to evaluating the density of any elliptical distribu...
Definition: read_cov_L.hpp:23
+ + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_L(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to...
Definition: read_corr_L.hpp:41
+ +
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diff --git a/doc/api/html/read__cov__matrix_8hpp.html b/doc/api/html/read__cov__matrix_8hpp.html new file mode 100644 index 00000000000..0cc321b48b0 --- /dev/null +++ b/doc/api/html/read__cov__matrix_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/read_cov_matrix.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::read_cov_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds, T &log_prob)
 A generally worse alternative to call prior to evaluating the density of an elliptical distribution. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::read_cov_matrix (const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds)
 Builds a covariance matrix from CPCs and standard deviations. More...
 
+
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diff --git a/doc/api/html/read__cov__matrix_8hpp_source.html b/doc/api/html/read__cov__matrix_8hpp_source.html new file mode 100644 index 00000000000..d7905fead2b --- /dev/null +++ b/doc/api/html/read__cov__matrix_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/read_cov_matrix.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_READ_COV_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_READ_COV_MATRIX_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
21  template <typename T>
+
22  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
23  read_cov_matrix(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
+
24  const Eigen::Array<T, Eigen::Dynamic, 1>& sds,
+
25  T& log_prob) {
+
26  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> L
+
27  = read_cov_L(CPCs, sds, log_prob);
+ + +
30  }
+
31 
+
39  template<typename T>
+
40  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
41  read_cov_matrix(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,
+
42  const Eigen::Array<T, Eigen::Dynamic, 1>& sds) {
+
43  size_t K = sds.rows();
+
44  Eigen::DiagonalMatrix<T, Eigen::Dynamic> D(K);
+
45  D.diagonal() = sds;
+
46  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> L
+
47  = D * read_corr_L(CPCs, K);
+ + +
50  }
+
51 
+
52  }
+
53 
+
54 }
+
55 
+
56 #endif
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_cov_matrix(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds, T &log_prob)
A generally worse alternative to call prior to evaluating the density of an elliptical distribution...
+ +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_cov_L(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const Eigen::Array< T, Eigen::Dynamic, 1 > &sds, T &log_prob)
This is the function that should be called prior to evaluating the density of any elliptical distribu...
Definition: read_cov_L.hpp:23
+ +
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose(const Eigen::Matrix< fvar< T >, R, C > &m)
+ + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > read_corr_L(const Eigen::Array< T, Eigen::Dynamic, 1 > &CPCs, const size_t K)
Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to...
Definition: read_corr_L.hpp:41
+
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diff --git a/doc/api/html/recover__memory_8hpp.html b/doc/api/html/recover__memory_8hpp.html new file mode 100644 index 00000000000..85cf357fcb6 --- /dev/null +++ b/doc/api/html/recover__memory_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/core/recover_memory.hpp File Reference + + + + + + + + + + +
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static void stan::math::recover_memory ()
 Recover memory used for all variables for reuse. More...
 
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diff --git a/doc/api/html/recover__memory_8hpp_source.html b/doc/api/html/recover__memory_8hpp_source.html new file mode 100644 index 00000000000..b6907ced140 --- /dev/null +++ b/doc/api/html/recover__memory_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/rev/core/recover_memory.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_RECOVER_MEMORY_HPP
+
2 #define STAN_MATH_REV_CORE_RECOVER_MEMORY_HPP
+
3 
+ + + +
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
18  static inline void recover_memory() {
+
19  if (!empty_nested())
+
20  throw std::logic_error("empty_nested() must be true"
+
21  " before calling recover_memory()");
+ + +
24  for (size_t i = 0; i < ChainableStack::var_alloc_stack_.size(); ++i) {
+ +
26  }
+ + +
29  }
+
30 
+
31  }
+
32 }
+
33 #endif
+
static bool empty_nested()
Return true if there is no nested autodiff being executed.
+ + + + +
void recover_all()
Recover all the memory used by the stack allocator.
+
static std::vector< ChainableAllocT * > var_alloc_stack_
+
static std::vector< ChainableT * > var_nochain_stack_
+
static void recover_memory()
Recover memory used for all variables for reuse.
+ +
static std::vector< ChainableT * > var_stack_
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/recover__memory__nested_8hpp.html b/doc/api/html/recover__memory__nested_8hpp.html new file mode 100644 index 00000000000..77dbc5bc388 --- /dev/null +++ b/doc/api/html/recover__memory__nested_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/core/recover_memory_nested.hpp File Reference + + + + + + + + + + +
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static void stan::math::recover_memory_nested ()
 Recover only the memory used for the top nested call. More...
 
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diff --git a/doc/api/html/recover__memory__nested_8hpp_source.html b/doc/api/html/recover__memory__nested_8hpp_source.html new file mode 100644 index 00000000000..87930d3a1f3 --- /dev/null +++ b/doc/api/html/recover__memory__nested_8hpp_source.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan/math/rev/core/recover_memory_nested.hpp Source File + + + + + + + + + + +
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recover_memory_nested.hpp
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1 #ifndef STAN_MATH_REV_CORE_RECOVER_MEMORY_NESTED_HPP
+
2 #define STAN_MATH_REV_CORE_RECOVER_MEMORY_NESTED_HPP
+
3 
+ + + +
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
20  static inline void recover_memory_nested() {
+
21  if (empty_nested())
+
22  throw std::logic_error("empty_nested() must be false"
+
23  " before calling recover_memory_nested()");
+
24 
+ + + +
28 
+ + + +
32 
+ + +
35  ++i) {
+ +
37  }
+ + + +
41 
+ +
43  }
+
44 
+
45  }
+
46 }
+
47 #endif
+
static bool empty_nested()
Return true if there is no nested autodiff being executed.
+ + +
void recover_nested()
recover memory back to the last start_nested call.
+ +
static std::vector< ChainableAllocT * > var_alloc_stack_
+
static std::vector< ChainableT * > var_nochain_stack_
+
static std::vector< size_t > nested_var_nochain_stack_sizes_
+ +
static std::vector< size_t > nested_var_stack_sizes_
+
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+ +
static std::vector< ChainableT * > var_stack_
+
static std::vector< size_t > nested_var_alloc_stack_starts_
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rep__array_8hpp.html b/doc/api/html/rep__array_8hpp.html new file mode 100644 index 00000000000..99eec754ccd --- /dev/null +++ b/doc/api/html/rep__array_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/rep_array.hpp File Reference + + + + + + + + + + +
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rep_array.hpp File Reference
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#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <vector>
+
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template<typename T >
std::vector< T > stan::math::rep_array (const T &x, int n)
 
template<typename T >
std::vector< std::vector< T > > stan::math::rep_array (const T &x, int m, int n)
 
template<typename T >
std::vector< std::vector< std::vector< T > > > stan::math::rep_array (const T &x, int k, int m, int n)
 
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diff --git a/doc/api/html/rep__array_8hpp_source.html b/doc/api/html/rep__array_8hpp_source.html new file mode 100644 index 00000000000..10de43d9ba1 --- /dev/null +++ b/doc/api/html/rep__array_8hpp_source.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/rep_array.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_REP_ARRAY_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_REP_ARRAY_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  template <typename T>
+
12  inline std::vector<T>
+
13  rep_array(const T& x, int n) {
+ +
15  check_nonnegative("rep_array", "n", n);
+
16  return std::vector<T>(n, x);
+
17  }
+
18 
+
19  template <typename T>
+
20  inline std::vector<std::vector<T> >
+
21  rep_array(const T& x, int m, int n) {
+
22  using std::vector;
+ +
24  check_nonnegative("rep_array", "rows", m);
+
25  check_nonnegative("rep_array", "cols", n);
+
26  return vector<vector<T> >(m, vector<T>(n, x));
+
27  }
+
28 
+
29  template <typename T>
+
30  inline std::vector<std::vector<std::vector<T> > >
+
31  rep_array(const T& x, int k, int m, int n) {
+
32  using std::vector;
+ +
34  check_nonnegative("rep_array", "shelfs", k);
+
35  check_nonnegative("rep_array", "rows", m);
+
36  check_nonnegative("rep_array", "cols", n);
+
37  return vector<vector<vector<T> > >(k,
+
38  vector<vector<T> >(m,
+
39  vector<T>(n, x)));
+
40  }
+
41 
+
42  }
+
43 }
+
44 
+
45 #endif
+ +
std::vector< T > rep_array(const T &x, int n)
Definition: rep_array.hpp:13
+ +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rep__matrix_8hpp.html b/doc/api/html/rep__matrix_8hpp.html new file mode 100644 index 00000000000..cd6acfc6e09 --- /dev/null +++ b/doc/api/html/rep__matrix_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rep_matrix.hpp File Reference + + + + + + + + + + +
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+
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+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+
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template<typename T >
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, Eigen::Dynamic, Eigen::Dynamic > stan::math::rep_matrix (const T &x, int m, int n)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::rep_matrix (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, int n)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::rep_matrix (const Eigen::Matrix< T, 1, Eigen::Dynamic > &rv, int m)
 
+
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diff --git a/doc/api/html/rep__matrix_8hpp_source.html b/doc/api/html/rep__matrix_8hpp_source.html new file mode 100644 index 00000000000..9c00eca8c1c --- /dev/null +++ b/doc/api/html/rep__matrix_8hpp_source.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rep_matrix.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_REP_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_REP_MATRIX_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  Eigen::Matrix<typename boost::math::tools::promote_args<T>::type,
+
15  Eigen::Dynamic, Eigen::Dynamic>
+
16  rep_matrix(const T& x, int m, int n) {
+ +
18  check_nonnegative("rep_matrix", "rows", m);
+
19  check_nonnegative("rep_matrix", "cols", n);
+
20  return Eigen::Matrix<typename boost::math::tools::promote_args<T>::type,
+
21  Eigen::Dynamic, Eigen::Dynamic>::Constant(m, n, x);
+
22  }
+
23 
+
24  template <typename T>
+
25  inline Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
26  rep_matrix(const Eigen::Matrix<T, Eigen::Dynamic, 1>& v, int n) {
+ +
28  check_nonnegative("rep_matrix", "rows", n);
+
29  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> result(v.size(), n);
+
30  result.colwise() = v;
+
31  return result;
+
32  }
+
33 
+
34  template <typename T>
+
35  inline Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
36  rep_matrix(const Eigen::Matrix<T, 1, Eigen::Dynamic>& rv, int m) {
+ +
38  check_nonnegative("rep_matrix", "cols", m);
+
39  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> result(m, rv.size());
+
40  result.rowwise() = rv;
+
41  return result;
+
42  }
+
43  }
+
44 }
+
45 
+
46 #endif
+ + + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, Eigen::Dynamic, Eigen::Dynamic > rep_matrix(const T &x, int m, int n)
Definition: rep_matrix.hpp:16
+
+
+
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diff --git a/doc/api/html/rep__row__vector_8hpp.html b/doc/api/html/rep__row__vector_8hpp.html new file mode 100644 index 00000000000..6aa8722ee24 --- /dev/null +++ b/doc/api/html/rep__row__vector_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rep_row_vector.hpp File Reference + + + + + + + + + + +
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+
+
+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+
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template<typename T >
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, 1, Eigen::Dynamic > stan::math::rep_row_vector (const T &x, int m)
 
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diff --git a/doc/api/html/rep__row__vector_8hpp_source.html b/doc/api/html/rep__row__vector_8hpp_source.html new file mode 100644 index 00000000000..7d318af3813 --- /dev/null +++ b/doc/api/html/rep__row__vector_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rep_row_vector.hpp Source File + + + + + + + + + + +
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rep_row_vector.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_REP_ROW_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_REP_ROW_VECTOR_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline Eigen::Matrix<typename boost::math::tools::promote_args<T>::type,
+
14  1, Eigen::Dynamic>
+
15  rep_row_vector(const T& x, int m) {
+ +
17  check_nonnegative("rep_row_vector", "m", m);
+
18  return Eigen::Matrix<typename boost::math::tools::promote_args<T>::type,
+
19  1, Eigen::Dynamic>::Constant(m, x);
+
20  }
+
21 
+
22  }
+
23 }
+
24 
+
25 #endif
+ +
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, 1, Eigen::Dynamic > rep_row_vector(const T &x, int m)
+ + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rep__vector_8hpp.html b/doc/api/html/rep__vector_8hpp.html new file mode 100644 index 00000000000..a629cf07a4d --- /dev/null +++ b/doc/api/html/rep__vector_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rep_vector.hpp File Reference + + + + + + + + + + +
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rep_vector.hpp File Reference
+
+
+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/err/check_nonnegative.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+
+

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+Functions

template<typename T >
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, Eigen::Dynamic, 1 > stan::math::rep_vector (const T &x, int n)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rep__vector_8hpp_source.html b/doc/api/html/rep__vector_8hpp_source.html new file mode 100644 index 00000000000..0ad04b277c0 --- /dev/null +++ b/doc/api/html/rep__vector_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rep_vector.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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rep_vector.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_REP_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_REP_VECTOR_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <typename T>
+
13  inline
+
14  Eigen::Matrix<typename boost::math::tools::promote_args<T>::type,
+
15  Eigen::Dynamic, 1>
+
16  rep_vector(const T& x, int n) {
+ +
18  check_nonnegative("rep_vector", "n", n);
+
19  return Eigen::Matrix<typename boost::math::tools::promote_args<T>::type,
+
20  Eigen::Dynamic, 1>::Constant(n, x);
+
21  }
+
22 
+
23 
+
24  }
+
25 }
+
26 
+
27 #endif
+ +
Eigen::Matrix< typename boost::math::tools::promote_args< T >::type, Eigen::Dynamic, 1 > rep_vector(const T &x, int n)
Definition: rep_vector.hpp:16
+ + +
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/resize_8hpp.html b/doc/api/html/resize_8hpp.html new file mode 100644 index 00000000000..7d3b66a5d52 --- /dev/null +++ b/doc/api/html/resize_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/resize.hpp File Reference + + + + + + + + + + +
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resize.hpp File Reference
+
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
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template<typename T >
void stan::math::resize (T &x, std::vector< size_t > dims)
 Recursively resize the specified vector of vectors, which must bottom out at scalar values, Eigen vectors or Eigen matrices. More...
 
+
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/resize_8hpp_source.html b/doc/api/html/resize_8hpp_source.html new file mode 100644 index 00000000000..8b220767d9f --- /dev/null +++ b/doc/api/html/resize_8hpp_source.html @@ -0,0 +1,173 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/resize.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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resize.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_RESIZE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_RESIZE_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11 
+
12  template <typename T>
+
13  void resize(Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& x,
+
14  const std::vector<size_t>& dims,
+
15  size_t pos) {
+
16  x.resize(dims[pos], dims[pos+1]);
+
17  }
+
18 
+
19  template <typename T>
+
20  void resize(Eigen::Matrix<T, Eigen::Dynamic, 1>& x,
+
21  const std::vector<size_t>& dims,
+
22  size_t pos) {
+
23  x.resize(dims[pos]);
+
24  }
+
25 
+
26  template <typename T>
+
27  void resize(Eigen::Matrix<T, 1, Eigen::Dynamic>& x,
+
28  const std::vector<size_t>& dims,
+
29  size_t pos) {
+
30  x.resize(dims[pos]);
+
31  }
+
32 
+
33  template <typename T>
+
34  void resize(T /*x*/,
+
35  const std::vector<size_t>& /*dims*/,
+
36  size_t /*pos*/) {
+
37  // no-op
+
38  }
+
39 
+
40  template <typename T>
+
41  void resize(std::vector<T>& x,
+
42  const std::vector<size_t>& dims,
+
43  size_t pos) {
+
44  x.resize(dims[pos]);
+
45  ++pos;
+
46  if (pos >= dims.size()) return; // skips lowest loop to scalar
+
47  for (size_t i = 0; i < x.size(); ++i)
+
48  resize(x[i], dims, pos);
+
49  }
+
50 
+
51  }
+
52 
+
62  template <typename T>
+
63  inline void resize(T& x, std::vector<size_t> dims) {
+
64  resize(x, dims, 0U);
+
65  }
+
66 
+
67  }
+
68 }
+
69 #endif
+ +
void resize(T &x, std::vector< size_t > dims)
Recursively resize the specified vector of vectors, which must bottom out at scalar values...
Definition: resize.hpp:63
+
void dims(const T &x, std::vector< int > &result)
Definition: dims.hpp:13
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/return__type_8hpp.html b/doc/api/html/return__type_8hpp.html new file mode 100644 index 00000000000..030a6fe0504 --- /dev/null +++ b/doc/api/html/return__type_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/return_type.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
return_type.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/scalar_type.hpp>
+#include <boost/math/tools/promotion.hpp>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::return_type< T1, T2, T3, T4, T5, T6 >
 Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters. More...
 
+ + + +

+Namespaces

 stan
 
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diff --git a/doc/api/html/return__type_8hpp_source.html b/doc/api/html/return__type_8hpp_source.html new file mode 100644 index 00000000000..1fd1eaf8d49 --- /dev/null +++ b/doc/api/html/return__type_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/return_type.hpp Source File + + + + + + + + + + +
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return_type.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_RETURN_TYPE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_RETURN_TYPE_HPP
+
3 
+ +
5 #include <boost/math/tools/promotion.hpp>
+
6 
+
7 namespace stan {
+
8 
+
13  template <typename T1,
+
14  typename T2 = double,
+
15  typename T3 = double,
+
16  typename T4 = double,
+
17  typename T5 = double,
+
18  typename T6 = double>
+
19  struct return_type {
+
20  typedef typename
+
21  boost::math::tools::promote_args<typename scalar_type<T1>::type,
+
22  typename scalar_type<T2>::type,
+
23  typename scalar_type<T3>::type,
+
24  typename scalar_type<T4>::type,
+
25  typename scalar_type<T5>::type,
+ + +
28  };
+
29 
+
30 }
+
31 #endif
+
32 
+ +
Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of...
Definition: return_type.hpp:19
+
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2arr_2fun_2log__sum__exp_8hpp.html b/doc/api/html/rev_2arr_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..61cbaede8e6 --- /dev/null +++ b/doc/api/html/rev_2arr_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+ +
+
log_sum_exp.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/scal/fun/calculate_chain.hpp>
+#include <stan/math/prim/arr/fun/log_sum_exp.hpp>
+#include <vector>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

var stan::math::log_sum_exp (const std::vector< var > &x)
 Returns the log sum of exponentials. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2arr_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/rev_2arr_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..e9e4f6fb854 --- /dev/null +++ b/doc/api/html/rev_2arr_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
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log_sum_exp.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_ARR_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_REV_ARR_FUN_LOG_SUM_EXP_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <vector>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  double log_sum_exp_as_double(const std::vector<var>& x) {
+
15  using std::numeric_limits;
+
16  using std::exp;
+
17  using std::log;
+
18  double max = -numeric_limits<double>::infinity();
+
19  for (size_t i = 0; i < x.size(); ++i)
+
20  if (x[i] > max)
+
21  max = x[i].val();
+
22  double sum = 0.0;
+
23  for (size_t i = 0; i < x.size(); ++i)
+
24  if (x[i] != -numeric_limits<double>::infinity())
+
25  sum += exp(x[i].val() - max);
+
26  return max + log(sum);
+
27  }
+
28 
+
29  class log_sum_exp_vector_vari : public op_vector_vari {
+
30  public:
+
31  explicit log_sum_exp_vector_vari(const std::vector<var>& x) :
+
32  op_vector_vari(log_sum_exp_as_double(x), x) {
+
33  }
+
34  void chain() {
+
35  for (size_t i = 0; i < size_; ++i) {
+
36  vis_[i]->adj_ += adj_ * calculate_chain(vis_[i]->val_, val_);
+
37  }
+
38  }
+
39  };
+
40  }
+
41 
+
45  inline var log_sum_exp(const std::vector<var>& x) {
+
46  return var(new log_sum_exp_vector_vari(x));
+
47  }
+
48 
+
49  }
+
50 }
+
51 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+ +
double calculate_chain(const double &x, const double &val)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
size_t size_
Definition: dot_self.hpp:18
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2arr_2fun_2sum_8hpp.html b/doc/api/html/rev_2arr_2fun_2sum_8hpp.html new file mode 100644 index 00000000000..2b0fdac3a50 --- /dev/null +++ b/doc/api/html/rev_2arr_2fun_2sum_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/fun/sum.hpp File Reference + + + + + + + + + + +
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+
sum.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

class  stan::math::sum_v_vari
 Class for sums of variables constructed with standard vectors. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

var stan::math::sum (const std::vector< var > &m)
 Returns the sum of the entries of the specified vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2arr_2fun_2sum_8hpp_source.html b/doc/api/html/rev_2arr_2fun_2sum_8hpp_source.html new file mode 100644 index 00000000000..f20c037060e --- /dev/null +++ b/doc/api/html/rev_2arr_2fun_2sum_8hpp_source.html @@ -0,0 +1,176 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/fun/sum.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+ + +
+ +
+ + +
+
+
+
sum.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_ARR_FUN_SUM_HPP
+
2 #define STAN_MATH_REV_ARR_FUN_SUM_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
14  class sum_v_vari : public vari {
+
15  protected:
+
16  vari** v_;
+
17  size_t length_;
+
18 
+
19  inline static double sum_of_val(const std::vector<var>& v) {
+
20  double result = 0;
+
21  for (size_t i = 0; i < v.size(); i++)
+
22  result += v[i].val();
+
23  return result;
+
24  }
+
25 
+
26  public:
+
27  explicit sum_v_vari(double value, vari** v, size_t length)
+
28  : vari(value), v_(v), length_(length) {
+
29  }
+
30 
+
31  explicit sum_v_vari(const std::vector<var> &v1)
+
32  : vari(sum_of_val(v1)),
+
33  v_(reinterpret_cast<vari**>(ChainableStack::memalloc_
+
34  .alloc(v1.size() * sizeof(vari*)))),
+
35  length_(v1.size()) {
+
36  for (size_t i = 0; i < length_; i++)
+
37  v_[i] = v1[i].vi_;
+
38  }
+
39 
+
40  virtual void chain() {
+
41  for (size_t i = 0; i < length_; i++) {
+
42  v_[i]->adj_ += adj_;
+
43  }
+
44  }
+
45  };
+
46 
+
53  inline var sum(const std::vector<var>& m) {
+
54  if (m.size() == 0)
+
55  return 0.0;
+
56  return var(new sum_v_vari(m));
+
57  }
+
58 
+
59  }
+
60 }
+
61 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+
sum_v_vari(double value, vari **v, size_t length)
Definition: sum.hpp:27
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
virtual void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
Definition: sum.hpp:40
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+
static double sum_of_val(const std::vector< var > &v)
Definition: sum.hpp:19
+
Class for sums of variables constructed with standard vectors.
Definition: sum.hpp:14
+
sum_v_vari(const std::vector< var > &v1)
Definition: sum.hpp:31
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2arr_2functor_2coupled__ode__system_8hpp.html b/doc/api/html/rev_2arr_2functor_2coupled__ode__system_8hpp.html new file mode 100644 index 00000000000..272eb917655 --- /dev/null +++ b/doc/api/html/rev_2arr_2functor_2coupled__ode__system_8hpp.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/functor/coupled_ode_system.hpp File Reference + + + + + + + + + + +
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coupled_ode_system.hpp File Reference
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+ +

Go to the source code of this file.

+ + + + + + + + + + + +

+Classes

struct  stan::math::coupled_ode_system< F, double, stan::math::var >
 The coupled ODE system for known initial values and unknown parameters. More...
 
struct  stan::math::coupled_ode_system< F, stan::math::var, double >
 The coupled ODE system for unknown initial values and known parameters. More...
 
struct  stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
 The coupled ode system for unknown intial values and unknown parameters. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

void stan::math::add_initial_values (const std::vector< stan::math::var > &y0, std::vector< std::vector< stan::math::var > > &y)
 Increment the state derived from the coupled system in the with the original initial state. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2arr_2functor_2coupled__ode__system_8hpp_source.html b/doc/api/html/rev_2arr_2functor_2coupled__ode__system_8hpp_source.html new file mode 100644 index 00000000000..e3fa4d6ca5e --- /dev/null +++ b/doc/api/html/rev_2arr_2functor_2coupled__ode__system_8hpp_source.html @@ -0,0 +1,583 @@ + + + + + + +Stan Math Library: stan/math/rev/arr/functor/coupled_ode_system.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
coupled_ode_system.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_ARR_FUNCTOR_COUPLED_ODE_SYSTEM_HPP
+
2 #define STAN_MATH_REV_ARR_FUNCTOR_COUPLED_ODE_SYSTEM_HPP
+
3 
+ + + + + + +
10 #include <stan/math/rev/core.hpp>
+
11 #include <ostream>
+
12 #include <stdexcept>
+
13 #include <vector>
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  // This code is in this directory because it includes var
+
19  // It is in namespace stan::math so that the partial template
+
20  // specializations are treated as such.
+
21 
+
22 
+
34  void add_initial_values(const std::vector<stan::math::var>& y0,
+
35  std::vector<std::vector<stan::math::var> >& y) {
+
36  for (size_t n = 0; n < y.size(); n++)
+
37  for (size_t m = 0; m < y0.size(); m++)
+
38  y[n][m] += y0[m];
+
39  }
+
40 
+
62  template <typename F>
+
63  struct coupled_ode_system <F, double, stan::math::var> {
+
64  const F& f_;
+
65  const std::vector<double>& y0_dbl_;
+
66  const std::vector<stan::math::var>& theta_;
+
67  std::vector<double> theta_dbl_;
+
68  const std::vector<double>& x_;
+
69  const std::vector<int>& x_int_;
+
70  const size_t N_;
+
71  const size_t M_;
+
72  const size_t size_;
+
73  std::ostream* msgs_;
+
74 
+
87  coupled_ode_system(const F& f,
+
88  const std::vector<double>& y0,
+
89  const std::vector<stan::math::var>& theta,
+
90  const std::vector<double>& x,
+
91  const std::vector<int>& x_int,
+
92  std::ostream* msgs)
+
93  : f_(f),
+
94  y0_dbl_(y0),
+
95  theta_(theta),
+
96  theta_dbl_(theta.size(), 0.0),
+
97  x_(x),
+
98  x_int_(x_int),
+
99  N_(y0.size()),
+
100  M_(theta.size()),
+
101  size_(N_ + N_ * M_),
+
102  msgs_(msgs) {
+
103  for (size_t m = 0; m < M_; m++)
+
104  theta_dbl_[m] = stan::math::value_of(theta[m]);
+
105  }
+
106 
+
124  void operator()(const std::vector<double>& z,
+
125  std::vector<double>& dz_dt,
+
126  double t) {
+
127  using std::vector;
+
128  using stan::math::var;
+
129 
+
130  vector<double> y(z.begin(), z.begin() + N_);
+
131  dz_dt = f_(t, y, theta_dbl_, x_, x_int_, msgs_);
+
132  stan::math::check_equal("coupled_ode_system",
+
133  "dz_dt", dz_dt.size(), N_);
+
134 
+
135  vector<double> coupled_sys(N_ * M_);
+
136  vector<double> grad(N_ + M_);
+
137 
+
138  try {
+ +
140 
+
141  vector<var> z_vars;
+
142  z_vars.reserve(N_ + M_);
+
143 
+
144  vector<var> y_vars(y.begin(), y.end());
+
145  z_vars.insert(z_vars.end(), y_vars.begin(), y_vars.end());
+
146 
+
147  vector<var> theta_vars(theta_dbl_.begin(), theta_dbl_.end());
+
148  z_vars.insert(z_vars.end(), theta_vars.begin(), theta_vars.end());
+
149 
+
150  vector<var> dy_dt_vars = f_(t, y_vars, theta_vars, x_, x_int_, msgs_);
+
151 
+
152  for (size_t i = 0; i < N_; i++) {
+ +
154  dy_dt_vars[i].grad(z_vars, grad);
+
155 
+
156  for (size_t j = 0; j < M_; j++) {
+
157  // orders derivatives by equation (i.e. if there are 2 eqns
+
158  // (y1, y2) and 2 parameters (a, b), dy_dt will be ordered as:
+
159  // dy1_dt, dy2_dt, dy1_da, dy2_da, dy1_db, dy2_db
+
160  double temp_deriv = grad[N_ + j];
+
161  for (size_t k = 0; k < N_; k++)
+
162  temp_deriv += z[N_ + N_ * j + k] * grad[k];
+
163 
+
164  coupled_sys[i + j * N_] = temp_deriv;
+
165  }
+
166  }
+
167  } catch (const std::exception& e) {
+ +
169  throw;
+
170  }
+ +
172 
+
173  dz_dt.insert(dz_dt.end(), coupled_sys.begin(), coupled_sys.end());
+
174  }
+
175 
+
181  size_t size() const {
+
182  return size_;
+
183  }
+
184 
+
198  std::vector<double> initial_state() {
+
199  std::vector<double> state(size_, 0.0);
+
200  for (size_t n = 0; n < N_; n++)
+
201  state[n] = y0_dbl_[n];
+
202  return state;
+
203  }
+
204 
+
211  std::vector<std::vector<stan::math::var> >
+
212  decouple_states(const std::vector<std::vector<double> >& y) {
+ +
214  std::vector<stan::math::var> temp_vars(N_);
+
215  std::vector<double> temp_gradients(M_);
+
216  std::vector<std::vector<stan::math::var> > y_return(y.size());
+
217 
+
218  for (size_t i = 0; i < y.size(); i++) {
+
219  // iterate over number of equations
+
220  for (size_t j = 0; j < N_; j++) {
+
221  // iterate over parameters for each equation
+
222  for (size_t k = 0; k < M_; k++)
+
223  temp_gradients[k] = y[i][y0_dbl_.size() + y0_dbl_.size() * k + j];
+
224 
+
225  temp_vars[j] = precomputed_gradients(y[i][j],
+
226  theta_,
+
227  temp_gradients);
+
228  }
+
229  y_return[i] = temp_vars;
+
230  }
+
231  return y_return;
+
232  }
+
233  };
+
234 
+
261  template <typename F>
+
262  struct coupled_ode_system <F, stan::math::var, double> {
+
263  const F& f_;
+
264  const std::vector<stan::math::var>& y0_;
+
265  std::vector<double> y0_dbl_;
+
266  const std::vector<double>& theta_dbl_;
+
267  const std::vector<double>& x_;
+
268  const std::vector<int>& x_int_;
+
269  std::ostream* msgs_;
+
270  const size_t N_;
+
271  const size_t M_;
+
272  const size_t size_;
+
273 
+
287  coupled_ode_system(const F& f,
+
288  const std::vector<stan::math::var>& y0,
+
289  const std::vector<double>& theta,
+
290  const std::vector<double>& x,
+
291  const std::vector<int>& x_int,
+
292  std::ostream* msgs)
+
293  : f_(f),
+
294  y0_(y0),
+
295  y0_dbl_(y0.size(), 0.0),
+
296  theta_dbl_(theta),
+
297  x_(x),
+
298  x_int_(x_int),
+
299  msgs_(msgs),
+
300  N_(y0.size()),
+
301  M_(theta.size()),
+
302  size_(N_ + N_ * N_) {
+
303  for (size_t n = 0; n < N_; n++)
+
304  y0_dbl_[n] = stan::math::value_of(y0_[n]);
+
305  }
+
306 
+
323  void operator()(const std::vector<double>& z,
+
324  std::vector<double>& dz_dt,
+
325  double t) {
+
326  using std::vector;
+
327  using stan::math::var;
+
328 
+
329  std::vector<double> y(z.begin(), z.begin() + N_);
+
330  for (size_t n = 0; n < N_; n++)
+
331  y[n] += y0_dbl_[n];
+
332 
+
333  dz_dt = f_(t, y, theta_dbl_, x_, x_int_, msgs_);
+
334  stan::math::check_equal("coupled_ode_system",
+
335  "dz_dt", dz_dt.size(), N_);
+
336 
+
337  std::vector<double> coupled_sys(N_ * N_);
+
338  std::vector<double> grad(N_);
+
339 
+
340  try {
+ +
342 
+
343  vector<var> z_vars;
+
344  z_vars.reserve(N_);
+
345 
+
346  vector<var> y_vars(y.begin(), y.end());
+
347  z_vars.insert(z_vars.end(), y_vars.begin(), y_vars.end());
+
348 
+
349  vector<var> dy_dt_vars = f_(t, y_vars, theta_dbl_, x_, x_int_, msgs_);
+
350 
+
351  for (size_t i = 0; i < N_; i++) {
+ +
353  dy_dt_vars[i].grad(z_vars, grad);
+
354 
+
355  for (size_t j = 0; j < N_; j++) {
+
356  // orders derivatives by equation (i.e. if there are 2 eqns
+
357  // (y1, y2) and 2 parameters (a, b), dy_dt will be ordered as:
+
358  // dy1_dt, dy2_dt, dy1_da, dy2_da, dy1_db, dy2_db
+
359  double temp_deriv = grad[j];
+
360  for (size_t k = 0; k < N_; k++)
+
361  temp_deriv += z[N_ + N_ * j + k] * grad[k];
+
362 
+
363  coupled_sys[i + j * N_] = temp_deriv;
+
364  }
+
365  }
+
366  } catch (const std::exception& e) {
+ +
368  throw;
+
369  }
+ +
371 
+
372  dz_dt.insert(dz_dt.end(), coupled_sys.begin(), coupled_sys.end());
+
373  }
+
374 
+
380  size_t size() const {
+
381  return size_;
+
382  }
+
383 
+
398  std::vector<double> initial_state() {
+
399  return std::vector<double>(size_, 0.0);
+
400  }
+
401 
+
409  std::vector<std::vector<stan::math::var> >
+
410  decouple_states(const std::vector<std::vector<double> >& y) {
+ +
412  using stan::math::var;
+
413  using std::vector;
+
414 
+
415  vector<var> temp_vars(N_);
+
416  vector<double> temp_gradients(N_);
+
417  vector<vector<var> > y_return(y.size());
+
418 
+
419  for (size_t i = 0; i < y.size(); i++) {
+
420  // iterate over number of equations
+
421  for (size_t j = 0; j < N_; j++) {
+
422  // iterate over parameters for each equation
+
423  for (size_t k = 0; k < N_; k++)
+
424  temp_gradients[k] = y[i][y0_.size() + y0_.size() * k + j];
+
425 
+
426  temp_vars[j] = precomputed_gradients(y[i][j],
+
427  y0_, temp_gradients);
+
428  }
+
429  y_return[i] = temp_vars;
+
430  }
+
431 
+
432  add_initial_values(y0_, y_return);
+
433 
+
434  return y_return;
+
435  }
+
436  };
+
437 
+
473  template <typename F>
+ +
475  const F& f_;
+
476  const std::vector<stan::math::var>& y0_;
+
477  std::vector<double> y0_dbl_;
+
478  const std::vector<stan::math::var>& theta_;
+
479  std::vector<double> theta_dbl_;
+
480  const std::vector<double>& x_;
+
481  const std::vector<int>& x_int_;
+
482  const size_t N_;
+
483  const size_t M_;
+
484  const size_t size_;
+
485  std::ostream* msgs_;
+
486 
+
500  coupled_ode_system(const F& f,
+
501  const std::vector<stan::math::var>& y0,
+
502  const std::vector<stan::math::var>& theta,
+
503  const std::vector<double>& x,
+
504  const std::vector<int>& x_int,
+
505  std::ostream* msgs)
+
506  : f_(f),
+
507  y0_(y0),
+
508  y0_dbl_(y0.size(), 0.0),
+
509  theta_(theta),
+
510  theta_dbl_(theta.size(), 0.0),
+
511  x_(x),
+
512  x_int_(x_int),
+
513  N_(y0.size()),
+
514  M_(theta.size()),
+
515  size_(N_ + N_ * (N_ + M_)),
+
516  msgs_(msgs) {
+
517  for (size_t n = 0; n < N_; n++)
+
518  y0_dbl_[n] = stan::math::value_of(y0[n]);
+
519 
+
520  for (size_t m = 0; m < M_; m++)
+
521  theta_dbl_[m] = stan::math::value_of(theta[m]);
+
522  }
+
523 
+
540  void operator()(const std::vector<double>& z,
+
541  std::vector<double>& dz_dt,
+
542  double t) {
+
543  using std::vector;
+
544  using stan::math::var;
+
545 
+
546  vector<double> y(z.begin(), z.begin() + N_);
+
547  for (size_t n = 0; n < N_; n++)
+
548  y[n] += y0_dbl_[n];
+
549 
+
550  dz_dt = f_(t, y, theta_dbl_, x_, x_int_, msgs_);
+
551  stan::math::check_equal("coupled_ode_system",
+
552  "dz_dt", dz_dt.size(), N_);
+
553 
+
554  vector<double> coupled_sys(N_ * (N_ + M_));
+
555  vector<double> grad(N_ + M_);
+
556 
+
557  try {
+ +
559 
+
560  vector<var> z_vars;
+
561  z_vars.reserve(N_ + M_);
+
562 
+
563  vector<var> y_vars(y.begin(), y.end());
+
564  z_vars.insert(z_vars.end(), y_vars.begin(), y_vars.end());
+
565 
+
566  vector<var> theta_vars(theta_dbl_.begin(), theta_dbl_.end());
+
567  z_vars.insert(z_vars.end(), theta_vars.begin(), theta_vars.end());
+
568 
+
569  vector<var> dy_dt_vars = f_(t, y_vars, theta_vars, x_, x_int_, msgs_);
+
570 
+
571  for (size_t i = 0; i < N_; i++) {
+ +
573  dy_dt_vars[i].grad(z_vars, grad);
+
574 
+
575  for (size_t j = 0; j < N_ + M_; j++) {
+
576  // orders derivatives by equation (i.e. if there are 2 eqns
+
577  // (y1, y2) and 2 parameters (a, b), dy_dt will be ordered as:
+
578  // dy1_dt, dy2_dt, dy1_da, dy2_da, dy1_db, dy2_db
+
579  double temp_deriv = grad[j];
+
580  for (size_t k = 0; k < N_; k++)
+
581  temp_deriv += z[N_ + N_ * j + k] * grad[k];
+
582 
+
583  coupled_sys[i + j * N_] = temp_deriv;
+
584  }
+
585  }
+
586  } catch (const std::exception& e) {
+ +
588  throw;
+
589  }
+ +
591 
+
592  dz_dt.insert(dz_dt.end(), coupled_sys.begin(), coupled_sys.end());
+
593  }
+
594 
+
600  size_t size() const {
+
601  return size_;
+
602  }
+
603 
+
615  std::vector<double> initial_state() {
+
616  return std::vector<double>(size_, 0.0);
+
617  }
+
618 
+
626  std::vector<std::vector<stan::math::var> >
+
627  decouple_states(const std::vector<std::vector<double> >& y) {
+
628  using std::vector;
+
629  using stan::math::var;
+ +
631 
+
632  vector<var> vars = y0_;
+
633  vars.insert(vars.end(), theta_.begin(), theta_.end());
+
634 
+
635  vector<var> temp_vars(N_);
+
636  vector<double> temp_gradients(N_ + M_);
+
637  vector<vector<var> > y_return(y.size());
+
638 
+
639  for (size_t i = 0; i < y.size(); i++) {
+
640  // iterate over number of equations
+
641  for (size_t j = 0; j < N_; j++) {
+
642  // iterate over parameters for each equation
+
643  for (size_t k = 0; k < N_ + M_; k++)
+
644  temp_gradients[k] = y[i][N_ + N_ * k + j];
+
645 
+
646  temp_vars[j] = precomputed_gradients(y[i][j],
+
647  vars, temp_gradients);
+
648  }
+
649  y_return[i] = temp_vars;
+
650  }
+
651  add_initial_values(y0_, y_return);
+
652  return y_return;
+
653  }
+
654  };
+
655  } // math
+
656 } // stan
+
657 
+
658 #endif
+
var precomputed_gradients(const double value, const std::vector< var > &operands, const std::vector< double > &gradients)
This function returns a var for an expression that has the specified value, vector of operands...
+ + + +
std::vector< std::vector< stan::math::var > > decouple_states(const std::vector< std::vector< double > > &y)
Returns the base ODE system state corresponding to the specified coupled system state.
+ + +
std::vector< std::vector< stan::math::var > > decouple_states(const std::vector< std::vector< double > > &y)
Return the solutions to the basic ODE system, including appropriate autodiff partial derivatives...
+
coupled_ode_system(const F &f, const std::vector< double > &y0, const std::vector< stan::math::var > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
Construct a coupled ODE system with the specified base ODE system, base initial state, parameters, data, and a message stream.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
static void set_zero_all_adjoints_nested()
Reset all adjoint values in the top nested portion of the stack to zero.
+ +
std::vector< double > initial_state()
Returns the initial state of the coupled system.
+
std::vector< std::vector< stan::math::var > > decouple_states(const std::vector< std::vector< double > > &y)
Return the basic ODE solutions given the specified coupled system solutions, including the partials v...
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+
size_t size() const
Returns the size of the coupled system.
+ + +
void operator()(const std::vector< double > &z, std::vector< double > &dz_dt, double t)
Calculates the derivative of the coupled ode system with respect to the state y at time t...
+
void operator()(const std::vector< double > &z, std::vector< double > &dz_dt, double t)
Assign the derivative vector with the system derivatives at the specified state and time...
+
int M_
+ +
size_t size_
Definition: dot_self.hpp:18
+
std::vector< double > initial_state()
Returns the initial state of the coupled system.
+
coupled_ode_system(const F &f, const std::vector< stan::math::var > &y0, const std::vector< double > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
Construct a coupled ODE system for an unknown initial state and known parameters givne the specified ...
+ + + + + + +
bool check_equal(const char *function, const char *name, const T_y &y, const T_eq &eq)
Return true if y is equal to eq.
Definition: check_equal.hpp:90
+ + +
void add_initial_values(const std::vector< stan::math::var > &y0, std::vector< std::vector< stan::math::var > > &y)
Increment the state derived from the coupled system in the with the original initial state...
+ + + +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+ +
std::vector< double > initial_state()
Returns the initial state of the coupled system.
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
coupled_ode_system(const F &f, const std::vector< stan::math::var > &y0, const std::vector< stan::math::var > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
Construct a coupled ODE system with unknown initial value and known parameters, given the base ODE sy...
+ + +
void operator()(const std::vector< double > &z, std::vector< double > &dz_dt, double t)
Populates the derivative vector with derivatives of the coupled ODE system state with respect to time...
+ +
Base template class for a coupled ordinary differential equation system, which adds sensitivities to ...
+
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+ + + + + + +
size_t size() const
Returns the size of the coupled system.
+
int N_
+ + +
size_t size() const
Returns the size of the coupled system.
+ + +
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2arr_8hpp.html b/doc/api/html/rev_2arr_8hpp.html new file mode 100644 index 00000000000..0ca6cf7fda5 --- /dev/null +++ b/doc/api/html/rev_2arr_8hpp.html @@ -0,0 +1,120 @@ + + + + + + +Stan Math Library: stan/math/rev/arr.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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arr.hpp File Reference
+
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diff --git a/doc/api/html/rev_2arr_8hpp_source.html b/doc/api/html/rev_2arr_8hpp_source.html new file mode 100644 index 00000000000..d7cc4c59e59 --- /dev/null +++ b/doc/api/html/rev_2arr_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/arr.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
+
+
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+
+
arr.hpp
+
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diff --git a/doc/api/html/rev_2core_2operator__addition_8hpp.html b/doc/api/html/rev_2core_2operator__addition_8hpp.html new file mode 100644 index 00000000000..9110cb45559 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__addition_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_addition.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+ +
+
operator_addition.hpp File Reference
+
+
+
#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/vv_vari.hpp>
+#include <stan/math/rev/core/vd_vari.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::operator+ (const var &a, const var &b)
 Addition operator for variables (C++). More...
 
var stan::math::operator+ (const var &a, const double b)
 Addition operator for variable and scalar (C++). More...
 
var stan::math::operator+ (const double a, const var &b)
 Addition operator for scalar and variable (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__addition_8hpp_source.html b/doc/api/html/rev_2core_2operator__addition_8hpp_source.html new file mode 100644 index 00000000000..3928800f527 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__addition_8hpp_source.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_addition.hpp Source File + + + + + + + + + + +
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+
Stan Math Library +  2.10.0 +
+
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+
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+
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+ + +
+
+
+
operator_addition.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_ADDITION_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_ADDITION_HPP
+
3 
+ + + +
7 #include <boost/math/special_functions/fpclassify.hpp>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class add_vv_vari : public op_vv_vari {
+
15  public:
+
16  add_vv_vari(vari* avi, vari* bvi) :
+
17  op_vv_vari(avi->val_ + bvi->val_, avi, bvi) {
+
18  }
+
19  void chain() {
+
20  if (unlikely(boost::math::isnan(avi_->val_)
+
21  || boost::math::isnan(bvi_->val_))) {
+
22  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
23  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
24  } else {
+
25  avi_->adj_ += adj_;
+
26  bvi_->adj_ += adj_;
+
27  }
+
28  }
+
29  };
+
30 
+
31  class add_vd_vari : public op_vd_vari {
+
32  public:
+
33  add_vd_vari(vari* avi, double b) :
+
34  op_vd_vari(avi->val_ + b, avi, b) {
+
35  }
+
36  void chain() {
+
37  if (unlikely(boost::math::isnan(avi_->val_)
+
38  || boost::math::isnan(bd_)))
+
39  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
40  else
+
41  avi_->adj_ += adj_;
+
42  }
+
43  };
+
44  }
+
45 
+
84  inline var operator+(const var& a, const var& b) {
+
85  return var(new add_vv_vari(a.vi_, b.vi_));
+
86  }
+
87 
+
99  inline var operator+(const var& a, const double b) {
+
100  if (b == 0.0)
+
101  return a;
+
102  return var(new add_vd_vari(a.vi_, b));
+
103  }
+
104 
+
116  inline var operator+(const double a, const var& b) {
+
117  if (a == 0.0)
+
118  return b;
+
119  return var(new add_vd_vari(b.vi_, a)); // by symmetry
+
120  }
+
121 
+
122  }
+
123 }
+
124 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > operator+(const fvar< T > &x1, const fvar< T > &x2)
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__division_8hpp.html b/doc/api/html/rev_2core_2operator__division_8hpp.html new file mode 100644 index 00000000000..f122c7aeb87 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__division_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_division.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+ +
+
operator_division.hpp File Reference
+
+
+
#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/vv_vari.hpp>
+#include <stan/math/rev/core/vd_vari.hpp>
+#include <stan/math/rev/core/dv_vari.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

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 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::operator/ (const var &a, const var &b)
 Division operator for two variables (C++). More...
 
var stan::math::operator/ (const var &a, const double b)
 Division operator for dividing a variable by a scalar (C++). More...
 
var stan::math::operator/ (const double a, const var &b)
 Division operator for dividing a scalar by a variable (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__division_8hpp_source.html b/doc/api/html/rev_2core_2operator__division_8hpp_source.html new file mode 100644 index 00000000000..8d2f654f60e --- /dev/null +++ b/doc/api/html/rev_2core_2operator__division_8hpp_source.html @@ -0,0 +1,193 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_division.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+ + +
+
+
+
operator_division.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_DIVISION_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_DIVISION_HPP
+
3 
+ + + + +
8 #include <boost/math/special_functions/fpclassify.hpp>
+
9 #include <limits>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  namespace {
+
15  // (a/b)' = a' * (1 / b) - b' * (a / [b * b])
+
16  class divide_vv_vari : public op_vv_vari {
+
17  public:
+
18  divide_vv_vari(vari* avi, vari* bvi) :
+
19  op_vv_vari(avi->val_ / bvi->val_, avi, bvi) {
+
20  }
+
21  void chain() {
+
22  if (unlikely(boost::math::isnan(avi_->val_)
+
23  || boost::math::isnan(bvi_->val_))) {
+
24  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
25  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
26  } else {
+
27  avi_->adj_ += adj_ / bvi_->val_;
+
28  bvi_->adj_ -= adj_ * avi_->val_ / (bvi_->val_ * bvi_->val_);
+
29  }
+
30  }
+
31  };
+
32 
+
33  class divide_vd_vari : public op_vd_vari {
+
34  public:
+
35  divide_vd_vari(vari* avi, double b) :
+
36  op_vd_vari(avi->val_ / b, avi, b) {
+
37  }
+
38  void chain() {
+
39  if (unlikely(boost::math::isnan(avi_->val_)
+
40  || boost::math::isnan(bd_)))
+
41  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
42  else
+
43  avi_->adj_ += adj_ / bd_;
+
44  }
+
45  };
+
46 
+
47  class divide_dv_vari : public op_dv_vari {
+
48  public:
+
49  divide_dv_vari(double a, vari* bvi) :
+
50  op_dv_vari(a / bvi->val_, a, bvi) {
+
51  }
+
52  void chain() {
+
53  bvi_->adj_ -= adj_ * ad_ / (bvi_->val_ * bvi_->val_);
+
54  }
+
55  };
+
56  }
+
57 
+
96  inline var operator/(const var& a, const var& b) {
+
97  return var(new divide_vv_vari(a.vi_, b.vi_));
+
98  }
+
99 
+
111  inline var operator/(const var& a, const double b) {
+
112  if (b == 1.0)
+
113  return a;
+
114  return var(new divide_vd_vari(a.vi_, b));
+
115  }
+
116 
+
128  inline var operator/(const double a, const var& b) {
+
129  return var(new divide_dv_vari(a, b.vi_));
+
130  }
+
131 
+
132  }
+
133 }
+
134 #endif
+ +
fvar< T > operator/(const fvar< T > &x1, const fvar< T > &x2)
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__equal_8hpp.html b/doc/api/html/rev_2core_2operator__equal_8hpp.html new file mode 100644 index 00000000000..45f40364afc --- /dev/null +++ b/doc/api/html/rev_2core_2operator__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_equal.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+ +
+
operator_equal.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

bool stan::math::operator== (const var &a, const var &b)
 Equality operator comparing two variables' values (C++). More...
 
bool stan::math::operator== (const var &a, const double b)
 Equality operator comparing a variable's value and a double (C++). More...
 
bool stan::math::operator== (const double a, const var &b)
 Equality operator comparing a scalar and a variable's value (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__equal_8hpp_source.html b/doc/api/html/rev_2core_2operator__equal_8hpp_source.html new file mode 100644 index 00000000000..92d7074b740 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__equal_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_equal.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
operator_equal.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_EQUAL_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_EQUAL_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
26  inline bool operator==(const var& a, const var& b) {
+
27  return a.val() == b.val();
+
28  }
+
29 
+
39  inline bool operator==(const var& a, const double b) {
+
40  return a.val() == b;
+
41  }
+
42 
+
51  inline bool operator==(const double a, const var& b) {
+
52  return a == b.val();
+
53  }
+
54 
+
55  }
+
56 }
+
57 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
bool operator==(const fvar< T > &x, const fvar< T > &y)
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__greater__than_8hpp.html b/doc/api/html/rev_2core_2operator__greater__than_8hpp.html new file mode 100644 index 00000000000..d34496d7e41 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__greater__than_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_greater_than.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
operator_greater_than.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

bool stan::math::operator> (const var &a, const var &b)
 Greater than operator comparing variables' values (C++). More...
 
bool stan::math::operator> (const var &a, const double b)
 Greater than operator comparing variable's value and double (C++). More...
 
bool stan::math::operator> (const double a, const var &b)
 Greater than operator comparing a double and a variable's value (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__greater__than_8hpp_source.html b/doc/api/html/rev_2core_2operator__greater__than_8hpp_source.html new file mode 100644 index 00000000000..8caf25349d6 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__greater__than_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_greater_than.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
operator_greater_than.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_GREATER_THAN_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_GREATER_THAN_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
25  inline bool operator>(const var& a, const var& b) {
+
26  return a.val() > b.val();
+
27  }
+
28 
+
37  inline bool operator>(const var& a, const double b) {
+
38  return a.val() > b;
+
39  }
+
40 
+
49  inline bool operator>(const double a, const var& b) {
+
50  return a > b.val();
+
51  }
+
52 
+
53  }
+
54 }
+
55 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
bool operator>(const fvar< T > &x, const fvar< T > &y)
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__greater__than__or__equal_8hpp.html b/doc/api/html/rev_2core_2operator__greater__than__or__equal_8hpp.html new file mode 100644 index 00000000000..7b7c2ab34a0 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__greater__than__or__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_greater_than_or_equal.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+
+ +
+
operator_greater_than_or_equal.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

bool stan::math::operator>= (const var &a, const var &b)
 Greater than or equal operator comparing two variables' values (C++). More...
 
bool stan::math::operator>= (const var &a, const double b)
 Greater than or equal operator comparing variable's value and double (C++). More...
 
bool stan::math::operator>= (const double a, const var &b)
 Greater than or equal operator comparing double and variable's value (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__greater__than__or__equal_8hpp_source.html b/doc/api/html/rev_2core_2operator__greater__than__or__equal_8hpp_source.html new file mode 100644 index 00000000000..38c32d98ed2 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__greater__than__or__equal_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_greater_than_or_equal.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
operator_greater_than_or_equal.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_GREATER_THAN_OR_EQUAL_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_GREATER_THAN_OR_EQUAL_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
27  inline bool operator>=(const var& a, const var& b) {
+
28  return a.val() >= b.val();
+
29  }
+
30 
+
40  inline bool operator>=(const var& a, const double b) {
+
41  return a.val() >= b;
+
42  }
+
43 
+
53  inline bool operator>=(const double a, const var& b) {
+
54  return a >= b.val();
+
55  }
+
56 
+
57  }
+
58 }
+
59 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
bool operator>=(const fvar< T > &x, const fvar< T > &y)
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__less__than_8hpp.html b/doc/api/html/rev_2core_2operator__less__than_8hpp.html new file mode 100644 index 00000000000..5f261802e92 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__less__than_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_less_than.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
operator_less_than.hpp File Reference
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 Matrices and templated mathematical functions.
 
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bool stan::math::operator< (const var &a, const var &b)
 Less than operator comparing variables' values (C++). More...
 
bool stan::math::operator< (const var &a, const double b)
 Less than operator comparing variable's value and a double (C++). More...
 
bool stan::math::operator< (const double a, const var &b)
 Less than operator comparing a double and variable's value (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__less__than_8hpp_source.html b/doc/api/html/rev_2core_2operator__less__than_8hpp_source.html new file mode 100644 index 00000000000..965c49645e0 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__less__than_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_less_than.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
operator_less_than.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_LESS_THAN_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_LESS_THAN_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
24  inline bool operator<(const var& a, const var& b) {
+
25  return a.val() < b.val();
+
26  }
+
27 
+
36  inline bool operator<(const var& a, const double b) {
+
37  return a.val() < b;
+
38  }
+
39 
+
48  inline bool operator<(const double a, const var& b) {
+
49  return a < b.val();
+
50  }
+
51 
+
52  }
+
53 }
+
54 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
bool operator<(const fvar< T > &x, double y)
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__less__than__or__equal_8hpp.html b/doc/api/html/rev_2core_2operator__less__than__or__equal_8hpp.html new file mode 100644 index 00000000000..e3b4468c632 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__less__than__or__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_less_than_or_equal.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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operator_less_than_or_equal.hpp File Reference
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 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

bool stan::math::operator<= (const var &a, const var &b)
 Less than or equal operator comparing two variables' values (C++). More...
 
bool stan::math::operator<= (const var &a, const double b)
 Less than or equal operator comparing a variable's value and a scalar (C++). More...
 
bool stan::math::operator<= (const double a, const var &b)
 Less than or equal operator comparing a double and variable's value (C++). More...
 
+
+
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diff --git a/doc/api/html/rev_2core_2operator__less__than__or__equal_8hpp_source.html b/doc/api/html/rev_2core_2operator__less__than__or__equal_8hpp_source.html new file mode 100644 index 00000000000..c7e931d2794 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__less__than__or__equal_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_less_than_or_equal.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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operator_less_than_or_equal.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_LESS_THAN_OR_EQUAL_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_LESS_THAN_OR_EQUAL_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
26  inline bool operator<=(const var& a, const var& b) {
+
27  return a.val() <= b.val();
+
28  }
+
29 
+
39  inline bool operator<=(const var& a, const double b) {
+
40  return a.val() <= b;
+
41  }
+
42 
+
52  inline bool operator<=(const double a, const var& b) {
+
53  return a <= b.val();
+
54  }
+
55 
+
56  }
+
57 }
+
58 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool operator<=(const fvar< T > &x, const fvar< T > &y)
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__multiplication_8hpp.html b/doc/api/html/rev_2core_2operator__multiplication_8hpp.html new file mode 100644 index 00000000000..b808b584388 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__multiplication_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_multiplication.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
operator_multiplication.hpp File Reference
+
+
+
#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/vv_vari.hpp>
+#include <stan/math/rev/core/vd_vari.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
+

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+Functions

var stan::math::operator* (const var &a, const var &b)
 Multiplication operator for two variables (C++). More...
 
var stan::math::operator* (const var &a, const double b)
 Multiplication operator for a variable and a scalar (C++). More...
 
var stan::math::operator* (const double a, const var &b)
 Multiplication operator for a scalar and a variable (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__multiplication_8hpp_source.html b/doc/api/html/rev_2core_2operator__multiplication_8hpp_source.html new file mode 100644 index 00000000000..cd808d91be6 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__multiplication_8hpp_source.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_multiplication.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
operator_multiplication.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_MULTIPLICATION_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_MULTIPLICATION_HPP
+
3 
+ + + +
7 #include <boost/math/special_functions/fpclassify.hpp>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class multiply_vv_vari : public op_vv_vari {
+
15  public:
+
16  multiply_vv_vari(vari* avi, vari* bvi) :
+
17  op_vv_vari(avi->val_ * bvi->val_, avi, bvi) {
+
18  }
+
19  void chain() {
+
20  if (unlikely(boost::math::isnan(avi_->val_)
+
21  || boost::math::isnan(bvi_->val_))) {
+
22  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
23  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
24  } else {
+
25  avi_->adj_ += bvi_->val_ * adj_;
+
26  bvi_->adj_ += avi_->val_ * adj_;
+
27  }
+
28  }
+
29  };
+
30 
+
31  class multiply_vd_vari : public op_vd_vari {
+
32  public:
+
33  multiply_vd_vari(vari* avi, double b) :
+
34  op_vd_vari(avi->val_ * b, avi, b) {
+
35  }
+
36  void chain() {
+
37  if (unlikely(boost::math::isnan(avi_->val_)
+
38  || boost::math::isnan(bd_)))
+
39  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
40  else
+
41  avi_->adj_ += adj_ * bd_;
+
42  }
+
43  };
+
44  }
+
45 
+
83  inline var operator*(const var& a, const var& b) {
+
84  return var(new multiply_vv_vari(a.vi_, b.vi_));
+
85  }
+
86 
+
98  inline var operator*(const var& a, const double b) {
+
99  if (b == 1.0)
+
100  return a;
+
101  return var(new multiply_vd_vari(a.vi_, b));
+
102  }
+
103 
+
115  inline var operator*(const double a, const var& b) {
+
116  if (a == 1.0)
+
117  return b;
+
118  return var(new multiply_vd_vari(b.vi_, a)); // by symmetry
+
119  }
+
120 
+
121  }
+
122 }
+
123 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
fvar< T > operator*(const fvar< T > &x1, const fvar< T > &x2)
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__not__equal_8hpp.html b/doc/api/html/rev_2core_2operator__not__equal_8hpp.html new file mode 100644 index 00000000000..143ee2163d6 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__not__equal_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_not_equal.hpp File Reference + + + + + + + + + + +
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
operator_not_equal.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

bool stan::math::operator!= (const var &a, const var &b)
 Inequality operator comparing two variables' values (C++). More...
 
bool stan::math::operator!= (const var &a, const double b)
 Inequality operator comparing a variable's value and a double (C++). More...
 
bool stan::math::operator!= (const double a, const var &b)
 Inequality operator comparing a double and a variable's value (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__not__equal_8hpp_source.html b/doc/api/html/rev_2core_2operator__not__equal_8hpp_source.html new file mode 100644 index 00000000000..af1d251a002 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__not__equal_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_not_equal.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+
+
operator_not_equal.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_NOT_EQUAL_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_NOT_EQUAL_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
26  inline bool operator!=(const var& a, const var& b) {
+
27  return a.val() != b.val();
+
28  }
+
29 
+
39  inline bool operator!=(const var& a, const double b) {
+
40  return a.val() != b;
+
41  }
+
42 
+
52  inline bool operator!=(const double a, const var& b) {
+
53  return a != b.val();
+
54  }
+
55 
+
56  }
+
57 }
+
58 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool operator!=(const fvar< T > &x, const fvar< T > &y)
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__subtraction_8hpp.html b/doc/api/html/rev_2core_2operator__subtraction_8hpp.html new file mode 100644 index 00000000000..fb009524cbd --- /dev/null +++ b/doc/api/html/rev_2core_2operator__subtraction_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_subtraction.hpp File Reference + + + + + + + + + + +
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+
operator_subtraction.hpp File Reference
+
+
+
#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/vv_vari.hpp>
+#include <stan/math/rev/core/vd_vari.hpp>
+#include <stan/math/rev/core/dv_vari.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
+

Go to the source code of this file.

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 Matrices and templated mathematical functions.
 
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+Functions

var stan::math::operator- (const var &a, const var &b)
 Subtraction operator for variables (C++). More...
 
var stan::math::operator- (const var &a, const double b)
 Subtraction operator for variable and scalar (C++). More...
 
var stan::math::operator- (const double a, const var &b)
 Subtraction operator for scalar and variable (C++). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2operator__subtraction_8hpp_source.html b/doc/api/html/rev_2core_2operator__subtraction_8hpp_source.html new file mode 100644 index 00000000000..f5bbabad2f7 --- /dev/null +++ b/doc/api/html/rev_2core_2operator__subtraction_8hpp_source.html @@ -0,0 +1,196 @@ + + + + + + +Stan Math Library: stan/math/rev/core/operator_subtraction.hpp Source File + + + + + + + + + + +
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+
Stan Math Library +  2.10.0 +
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+
operator_subtraction.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_OPERATOR_SUBTRACTION_HPP
+
2 #define STAN_MATH_REV_CORE_OPERATOR_SUBTRACTION_HPP
+
3 
+ + + + +
8 #include <boost/math/special_functions/fpclassify.hpp>
+
9 #include <limits>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  namespace {
+
15  class subtract_vv_vari : public op_vv_vari {
+
16  public:
+
17  subtract_vv_vari(vari* avi, vari* bvi) :
+
18  op_vv_vari(avi->val_ - bvi->val_, avi, bvi) {
+
19  }
+
20  void chain() {
+
21  if (unlikely(boost::math::isnan(avi_->val_)
+
22  || boost::math::isnan(bvi_->val_))) {
+
23  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
24  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
25  } else {
+
26  avi_->adj_ += adj_;
+
27  bvi_->adj_ -= adj_;
+
28  }
+
29  }
+
30  };
+
31 
+
32  class subtract_vd_vari : public op_vd_vari {
+
33  public:
+
34  subtract_vd_vari(vari* avi, double b) :
+
35  op_vd_vari(avi->val_ - b, avi, b) {
+
36  }
+
37  void chain() {
+
38  if (unlikely(boost::math::isnan(avi_->val_)
+
39  || boost::math::isnan(bd_)))
+
40  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
41  else
+
42  avi_->adj_ += adj_;
+
43  }
+
44  };
+
45 
+
46  class subtract_dv_vari : public op_dv_vari {
+
47  public:
+
48  subtract_dv_vari(double a, vari* bvi) :
+
49  op_dv_vari(a - bvi->val_, a, bvi) {
+
50  }
+
51  void chain() {
+ +
53  || boost::math::isnan(bvi_->val_)))
+
54  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
55  else
+
56  bvi_->adj_ -= adj_;
+
57  }
+
58  };
+
59  }
+
60 
+
99  inline var operator-(const var& a, const var& b) {
+
100  return var(new subtract_vv_vari(a.vi_, b.vi_));
+
101  }
+
102 
+
114  inline var operator-(const var& a, const double b) {
+
115  if (b == 0.0)
+
116  return a;
+
117  return var(new subtract_vd_vari(a.vi_, b));
+
118  }
+
119 
+
131  inline var operator-(const double a, const var& b) {
+
132  return var(new subtract_dv_vari(a, b.vi_));
+
133  }
+
134 
+
135  }
+
136 }
+
137 #endif
+ +
fvar< T > operator-(const fvar< T > &x1, const fvar< T > &x2)
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2std__numeric__limits_8hpp.html b/doc/api/html/rev_2core_2std__numeric__limits_8hpp.html new file mode 100644 index 00000000000..5b82e7b0b5a --- /dev/null +++ b/doc/api/html/rev_2core_2std__numeric__limits_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/rev/core/std_numeric_limits.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+ + +
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+
+ +
+
std_numeric_limits.hpp File Reference
+
+
+
#include <stan/math/rev/core/var.hpp>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + +

+Classes

struct  std::numeric_limits< stan::math::var >
 Specialization of numeric limits for var objects. More...
 
+ + + +

+Namespaces

 std
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_2std__numeric__limits_8hpp_source.html b/doc/api/html/rev_2core_2std__numeric__limits_8hpp_source.html new file mode 100644 index 00000000000..539c0280d86 --- /dev/null +++ b/doc/api/html/rev_2core_2std__numeric__limits_8hpp_source.html @@ -0,0 +1,186 @@ + + + + + + +Stan Math Library: stan/math/rev/core/std_numeric_limits.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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+ + +
+
+
+
std_numeric_limits.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_STD_NUMERIC_LIMITS_HPP
+
2 #define STAN_MATH_REV_CORE_STD_NUMERIC_LIMITS_HPP
+
3 
+ +
5 #include <limits>
+
6 
+
7 namespace std {
+
8 
+
15  template<>
+
16  struct numeric_limits<stan::math::var> {
+
17  static const bool is_specialized = true;
+ + +
20  static const int digits = numeric_limits<double>::digits;
+
21  static const int digits10 = numeric_limits<double>::digits10;
+
22  static const bool is_signed = numeric_limits<double>::is_signed;
+
23  static const bool is_integer = numeric_limits<double>::is_integer;
+
24  static const bool is_exact = numeric_limits<double>::is_exact;
+
25  static const int radix = numeric_limits<double>::radix;
+ +
27  return numeric_limits<double>::epsilon();
+
28  }
+ +
30  return numeric_limits<double>::round_error();
+
31  }
+
32 
+
33  static const int min_exponent = numeric_limits<double>::min_exponent;
+
34  static const int min_exponent10 = numeric_limits<double>::min_exponent10;
+
35  static const int max_exponent = numeric_limits<double>::max_exponent;
+
36  static const int max_exponent10 = numeric_limits<double>::max_exponent10;
+
37 
+
38  static const bool has_infinity = numeric_limits<double>::has_infinity;
+
39  static const bool has_quiet_NaN = numeric_limits<double>::has_quiet_NaN;
+
40  static const bool has_signaling_NaN
+
41  = numeric_limits<double>::has_signaling_NaN;
+
42  static const float_denorm_style has_denorm
+
43  = numeric_limits<double>::has_denorm;
+
44  static const bool has_denorm_loss = numeric_limits<double>::has_denorm_loss;
+ +
46  return numeric_limits<double>::infinity();
+
47  }
+ +
49  return numeric_limits<double>::quiet_NaN();
+
50  }
+ +
52  return numeric_limits<double>::signaling_NaN();
+
53  }
+ +
55  return numeric_limits<double>::denorm_min();
+
56  }
+
57 
+
58  static const bool is_iec559 = numeric_limits<double>::is_iec559;
+
59  static const bool is_bounded = numeric_limits<double>::is_bounded;
+
60  static const bool is_modulo = numeric_limits<double>::is_modulo;
+
61 
+
62  static const bool traps = numeric_limits<double>::traps;
+
63  static const bool tinyness_before = numeric_limits<double>::tinyness_before;
+
64  static const float_round_style round_style
+
65  = numeric_limits<double>::round_style;
+
66  };
+
67 
+
68 }
+
69 #endif
+ + +
int min(const std::vector< int > &x)
Returns the minimum coefficient in the specified column vector.
Definition: min.hpp:20
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ + + + +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2core_8hpp.html b/doc/api/html/rev_2core_8hpp.html new file mode 100644 index 00000000000..dd5d2d9c554 --- /dev/null +++ b/doc/api/html/rev_2core_8hpp.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan/math/rev/core.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
core.hpp File Reference
+
+
+
#include <stan/math/rev/core/autodiffstackstorage.hpp>
+#include <stan/math/rev/core/chainable_alloc.hpp>
+#include <stan/math/rev/core/chainablestack.hpp>
+#include <stan/math/rev/core/ddv_vari.hpp>
+#include <stan/math/rev/core/dv_vari.hpp>
+#include <stan/math/rev/core/dvd_vari.hpp>
+#include <stan/math/rev/core/dvv_vari.hpp>
+#include <stan/math/rev/core/empty_nested.hpp>
+#include <stan/math/rev/core/gevv_vvv_vari.hpp>
+#include <stan/math/rev/core/grad.hpp>
+#include <stan/math/rev/core/matrix_vari.hpp>
+#include <stan/math/rev/core/nested_size.hpp>
+#include <stan/math/rev/core/operator_addition.hpp>
+#include <stan/math/rev/core/operator_divide_equal.hpp>
+#include <stan/math/rev/core/operator_division.hpp>
+#include <stan/math/rev/core/operator_equal.hpp>
+#include <stan/math/rev/core/operator_greater_than.hpp>
+#include <stan/math/rev/core/operator_greater_than_or_equal.hpp>
+#include <stan/math/rev/core/operator_less_than.hpp>
+#include <stan/math/rev/core/operator_less_than_or_equal.hpp>
+#include <stan/math/rev/core/operator_minus_equal.hpp>
+#include <stan/math/rev/core/operator_multiplication.hpp>
+#include <stan/math/rev/core/operator_multiply_equal.hpp>
+#include <stan/math/rev/core/operator_not_equal.hpp>
+#include <stan/math/rev/core/operator_plus_equal.hpp>
+#include <stan/math/rev/core/operator_subtraction.hpp>
+#include <stan/math/rev/core/operator_unary_decrement.hpp>
+#include <stan/math/rev/core/operator_unary_increment.hpp>
+#include <stan/math/rev/core/operator_unary_negative.hpp>
+#include <stan/math/rev/core/operator_unary_not.hpp>
+#include <stan/math/rev/core/operator_unary_plus.hpp>
+#include <stan/math/rev/core/precomp_v_vari.hpp>
+#include <stan/math/rev/core/precomp_vv_vari.hpp>
+#include <stan/math/rev/core/precomp_vvv_vari.hpp>
+#include <stan/math/rev/core/precomputed_gradients.hpp>
+#include <stan/math/rev/core/print_stack.hpp>
+#include <stan/math/rev/core/recover_memory.hpp>
+#include <stan/math/rev/core/recover_memory_nested.hpp>
+#include <stan/math/rev/core/set_zero_all_adjoints.hpp>
+#include <stan/math/rev/core/set_zero_all_adjoints_nested.hpp>
+#include <stan/math/rev/core/start_nested.hpp>
+#include <stan/math/rev/core/std_isinf.hpp>
+#include <stan/math/rev/core/std_isnan.hpp>
+#include <stan/math/rev/core/std_numeric_limits.hpp>
+#include <stan/math/rev/core/stored_gradient_vari.hpp>
+#include <stan/math/rev/core/v_vari.hpp>
+#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/vari.hpp>
+#include <stan/math/rev/core/vd_vari.hpp>
+#include <stan/math/rev/core/vdd_vari.hpp>
+#include <stan/math/rev/core/vdv_vari.hpp>
+#include <stan/math/rev/core/vector_vari.hpp>
+#include <stan/math/rev/core/vv_vari.hpp>
+#include <stan/math/rev/core/vvd_vari.hpp>
+#include <stan/math/rev/core/vvv_vari.hpp>
+
+

Go to the source code of this file.

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+
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diff --git a/doc/api/html/rev_2core_8hpp_source.html b/doc/api/html/rev_2core_8hpp_source.html new file mode 100644 index 00000000000..b7c6b0a1986 --- /dev/null +++ b/doc/api/html/rev_2core_8hpp_source.html @@ -0,0 +1,224 @@ + + + + + + +Stan Math Library: stan/math/rev/core.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
core.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_HPP
+
2 #define STAN_MATH_REV_CORE_HPP
+
3 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
59 
+
60 #endif
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2_eigen___num_traits_8hpp.html b/doc/api/html/rev_2mat_2fun_2_eigen___num_traits_8hpp.html new file mode 100644 index 00000000000..58ec6e4630e --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2_eigen___num_traits_8hpp.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/Eigen_NumTraits.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen_NumTraits.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + + + + + + + + + + + + + + + +

+Classes

struct  Eigen::NumTraits< stan::math::var >
 Numerical traits template override for Eigen for automatic gradient variables. More...
 
struct  Eigen::internal::significant_decimals_default_impl< stan::math::var, false >
 Implemented this for printing to stream. More...
 
struct  Eigen::internal::scalar_product_traits< stan::math::var, double >
 Scalar product traits override for Eigen for automatic gradient variables. More...
 
struct  Eigen::internal::scalar_product_traits< double, stan::math::var >
 Scalar product traits override for Eigen for automatic gradient variables. More...
 
struct  Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs >
 Override matrix-vector and matrix-matrix products to use more efficient implementation. More...
 
struct  Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs >
 
struct  Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor >
 
+ + + + + + + +

+Namespaces

 Eigen
 (Expert) Numerical traits for algorithmic differentiation variables.
 
 Eigen::internal
 (Expert) Product traits for algorithmic differentiation variables.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2_eigen___num_traits_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2_eigen___num_traits_8hpp_source.html new file mode 100644 index 00000000000..e2f462d91a8 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2_eigen___num_traits_8hpp_source.html @@ -0,0 +1,303 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/Eigen_NumTraits.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
Eigen_NumTraits.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_EIGEN_NUMTRAITS_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_EIGEN_NUMTRAITS_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <limits>
+
8 
+
9 namespace Eigen {
+
10 
+
15  template <>
+
16  struct NumTraits<stan::math::var> {
+ +
23 
+ +
30 
+ +
37 
+
44  inline static Real epsilon() {
+
45  return std::numeric_limits<double>::epsilon();
+
46  }
+
47 
+
51  inline static Real dummy_precision() {
+
52  return 1e-12; // copied from NumTraits.h values for double
+
53  }
+
54 
+
61  inline static Real highest() {
+ +
63  }
+
64 
+
71  inline static Real lowest() {
+ +
73  }
+
74 
+
79  enum {
+
80  IsInteger = 0,
+
81  IsSigned = 1,
+
82  IsComplex = 0,
+
83  RequireInitialization = 0,
+
84  ReadCost = 1,
+
85  AddCost = 1,
+
86  MulCost = 1,
+
87  HasFloatingPoint = 1
+
88  };
+
89  };
+
90 
+
91  namespace internal {
+
95  template<>
+
96  struct significant_decimals_default_impl<stan::math::var, false> {
+
97  static inline int run() {
+
98  using std::ceil;
+
99  using std::log;
+
100  return cast<double, int>(ceil(-log(std::numeric_limits<double>
+
101  ::epsilon())
+
102  / log(10.0)));
+
103  }
+
104  };
+
105 
+
110  template <>
+
111  struct scalar_product_traits<stan::math::var, double> {
+ +
113  };
+
114 
+
119  template <>
+
120  struct scalar_product_traits<double, stan::math::var> {
+ +
122  };
+
123 
+
127  template<typename Index, bool ConjugateLhs, bool ConjugateRhs>
+
128  struct general_matrix_vector_product<Index, stan::math::var, ColMajor,
+
129  ConjugateLhs, stan::math::var,
+
130  ConjugateRhs> {
+ + +
133  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType
+ +
135  enum { LhsStorageOrder = ColMajor };
+
136 
+
137  EIGEN_DONT_INLINE static void run(
+
138  Index rows, Index cols,
+
139  const LhsScalar* lhs, Index lhsStride,
+
140  const RhsScalar* rhs, Index rhsIncr,
+
141  ResScalar* res, Index resIncr,
+
142  const ResScalar &alpha) {
+
143  for (Index i = 0; i < rows; i++) {
+
144  res[i*resIncr]
+
145  += stan::math::var
+ +
147  (&alpha,
+
148  (static_cast<int>(LhsStorageOrder) == static_cast<int>(ColMajor))
+
149  ?(&lhs[i]):(&lhs[i*lhsStride]),
+
150  (static_cast<int>(LhsStorageOrder) == static_cast<int>(ColMajor))
+
151  ?(lhsStride):(1),
+
152  rhs, rhsIncr, cols));
+
153  }
+
154  }
+
155  };
+
156  template<typename Index, bool ConjugateLhs, bool ConjugateRhs>
+
157  struct general_matrix_vector_product<Index, stan::math::var,
+
158  RowMajor, ConjugateLhs,
+
159  stan::math::var, ConjugateRhs> {
+ + +
162  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType
+ +
164  enum { LhsStorageOrder = RowMajor };
+
165 
+
166  EIGEN_DONT_INLINE static void
+
167  run(Index rows, Index cols,
+
168  const LhsScalar* lhs, Index lhsStride,
+
169  const RhsScalar* rhs, Index rhsIncr,
+
170  ResScalar* res, Index resIncr, const RhsScalar &alpha) {
+
171  for (Index i = 0; i < rows; i++) {
+
172  res[i*resIncr]
+
173  += stan::math::var
+ +
175  (&alpha,
+
176  (static_cast<int>(LhsStorageOrder) == static_cast<int>(ColMajor))
+
177  ? (&lhs[i]) : (&lhs[i*lhsStride]),
+
178  (static_cast<int>(LhsStorageOrder) == static_cast<int>(ColMajor))
+
179  ? (lhsStride) : (1),
+
180  rhs, rhsIncr, cols));
+
181  }
+
182  }
+
183  };
+
184  template<typename Index, int LhsStorageOrder, bool ConjugateLhs,
+
185  int RhsStorageOrder, bool ConjugateRhs>
+
186  struct general_matrix_matrix_product<Index, stan::math::var,
+
187  LhsStorageOrder, ConjugateLhs,
+
188  stan::math::var, RhsStorageOrder,
+
189  ConjugateRhs, ColMajor> {
+ + +
192  typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType
+ +
194  static void run(Index rows, Index cols, Index depth,
+
195  const LhsScalar* _lhs, Index lhsStride,
+
196  const RhsScalar* _rhs, Index rhsStride,
+
197  ResScalar* res, Index resStride,
+
198  const ResScalar &alpha,
+
199  level3_blocking<LhsScalar, RhsScalar>& /* blocking */,
+
200  GemmParallelInfo<Index>* /* info = 0 */) {
+
201  for (Index i = 0; i < cols; i++) {
+
202  general_matrix_vector_product<Index, LhsScalar, LhsStorageOrder,
+
203  ConjugateLhs, RhsScalar, ConjugateRhs>
+
204  ::run(rows, depth, _lhs, lhsStride,
+
205  &_rhs[(static_cast<int>(RhsStorageOrder)
+
206  == static_cast<int>(ColMajor))
+
207  ? (i*rhsStride) :(i) ],
+
208  (static_cast<int>(RhsStorageOrder)
+
209  == static_cast<int>(ColMajor)) ? (1) : (rhsStride),
+
210  &res[i*resStride], 1, alpha);
+
211  }
+
212  }
+
213  };
+
214  }
+
215 }
+
216 
+
217 #endif
+
static Real lowest()
Return standard library's lowest for double-precision floating point, -std::numeric_limitsmax...
+
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ +
static EIGEN_DONT_INLINE void run(Index rows, Index cols, const LhsScalar *lhs, Index lhsStride, const RhsScalar *rhs, Index rhsIncr, ResScalar *res, Index resIncr, const ResScalar &alpha)
+ + + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
static Real dummy_precision()
Return dummy precision.
+ +
stan::math::var NonInteger
Non-integer valued variables.
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
static Real highest()
Return standard library's highest for double-precision floating point, std::numeric_limitsmax...
+
(Expert) Numerical traits for algorithmic differentiation variables.
+ + + + + +
stan::math::var Real
Real-valued variables.
+
static Real epsilon()
Return standard library's epsilon for double-precision floating point, std::numeric_limits::e...
+
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+ +
stan::math::var Nested
Nested variables.
+ +
static void run(Index rows, Index cols, Index depth, const LhsScalar *_lhs, Index lhsStride, const RhsScalar *_rhs, Index rhsStride, ResScalar *res, Index resStride, const ResScalar &alpha, level3_blocking< LhsScalar, RhsScalar > &, GemmParallelInfo< Index > *)
+
static EIGEN_DONT_INLINE void run(Index rows, Index cols, const LhsScalar *lhs, Index lhsStride, const RhsScalar *rhs, Index rhsIncr, ResScalar *res, Index resIncr, const RhsScalar &alpha)
+ + +
fvar< T > ceil(const fvar< T > &x)
Definition: ceil.hpp:11
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2_l_d_l_t__factor_8hpp.html b/doc/api/html/rev_2mat_2fun_2_l_d_l_t__factor_8hpp.html new file mode 100644 index 00000000000..33c47e3bf40 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2_l_d_l_t__factor_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/LDLT_factor.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
LDLT_factor.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + +

+Classes

class  stan::math::LDLT_factor< stan::math::var, R, C >
 A template specialization of src/stan/math/matrix/LDLT_factor.hpp for stan::math::var which can be used with all the *_ldlt functions. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2_l_d_l_t__factor_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2_l_d_l_t__factor_8hpp_source.html new file mode 100644 index 00000000000..0038f3789e4 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2_l_d_l_t__factor_8hpp_source.html @@ -0,0 +1,187 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/LDLT_factor.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
LDLT_factor.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_LDLT_FACTOR_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_LDLT_FACTOR_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
44  template<int R, int C>
+
45  class LDLT_factor<stan::math::var, R, C> {
+
46  public:
+
52  LDLT_factor() : _alloc(new stan::math::LDLT_alloc<R, C>()) {}
+
53 
+
54  explicit LDLT_factor(const Eigen::Matrix<stan::math::var, R, C> &A)
+
55  : _alloc(new stan::math::LDLT_alloc<R, C>()) {
+
56  compute(A);
+
57  }
+
58 
+
67  inline void compute(const Eigen::Matrix<stan::math::var, R, C> &A) {
+
68  stan::math::check_square("comute", "A", A);
+
69  _alloc->compute(A);
+
70  }
+
71 
+
83  template<typename Rhs>
+
84  inline const
+
85  Eigen::internal::solve_retval<Eigen::LDLT<Eigen::Matrix<double, R, C> >,
+
86  Rhs>
+
87  solve(const Eigen::MatrixBase<Rhs>& b) const {
+
88  return _alloc->_ldlt.solve(b);
+
89  }
+
90 
+
96  inline bool success() const {
+
97  bool ret;
+
98  ret = _alloc->N_ != 0;
+
99  ret = ret && _alloc->_ldlt.info() == Eigen::Success;
+
100  ret = ret && _alloc->_ldlt.isPositive();
+
101  ret = ret && (_alloc->_ldlt.vectorD().array() > 0).all();
+
102  return ret;
+
103  }
+
104 
+
112  inline Eigen::VectorXd vectorD() const {
+
113  return _alloc->_ldlt.vectorD();
+
114  }
+
115 
+
116  inline size_t rows() const { return _alloc->N_; }
+
117  inline size_t cols() const { return _alloc->N_; }
+
118 
+
119  typedef size_t size_type;
+ +
121 
+ +
131  };
+
132  }
+
133 }
+
134 #endif
+
LDLT_factor(const Eigen::Matrix< stan::math::var, R, C > &A)
Definition: LDLT_factor.hpp:54
+ + + + +
void compute(const Eigen::Matrix< stan::math::var, R, C > &A)
Use the LDLT_factor object to factorize a new matrix.
Definition: LDLT_factor.hpp:67
+ +
stan::math::LDLT_alloc< R, C > * _alloc
The LDLT_alloc object actually contains the factorization but is derived from the chainable_alloc cla...
+
This object stores the actual (double typed) LDLT factorization of an Eigen::Matrix along with p...
Definition: LDLT_alloc.hpp:20
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
mdivide_left_ldlt_alloc< R1, C1, R2, C2 > * _alloc
+ + + + +
Eigen::VectorXd vectorD() const
The entries of the diagonal matrix D.
+ +
const Eigen::internal::solve_retval< Eigen::LDLT< Eigen::Matrix< double, R, C > >, Rhs > solve(const Eigen::MatrixBase< Rhs > &b) const
Compute the actual numerical result of inv(A)*b.
Definition: LDLT_factor.hpp:87
+
bool success() const
Determine whether the most recent factorization succeeded.
Definition: LDLT_factor.hpp:96
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
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diff --git a/doc/api/html/rev_2mat_2fun_2cholesky__decompose_8hpp.html b/doc/api/html/rev_2mat_2fun_2cholesky__decompose_8hpp.html new file mode 100644 index 00000000000..56bb3f5ff3b --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2cholesky__decompose_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/cholesky_decompose.hpp File Reference + + + + + + + + + + +
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cholesky_decompose.hpp File Reference
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class  stan::math::cholesky_decompose_v_vari
 
+ + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + +

+Functions

Eigen::Matrix< var,-1,-1 > stan::math::cholesky_decompose (const Eigen::Matrix< var,-1,-1 > &A)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2cholesky__decompose_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2cholesky__decompose_8hpp_source.html new file mode 100644 index 00000000000..86a51304530 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2cholesky__decompose_8hpp_source.html @@ -0,0 +1,305 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/cholesky_decompose.hpp Source File + + + + + + + + + + +
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cholesky_decompose.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_CHOLESKY_DECOMPOSE_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_CHOLESKY_DECOMPOSE_HPP
+
3 
+ + + + + +
9 #include <stan/math/rev/core.hpp>
+ + + + +
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+ +
19  public:
+
20  int M_; // A.rows() = A.cols()
+ + +
23 
+
24  /* ctor for cholesky function
+
25  *
+
26  * Stores varis for A
+
27  * Instantiates and stores varis for L
+
28  * Instantiates and stores dummy vari for
+
29  * upper triangular part of var result returned
+
30  * in cholesky_decompose function call
+
31  *
+
32  * variRefL aren't on the chainable
+
33  * autodiff stack, only used for storage
+
34  * and computation. Note that varis for
+
35  * L are constructed externally in
+
36  * cholesky_decompose.
+
37  *
+
38  * @param matrix A
+
39  * @param matrix L, cholesky factor of A
+
40  * */
+
41  cholesky_decompose_v_vari(const Eigen::Matrix<var, -1, -1>& A,
+
42  const Eigen::Matrix<double, -1, -1>& L_A)
+
43  : vari(0.0),
+
44  M_(A.rows()),
+
45  variRefA_(ChainableStack::memalloc_.alloc_array<vari*>
+
46  (A.rows() * (A.rows() + 1) / 2)),
+
47  variRefL_(ChainableStack::memalloc_.alloc_array<vari*>
+
48  (A.rows() * (A.rows() + 1) / 2)) {
+
49  size_t accum = 0;
+
50  size_t accum_i = accum;
+
51  for (size_type j = 0; j < M_; ++j) {
+
52  for (size_type i = j; i < M_; ++i) {
+
53  accum_i += i;
+
54  size_t pos = j + accum_i;
+
55  variRefA_[pos] = A.coeffRef(i, j).vi_;
+
56  variRefL_[pos] = new vari(L_A.coeffRef(i, j), false);
+
57  }
+
58  accum += j;
+
59  accum_i = accum;
+
60  }
+
61  }
+
62 
+
63  /* Reverse mode differentiation
+
64  * algorithm refernce:
+
65  *
+
66  * Mike Giles. An extended collection of matrix
+
67  * derivative results for forward and reverse mode AD.
+
68  * Jan. 2008.
+
69  *
+
70  * Note algorithm as laid out in Giles is
+
71  * row-major, so Eigen::Matrices are explicitly storage
+
72  * order RowMajor, whereas Eigen defaults to
+
73  * ColumnMajor. Also note algorithm
+
74  * starts by calculating the adjoint for
+
75  * A(M_ - 1, M_ - 1), hence pos on line 94 is decremented
+
76  * to start at pos = M_ * (M_ + 1) / 2.
+
77  * */
+
78  virtual void chain() {
+
79  using Eigen::Matrix;
+
80  using Eigen::RowMajor;
+
81  Matrix<double, -1, -1, RowMajor> adjL(M_, M_);
+
82  Matrix<double, -1, -1, RowMajor> LA(M_, M_);
+
83  Matrix<double, -1, -1, RowMajor> adjA(M_, M_);
+
84  size_t pos = 0;
+
85  for (size_type i = 0; i < M_; ++i) {
+
86  for (size_type j = 0; j <= i; ++j) {
+
87  adjL.coeffRef(i, j) = variRefL_[pos]->adj_;
+
88  LA.coeffRef(i, j) = variRefL_[pos]->val_;
+
89  ++pos;
+
90  }
+
91  }
+
92 
+
93  --pos;
+
94  for (int i = M_ - 1; i >= 0; --i) {
+
95  for (int j = i; j >= 0; --j) {
+
96  if (i == j) {
+
97  adjA.coeffRef(i, j) = 0.5 * adjL.coeff(i, j)
+
98  / LA.coeff(i, j);
+
99  } else {
+
100  adjA.coeffRef(i, j) = adjL.coeff(i, j)
+
101  / LA.coeff(j, j);
+
102  adjL.coeffRef(j, j) -= adjL.coeff(i, j)
+
103  * LA.coeff(i, j) / LA.coeff(j, j);
+
104  }
+
105  for (int k = j - 1; k >=0; --k) {
+
106  adjL.coeffRef(i, k) -= adjA.coeff(i, j)
+
107  * LA.coeff(j, k);
+
108  adjL.coeffRef(j, k) -= adjA.coeff(i, j)
+
109  * LA.coeff(i, k);
+
110  }
+
111  variRefA_[pos--]->adj_ += adjA.coeffRef(i, j);
+
112  }
+
113  }
+
114  }
+
115  };
+
116 
+
117  /* Reverse mode specialization of
+
118  * cholesky decomposition
+
119  *
+
120  * Internally calls llt rather than using
+
121  * stan::math::cholesky_decompose in order
+
122  * to use selfadjointView<Lower> optimization.
+
123  *
+
124  * Note chainable stack varis are created
+
125  * below in Matrix<var, -1, -1>
+
126  *
+
127  * @param Matrix A
+
128  * @return L cholesky factor of A
+
129  */
+
130  Eigen::Matrix<var, -1, -1>
+
131  cholesky_decompose(const Eigen::Matrix<var, -1, -1> &A) {
+
132  stan::math::check_square("cholesky_decompose", "A", A);
+
133  stan::math::check_symmetric("cholesky_decompose", "A", A);
+
134 
+
135  Eigen::Matrix<double, -1, -1> L_A(value_of_rec(A));
+
136  Eigen::LLT<Eigen::MatrixXd> L_factor
+
137  = L_A.selfadjointView<Eigen::Lower>().llt();
+
138  check_pos_definite("cholesky_decompose", "m", L_factor);
+
139  L_A = L_factor.matrixL();
+
140 
+
141  // NOTE: this is not a memory leak, this vari is used in the
+
142  // expression graph to evaluate the adjoint, but is not needed
+
143  // for the returned matrix. Memory will be cleaned up with the
+
144  // arena allocator.
+
145  cholesky_decompose_v_vari *baseVari
+
146  = new cholesky_decompose_v_vari(A, L_A);
+
147  stan::math::vari dummy(0.0, false);
+
148  Eigen::Matrix<var, -1, -1> L(A.rows(), A.cols());
+
149  size_t accum = 0;
+
150  size_t accum_i = accum;
+
151  for (size_type j = 0; j < L.cols(); ++j) {
+
152  for (size_type i = j; i < L.cols(); ++i) {
+
153  accum_i += i;
+
154  size_t pos = j + accum_i;
+
155  L.coeffRef(i, j).vi_ = baseVari->variRefL_[pos];
+
156  }
+
157  for (size_type k = 0; k < j; ++k)
+
158  L.coeffRef(k, j).vi_ = &dummy;
+
159  accum += j;
+
160  accum_i = accum;
+
161  }
+
162  return L;
+
163  }
+
164  }
+
165 }
+
166 #endif
+
vari(const double x)
Construct a variable implementation from a value.
Definition: vari.hpp:58
+ +
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ + +
virtual void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
+
cholesky_decompose_v_vari(const Eigen::Matrix< var,-1,-1 > &A, const Eigen::Matrix< double,-1,-1 > &L_A)
+ + +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+
The variable implementation base class.
Definition: vari.hpp:30
+ +
const double val_
The value of this variable.
Definition: vari.hpp:38
+
Empty struct for use in boost::condtional::value, T1, dummy>::type as false co...
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ + +
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > cholesky_decompose(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Return the lower-triangular Cholesky factor (i.e., matrix square root) of the specified square...
+
bool check_pos_definite(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified square, symmetric matrix is positive definite.
+ + + +
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + + + +
+
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diff --git a/doc/api/html/rev_2mat_2fun_2columns__dot__product_8hpp.html b/doc/api/html/rev_2mat_2fun_2columns__dot__product_8hpp.html new file mode 100644 index 00000000000..f3045ce4084 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2columns__dot__product_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/columns_dot_product.hpp File Reference + + + + + + + + + + +
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columns_dot_product.hpp File Reference
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template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, Eigen::Matrix< var, 1, C1 > >::type stan::math::columns_dot_product (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 
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diff --git a/doc/api/html/rev_2mat_2fun_2columns__dot__product_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2columns__dot__product_8hpp_source.html new file mode 100644 index 00000000000..05eeb68ca7e --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2columns__dot__product_8hpp_source.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/columns_dot_product.hpp Source File + + + + + + + + + + +
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columns_dot_product.hpp
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1 #ifndef STAN_MATH_REV_MAT_FUN_COLUMNS_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_COLUMNS_DOT_PRODUCT_HPP
+
3 
+ + + + + +
9 #include <stan/math/rev/core.hpp>
+ + + +
13 #include <boost/utility/enable_if.hpp>
+
14 #include <boost/type_traits.hpp>
+
15 #include <vector>
+
16 
+
17 namespace stan {
+
18  namespace math {
+
19 
+
20  template<typename T1, int R1, int C1, typename T2, int R2, int C2>
+
21  inline
+
22  typename boost::enable_if_c<boost::is_same<T1, var>::value ||
+
23  boost::is_same<T2, var>::value,
+
24  Eigen::Matrix<var, 1, C1> >::type
+
25  columns_dot_product(const Eigen::Matrix<T1, R1, C1>& v1,
+
26  const Eigen::Matrix<T2, R2, C2>& v2) {
+ +
28  "v1", v1,
+
29  "v2", v2);
+
30  Eigen::Matrix<var, 1, C1> ret(1, v1.cols());
+
31  for (size_type j = 0; j < v1.cols(); ++j) {
+
32  ret(j) = var(new dot_product_vari<T1, T2>(v1.col(j), v2.col(j)));
+
33  }
+
34  return ret;
+
35  }
+
36 
+
37  }
+
38 }
+
39 #endif
+
Eigen::Matrix< fvar< T >, 1, C1 > columns_dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ +
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ + + + + + +
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diff --git a/doc/api/html/rev_2mat_2fun_2columns__dot__self_8hpp.html b/doc/api/html/rev_2mat_2fun_2columns__dot__self_8hpp.html new file mode 100644 index 00000000000..9caed2e1ca1 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2columns__dot__self_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/columns_dot_self.hpp File Reference + + + + + + + + + + +
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template<int R, int C>
Eigen::Matrix< var, 1, C > stan::math::columns_dot_self (const Eigen::Matrix< var, R, C > &x)
 Returns the dot product of each column of a matrix with itself. More...
 
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diff --git a/doc/api/html/rev_2mat_2fun_2columns__dot__self_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2columns__dot__self_8hpp_source.html new file mode 100644 index 00000000000..27c07eaa34a --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2columns__dot__self_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/columns_dot_self.hpp Source File + + + + + + + + + + +
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columns_dot_self.hpp
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1 #ifndef STAN_MATH_REV_MAT_FUN_COLUMNS_DOT_SELF_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_COLUMNS_DOT_SELF_HPP
+
3 
+ + + +
7 #include <stan/math/rev/core.hpp>
+ + +
10 #include <vector>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
20  template<int R, int C>
+
21  inline Eigen::Matrix<var, 1, C>
+
22  columns_dot_self(const Eigen::Matrix<var, R, C>& x) {
+
23  Eigen::Matrix<var, 1, C> ret(1, x.cols());
+
24  for (size_type i = 0; i < x.cols(); i++) {
+
25  ret(i) = var(new dot_self_vari(x.col(i)));
+
26  }
+
27  return ret;
+
28  }
+
29 
+
30 
+
31  }
+
32 }
+
33 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ + + + +
Eigen::Matrix< fvar< T >, 1, C > columns_dot_self(const Eigen::Matrix< fvar< T >, R, C > &x)
+ +
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+
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diff --git a/doc/api/html/rev_2mat_2fun_2crossprod_8hpp.html b/doc/api/html/rev_2mat_2fun_2crossprod_8hpp.html new file mode 100644 index 00000000000..9bac455ae51 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2crossprod_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/crossprod.hpp File Reference + + + + + + + + + + +
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matrix_v stan::math::crossprod (const matrix_v &M)
 Returns the result of pre-multiplying a matrix by its own transpose. More...
 
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2crossprod_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2crossprod_8hpp_source.html new file mode 100644 index 00000000000..638a65d12c8 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2crossprod_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/crossprod.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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crossprod.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_CROSSPROD_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_CROSSPROD_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
16  inline matrix_v
+
17  crossprod(const matrix_v& M) {
+
18  return tcrossprod(static_cast<matrix_v>(M.transpose()));
+
19  }
+
20 
+
21  }
+
22 }
+
23 #endif
+ +
Eigen::Matrix< fvar< T >, R, R > tcrossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: tcrossprod.hpp:17
+
Eigen::Matrix< var, Eigen::Dynamic, Eigen::Dynamic > matrix_v
The type of a matrix holding stan::math::var values.
Definition: typedefs.hpp:21
+ + +
Eigen::Matrix< fvar< T >, C, C > crossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: crossprod.hpp:17
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2determinant_8hpp.html b/doc/api/html/rev_2mat_2fun_2determinant_8hpp.html new file mode 100644 index 00000000000..291251bb0e7 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2determinant_8hpp.html @@ -0,0 +1,192 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/determinant.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
determinant.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<int R, int C>
var stan::math::determinant (const Eigen::Matrix< var, R, C > &m)
 
+

Variable Documentation

+ +
+
+ + + + +
vari** _adjARef
+
+ +

Definition at line 20 of file determinant.hpp.

+ +
+
+ +
+
+ + + + +
int _cols
+
+ +

Definition at line 18 of file determinant.hpp.

+ +
+
+ +
+
+ + + + +
int _rows
+
+ +

Definition at line 17 of file determinant.hpp.

+ +
+
+ +
+
+ + + + +
double* A_
+
+ +

Definition at line 19 of file determinant.hpp.

+ +
+
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+
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2determinant_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2determinant_8hpp_source.html new file mode 100644 index 00000000000..cbb2340d0a8 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2determinant_8hpp_source.html @@ -0,0 +1,199 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/determinant.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
determinant.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_DETERMINANT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_DETERMINANT_HPP
+
3 
+ + + +
7 #include <stan/math/rev/core.hpp>
+ +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  namespace {
+
15  template<int R, int C>
+
16  class determinant_vari : public vari {
+
17  int _rows;
+
18  int _cols;
+
19  double* A_;
+
20  vari** _adjARef;
+
21 
+
22  public:
+
23  explicit determinant_vari(const Eigen::Matrix<var, R, C> &A)
+
24  : vari(determinant_vari_calc(A)),
+
25  _rows(A.rows()),
+
26  _cols(A.cols()),
+
27  A_(reinterpret_cast<double*>
+
28  (stan::math::ChainableStack::memalloc_
+
29  .alloc(sizeof(double) * A.rows() * A.cols()))),
+
30  _adjARef(reinterpret_cast<vari**>
+
31  (stan::math::ChainableStack::memalloc_
+
32  .alloc(sizeof(vari*) * A.rows() * A.cols()))) {
+
33  size_t pos = 0;
+
34  for (size_type j = 0; j < _cols; j++) {
+
35  for (size_type i = 0; i < _rows; i++) {
+
36  A_[pos] = A(i, j).val();
+
37  _adjARef[pos++] = A(i, j).vi_;
+
38  }
+
39  }
+
40  }
+
41  static
+
42  double determinant_vari_calc(const Eigen::Matrix<var, R, C> &A) {
+
43  Eigen::Matrix<double, R, C> Ad(A.rows(), A.cols());
+
44  for (size_type j = 0; j < A.rows(); j++)
+
45  for (size_type i = 0; i < A.cols(); i++)
+
46  Ad(i, j) = A(i, j).val();
+
47  return Ad.determinant();
+
48  }
+
49  virtual void chain() {
+
50  using Eigen::Matrix;
+
51  using Eigen::Map;
+
52  Matrix<double, R, C> adjA(_rows, _cols);
+
53  adjA = (adj_ * val_) *
+
54  Map<Matrix<double, R, C> >(A_, _rows, _cols).inverse().transpose();
+
55  size_t pos = 0;
+
56  for (size_type j = 0; j < _cols; j++) {
+
57  for (size_type i = 0; i < _rows; i++) {
+
58  _adjARef[pos++]->adj_ += adjA(i, j);
+
59  }
+
60  }
+
61  }
+
62  };
+
63  }
+
64 
+
65  template <int R, int C>
+
66  inline var determinant(const Eigen::Matrix<var, R, C>& m) {
+
67  stan::math::check_square("determinant", "m", m);
+
68  return var(new determinant_vari<R, C>(m));
+
69  }
+
70 
+
71  }
+
72 }
+
73 #endif
+
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
double * A_
Definition: determinant.hpp:19
+ +
fvar< T > determinant(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: determinant.hpp:21
+
vari ** _adjARef
Definition: determinant.hpp:20
+
int _rows
Definition: determinant.hpp:17
+
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
AutodiffStackStorage< vari, chainable_alloc > ChainableStack
+
int _cols
Definition: determinant.hpp:18
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2divide_8hpp.html b/doc/api/html/rev_2mat_2fun_2divide_8hpp.html new file mode 100644 index 00000000000..191aeedfb57 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2divide_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/divide.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
divide.hpp File Reference
+
+
+ +

Go to the source code of this file.

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+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< var, R, C > stan::math::divide (const Eigen::Matrix< T1, R, C > &v, const T2 &c)
 Return the division of the specified column vector by the specified scalar. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2divide_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2divide_8hpp_source.html new file mode 100644 index 00000000000..051dfae32e4 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2divide_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/divide.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
divide.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_DIVIDE_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_DIVIDE_HPP
+
3 
+ + +
6 #include <stan/math/rev/core.hpp>
+ + +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
21  template <typename T1, typename T2, int R, int C>
+
22  inline Eigen::Matrix<var, R, C>
+
23  divide(const Eigen::Matrix<T1, R, C>& v, const T2& c) {
+
24  return to_var(v) / to_var(c);
+
25  }
+
26 
+
27  }
+
28 }
+
29 #endif
+ + + + +
Eigen::Matrix< fvar< T >, R, C > divide(const Eigen::Matrix< fvar< T >, R, C > &v, const fvar< T > &c)
Definition: divide.hpp:16
+ +
std::vector< var > to_var(const std::vector< double > &v)
Converts argument to an automatic differentiation variable.
Definition: to_var.hpp:20
+ +
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2dot__product_8hpp.html b/doc/api/html/rev_2mat_2fun_2dot__product_8hpp.html new file mode 100644 index 00000000000..c1d40d54dec --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2dot__product_8hpp.html @@ -0,0 +1,192 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/dot_product.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
dot_product.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/typedefs.hpp>
+#include <stan/math/prim/mat/err/check_vector.hpp>
+#include <stan/math/prim/mat/err/check_matching_sizes.hpp>
+#include <stan/math/prim/scal/fun/value_of.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/mat/fun/typedefs.hpp>
+#include <stan/math/rev/scal/fun/value_of.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + +

+Functions

template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, var >::type stan::math::dot_product (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 Returns the dot product. More...
 
template<typename T1 , typename T2 >
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, var >::type stan::math::dot_product (const T1 *v1, const T2 *v2, size_t length)
 Returns the dot product. More...
 
template<typename T1 , typename T2 >
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, var >::type stan::math::dot_product (const std::vector< T1 > &v1, const std::vector< T2 > &v2)
 Returns the dot product. More...
 
+

Variable Documentation

+ +
+
+ + + + +
size_t length_
+
+ +

Definition at line 38 of file dot_product.hpp.

+ +
+
+ +
+
+ + + + +
dot_product_store_type<T1>::type v1_
+
+ +

Definition at line 36 of file dot_product.hpp.

+ +
+
+ +
+
+ + + + +
dot_product_store_type<T2>::type v2_
+
+ +

Definition at line 37 of file dot_product.hpp.

+ +
+
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+
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diff --git a/doc/api/html/rev_2mat_2fun_2dot__product_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2dot__product_8hpp_source.html new file mode 100644 index 00000000000..e129d5e48c1 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2dot__product_8hpp_source.html @@ -0,0 +1,367 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/dot_product.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
dot_product.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_DOT_PRODUCT_HPP
+
3 
+ + + + + +
9 #include <stan/math/rev/core.hpp>
+ + +
12 #include <boost/utility/enable_if.hpp>
+
13 #include <boost/type_traits.hpp>
+
14 #include <vector>
+
15 
+
16 namespace stan {
+
17  namespace math {
+
18 
+
19  namespace {
+
20  template<typename T>
+
21  struct dot_product_store_type;
+
22 
+
23  template<>
+
24  struct dot_product_store_type<var> {
+
25  typedef vari** type;
+
26  };
+
27 
+
28  template<>
+
29  struct dot_product_store_type<double> {
+
30  typedef double* type;
+
31  };
+
32 
+
33  template<typename T1, typename T2>
+
34  class dot_product_vari : public vari {
+
35  protected:
+
36  typename dot_product_store_type<T1>::type v1_;
+
37  typename dot_product_store_type<T2>::type v2_;
+
38  size_t length_;
+
39 
+
40  inline static double var_dot(vari** v1, vari** v2,
+
41  size_t length) {
+
42  Eigen::VectorXd vd1(length), vd2(length);
+
43  for (size_t i = 0; i < length; i++) {
+
44  vd1[i] = v1[i]->val_;
+
45  vd2[i] = v2[i]->val_;
+
46  }
+
47  return vd1.dot(vd2);
+
48  }
+
49 
+
50  inline static double var_dot(const T1* v1, const T2* v2,
+
51  size_t length) {
+ +
53  Eigen::VectorXd vd1(length), vd2(length);
+
54  for (size_t i = 0; i < length; i++) {
+
55  vd1[i] = value_of(v1[i]);
+
56  vd2[i] = value_of(v2[i]);
+
57  }
+
58  return vd1.dot(vd2);
+
59  }
+
60 
+
61  template<typename Derived1, typename Derived2>
+
62  inline static double var_dot(const Eigen::DenseBase<Derived1> &v1,
+
63  const Eigen::DenseBase<Derived2> &v2) {
+ + +
66  Eigen::VectorXd vd1(v1.size()), vd2(v1.size());
+
67  for (int i = 0; i < v1.size(); i++) {
+
68  vd1[i] = value_of(v1[i]);
+
69  vd2[i] = value_of(v2[i]);
+
70  }
+
71  return vd1.dot(vd2);
+
72  }
+
73  inline void chain(vari** v1, vari** v2) {
+
74  for (size_t i = 0; i < length_; i++) {
+
75  v1[i]->adj_ += adj_ * v2_[i]->val_;
+
76  v2[i]->adj_ += adj_ * v1_[i]->val_;
+
77  }
+
78  }
+
79  inline void chain(double* v1, vari** v2) {
+
80  for (size_t i = 0; i < length_; i++) {
+
81  v2[i]->adj_ += adj_ * v1_[i];
+
82  }
+
83  }
+
84  inline void chain(vari** v1, double* v2) {
+
85  for (size_t i = 0; i < length_; i++) {
+
86  v1[i]->adj_ += adj_ * v2_[i];
+
87  }
+
88  }
+
89  inline void initialize(vari** &mem_v, const var *inv,
+
90  vari **shared = NULL) {
+
91  if (shared == NULL) {
+
92  mem_v = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
93  .alloc(length_*sizeof(vari*)));
+
94  for (size_t i = 0; i < length_; i++)
+
95  mem_v[i] = inv[i].vi_;
+
96  } else {
+
97  mem_v = shared;
+
98  }
+
99  }
+
100  template<typename Derived>
+
101  inline void initialize(vari** &mem_v,
+
102  const Eigen::DenseBase<Derived> &inv,
+
103  vari **shared = NULL) {
+
104  if (shared == NULL) {
+
105  mem_v = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
106  .alloc(length_*sizeof(vari*)));
+
107  for (size_t i = 0; i < length_; i++)
+
108  mem_v[i] = inv(i).vi_;
+
109  } else {
+
110  mem_v = shared;
+
111  }
+
112  }
+
113 
+
114  inline void initialize(double* &mem_d, const double *ind,
+
115  double *shared = NULL) {
+
116  if (shared == NULL) {
+
117  mem_d = reinterpret_cast<double*>(ChainableStack::memalloc_
+
118  .alloc(length_*sizeof(double)));
+
119  for (size_t i = 0; i < length_; i++)
+
120  mem_d[i] = ind[i];
+
121  } else {
+
122  mem_d = shared;
+
123  }
+
124  }
+
125  template<typename Derived>
+
126  inline void initialize(double* &mem_d,
+
127  const Eigen::DenseBase<Derived> &ind,
+
128  double *shared = NULL) {
+
129  if (shared == NULL) {
+
130  mem_d = reinterpret_cast<double*>
+
131  (ChainableStack::memalloc_.alloc(length_*sizeof(double)));
+
132  for (size_t i = 0; i < length_; i++)
+
133  mem_d[i] = ind(i);
+
134  } else {
+
135  mem_d = shared;
+
136  }
+
137  }
+
138 
+
139  public:
+
140  dot_product_vari(typename dot_product_store_type<T1>::type v1,
+
141  typename dot_product_store_type<T2>::type v2,
+
142  size_t length)
+
143  : vari(var_dot(v1, v2, length)), v1_(v1), v2_(v2), length_(length) {}
+
144 
+
145  dot_product_vari(const T1* v1, const T2* v2, size_t length,
+
146  dot_product_vari<T1, T2>* shared_v1 = NULL,
+
147  dot_product_vari<T1, T2>* shared_v2 = NULL) :
+
148  vari(var_dot(v1, v2, length)), length_(length) {
+
149  if (shared_v1 == NULL) {
+
150  initialize(v1_, v1);
+
151  } else {
+
152  initialize(v1_, v1, shared_v1->v1_);
+
153  }
+
154  if (shared_v2 == NULL) {
+
155  initialize(v2_, v2);
+
156  } else {
+
157  initialize(v2_, v2, shared_v2->v2_);
+
158  }
+
159  }
+
160  template<typename Derived1, typename Derived2>
+
161  dot_product_vari(const Eigen::DenseBase<Derived1> &v1,
+
162  const Eigen::DenseBase<Derived2> &v2,
+
163  dot_product_vari<T1, T2>* shared_v1 = NULL,
+
164  dot_product_vari<T1, T2>* shared_v2 = NULL) :
+
165  vari(var_dot(v1, v2)), length_(v1.size()) {
+
166  if (shared_v1 == NULL) {
+
167  initialize(v1_, v1);
+
168  } else {
+
169  initialize(v1_, v1, shared_v1->v1_);
+
170  }
+
171  if (shared_v2 == NULL) {
+
172  initialize(v2_, v2);
+
173  } else {
+
174  initialize(v2_, v2, shared_v2->v2_);
+
175  }
+
176  }
+
177  template<int R1, int C1, int R2, int C2>
+
178  dot_product_vari(const Eigen::Matrix<T1, R1, C1> &v1,
+
179  const Eigen::Matrix<T2, R2, C2> &v2,
+
180  dot_product_vari<T1, T2>* shared_v1 = NULL,
+
181  dot_product_vari<T1, T2>* shared_v2 = NULL) :
+
182  vari(var_dot(v1, v2)), length_(v1.size()) {
+
183  if (shared_v1 == NULL) {
+
184  initialize(v1_, v1);
+
185  } else {
+
186  initialize(v1_, v1, shared_v1->v1_);
+
187  }
+
188  if (shared_v2 == NULL) {
+
189  initialize(v2_, v2);
+
190  } else {
+
191  initialize(v2_, v2, shared_v2->v2_);
+
192  }
+
193  }
+
194  virtual void chain() {
+
195  chain(v1_, v2_);
+
196  }
+
197  };
+
198  }
+
199 
+
208  template<typename T1, int R1, int C1, typename T2, int R2, int C2>
+
209  inline
+
210  typename boost::enable_if_c<boost::is_same<T1, var>::value ||
+
211  boost::is_same<T2, var>::value, var>::type
+
212  dot_product(const Eigen::Matrix<T1, R1, C1>& v1,
+
213  const Eigen::Matrix<T2, R2, C2>& v2) {
+
214  stan::math::check_vector("dot_product", "v1", v1);
+
215  stan::math::check_vector("dot_product", "v2", v2);
+
216  stan::math::check_matching_sizes("dot_product",
+
217  "v1", v1,
+
218  "v2", v2);
+
219  return var(new dot_product_vari<T1, T2>(v1, v2));
+
220  }
+
229  template<typename T1, typename T2>
+
230  inline
+
231  typename boost::enable_if_c<boost::is_same<T1, var>::value ||
+
232  boost::is_same<T2, var>::value, var>::type
+
233  dot_product(const T1* v1, const T2* v2, size_t length) {
+
234  return var(new dot_product_vari<T1, T2>(v1, v2, length));
+
235  }
+
236 
+
245  template<typename T1, typename T2>
+
246  inline
+
247  typename boost::enable_if_c<boost::is_same<T1, var>::value ||
+
248  boost::is_same<T2, var>::value, var>::type
+
249  dot_product(const std::vector<T1>& v1,
+
250  const std::vector<T2>& v2) {
+
251  stan::math::check_matching_sizes("dot_product",
+
252  "v1", v1,
+
253  "v2", v2);
+
254  return var(new dot_product_vari<T1, T2>(&v1[0], &v2[0], v1.size()));
+
255  }
+
256 
+
257  }
+
258 }
+
259 #endif
+ +
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
dot_product_store_type< T1 >::type v1_
Definition: dot_product.hpp:36
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
dot_product_store_type< T2 >::type v2_
Definition: dot_product.hpp:37
+
void initialize(T &x, const T &v)
Definition: initialize.hpp:17
+ +
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
size_t length_
Definition: dot_product.hpp:38
+ + +
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+
fvar< T > inv(const fvar< T > &x)
Definition: inv.hpp:15
+ +
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2dot__self_8hpp.html b/doc/api/html/rev_2mat_2fun_2dot__self_8hpp.html new file mode 100644 index 00000000000..6286bfea298 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2dot__self_8hpp.html @@ -0,0 +1,165 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/dot_self.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
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+ +
+
dot_self.hpp File Reference
+
+
+ +

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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<int R, int C>
var stan::math::dot_self (const Eigen::Matrix< var, R, C > &v)
 Returns the dot product of a vector with itself. More...
 
+

Variable Documentation

+ +
+
+ + + + +
size_t size_
+
+ +

Definition at line 18 of file dot_self.hpp.

+ +
+
+ +
+
+ + + + +
vari** v_
+
+ +

Definition at line 17 of file dot_self.hpp.

+ +
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diff --git a/doc/api/html/rev_2mat_2fun_2dot__self_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2dot__self_8hpp_source.html new file mode 100644 index 00000000000..f96b9b59c60 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2dot__self_8hpp_source.html @@ -0,0 +1,202 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/dot_self.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
+
+
dot_self.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_DOT_SELF_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_DOT_SELF_HPP
+
3 
+ + + +
7 #include <stan/math/rev/core.hpp>
+ +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  namespace {
+
15  class dot_self_vari : public vari {
+
16  protected:
+
17  vari** v_;
+
18  size_t size_;
+
19 
+
20  public:
+
21  dot_self_vari(vari** v, size_t size)
+
22  : vari(var_dot_self(v, size)),
+
23  v_(v),
+
24  size_(size) {
+
25  }
+
26  template<typename Derived>
+
27  explicit dot_self_vari(const Eigen::DenseBase<Derived> &v) :
+
28  vari(var_dot_self(v)), size_(v.size()) {
+
29  v_ = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
30  .alloc(size_*sizeof(vari*)));
+
31  for (size_t i = 0; i < size_; i++)
+
32  v_[i] = v[i].vi_;
+
33  }
+
34  template <int R, int C>
+
35  explicit dot_self_vari(const Eigen::Matrix<var, R, C>& v) :
+
36  vari(var_dot_self(v)), size_(v.size()) {
+
37  v_ = reinterpret_cast<vari**>
+
38  (ChainableStack::memalloc_.alloc(size_ * sizeof(vari*)));
+
39  for (size_t i = 0; i < size_; ++i)
+
40  v_[i] = v(i).vi_;
+
41  }
+
42  inline static double square(double x) { return x * x; }
+
43  inline static double var_dot_self(vari** v, size_t size) {
+
44  double sum = 0.0;
+
45  for (size_t i = 0; i < size; ++i)
+
46  sum += square(v[i]->val_);
+
47  return sum;
+
48  }
+
49  template<typename Derived>
+
50  double var_dot_self(const Eigen::DenseBase<Derived> &v) {
+
51  double sum = 0.0;
+
52  for (int i = 0; i < v.size(); ++i)
+
53  sum += square(v(i).vi_->val_);
+
54  return sum;
+
55  }
+
56  template <int R, int C>
+
57  inline static double var_dot_self(const Eigen::Matrix<var, R, C> &v) {
+
58  double sum = 0.0;
+
59  for (int i = 0; i < v.size(); ++i)
+
60  sum += square(v(i).vi_->val_);
+
61  return sum;
+
62  }
+
63  virtual void chain() {
+
64  for (size_t i = 0; i < size_; ++i)
+
65  v_[i]->adj_ += adj_ * 2.0 * v_[i]->val_;
+
66  }
+
67  };
+
68  }
+
79  template<int R, int C>
+
80  inline var dot_self(const Eigen::Matrix<var, R, C>& v) {
+
81  stan::math::check_vector("dot_self", "v", v);
+
82  return var(new dot_self_vari(v));
+
83  }
+
84 
+
85  }
+
86 }
+
87 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
size_t size_
Definition: dot_self.hpp:18
+
vari ** v_
Definition: dot_self.hpp:17
+ + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2log__determinant_8hpp.html b/doc/api/html/rev_2mat_2fun_2log__determinant_8hpp.html new file mode 100644 index 00000000000..9e17bb61619 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__determinant_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_determinant.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+ +
+
log_determinant.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<int R, int C>
var stan::math::log_determinant (const Eigen::Matrix< var, R, C > &m)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2log__determinant_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2log__determinant_8hpp_source.html new file mode 100644 index 00000000000..ec77c53bb13 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__determinant_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_determinant.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
log_determinant.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_LOG_DETERMINANT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_LOG_DETERMINANT_HPP
+
3 
+ + +
6 #include <stan/math/rev/core.hpp>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
12  template <int R, int C>
+
13  inline var log_determinant(const Eigen::Matrix<var, R, C>& m) {
+
14  using Eigen::Matrix;
+
15 
+
16  math::check_square("log_determinant", "m", m);
+
17 
+
18  Matrix<double, R, C> m_d(m.rows(), m.cols());
+
19  for (int i = 0; i < m.size(); ++i)
+
20  m_d(i) = m(i).val();
+
21 
+
22  Eigen::FullPivHouseholderQR<Matrix<double, R, C> > hh
+
23  = m_d.fullPivHouseholderQr();
+
24 
+
25  double val = hh.logAbsDeterminant();
+
26 
+
27  vari** varis
+ +
29  for (int i = 0; i < m.size(); ++i)
+
30  varis[i] = m(i).vi_;
+
31 
+
32  Matrix<double, R, C> m_inv_transpose = hh.inverse().transpose();
+
33  double* gradients
+
34  = ChainableStack::memalloc_.alloc_array<double>(m.size());
+
35  for (int i = 0; i < m.size(); ++i)
+
36  gradients[i] = m_inv_transpose(i);
+
37 
+
38  return var(new precomputed_gradients_vari(val, m.size(),
+
39  varis, gradients));
+
40  }
+
41 
+
42  }
+
43 }
+
44 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+
fvar< T > log_determinant(const Eigen::Matrix< fvar< T >, R, C > &m)
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
A variable implementation taking a sequence of operands and partial derivatives with respect to the o...
+ +
T * alloc_array(size_t n)
Allocate an array on the arena of the specified size to hold values of the specified template paramet...
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2log__determinant__ldlt_8hpp.html b/doc/api/html/rev_2mat_2fun_2log__determinant__ldlt_8hpp.html new file mode 100644 index 00000000000..8afc434ddd5 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__determinant__ldlt_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_determinant_ldlt.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
log_determinant_ldlt.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<int R, int C>
var stan::math::log_determinant_ldlt (stan::math::LDLT_factor< var, R, C > &A)
 
+

Variable Documentation

+ +
+
+ + + + +
const LDLT_alloc<R, C>* _alloc_ldlt
+
+ +

Definition at line 43 of file log_determinant_ldlt.hpp.

+ +
+
+
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2log__determinant__ldlt_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2log__determinant__ldlt_8hpp_source.html new file mode 100644 index 00000000000..dd159fec560 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__determinant__ldlt_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_determinant_ldlt.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
+
log_determinant_ldlt.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_LOG_DETERMINANT_LDLT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_LOG_DETERMINANT_LDLT_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+ + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11  namespace {
+
12 
+
22  template<int R, int C>
+
23  class log_det_ldlt_vari : public vari {
+
24  public:
+
25  explicit log_det_ldlt_vari(const stan::math::LDLT_factor<var, R, C> &A)
+
26  : vari(A._alloc->log_abs_det()), _alloc_ldlt(A._alloc)
+
27  { }
+
28 
+
29  virtual void chain() {
+
30  Eigen::Matrix<double, R, C> invA;
+
31 
+
32  // If we start computing Jacobians, this may be a bit inefficient
+
33  invA.setIdentity(_alloc_ldlt->N_, _alloc_ldlt->N_);
+
34  _alloc_ldlt->_ldlt.solveInPlace(invA);
+
35 
+
36  for (size_t j = 0; j < _alloc_ldlt->N_; j++) {
+
37  for (size_t i = 0; i < _alloc_ldlt->N_; i++) {
+
38  _alloc_ldlt->_variA(i, j)->adj_ += adj_ * invA(i, j);
+
39  }
+
40  }
+
41  }
+
42 
+
43  const LDLT_alloc<R, C> *_alloc_ldlt;
+
44  };
+
45  }
+
46 
+
47  template<int R, int C>
+ +
49  return var(new log_det_ldlt_vari<R, C>(A));
+
50  }
+
51  }
+
52 }
+
53 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
mdivide_left_ldlt_alloc< R1, C1, R2, C2 > * _alloc
+ + + +
const LDLT_alloc< R, C > * _alloc_ldlt
+
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2log__determinant__spd_8hpp.html b/doc/api/html/rev_2mat_2fun_2log__determinant__spd_8hpp.html new file mode 100644 index 00000000000..b7f24120d55 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__determinant__spd_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_determinant_spd.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+ +
+
log_determinant_spd.hpp File Reference
+
+
+
#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/prim/scal/err/domain_error.hpp>
+#include <stan/math/prim/mat/err/check_square.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<int R, int C>
var stan::math::log_determinant_spd (const Eigen::Matrix< var, R, C > &m)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2log__determinant__spd_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2log__determinant__spd_8hpp_source.html new file mode 100644 index 00000000000..a6f30874840 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__determinant__spd_8hpp_source.html @@ -0,0 +1,195 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_determinant_spd.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
log_determinant_spd.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_LOG_DETERMINANT_SPD_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_LOG_DETERMINANT_SPD_HPP
+
3 
+
4 #include <boost/math/special_functions/fpclassify.hpp>
+ + + +
8 #include <stan/math/rev/core.hpp>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
14  template <int R, int C>
+
15  inline var log_determinant_spd(const Eigen::Matrix<var, R, C>& m) {
+ +
17  using Eigen::Matrix;
+
18 
+
19  math::check_square("log_determinant_spd", "m", m);
+
20 
+
21  Matrix<double, R, C> m_d(m.rows(), m.cols());
+
22  for (int i = 0; i < m.size(); ++i)
+
23  m_d(i) = m(i).val();
+
24 
+
25  Eigen::LDLT<Matrix<double, R, C> > ldlt(m_d);
+
26  if (ldlt.info() != Eigen::Success) {
+
27  double y = 0;
+
28  domain_error("log_determinant_spd",
+
29  "matrix argument", y,
+
30  "failed LDLT factorization");
+
31  }
+
32 
+
33  // compute the inverse of A (needed for the derivative)
+
34  m_d.setIdentity(m.rows(), m.cols());
+
35  ldlt.solveInPlace(m_d);
+
36 
+
37  if (ldlt.isNegative() || (ldlt.vectorD().array() <= 1e-16).any()) {
+
38  double y = 0;
+
39  domain_error("log_determinant_spd",
+
40  "matrix argument", y,
+
41  "matrix is negative definite");
+
42  }
+
43 
+
44  double val = ldlt.vectorD().array().log().sum();
+
45 
+
46  if (!boost::math::isfinite(val)) {
+
47  double y = 0;
+
48  domain_error("log_determinant_spd",
+
49  "matrix argument", y,
+
50  "log determininant is infinite");
+
51  }
+
52 
+
53  vari** operands = ChainableStack::memalloc_
+
54  .alloc_array<vari*>(m.size());
+
55  for (int i = 0; i < m.size(); ++i)
+
56  operands[i] = m(i).vi_;
+
57 
+
58  double* gradients = ChainableStack::memalloc_
+
59  .alloc_array<double>(m.size());
+
60  for (int i = 0; i < m.size(); ++i)
+
61  gradients[i] = m_d(i);
+
62 
+
63  return var(new precomputed_gradients_vari(val, m.size(),
+
64  operands, gradients));
+
65  }
+
66 
+
67 
+
68  }
+
69 
+
70 }
+
71 #endif
+ +
bool isfinite(const stan::math::var &v)
Checks if the given number has finite value.
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
A variable implementation taking a sequence of operands and partial derivatives with respect to the o...
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
T * alloc_array(size_t n)
Allocate an array on the arena of the specified size to hold values of the specified template paramet...
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
T log_determinant_spd(const Eigen::Matrix< T, R, C > &m)
Returns the log absolute determinant of the specified square matrix.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2log__softmax_8hpp.html b/doc/api/html/rev_2mat_2fun_2log__softmax_8hpp.html new file mode 100644 index 00000000000..e39e1add77b --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__softmax_8hpp.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_softmax.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
log_softmax.hpp File Reference
+
+
+
#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/log_softmax.hpp>
+#include <stan/math/prim/mat/fun/softmax.hpp>
+#include <stan/math/rev/core.hpp>
+#include <cmath>
+#include <stdexcept>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

Eigen::Matrix< var, Eigen::Dynamic, 1 > stan::math::log_softmax (const Eigen::Matrix< var, Eigen::Dynamic, 1 > &alpha)
 Return the softmax of the specified Eigen vector. More...
 
+

Variable Documentation

+ +
+
+ + + + +
vari** alpha_
+
+ +

Definition at line 20 of file log_softmax.hpp.

+ +
+
+ +
+
+ + + + +
const int idx_
+
+ +

Definition at line 23 of file log_softmax.hpp.

+ +
+
+ +
+
+ + + + +
const int size_
+
+ +

Definition at line 22 of file log_softmax.hpp.

+ +
+
+ +
+
+ + + + +
const double* softmax_alpha_
+
+ +

Definition at line 21 of file log_softmax.hpp.

+ +
+
+
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2log__softmax_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2log__softmax_8hpp_source.html new file mode 100644 index 00000000000..71e0ee41989 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__softmax_8hpp_source.html @@ -0,0 +1,252 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_softmax.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
log_softmax.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_LOG_SOFTMAX_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_LOG_SOFTMAX_HPP
+
3 
+ + + + +
8 #include <stan/math/rev/core.hpp>
+
9 #include <cmath>
+
10 #include <stdexcept>
+
11 #include <vector>
+
12 
+
13 namespace stan {
+
14  namespace math {
+
15 
+
16  namespace {
+
17 
+
18  class log_softmax_elt_vari : public vari {
+
19  private:
+
20  vari** alpha_;
+
21  const double* softmax_alpha_;
+
22  const int size_; // array sizes
+
23  const int idx_; // in in softmax output
+
24 
+
25  public:
+
26  log_softmax_elt_vari(double val,
+
27  vari** alpha,
+
28  const double* softmax_alpha,
+
29  int size,
+
30  int idx)
+
31  : vari(val),
+
32  alpha_(alpha),
+
33  softmax_alpha_(softmax_alpha),
+
34  size_(size),
+
35  idx_(idx) {
+
36  }
+
37  void chain() {
+
38  for (int m = 0; m < size_; ++m) {
+
39  if (m == idx_)
+
40  alpha_[m]->adj_ += adj_ * (1 - softmax_alpha_[m]);
+
41  else
+
42  alpha_[m]->adj_ -= adj_ * softmax_alpha_[m];
+
43  }
+
44  }
+
45  };
+
46 
+
47  }
+
48 
+
49 
+
60  inline Eigen::Matrix<var, Eigen::Dynamic, 1>
+
61  log_softmax(const Eigen::Matrix<var, Eigen::Dynamic, 1>& alpha) {
+
62  using Eigen::Matrix;
+
63  using Eigen::Dynamic;
+
64 
+
65  stan::math::check_nonzero_size("log_softmax", "alpha", alpha);
+
66 
+
67  if (alpha.size() == 0)
+
68  throw std::domain_error("arg vector to log_softmax() "
+
69  "must have size > 0");
+
70  if (alpha.size() == 0)
+
71  throw std::domain_error("arg vector to log_softmax() "
+
72  "must have size > 0");
+
73  if (alpha.size() == 0)
+
74  throw std::domain_error("arg vector to log_softmax() "
+
75  "must have size > 0");
+
76 
+
77  // TODO(carpenter): replace with array alloc
+
78  vari** alpha_vi_array
+
79  = reinterpret_cast<vari**>
+
80  (vari::operator new(sizeof(vari*) * alpha.size()));
+
81  for (int i = 0; i < alpha.size(); ++i)
+
82  alpha_vi_array[i] = alpha(i).vi_;
+
83 
+
84 
+
85  Matrix<double, Dynamic, 1> alpha_d(alpha.size());
+
86  for (int i = 0; i < alpha_d.size(); ++i)
+
87  alpha_d(i) = alpha(i).val();
+
88 
+
89  // fold logic of math::softmax() and math::log_softmax()
+
90  // to save computations
+
91 
+
92  Matrix<double, Dynamic, 1> softmax_alpha_d(alpha_d.size());
+
93  Matrix<double, Dynamic, 1> log_softmax_alpha_d(alpha_d.size());
+
94 
+
95  double max_v = alpha_d.maxCoeff();
+
96 
+
97  double sum = 0.0;
+
98  for (int i = 0; i < alpha_d.size(); ++i) {
+
99  softmax_alpha_d(i) = std::exp(alpha_d(i) - max_v);
+
100  sum += softmax_alpha_d(i);
+
101  }
+
102 
+
103  for (int i = 0; i < alpha_d.size(); ++i)
+
104  softmax_alpha_d(i) /= sum;
+
105  double log_sum = std::log(sum);
+
106 
+
107  for (int i = 0; i < alpha_d.size(); ++i)
+
108  log_softmax_alpha_d(i) = (alpha_d(i) - max_v) - log_sum;
+
109 
+
110  // end fold
+
111  // TODO(carpenter): replace with array alloc
+
112  double* softmax_alpha_d_array
+
113  = reinterpret_cast<double*>
+
114  (vari::operator new(sizeof(double) * alpha_d.size()));
+
115 
+
116  for (int i = 0; i < alpha_d.size(); ++i)
+
117  softmax_alpha_d_array[i] = softmax_alpha_d(i);
+
118 
+
119  Matrix<var, Dynamic, 1> log_softmax_alpha(alpha.size());
+
120  for (int k = 0; k < log_softmax_alpha.size(); ++k)
+
121  log_softmax_alpha(k)
+
122  = var(new log_softmax_elt_vari(log_softmax_alpha_d[k],
+
123  alpha_vi_array,
+
124  softmax_alpha_d_array,
+
125  alpha.size(),
+
126  k));
+
127  return log_softmax_alpha;
+
128  }
+
129 
+
130 
+
131  }
+
132 }
+
133 
+
134 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+
const int size_
Definition: log_softmax.hpp:22
+ +
const int idx_
Definition: log_softmax.hpp:23
+ +
const double * softmax_alpha_
Definition: log_softmax.hpp:21
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > log_softmax(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
Definition: log_softmax.hpp:16
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
vari ** alpha_
Definition: log_softmax.hpp:20
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2log__sum__exp_8hpp.html b/doc/api/html/rev_2mat_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..dad2853fe78 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
log_sum_exp.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<int R, int C>
var stan::math::log_sum_exp (const Eigen::Matrix< var, R, C > &x)
 Returns the log sum of exponentials. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..68cd0679eef --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
+ + +
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+ + +
+
+
+
log_sum_exp.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_LOG_SUM_EXP_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + +
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14 
+
15  // these function and the following class just translate
+
16  // log_sum_exp for std::vector for Eigen::Matrix
+
17 
+
18  template <int R, int C>
+
19  double log_sum_exp_as_double(const Eigen::Matrix<var, R, C>& x) {
+
20  using std::numeric_limits;
+
21  using std::exp;
+
22  using std::log;
+
23  double max = -numeric_limits<double>::infinity();
+
24  for (int i = 0; i < x.size(); ++i)
+
25  if (x(i) > max)
+
26  max = x(i).val();
+
27  double sum = 0.0;
+
28  for (int i = 0; i < x.size(); ++i)
+
29  if (x(i) != -numeric_limits<double>::infinity())
+
30  sum += exp(x(i).val() - max);
+
31  return max + log(sum);
+
32  }
+
33 
+
34  class log_sum_exp_matrix_vari : public op_matrix_vari {
+
35  public:
+
36  template <int R, int C>
+
37  explicit log_sum_exp_matrix_vari(const Eigen::Matrix<var, R, C>& x) :
+
38  op_matrix_vari(log_sum_exp_as_double(x), x) {
+
39  }
+
40  void chain() {
+
41  for (size_t i = 0; i < size_; ++i) {
+
42  vis_[i]->adj_ += adj_ * calculate_chain(vis_[i]->val_, val_);
+
43  }
+
44  }
+
45  };
+
46  }
+
47 
+
53  template <int R, int C>
+
54  inline var log_sum_exp(const Eigen::Matrix<var, R, C>& x) {
+
55  return var(new log_sum_exp_matrix_vari(x));
+
56  }
+
57 
+
58  }
+
59 }
+
60 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+ +
double calculate_chain(const double &x, const double &val)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
size_t size_
Definition: dot_self.hpp:18
+ +
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2mdivide__left_8hpp.html b/doc/api/html/rev_2mat_2fun_2mdivide__left_8hpp.html new file mode 100644 index 00000000000..52ef518a77a --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2mdivide__left_8hpp.html @@ -0,0 +1,241 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/mdivide_left.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
mdivide_left.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
+

Variable Documentation

+ +
+
+ + + + +
vari** _variRefA
+
+ +

Definition at line 23 of file mdivide_left.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefB
+
+ +

Definition at line 24 of file mdivide_left.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefC
+
+ +

Definition at line 25 of file mdivide_left.hpp.

+ +
+
+ +
+
+ + + + +
double* A_
+
+ +

Definition at line 21 of file mdivide_left.hpp.

+ +
+
+ +
+
+ + + + +
double* C_
+
+ +

Definition at line 22 of file mdivide_left.hpp.

+ +
+
+ +
+
+ + + + +
int M_
+
+ +

Definition at line 19 of file mdivide_left.hpp.

+ +
+
+ +
+
+ + + + +
int N_
+
+ +

Definition at line 20 of file mdivide_left.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2mdivide__left_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2mdivide__left_8hpp_source.html new file mode 100644 index 00000000000..e2a79d39ba0 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2mdivide__left_8hpp_source.html @@ -0,0 +1,485 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/mdivide_left.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
mdivide_left.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_MDIVIDE_LEFT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_MDIVIDE_LEFT_HPP
+
3 
+ + + +
7 #include <stan/math/rev/core.hpp>
+ + +
10 #include <vector>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  namespace {
+
16  template <int R1, int C1, int R2, int C2>
+
17  class mdivide_left_vv_vari : public vari {
+
18  public:
+
19  int M_; // A.rows() = A.cols() = B.rows()
+
20  int N_; // B.cols()
+
21  double* A_;
+
22  double* C_;
+
23  vari** _variRefA;
+
24  vari** _variRefB;
+
25  vari** _variRefC;
+
26 
+
27  mdivide_left_vv_vari(const Eigen::Matrix<var, R1, C1> &A,
+
28  const Eigen::Matrix<var, R2, C2> &B)
+
29  : vari(0.0),
+
30  M_(A.rows()),
+
31  N_(B.cols()),
+
32  A_(reinterpret_cast<double*>
+
33  (stan::math::ChainableStack::memalloc_
+
34  .alloc(sizeof(double) * A.rows() * A.cols()))),
+
35  C_(reinterpret_cast<double*>
+
36  (stan::math::ChainableStack::memalloc_
+
37  .alloc(sizeof(double) * B.rows() * B.cols()))),
+
38  _variRefA(reinterpret_cast<vari**>
+
39  (stan::math::ChainableStack::memalloc_
+
40  .alloc(sizeof(vari*) * A.rows() * A.cols()))),
+
41  _variRefB(reinterpret_cast<vari**>
+
42  (stan::math::ChainableStack::memalloc_
+
43  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
44  _variRefC(reinterpret_cast<vari**>
+
45  (stan::math::ChainableStack::memalloc_
+
46  .alloc(sizeof(vari*) * B.rows() * B.cols()))) {
+
47  using Eigen::Matrix;
+
48  using Eigen::Map;
+
49 
+
50  size_t pos = 0;
+
51  for (size_type j = 0; j < M_; j++) {
+
52  for (size_type i = 0; i < M_; i++) {
+
53  _variRefA[pos] = A(i, j).vi_;
+
54  A_[pos++] = A(i, j).val();
+
55  }
+
56  }
+
57 
+
58  pos = 0;
+
59  for (size_type j = 0; j < N_; j++) {
+
60  for (size_type i = 0; i < M_; i++) {
+
61  _variRefB[pos] = B(i, j).vi_;
+
62  C_[pos++] = B(i, j).val();
+
63  }
+
64  }
+
65 
+
66  Matrix<double, R1, C2> C(M_, N_);
+
67  C = Map<Matrix<double, R1, C2> >(C_, M_, N_);
+
68 
+
69  C = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
70  .colPivHouseholderQr().solve(C);
+
71 
+
72  pos = 0;
+
73  for (size_type j = 0; j < N_; j++) {
+
74  for (size_type i = 0; i < M_; i++) {
+
75  C_[pos] = C(i, j);
+
76  _variRefC[pos] = new vari(C_[pos], false);
+
77  pos++;
+
78  }
+
79  }
+
80  }
+
81 
+
82  virtual void chain() {
+
83  using Eigen::Matrix;
+
84  using Eigen::Map;
+
85  Eigen::Matrix<double, R1, C1> adjA(M_, M_);
+
86  Eigen::Matrix<double, R2, C2> adjB(M_, N_);
+
87  Eigen::Matrix<double, R1, C2> adjC(M_, N_);
+
88 
+
89  size_t pos = 0;
+
90  for (size_type j = 0; j < adjC.cols(); j++)
+
91  for (size_type i = 0; i < adjC.rows(); i++)
+
92  adjC(i, j) = _variRefC[pos++]->adj_;
+
93 
+
94 
+
95  adjB = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
96  .transpose().colPivHouseholderQr().solve(adjC);
+
97  adjA.noalias() = -adjB
+
98  * Map<Matrix<double, R1, C2> >(C_, M_, N_).transpose();
+
99 
+
100  pos = 0;
+
101  for (size_type j = 0; j < adjA.cols(); j++)
+
102  for (size_type i = 0; i < adjA.rows(); i++)
+
103  _variRefA[pos++]->adj_ += adjA(i, j);
+
104 
+
105  pos = 0;
+
106  for (size_type j = 0; j < adjB.cols(); j++)
+
107  for (size_type i = 0; i < adjB.rows(); i++)
+
108  _variRefB[pos++]->adj_ += adjB(i, j);
+
109  }
+
110  };
+
111 
+
112  template <int R1, int C1, int R2, int C2>
+
113  class mdivide_left_dv_vari : public vari {
+
114  public:
+
115  int M_; // A.rows() = A.cols() = B.rows()
+
116  int N_; // B.cols()
+
117  double* A_;
+
118  double* C_;
+
119  vari** _variRefB;
+
120  vari** _variRefC;
+
121 
+
122  mdivide_left_dv_vari(const Eigen::Matrix<double, R1, C1> &A,
+
123  const Eigen::Matrix<var, R2, C2> &B)
+
124  : vari(0.0),
+
125  M_(A.rows()),
+
126  N_(B.cols()),
+
127  A_(reinterpret_cast<double*>
+
128  (stan::math::ChainableStack::memalloc_
+
129  .alloc(sizeof(double) * A.rows() * A.cols()))),
+
130  C_(reinterpret_cast<double*>
+
131  (stan::math::ChainableStack::memalloc_
+
132  .alloc(sizeof(double) * B.rows() * B.cols()))),
+
133  _variRefB(reinterpret_cast<vari**>
+
134  (stan::math::ChainableStack::memalloc_
+
135  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
136  _variRefC(reinterpret_cast<vari**>
+
137  (stan::math::ChainableStack::memalloc_
+
138  .alloc(sizeof(vari*) * B.rows() * B.cols()))) {
+
139  using Eigen::Matrix;
+
140  using Eigen::Map;
+
141 
+
142  size_t pos = 0;
+
143  for (size_type j = 0; j < M_; j++) {
+
144  for (size_type i = 0; i < M_; i++) {
+
145  A_[pos++] = A(i, j);
+
146  }
+
147  }
+
148 
+
149  pos = 0;
+
150  for (size_type j = 0; j < N_; j++) {
+
151  for (size_type i = 0; i < M_; i++) {
+
152  _variRefB[pos] = B(i, j).vi_;
+
153  C_[pos++] = B(i, j).val();
+
154  }
+
155  }
+
156 
+
157  Matrix<double, R1, C2> C(M_, N_);
+
158  C = Map<Matrix<double, R1, C2> >(C_, M_, N_);
+
159 
+
160  C = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
161  .colPivHouseholderQr().solve(C);
+
162 
+
163  pos = 0;
+
164  for (size_type j = 0; j < N_; j++) {
+
165  for (size_type i = 0; i < M_; i++) {
+
166  C_[pos] = C(i, j);
+
167  _variRefC[pos] = new vari(C_[pos], false);
+
168  pos++;
+
169  }
+
170  }
+
171  }
+
172 
+
173  virtual void chain() {
+
174  using Eigen::Matrix;
+
175  using Eigen::Map;
+
176  Eigen::Matrix<double, R2, C2> adjB(M_, N_);
+
177  Eigen::Matrix<double, R1, C2> adjC(M_, N_);
+
178 
+
179  size_t pos = 0;
+
180  for (size_type j = 0; j < adjC.cols(); j++)
+
181  for (size_type i = 0; i < adjC.rows(); i++)
+
182  adjC(i, j) = _variRefC[pos++]->adj_;
+
183 
+
184  adjB = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
185  .transpose().colPivHouseholderQr().solve(adjC);
+
186 
+
187  pos = 0;
+
188  for (size_type j = 0; j < adjB.cols(); j++)
+
189  for (size_type i = 0; i < adjB.rows(); i++)
+
190  _variRefB[pos++]->adj_ += adjB(i, j);
+
191  }
+
192  };
+
193 
+
194  template <int R1, int C1, int R2, int C2>
+
195  class mdivide_left_vd_vari : public vari {
+
196  public:
+
197  int M_; // A.rows() = A.cols() = B.rows()
+
198  int N_; // B.cols()
+
199  double* A_;
+
200  double* C_;
+
201  vari** _variRefA;
+
202  vari** _variRefC;
+
203 
+
204  mdivide_left_vd_vari(const Eigen::Matrix<var, R1, C1> &A,
+
205  const Eigen::Matrix<double, R2, C2> &B)
+
206  : vari(0.0),
+
207  M_(A.rows()),
+
208  N_(B.cols()),
+
209  A_(reinterpret_cast<double*>
+
210  (stan::math::ChainableStack::memalloc_
+
211  .alloc(sizeof(double) * A.rows() * A.cols()))),
+
212  C_(reinterpret_cast<double*>
+
213  (stan::math::ChainableStack::memalloc_
+
214  .alloc(sizeof(double) * B.rows() * B.cols()))),
+
215  _variRefA(reinterpret_cast<vari**>
+
216  (stan::math::ChainableStack::memalloc_
+
217  .alloc(sizeof(vari*) * A.rows() * A.cols()))),
+
218  _variRefC(reinterpret_cast<vari**>
+
219  (stan::math::ChainableStack::memalloc_
+
220  .alloc(sizeof(vari*) * B.rows() * B.cols()))) {
+
221  using Eigen::Matrix;
+
222  using Eigen::Map;
+
223 
+
224  size_t pos = 0;
+
225  for (size_type j = 0; j < M_; j++) {
+
226  for (size_type i = 0; i < M_; i++) {
+
227  _variRefA[pos] = A(i, j).vi_;
+
228  A_[pos++] = A(i, j).val();
+
229  }
+
230  }
+
231 
+
232  Matrix<double, R1, C2> C(M_, N_);
+
233  C = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
234  .colPivHouseholderQr().solve(B);
+
235 
+
236  pos = 0;
+
237  for (size_type j = 0; j < N_; j++) {
+
238  for (size_type i = 0; i < M_; i++) {
+
239  C_[pos] = C(i, j);
+
240  _variRefC[pos] = new vari(C_[pos], false);
+
241  pos++;
+
242  }
+
243  }
+
244  }
+
245 
+
246  virtual void chain() {
+
247  using Eigen::Matrix;
+
248  using Eigen::Map;
+
249  Eigen::Matrix<double, R1, C1> adjA(M_, M_);
+
250  Eigen::Matrix<double, R1, C2> adjC(M_, N_);
+
251 
+
252  size_t pos = 0;
+
253  for (size_type j = 0; j < adjC.cols(); j++)
+
254  for (size_type i = 0; i < adjC.rows(); i++)
+
255  adjC(i, j) = _variRefC[pos++]->adj_;
+
256 
+
257  // FIXME: add .noalias() to LHS
+
258  adjA = -Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
259  .transpose()
+
260  .colPivHouseholderQr()
+
261  .solve(adjC*Map<Matrix<double, R1, C2> >(C_, M_, N_).transpose());
+
262 
+
263  pos = 0;
+
264  for (size_type j = 0; j < adjA.cols(); j++)
+
265  for (size_type i = 0; i < adjA.rows(); i++)
+
266  _variRefA[pos++]->adj_ += adjA(i, j);
+
267  }
+
268  };
+
269  }
+
270 
+
271  template <int R1, int C1, int R2, int C2>
+
272  inline
+
273  Eigen::Matrix<var, R1, C2>
+
274  mdivide_left(const Eigen::Matrix<var, R1, C1> &A,
+
275  const Eigen::Matrix<var, R2, C2> &b) {
+
276  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
277 
+
278  stan::math::check_square("mdivide_left", "A", A);
+
279  stan::math::check_multiplicable("mdivide_left",
+
280  "A", A,
+
281  "b", b);
+
282 
+
283  // NOTE: this is not a memory leak, this vari is used in the
+
284  // expression graph to evaluate the adjoint, but is not needed
+
285  // for the returned matrix. Memory will be cleaned up with the
+
286  // arena allocator.
+
287  mdivide_left_vv_vari<R1, C1, R2, C2> *baseVari
+
288  = new mdivide_left_vv_vari<R1, C1, R2, C2>(A, b);
+
289 
+
290  size_t pos = 0;
+
291  for (size_type j = 0; j < res.cols(); j++)
+
292  for (size_type i = 0; i < res.rows(); i++)
+
293  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
294 
+
295  return res;
+
296  }
+
297 
+
298  template <int R1, int C1, int R2, int C2>
+
299  inline
+
300  Eigen::Matrix<var, R1, C2>
+
301  mdivide_left(const Eigen::Matrix<var, R1, C1> &A,
+
302  const Eigen::Matrix<double, R2, C2> &b) {
+
303  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
304 
+
305  stan::math::check_square("mdivide_left", "A", A);
+
306  stan::math::check_multiplicable("mdivide_left",
+
307  "A", A,
+
308  "b", b);
+
309 
+
310  // NOTE: this is not a memory leak, this vari is used in the
+
311  // expression graph to evaluate the adjoint, but is not needed
+
312  // for the returned matrix. Memory will be cleaned up with the
+
313  // arena allocator.
+
314  mdivide_left_vd_vari<R1, C1, R2, C2> *baseVari
+
315  = new mdivide_left_vd_vari<R1, C1, R2, C2>(A, b);
+
316 
+
317  size_t pos = 0;
+
318  for (size_type j = 0; j < res.cols(); j++)
+
319  for (size_type i = 0; i < res.rows(); i++)
+
320  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
321 
+
322  return res;
+
323  }
+
324 
+
325  template <int R1, int C1, int R2, int C2>
+
326  inline
+
327  Eigen::Matrix<var, R1, C2>
+
328  mdivide_left(const Eigen::Matrix<double, R1, C1> &A,
+
329  const Eigen::Matrix<var, R2, C2> &b) {
+
330  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
331 
+
332  stan::math::check_square("mdivide_left", "A", A);
+
333  stan::math::check_multiplicable("mdivide_left",
+
334  "A", A,
+
335  "b", b);
+
336 
+
337  // NOTE: this is not a memory leak, this vari is used in the
+
338  // expression graph to evaluate the adjoint, but is not needed
+
339  // for the returned matrix. Memory will be cleaned up with the
+
340  // arena allocator.
+
341  mdivide_left_dv_vari<R1, C1, R2, C2> *baseVari
+
342  = new mdivide_left_dv_vari<R1, C1, R2, C2>(A, b);
+
343 
+
344  size_t pos = 0;
+
345  for (size_type j = 0; j < res.cols(); j++)
+
346  for (size_type i = 0; i < res.rows(); i++)
+
347  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
348 
+
349  return res;
+
350  }
+
351 
+
352  }
+
353 }
+
354 #endif
+
Eigen::Matrix< fvar< T >, R1, C2 > mdivide_left(const Eigen::Matrix< fvar< T >, R1, C1 > &A, const Eigen::Matrix< fvar< T >, R2, C2 > &b)
+
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ + +
double * C_
+ +
vari ** _variRefB
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
int M_
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
vari ** _variRefA
+
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ +
double * A_
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
AutodiffStackStorage< vari, chainable_alloc > ChainableStack
+
int N_
+
vari ** _variRefC
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2mdivide__left__ldlt_8hpp.html b/doc/api/html/rev_2mat_2fun_2mdivide__left__ldlt_8hpp.html new file mode 100644 index 00000000000..c3556c35bc8 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2mdivide__left__ldlt_8hpp.html @@ -0,0 +1,259 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/mdivide_left_ldlt.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
mdivide_left_ldlt.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + +

+Functions

template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< var, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< var, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_ldlt (const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 Returns the solution of the system Ax=b given an LDLT_factor of A. More...
 
+

Variable Documentation

+ +
+
+ + + + +
mdivide_left_ldlt_alloc<R1, C1, R2, C2>* _alloc
+
+ +

Definition at line 44 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
const LDLT_alloc<R1, C1>* _alloc_ldlt
+
+ +

Definition at line 45 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
boost::shared_ptr<Eigen::LDLT<Eigen::Matrix<double, R1, C1> > > _ldltP
+
+ +

This share_ptr is used to prevent copying the LDLT factorizations for mdivide_left_ldlt(ldltA, b) when ldltA is a LDLT_factor<double>.

+

The pointer is shared with the LDLT_factor<double> class.

+ +

Definition at line 23 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefB
+
+ +

Definition at line 42 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefC
+
+ +

Definition at line 43 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<double, R2, C2> C_
+
+ +

Definition at line 24 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
int M_
+
+ +

Definition at line 40 of file mdivide_left_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
int N_
+
+ +

Definition at line 41 of file mdivide_left_ldlt.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html new file mode 100644 index 00000000000..4b38342aefd --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2mdivide__left__ldlt_8hpp_source.html @@ -0,0 +1,396 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/mdivide_left_ldlt.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
mdivide_left_ldlt.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_MDIVIDE_LEFT_LDLT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_MDIVIDE_LEFT_LDLT_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + + +
9 
+
10 namespace stan {
+
11  namespace math {
+
12  namespace {
+
13  template <int R1, int C1, int R2, int C2>
+
14  class mdivide_left_ldlt_alloc : public chainable_alloc {
+
15  public:
+
16  virtual ~mdivide_left_ldlt_alloc() {}
+
17 
+
23  boost::shared_ptr<Eigen::LDLT<Eigen::Matrix<double, R1, C1> > > _ldltP;
+
24  Eigen::Matrix<double, R2, C2> C_;
+
25  };
+
26 
+
37  template <int R1, int C1, int R2, int C2>
+
38  class mdivide_left_ldlt_vv_vari : public vari {
+
39  public:
+
40  int M_; // A.rows() = A.cols() = B.rows()
+
41  int N_; // B.cols()
+
42  vari** _variRefB;
+
43  vari** _variRefC;
+
44  mdivide_left_ldlt_alloc<R1, C1, R2, C2> *_alloc;
+
45  const LDLT_alloc<R1, C1> *_alloc_ldlt;
+
46 
+
47  mdivide_left_ldlt_vv_vari(const stan::math::LDLT_factor<var, R1, C1> &A,
+
48  const Eigen::Matrix<var, R2, C2> &B)
+
49  : vari(0.0),
+
50  M_(A.rows()),
+
51  N_(B.cols()),
+
52  _variRefB(reinterpret_cast<vari**>
+
53  (stan::math::ChainableStack::memalloc_
+
54  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
55  _variRefC(reinterpret_cast<vari**>
+
56  (stan::math::ChainableStack::memalloc_
+
57  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
58  _alloc(new mdivide_left_ldlt_alloc<R1, C1, R2, C2>()),
+
59  _alloc_ldlt(A._alloc) {
+
60  int pos = 0;
+
61  _alloc->C_.resize(M_, N_);
+
62  for (int j = 0; j < N_; j++) {
+
63  for (int i = 0; i < M_; i++) {
+
64  _variRefB[pos] = B(i, j).vi_;
+
65  _alloc->C_(i, j) = B(i, j).val();
+
66  pos++;
+
67  }
+
68  }
+
69 
+
70  _alloc_ldlt->_ldlt.solveInPlace(_alloc->C_);
+
71 
+
72  pos = 0;
+
73  for (int j = 0; j < N_; j++) {
+
74  for (int i = 0; i < M_; i++) {
+
75  _variRefC[pos] = new vari(_alloc->C_(i, j), false);
+
76  pos++;
+
77  }
+
78  }
+
79  }
+
80 
+
81  virtual void chain() {
+
82  Eigen::Matrix<double, R1, C1> adjA(M_, M_);
+
83  Eigen::Matrix<double, R2, C2> adjB(M_, N_);
+
84 
+
85  int pos = 0;
+
86  for (int j = 0; j < N_; j++)
+
87  for (int i = 0; i < M_; i++)
+
88  adjB(i, j) = _variRefC[pos++]->adj_;
+
89 
+
90  _alloc_ldlt->_ldlt.solveInPlace(adjB);
+
91  adjA.noalias() = -adjB * _alloc->C_.transpose();
+
92 
+
93  for (int j = 0; j < M_; j++)
+
94  for (int i = 0; i < M_; i++)
+
95  _alloc_ldlt->_variA(i, j)->adj_ += adjA(i, j);
+
96 
+
97  pos = 0;
+
98  for (int j = 0; j < N_; j++)
+
99  for (int i = 0; i < M_; i++)
+
100  _variRefB[pos++]->adj_ += adjB(i, j);
+
101  }
+
102  };
+
103 
+
114  template <int R1, int C1, int R2, int C2>
+
115  class mdivide_left_ldlt_dv_vari : public vari {
+
116  public:
+
117  int M_; // A.rows() = A.cols() = B.rows()
+
118  int N_; // B.cols()
+
119  vari** _variRefB;
+
120  vari** _variRefC;
+
121  mdivide_left_ldlt_alloc<R1, C1, R2, C2> *_alloc;
+
122 
+
123  mdivide_left_ldlt_dv_vari(const stan::math::LDLT_factor<double, R1, C1>
+
124  &A,
+
125  const Eigen::Matrix<var, R2, C2> &B)
+
126  : vari(0.0),
+
127  M_(A.rows()),
+
128  N_(B.cols()),
+
129  _variRefB(reinterpret_cast<vari**>
+
130  (stan::math::ChainableStack::memalloc_
+
131  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
132  _variRefC(reinterpret_cast<vari**>
+
133  (stan::math::ChainableStack::memalloc_
+
134  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
135  _alloc(new mdivide_left_ldlt_alloc<R1, C1, R2, C2>()) {
+
136  using Eigen::Matrix;
+
137  using Eigen::Map;
+
138 
+
139  int pos = 0;
+
140  _alloc->C_.resize(M_, N_);
+
141  for (int j = 0; j < N_; j++) {
+
142  for (int i = 0; i < M_; i++) {
+
143  _variRefB[pos] = B(i, j).vi_;
+
144  _alloc->C_(i, j) = B(i, j).val();
+
145  pos++;
+
146  }
+
147  }
+
148 
+
149  _alloc->_ldltP = A._ldltP;
+
150  _alloc->_ldltP->solveInPlace(_alloc->C_);
+
151 
+
152  pos = 0;
+
153  for (int j = 0; j < N_; j++) {
+
154  for (int i = 0; i < M_; i++) {
+
155  _variRefC[pos] = new vari(_alloc->C_(i, j), false);
+
156  pos++;
+
157  }
+
158  }
+
159  }
+
160 
+
161  virtual void chain() {
+
162  Eigen::Matrix<double, R2, C2> adjB(M_, N_);
+
163 
+
164  int pos = 0;
+
165  for (int j = 0; j < adjB.cols(); j++)
+
166  for (int i = 0; i < adjB.rows(); i++)
+
167  adjB(i, j) = _variRefC[pos++]->adj_;
+
168 
+
169  _alloc->_ldltP->solveInPlace(adjB);
+
170 
+
171  pos = 0;
+
172  for (int j = 0; j < adjB.cols(); j++)
+
173  for (int i = 0; i < adjB.rows(); i++)
+
174  _variRefB[pos++]->adj_ += adjB(i, j);
+
175  }
+
176  };
+
177 
+
188  template <int R1, int C1, int R2, int C2>
+
189  class mdivide_left_ldlt_vd_vari : public vari {
+
190  public:
+
191  int M_; // A.rows() = A.cols() = B.rows()
+
192  int N_; // B.cols()
+
193  vari** _variRefC;
+
194  mdivide_left_ldlt_alloc<R1, C1, R2, C2> *_alloc;
+
195  const LDLT_alloc<R1, C1> *_alloc_ldlt;
+
196 
+
197  mdivide_left_ldlt_vd_vari(const stan::math::LDLT_factor<var, R1, C1> &A,
+
198  const Eigen::Matrix<double, R2, C2> &B)
+
199  : vari(0.0),
+
200  M_(A.rows()),
+
201  N_(B.cols()),
+
202  _variRefC(reinterpret_cast<vari**>
+
203  (stan::math::ChainableStack::memalloc_
+
204  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
205  _alloc(new mdivide_left_ldlt_alloc<R1, C1, R2, C2>()),
+
206  _alloc_ldlt(A._alloc) {
+
207  _alloc->C_ = B;
+
208  _alloc_ldlt->_ldlt.solveInPlace(_alloc->C_);
+
209 
+
210  int pos = 0;
+
211  for (int j = 0; j < N_; j++) {
+
212  for (int i = 0; i < M_; i++) {
+
213  _variRefC[pos] = new vari(_alloc->C_(i, j), false);
+
214  pos++;
+
215  }
+
216  }
+
217  }
+
218 
+
219  virtual void chain() {
+
220  Eigen::Matrix<double, R1, C1> adjA(M_, M_);
+
221  Eigen::Matrix<double, R1, C2> adjC(M_, N_);
+
222 
+
223  int pos = 0;
+
224  for (int j = 0; j < adjC.cols(); j++)
+
225  for (int i = 0; i < adjC.rows(); i++)
+
226  adjC(i, j) = _variRefC[pos++]->adj_;
+
227 
+
228  adjA = -_alloc_ldlt->_ldlt.solve(adjC*_alloc->C_.transpose());
+
229 
+
230  for (int j = 0; j < adjA.cols(); j++)
+
231  for (int i = 0; i < adjA.rows(); i++)
+
232  _alloc_ldlt->_variA(i, j)->adj_ += adjA(i, j);
+
233  }
+
234  };
+
235  }
+
236 
+
244  template <int R1, int C1, int R2, int C2>
+
245  inline Eigen::Matrix<var, R1, C2>
+ +
247  const Eigen::Matrix<var, R2, C2> &b) {
+
248  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
249 
+
250  stan::math::check_multiplicable("mdivide_left_ldlt",
+
251  "A", A,
+
252  "b", b);
+
253 
+
254  mdivide_left_ldlt_vv_vari<R1, C1, R2, C2> *baseVari
+
255  = new mdivide_left_ldlt_vv_vari<R1, C1, R2, C2>(A, b);
+
256 
+
257  int pos = 0;
+
258  for (int j = 0; j < res.cols(); j++)
+
259  for (int i = 0; i < res.rows(); i++)
+
260  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
261 
+
262  return res;
+
263  }
+
264 
+
272  template <int R1, int C1, int R2, int C2>
+
273  inline Eigen::Matrix<var, R1, C2>
+ +
275  const Eigen::Matrix<double, R2, C2> &b) {
+
276  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
277 
+
278  stan::math::check_multiplicable("mdivide_left_ldlt",
+
279  "A", A,
+
280  "b", b);
+
281 
+
282  mdivide_left_ldlt_vd_vari<R1, C1, R2, C2> *baseVari
+
283  = new mdivide_left_ldlt_vd_vari<R1, C1, R2, C2>(A, b);
+
284 
+
285  int pos = 0;
+
286  for (int j = 0; j < res.cols(); j++)
+
287  for (int i = 0; i < res.rows(); i++)
+
288  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
289 
+
290  return res;
+
291  }
+
292 
+
300  template <int R1, int C1, int R2, int C2>
+
301  inline Eigen::Matrix<var, R1, C2>
+ +
303  const Eigen::Matrix<var, R2, C2> &b) {
+
304  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
305 
+
306  stan::math::check_multiplicable("mdivide_left_ldlt",
+
307  "A", A,
+
308  "b", b);
+
309 
+
310  mdivide_left_ldlt_dv_vari<R1, C1, R2, C2> *baseVari
+
311  = new mdivide_left_ldlt_dv_vari<R1, C1, R2, C2>(A, b);
+
312 
+
313  int pos = 0;
+
314  for (int j = 0; j < res.cols(); j++)
+
315  for (int i = 0; i < res.rows(); i++)
+
316  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
317 
+
318  return res;
+
319  }
+
320 
+
321  }
+
322 }
+
323 #endif
+
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ + + +
int N_
+ +
mdivide_left_ldlt_alloc< R1, C1, R2, C2 > * _alloc
+
int M_
+ +
vari ** _variRefC
+
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt(const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
Returns the solution of the system Ax=b given an LDLT_factor of A.
+
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
boost::shared_ptr< Eigen::LDLT< Eigen::Matrix< double, R1, C1 > > > _ldltP
This share_ptr is used to prevent copying the LDLT factorizations for mdivide_left_ldlt(ldltA, b) when ldltA is a LDLT_factor.
+ +
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ +
const LDLT_alloc< R1, C1 > * _alloc_ldlt
+
Eigen::Matrix< double, R2, C2 > C_
+
vari ** _variRefB
+
AutodiffStackStorage< vari, chainable_alloc > ChainableStack
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2mdivide__left__spd_8hpp.html b/doc/api/html/rev_2mat_2fun_2mdivide__left__spd_8hpp.html new file mode 100644 index 00000000000..1ca0a2793e7 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2mdivide__left__spd_8hpp.html @@ -0,0 +1,255 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/mdivide_left_spd.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
mdivide_left_spd.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_spd (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_spd (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
template<int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_spd (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
+

Variable Documentation

+ +
+
+ + + + +
mdivide_left_spd_alloc<R1, C1, R2, C2>* _alloc
+
+ +

Definition at line 33 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::LLT< Eigen::Matrix<double, R1, C1> > _llt
+
+ +

Definition at line 21 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefA
+
+ +

Definition at line 30 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefB
+
+ +

Definition at line 31 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefC
+
+ +

Definition at line 32 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<double, R2, C2> C_
+
+ +

Definition at line 22 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+ + + + +
int M_
+
+ +

Definition at line 28 of file mdivide_left_spd.hpp.

+ +
+
+ +
+
+ + + + +
int N_
+
+ +

Definition at line 29 of file mdivide_left_spd.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2mdivide__left__spd_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2mdivide__left__spd_8hpp_source.html new file mode 100644 index 00000000000..d4621cfed18 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2mdivide__left__spd_8hpp_source.html @@ -0,0 +1,459 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/mdivide_left_spd.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
mdivide_left_spd.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_MDIVIDE_LEFT_SPD_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_MDIVIDE_LEFT_SPD_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + + + +
10 #include <vector>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  namespace {
+
16  template <int R1, int C1, int R2, int C2>
+
17  class mdivide_left_spd_alloc : public chainable_alloc {
+
18  public:
+
19  virtual ~mdivide_left_spd_alloc() {}
+
20 
+
21  Eigen::LLT< Eigen::Matrix<double, R1, C1> > _llt;
+
22  Eigen::Matrix<double, R2, C2> C_;
+
23  };
+
24 
+
25  template <int R1, int C1, int R2, int C2>
+
26  class mdivide_left_spd_vv_vari : public vari {
+
27  public:
+
28  int M_; // A.rows() = A.cols() = B.rows()
+
29  int N_; // B.cols()
+
30  vari** _variRefA;
+
31  vari** _variRefB;
+
32  vari** _variRefC;
+
33  mdivide_left_spd_alloc<R1, C1, R2, C2> *_alloc;
+
34 
+
35  mdivide_left_spd_vv_vari(const Eigen::Matrix<var, R1, C1> &A,
+
36  const Eigen::Matrix<var, R2, C2> &B)
+
37  : vari(0.0),
+
38  M_(A.rows()),
+
39  N_(B.cols()),
+
40  _variRefA(reinterpret_cast<vari**>
+
41  (stan::math::ChainableStack::memalloc_
+
42  .alloc(sizeof(vari*) * A.rows() * A.cols()))),
+
43  _variRefB(reinterpret_cast<vari**>
+
44  (stan::math::ChainableStack::memalloc_
+
45  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
46  _variRefC(reinterpret_cast<vari**>
+
47  (stan::math::ChainableStack::memalloc_
+
48  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
49  _alloc(new mdivide_left_spd_alloc<R1, C1, R2, C2>()) {
+
50  using Eigen::Matrix;
+
51  using Eigen::Map;
+
52 
+
53  Matrix<double, R1, C1> Ad(A.rows(), A.cols());
+
54 
+
55  size_t pos = 0;
+
56  for (size_type j = 0; j < M_; j++) {
+
57  for (size_type i = 0; i < M_; i++) {
+
58  _variRefA[pos] = A(i, j).vi_;
+
59  Ad(i, j) = A(i, j).val();
+
60  pos++;
+
61  }
+
62  }
+
63 
+
64  pos = 0;
+
65  _alloc->C_.resize(M_, N_);
+
66  for (size_type j = 0; j < N_; j++) {
+
67  for (size_type i = 0; i < M_; i++) {
+
68  _variRefB[pos] = B(i, j).vi_;
+
69  _alloc->C_(i, j) = B(i, j).val();
+
70  pos++;
+
71  }
+
72  }
+
73 
+
74  _alloc->_llt = Ad.llt();
+
75  _alloc->_llt.solveInPlace(_alloc->C_);
+
76 
+
77  pos = 0;
+
78  for (size_type j = 0; j < N_; j++) {
+
79  for (size_type i = 0; i < M_; i++) {
+
80  _variRefC[pos] = new vari(_alloc->C_(i, j), false);
+
81  pos++;
+
82  }
+
83  }
+
84  }
+
85 
+
86  virtual void chain() {
+
87  using Eigen::Matrix;
+
88  using Eigen::Map;
+
89  Eigen::Matrix<double, R1, C1> adjA(M_, M_);
+
90  Eigen::Matrix<double, R2, C2> adjB(M_, N_);
+
91 
+
92  size_t pos = 0;
+
93  for (size_type j = 0; j < N_; j++)
+
94  for (size_type i = 0; i < M_; i++)
+
95  adjB(i, j) = _variRefC[pos++]->adj_;
+
96 
+
97  _alloc->_llt.solveInPlace(adjB);
+
98  adjA.noalias() = -adjB * _alloc->C_.transpose();
+
99 
+
100  pos = 0;
+
101  for (size_type j = 0; j < M_; j++)
+
102  for (size_type i = 0; i < M_; i++)
+
103  _variRefA[pos++]->adj_ += adjA(i, j);
+
104 
+
105  pos = 0;
+
106  for (size_type j = 0; j < N_; j++)
+
107  for (size_type i = 0; i < M_; i++)
+
108  _variRefB[pos++]->adj_ += adjB(i, j);
+
109  }
+
110  };
+
111 
+
112  template <int R1, int C1, int R2, int C2>
+
113  class mdivide_left_spd_dv_vari : public vari {
+
114  public:
+
115  int M_; // A.rows() = A.cols() = B.rows()
+
116  int N_; // B.cols()
+
117  vari** _variRefB;
+
118  vari** _variRefC;
+
119  mdivide_left_spd_alloc<R1, C1, R2, C2> *_alloc;
+
120 
+
121  mdivide_left_spd_dv_vari(const Eigen::Matrix<double, R1, C1> &A,
+
122  const Eigen::Matrix<var, R2, C2> &B)
+
123  : vari(0.0),
+
124  M_(A.rows()),
+
125  N_(B.cols()),
+
126  _variRefB(reinterpret_cast<vari**>
+
127  (stan::math::ChainableStack::memalloc_
+
128  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
129  _variRefC(reinterpret_cast<vari**>
+
130  (stan::math::ChainableStack::memalloc_
+
131  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
132  _alloc(new mdivide_left_spd_alloc<R1, C1, R2, C2>()) {
+
133  using Eigen::Matrix;
+
134  using Eigen::Map;
+
135 
+
136  size_t pos = 0;
+
137  _alloc->C_.resize(M_, N_);
+
138  for (size_type j = 0; j < N_; j++) {
+
139  for (size_type i = 0; i < M_; i++) {
+
140  _variRefB[pos] = B(i, j).vi_;
+
141  _alloc->C_(i, j) = B(i, j).val();
+
142  pos++;
+
143  }
+
144  }
+
145 
+
146  _alloc->_llt = A.llt();
+
147  _alloc->_llt.solveInPlace(_alloc->C_);
+
148 
+
149  pos = 0;
+
150  for (size_type j = 0; j < N_; j++) {
+
151  for (size_type i = 0; i < M_; i++) {
+
152  _variRefC[pos] = new vari(_alloc->C_(i, j), false);
+
153  pos++;
+
154  }
+
155  }
+
156  }
+
157 
+
158  virtual void chain() {
+
159  using Eigen::Matrix;
+
160  using Eigen::Map;
+
161  Eigen::Matrix<double, R2, C2> adjB(M_, N_);
+
162 
+
163  size_t pos = 0;
+
164  for (size_type j = 0; j < adjB.cols(); j++)
+
165  for (size_type i = 0; i < adjB.rows(); i++)
+
166  adjB(i, j) = _variRefC[pos++]->adj_;
+
167 
+
168  _alloc->_llt.solveInPlace(adjB);
+
169 
+
170  pos = 0;
+
171  for (size_type j = 0; j < adjB.cols(); j++)
+
172  for (size_type i = 0; i < adjB.rows(); i++)
+
173  _variRefB[pos++]->adj_ += adjB(i, j);
+
174  }
+
175  };
+
176 
+
177  template <int R1, int C1, int R2, int C2>
+
178  class mdivide_left_spd_vd_vari : public vari {
+
179  public:
+
180  int M_; // A.rows() = A.cols() = B.rows()
+
181  int N_; // B.cols()
+
182  vari** _variRefA;
+
183  vari** _variRefC;
+
184  mdivide_left_spd_alloc<R1, C1, R2, C2> *_alloc;
+
185 
+
186  mdivide_left_spd_vd_vari(const Eigen::Matrix<var, R1, C1> &A,
+
187  const Eigen::Matrix<double, R2, C2> &B)
+
188  : vari(0.0),
+
189  M_(A.rows()),
+
190  N_(B.cols()),
+
191  _variRefA(reinterpret_cast<vari**>
+
192  (stan::math::ChainableStack::memalloc_
+
193  .alloc(sizeof(vari*) * A.rows() * A.cols()))),
+
194  _variRefC(reinterpret_cast<vari**>
+
195  (stan::math::ChainableStack::memalloc_
+
196  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
197  _alloc(new mdivide_left_spd_alloc<R1, C1, R2, C2>()) {
+
198  using Eigen::Matrix;
+
199  using Eigen::Map;
+
200 
+
201  Matrix<double, R1, C1> Ad(A.rows(), A.cols());
+
202 
+
203  size_t pos = 0;
+
204  for (size_type j = 0; j < M_; j++) {
+
205  for (size_type i = 0; i < M_; i++) {
+
206  _variRefA[pos] = A(i, j).vi_;
+
207  Ad(i, j) = A(i, j).val();
+
208  pos++;
+
209  }
+
210  }
+
211 
+
212  _alloc->_llt = Ad.llt();
+
213  _alloc->C_ = _alloc->_llt.solve(B);
+
214 
+
215  pos = 0;
+
216  for (size_type j = 0; j < N_; j++) {
+
217  for (size_type i = 0; i < M_; i++) {
+
218  _variRefC[pos] = new vari(_alloc->C_(i, j), false);
+
219  pos++;
+
220  }
+
221  }
+
222  }
+
223 
+
224  virtual void chain() {
+
225  using Eigen::Matrix;
+
226  using Eigen::Map;
+
227  Eigen::Matrix<double, R1, C1> adjA(M_, M_);
+
228  Eigen::Matrix<double, R1, C2> adjC(M_, N_);
+
229 
+
230  size_t pos = 0;
+
231  for (size_type j = 0; j < adjC.cols(); j++)
+
232  for (size_type i = 0; i < adjC.rows(); i++)
+
233  adjC(i, j) = _variRefC[pos++]->adj_;
+
234 
+
235  adjA = -_alloc->_llt.solve(adjC*_alloc->C_.transpose());
+
236 
+
237  pos = 0;
+
238  for (size_type j = 0; j < adjA.cols(); j++)
+
239  for (size_type i = 0; i < adjA.rows(); i++)
+
240  _variRefA[pos++]->adj_ += adjA(i, j);
+
241  }
+
242  };
+
243  }
+
244 
+
245  template <int R1, int C1, int R2, int C2>
+
246  inline
+
247  Eigen::Matrix<var, R1, C2>
+
248  mdivide_left_spd(const Eigen::Matrix<var, R1, C1> &A,
+
249  const Eigen::Matrix<var, R2, C2> &b) {
+
250  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
251 
+
252  stan::math::check_square("mdivide_left_spd", "A", A);
+
253  stan::math::check_multiplicable("mdivide_left_spd",
+
254  "A", A,
+
255  "b", b);
+
256 
+
257  // NOTE: this is not a memory leak, this vari is used in the
+
258  // expression graph to evaluate the adjoint, but is not needed
+
259  // for the returned matrix. Memory will be cleaned up with the
+
260  // arena allocator.
+
261  mdivide_left_spd_vv_vari<R1, C1, R2, C2> *baseVari
+
262  = new mdivide_left_spd_vv_vari<R1, C1, R2, C2>(A, b);
+
263 
+
264  size_t pos = 0;
+
265  for (size_type j = 0; j < res.cols(); j++)
+
266  for (size_type i = 0; i < res.rows(); i++)
+
267  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
268 
+
269  return res;
+
270  }
+
271 
+
272  template <int R1, int C1, int R2, int C2>
+
273  inline
+
274  Eigen::Matrix<var, R1, C2>
+
275  mdivide_left_spd(const Eigen::Matrix<var, R1, C1> &A,
+
276  const Eigen::Matrix<double, R2, C2> &b) {
+
277  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
278 
+
279  stan::math::check_square("mdivide_left_spd", "A", A);
+
280  stan::math::check_multiplicable("mdivide_left_spd",
+
281  "A", A,
+
282  "b", b);
+
283 
+
284  // NOTE: this is not a memory leak, this vari is used in the
+
285  // expression graph to evaluate the adjoint, but is not needed
+
286  // for the returned matrix. Memory will be cleaned up with the
+
287  // arena allocator.
+
288  mdivide_left_spd_vd_vari<R1, C1, R2, C2> *baseVari
+
289  = new mdivide_left_spd_vd_vari<R1, C1, R2, C2>(A, b);
+
290 
+
291  size_t pos = 0;
+
292  for (size_type j = 0; j < res.cols(); j++)
+
293  for (size_type i = 0; i < res.rows(); i++)
+
294  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
295 
+
296  return res;
+
297  }
+
298 
+
299  template <int R1, int C1, int R2, int C2>
+
300  inline
+
301  Eigen::Matrix<var, R1, C2>
+
302  mdivide_left_spd(const Eigen::Matrix<double, R1, C1> &A,
+
303  const Eigen::Matrix<var, R2, C2> &b) {
+
304  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
305 
+
306  stan::math::check_square("mdivide_left_spd", "A", A);
+
307  stan::math::check_multiplicable("mdivide_left_spd",
+
308  "A", A,
+
309  "b", b);
+
310 
+
311  // NOTE: this is not a memory leak, this vari is used in the
+
312  // expression graph to evaluate the adjoint, but is not needed
+
313  // for the returned matrix. Memory will be cleaned up with the
+
314  // arena allocator.
+
315  mdivide_left_spd_dv_vari<R1, C1, R2, C2> *baseVari
+
316  = new mdivide_left_spd_dv_vari<R1, C1, R2, C2>(A, b);
+
317 
+
318  size_t pos = 0;
+
319  for (size_type j = 0; j < res.cols(); j++)
+
320  for (size_type i = 0; i < res.rows(); i++)
+
321  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
322 
+
323  return res;
+
324  }
+
325 
+
326  }
+
327 }
+
328 #endif
+
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ +
int N_
+
vari ** _variRefB
+ + +
Eigen::LLT< Eigen::Matrix< double, R1, C1 > > _llt
+
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_spd(const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
Returns the solution of the system Ax=b where A is symmetric positive definite.
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
int M_
+
mdivide_left_spd_alloc< R1, C1, R2, C2 > * _alloc
+
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ +
vari ** _variRefC
+
vari ** _variRefA
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
AutodiffStackStorage< vari, chainable_alloc > ChainableStack
+
Eigen::Matrix< double, R2, C2 > C_
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2mdivide__left__tri_8hpp.html b/doc/api/html/rev_2mat_2fun_2mdivide__left__tri_8hpp.html new file mode 100644 index 00000000000..f2ff6bddb6d --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2mdivide__left__tri_8hpp.html @@ -0,0 +1,241 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/mdivide_left_tri.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
mdivide_left_tri.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

template<int TriView, int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_tri (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int TriView, int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_tri (const Eigen::Matrix< double, R1, C1 > &A, const Eigen::Matrix< var, R2, C2 > &b)
 
template<int TriView, int R1, int C1, int R2, int C2>
Eigen::Matrix< var, R1, C2 > stan::math::mdivide_left_tri (const Eigen::Matrix< var, R1, C1 > &A, const Eigen::Matrix< double, R2, C2 > &b)
 
+

Variable Documentation

+ +
+
+ + + + +
vari** _variRefA
+
+ +

Definition at line 23 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefB
+
+ +

Definition at line 24 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+ + + + +
vari** _variRefC
+
+ +

Definition at line 25 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+ + + + +
double* A_
+
+ +

Definition at line 21 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+ + + + +
double* C_
+
+ +

Definition at line 22 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+ + + + +
int M_
+
+ +

Definition at line 19 of file mdivide_left_tri.hpp.

+ +
+
+ +
+
+ + + + +
int N_
+
+ +

Definition at line 20 of file mdivide_left_tri.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2mdivide__left__tri_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2mdivide__left__tri_8hpp_source.html new file mode 100644 index 00000000000..337e49125b8 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2mdivide__left__tri_8hpp_source.html @@ -0,0 +1,513 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/mdivide_left_tri.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
mdivide_left_tri.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_MDIVIDE_LEFT_TRI_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_MDIVIDE_LEFT_TRI_HPP
+
3 
+ + + + +
8 #include <stan/math/rev/core.hpp>
+ +
10 #include <vector>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  namespace {
+
16  template <int TriView, int R1, int C1, int R2, int C2>
+
17  class mdivide_left_tri_vv_vari : public vari {
+
18  public:
+
19  int M_; // A.rows() = A.cols() = B.rows()
+
20  int N_; // B.cols()
+
21  double* A_;
+
22  double* C_;
+
23  vari** _variRefA;
+
24  vari** _variRefB;
+
25  vari** _variRefC;
+
26 
+
27  mdivide_left_tri_vv_vari(const Eigen::Matrix<var, R1, C1> &A,
+
28  const Eigen::Matrix<var, R2, C2> &B)
+
29  : vari(0.0),
+
30  M_(A.rows()),
+
31  N_(B.cols()),
+
32  A_(reinterpret_cast<double*>
+
33  (stan::math::ChainableStack::memalloc_
+
34  .alloc(sizeof(double) * A.rows() * A.cols()))),
+
35  C_(reinterpret_cast<double*>
+
36  (stan::math::ChainableStack::memalloc_
+
37  .alloc(sizeof(double) * B.rows() * B.cols()))),
+
38  _variRefA(reinterpret_cast<vari**>
+
39  (stan::math::ChainableStack::memalloc_
+
40  .alloc(sizeof(vari*) * A.rows() * (A.rows() + 1) / 2))),
+
41  _variRefB(reinterpret_cast<vari**>
+
42  (stan::math::ChainableStack::memalloc_
+
43  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
44  _variRefC(reinterpret_cast<vari**>
+
45  (stan::math::ChainableStack::memalloc_
+
46  .alloc(sizeof(vari*) * B.rows() * B.cols()))) {
+
47  using Eigen::Matrix;
+
48  using Eigen::Map;
+
49 
+
50  size_t pos = 0;
+
51  if (TriView == Eigen::Lower) {
+
52  for (size_type j = 0; j < M_; j++)
+
53  for (size_type i = j; i < M_; i++)
+
54  _variRefA[pos++] = A(i, j).vi_;
+
55  } else if (TriView == Eigen::Upper) {
+
56  for (size_type j = 0; j < M_; j++)
+
57  for (size_type i = 0; i < j+1; i++)
+
58  _variRefA[pos++] = A(i, j).vi_;
+
59  }
+
60 
+
61  pos = 0;
+
62  for (size_type j = 0; j < M_; j++) {
+
63  for (size_type i = 0; i < M_; i++) {
+
64  A_[pos++] = A(i, j).val();
+
65  }
+
66  }
+
67 
+
68  pos = 0;
+
69  for (size_type j = 0; j < N_; j++) {
+
70  for (size_type i = 0; i < M_; i++) {
+
71  _variRefB[pos] = B(i, j).vi_;
+
72  C_[pos++] = B(i, j).val();
+
73  }
+
74  }
+
75 
+
76  Matrix<double, R1, C2> C(M_, N_);
+
77  C = Map<Matrix<double, R1, C2> >(C_, M_, N_);
+
78 
+
79  C = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
80  .template triangularView<TriView>().solve(C);
+
81 
+
82  pos = 0;
+
83  for (size_type j = 0; j < N_; j++) {
+
84  for (size_type i = 0; i < M_; i++) {
+
85  C_[pos] = C(i, j);
+
86  _variRefC[pos] = new vari(C_[pos], false);
+
87  pos++;
+
88  }
+
89  }
+
90  }
+
91 
+
92  virtual void chain() {
+
93  using Eigen::Matrix;
+
94  using Eigen::Map;
+
95  Matrix<double, R1, C1> adjA(M_, M_);
+
96  Matrix<double, R2, C2> adjB(M_, N_);
+
97  Matrix<double, R1, C2> adjC(M_, N_);
+
98 
+
99  size_t pos = 0;
+
100  for (size_type j = 0; j < adjC.cols(); j++)
+
101  for (size_type i = 0; i < adjC.rows(); i++)
+
102  adjC(i, j) = _variRefC[pos++]->adj_;
+
103 
+
104  adjB = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
105  .template triangularView<TriView>().transpose().solve(adjC);
+
106  adjA.noalias() = -adjB
+
107  * Map<Matrix<double, R1, C2> >(C_, M_, N_).transpose();
+
108 
+
109  pos = 0;
+
110  if (TriView == Eigen::Lower) {
+
111  for (size_type j = 0; j < adjA.cols(); j++)
+
112  for (size_type i = j; i < adjA.rows(); i++)
+
113  _variRefA[pos++]->adj_ += adjA(i, j);
+
114  } else if (TriView == Eigen::Upper) {
+
115  for (size_type j = 0; j < adjA.cols(); j++)
+
116  for (size_type i = 0; i < j+1; i++)
+
117  _variRefA[pos++]->adj_ += adjA(i, j);
+
118  }
+
119 
+
120  pos = 0;
+
121  for (size_type j = 0; j < adjB.cols(); j++)
+
122  for (size_type i = 0; i < adjB.rows(); i++)
+
123  _variRefB[pos++]->adj_ += adjB(i, j);
+
124  }
+
125  };
+
126 
+
127  template <int TriView, int R1, int C1, int R2, int C2>
+
128  class mdivide_left_tri_dv_vari : public vari {
+
129  public:
+
130  int M_; // A.rows() = A.cols() = B.rows()
+
131  int N_; // B.cols()
+
132  double* A_;
+
133  double* C_;
+
134  vari** _variRefB;
+
135  vari** _variRefC;
+
136 
+
137  mdivide_left_tri_dv_vari(const Eigen::Matrix<double, R1, C1> &A,
+
138  const Eigen::Matrix<var, R2, C2> &B)
+
139  : vari(0.0),
+
140  M_(A.rows()),
+
141  N_(B.cols()),
+
142  A_(reinterpret_cast<double*>
+
143  (stan::math::ChainableStack::memalloc_
+
144  .alloc(sizeof(double) * A.rows() * A.cols()))),
+
145  C_(reinterpret_cast<double*>
+
146  (stan::math::ChainableStack::memalloc_
+
147  .alloc(sizeof(double) * B.rows() * B.cols()))),
+
148  _variRefB(reinterpret_cast<vari**>
+
149  (stan::math::ChainableStack::memalloc_
+
150  .alloc(sizeof(vari*) * B.rows() * B.cols()))),
+
151  _variRefC(reinterpret_cast<vari**>
+
152  (stan::math::ChainableStack::memalloc_
+
153  .alloc(sizeof(vari*) * B.rows() * B.cols()))) {
+
154  using Eigen::Matrix;
+
155  using Eigen::Map;
+
156 
+
157  size_t pos = 0;
+
158  for (size_type j = 0; j < M_; j++) {
+
159  for (size_type i = 0; i < M_; i++) {
+
160  A_[pos++] = A(i, j);
+
161  }
+
162  }
+
163 
+
164  pos = 0;
+
165  for (size_type j = 0; j < N_; j++) {
+
166  for (size_type i = 0; i < M_; i++) {
+
167  _variRefB[pos] = B(i, j).vi_;
+
168  C_[pos++] = B(i, j).val();
+
169  }
+
170  }
+
171 
+
172  Matrix<double, R1, C2> C(M_, N_);
+
173  C = Map<Matrix<double, R1, C2> >(C_, M_, N_);
+
174 
+
175  C = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
176  .template triangularView<TriView>().solve(C);
+
177 
+
178  pos = 0;
+
179  for (size_type j = 0; j < N_; j++) {
+
180  for (size_type i = 0; i < M_; i++) {
+
181  C_[pos] = C(i, j);
+
182  _variRefC[pos] = new vari(C_[pos], false);
+
183  pos++;
+
184  }
+
185  }
+
186  }
+
187 
+
188  virtual void chain() {
+
189  using Eigen::Matrix;
+
190  using Eigen::Map;
+
191  Matrix<double, R2, C2> adjB(M_, N_);
+
192  Matrix<double, R1, C2> adjC(M_, N_);
+
193 
+
194  size_t pos = 0;
+
195  for (size_type j = 0; j < adjC.cols(); j++)
+
196  for (size_type i = 0; i < adjC.rows(); i++)
+
197  adjC(i, j) = _variRefC[pos++]->adj_;
+
198 
+
199  adjB = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
200  .template triangularView<TriView>().transpose().solve(adjC);
+
201 
+
202  pos = 0;
+
203  for (size_type j = 0; j < adjB.cols(); j++)
+
204  for (size_type i = 0; i < adjB.rows(); i++)
+
205  _variRefB[pos++]->adj_ += adjB(i, j);
+
206  }
+
207  };
+
208 
+
209  template <int TriView, int R1, int C1, int R2, int C2>
+
210  class mdivide_left_tri_vd_vari : public vari {
+
211  public:
+
212  int M_; // A.rows() = A.cols() = B.rows()
+
213  int N_; // B.cols()
+
214  double* A_;
+
215  double* C_;
+
216  vari** _variRefA;
+
217  vari** _variRefC;
+
218 
+
219  mdivide_left_tri_vd_vari(const Eigen::Matrix<var, R1, C1> &A,
+
220  const Eigen::Matrix<double, R2, C2> &B)
+
221  : vari(0.0),
+
222  M_(A.rows()),
+
223  N_(B.cols()),
+
224  A_(reinterpret_cast<double*>
+
225  (stan::math::ChainableStack::memalloc_
+
226  .alloc(sizeof(double) * A.rows() * A.cols()))),
+
227  C_(reinterpret_cast<double*>
+
228  (stan::math::ChainableStack::memalloc_
+
229  .alloc(sizeof(double) * B.rows() * B.cols()))),
+
230  _variRefA(reinterpret_cast<vari**>
+
231  (stan::math::ChainableStack::memalloc_
+
232  .alloc(sizeof(vari*) * A.rows() * (A.rows() + 1) / 2))),
+
233  _variRefC(reinterpret_cast<vari**>
+
234  (stan::math::ChainableStack::memalloc_
+
235  .alloc(sizeof(vari*) * B.rows() * B.cols()))) {
+
236  using Eigen::Matrix;
+
237  using Eigen::Map;
+
238 
+
239  size_t pos = 0;
+
240  if (TriView == Eigen::Lower) {
+
241  for (size_type j = 0; j < M_; j++)
+
242  for (size_type i = j; i < M_; i++)
+
243  _variRefA[pos++] = A(i, j).vi_;
+
244  } else if (TriView == Eigen::Upper) {
+
245  for (size_type j = 0; j < M_; j++)
+
246  for (size_type i = 0; i < j+1; i++)
+
247  _variRefA[pos++] = A(i, j).vi_;
+
248  }
+
249 
+
250  pos = 0;
+
251  for (size_type j = 0; j < M_; j++) {
+
252  for (size_type i = 0; i < M_; i++) {
+
253  A_[pos++] = A(i, j).val();
+
254  }
+
255  }
+
256 
+
257  Matrix<double, R1, C2> C(M_, N_);
+
258  C = Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
259  .template triangularView<TriView>().solve(B);
+
260 
+
261  pos = 0;
+
262  for (size_type j = 0; j < N_; j++) {
+
263  for (size_type i = 0; i < M_; i++) {
+
264  C_[pos] = C(i, j);
+
265  _variRefC[pos] = new vari(C_[pos], false);
+
266  pos++;
+
267  }
+
268  }
+
269  }
+
270 
+
271  virtual void chain() {
+
272  using Eigen::Matrix;
+
273  using Eigen::Map;
+
274  Matrix<double, R1, C1> adjA(M_, M_);
+
275  Matrix<double, R1, C2> adjC(M_, N_);
+
276 
+
277  size_t pos = 0;
+
278  for (size_type j = 0; j < adjC.cols(); j++)
+
279  for (size_type i = 0; i < adjC.rows(); i++)
+
280  adjC(i, j) = _variRefC[pos++]->adj_;
+
281 
+
282  adjA.noalias() = -Map<Matrix<double, R1, C1> >(A_, M_, M_)
+
283  .template triangularView<TriView>()
+
284  .transpose().solve(adjC * Map<Matrix<double, R1, C2> >(C_, M_, N_)
+
285  .transpose());
+
286 
+
287  pos = 0;
+
288  if (TriView == Eigen::Lower) {
+
289  for (size_type j = 0; j < adjA.cols(); j++)
+
290  for (size_type i = j; i < adjA.rows(); i++)
+
291  _variRefA[pos++]->adj_ += adjA(i, j);
+
292  } else if (TriView == Eigen::Upper) {
+
293  for (size_type j = 0; j < adjA.cols(); j++)
+
294  for (size_type i = 0; i < j+1; i++)
+
295  _variRefA[pos++]->adj_ += adjA(i, j);
+
296  }
+
297  }
+
298  };
+
299  }
+
300 
+
301  template <int TriView, int R1, int C1, int R2, int C2>
+
302  inline
+
303  Eigen::Matrix<var, R1, C2>
+
304  mdivide_left_tri(const Eigen::Matrix<var, R1, C1> &A,
+
305  const Eigen::Matrix<var, R2, C2> &b) {
+
306  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
307 
+
308  stan::math::check_square("mdivide_left_tri", "A", A);
+
309  stan::math::check_multiplicable("mdivide_left_tri",
+
310  "A", A,
+
311  "b", b);
+
312 
+
313  // NOTE: this is not a memory leak, this vari is used in the
+
314  // expression graph to evaluate the adjoint, but is not needed
+
315  // for the returned matrix. Memory will be cleaned up with the
+
316  // arena allocator.
+
317  mdivide_left_tri_vv_vari<TriView, R1, C1, R2, C2> *baseVari
+
318  = new mdivide_left_tri_vv_vari<TriView, R1, C1, R2, C2>(A, b);
+
319 
+
320  size_t pos = 0;
+
321  for (size_type j = 0; j < res.cols(); j++)
+
322  for (size_type i = 0; i < res.rows(); i++)
+
323  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
324 
+
325  return res;
+
326  }
+
327  template <int TriView, int R1, int C1, int R2, int C2>
+
328  inline
+
329  Eigen::Matrix<var, R1, C2>
+
330  mdivide_left_tri(const Eigen::Matrix<double, R1, C1> &A,
+
331  const Eigen::Matrix<var, R2, C2> &b) {
+
332  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
333 
+
334  stan::math::check_square("mdivide_left_tri", "A", A);
+
335  stan::math::check_multiplicable("mdivide_left_tri",
+
336  "A", A,
+
337  "b", b);
+
338 
+
339  // NOTE: this is not a memory leak, this vari is used in the
+
340  // expression graph to evaluate the adjoint, but is not needed
+
341  // for the returned matrix. Memory will be cleaned up with the
+
342  // arena allocator.
+
343  mdivide_left_tri_dv_vari<TriView, R1, C1, R2, C2> *baseVari
+
344  = new mdivide_left_tri_dv_vari<TriView, R1, C1, R2, C2>(A, b);
+
345 
+
346  size_t pos = 0;
+
347  for (size_type j = 0; j < res.cols(); j++)
+
348  for (size_type i = 0; i < res.rows(); i++)
+
349  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
350 
+
351  return res;
+
352  }
+
353  template <int TriView, int R1, int C1, int R2, int C2>
+
354  inline
+
355  Eigen::Matrix<var, R1, C2>
+
356  mdivide_left_tri(const Eigen::Matrix<var, R1, C1> &A,
+
357  const Eigen::Matrix<double, R2, C2> &b) {
+
358  Eigen::Matrix<var, R1, C2> res(b.rows(), b.cols());
+
359 
+
360  stan::math::check_square("mdivide_left_tri", "A", A);
+
361  stan::math::check_multiplicable("mdivide_left_tri",
+
362  "A", A,
+
363  "b", b);
+
364 
+
365  // NOTE: this is not a memory leak, this vari is used in the
+
366  // expression graph to evaluate the adjoint, but is not needed
+
367  // for the returned matrix. Memory will be cleaned up with the
+
368  // arena allocator.
+
369  mdivide_left_tri_vd_vari<TriView, R1, C1, R2, C2> *baseVari
+
370  = new mdivide_left_tri_vd_vari<TriView, R1, C1, R2, C2>(A, b);
+
371 
+
372  size_t pos = 0;
+
373  for (size_type j = 0; j < res.cols(); j++)
+
374  for (size_type i = 0; i < res.rows(); i++)
+
375  res(i, j).vi_ = baseVari->_variRefC[pos++];
+
376 
+
377  return res;
+
378  }
+
379 
+
380  }
+
381 }
+
382 #endif
+
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ + + +
int N_
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
double * C_
+
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R1, C2 > mdivide_left_tri(const Eigen::Matrix< T1, R1, C1 > &A, const Eigen::Matrix< T2, R2, C2 > &b)
Returns the solution of the system Ax=b when A is triangular.
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
vari ** _variRefC
+
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ +
double * A_
+
vari ** _variRefA
+
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
AutodiffStackStorage< vari, chainable_alloc > ChainableStack
+
int M_
+
vari ** _variRefB
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2multiply_8hpp.html b/doc/api/html/rev_2mat_2fun_2multiply_8hpp.html new file mode 100644 index 00000000000..cfe5e64a0b6 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2multiply_8hpp.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/multiply.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
multiply.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/mat/fun/Eigen_NumTraits.hpp>
+#include <stan/math/rev/mat/fun/typedefs.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/typedefs.hpp>
+#include <stan/math/prim/mat/err/check_multiplicable.hpp>
+#include <stan/math/rev/mat/fun/to_var.hpp>
+#include <stan/math/rev/mat/fun/dot_product.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <stdexcept>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + +

+Functions

template<typename T1 , typename T2 >
boost::enable_if_c< (boost::is_scalar< T1 >::value||boost::is_same< T1, var >::value)&&(boost::is_scalar< T2 >::value||boost::is_same< T2, var >::value), typename boost::math::tools::promote_args< T1, T2 >::type >::type stan::math::multiply (const T1 &v, const T2 &c)
 Return the product of two scalars. More...
 
template<typename T1 , typename T2 , int R2, int C2>
Eigen::Matrix< var, R2, C2 > stan::math::multiply (const T1 &c, const Eigen::Matrix< T2, R2, C2 > &m)
 Return the product of scalar and matrix. More...
 
template<typename T1 , int R1, int C1, typename T2 >
Eigen::Matrix< var, R1, C1 > stan::math::multiply (const Eigen::Matrix< T1, R1, C1 > &m, const T2 &c)
 Return the product of scalar and matrix. More...
 
template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, Eigen::Matrix< var, R1, C2 > >::type stan::math::multiply (const Eigen::Matrix< T1, R1, C1 > &m1, const Eigen::Matrix< T2, R2, C2 > &m2)
 Return the product of the specified matrices. More...
 
template<typename T1 , int C1, typename T2 , int R2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, var >::type stan::math::multiply (const Eigen::Matrix< T1, 1, C1 > &rv, const Eigen::Matrix< T2, R2, 1 > &v)
 Return the scalar product of the specified row vector and specified column vector. More...
 
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diff --git a/doc/api/html/rev_2mat_2fun_2multiply_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2multiply_8hpp_source.html new file mode 100644 index 00000000000..8138ef46496 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2multiply_8hpp_source.html @@ -0,0 +1,226 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/multiply.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
multiply.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_MULTIPLY_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_MULTIPLY_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + + + + + +
12 #include <boost/utility/enable_if.hpp>
+
13 #include <boost/type_traits.hpp>
+
14 #include <boost/math/tools/promotion.hpp>
+
15 #include <stdexcept>
+
16 
+
17 namespace stan {
+
18  namespace math {
+
19 
+
26  template <typename T1, typename T2>
+
27  inline typename
+
28  boost::enable_if_c<
+
29  (boost::is_scalar<T1>::value || boost::is_same<T1, var>::value)
+
30  && (boost::is_scalar<T2>::value || boost::is_same<T2, var>::value),
+
31  typename boost::math::tools::promote_args<T1, T2>::type>::type
+
32  multiply(const T1& v, const T2& c) {
+
33  return v * c;
+
34  }
+
35 
+
42  template<typename T1, typename T2, int R2, int C2>
+
43  inline Eigen::Matrix<var, R2, C2>
+
44  multiply(const T1& c, const Eigen::Matrix<T2, R2, C2>& m) {
+
45  // FIXME: pull out to eliminate overpromotion of one side
+
46  // move to matrix.hpp w. promotion?
+
47  return to_var(m) * to_var(c);
+
48  }
+
49 
+
56  template<typename T1, int R1, int C1, typename T2>
+
57  inline Eigen::Matrix<var, R1, C1>
+
58  multiply(const Eigen::Matrix<T1, R1, C1>& m, const T2& c) {
+
59  return to_var(m) * to_var(c);
+
60  }
+
61 
+
72  template<typename T1, int R1, int C1, typename T2, int R2, int C2>
+
73  inline typename
+
74  boost::enable_if_c< boost::is_same<T1, var>::value ||
+
75  boost::is_same<T2, var>::value,
+
76  Eigen::Matrix<var, R1, C2> >::type
+
77  multiply(const Eigen::Matrix<T1, R1, C1>& m1,
+
78  const Eigen::Matrix<T2, R2, C2>& m2) {
+ +
80  "m1", m1,
+
81  "m2", m2);
+
82  Eigen::Matrix<var, R1, C2> result(m1.rows(), m2.cols());
+
83  for (int i = 0; i < m1.rows(); i++) {
+
84  typename Eigen::Matrix<T1, R1, C1>::ConstRowXpr crow(m1.row(i));
+
85  for (int j = 0; j < m2.cols(); j++) {
+
86  typename Eigen::Matrix<T2, R2, C2>::ConstColXpr ccol(m2.col(j));
+
87  if (j == 0) {
+
88  if (i == 0) {
+
89  result(i, j) = var(new dot_product_vari<T1, T2>(crow, ccol));
+
90  } else {
+
91  dot_product_vari<T1, T2> *v2
+
92  = static_cast<dot_product_vari<T1, T2>*>(result(0, j).vi_);
+
93  result(i, j)
+
94  = var(new dot_product_vari<T1, T2>(crow, ccol, NULL, v2));
+
95  }
+
96  } else {
+
97  if (i == 0) {
+
98  dot_product_vari<T1, T2> *v1
+
99  = static_cast<dot_product_vari<T1, T2>*>(result(i, 0).vi_);
+
100  result(i, j)
+
101  = var(new dot_product_vari<T1, T2>(crow, ccol, v1, NULL));
+
102  } else /* if (i != 0 && j != 0) */ {
+
103  dot_product_vari<T1, T2> *v1
+
104  = static_cast<dot_product_vari<T1, T2>*>(result(i, 0).vi_);
+
105  dot_product_vari<T1, T2> *v2
+
106  = static_cast<dot_product_vari<T1, T2>*>(result(0, j).vi_);
+
107  result(i, j)
+
108  = var(new dot_product_vari<T1, T2>(crow, ccol, v1, v2));
+
109  }
+
110  }
+
111  }
+
112  }
+
113  return result;
+
114  }
+
115 
+
125  template <typename T1, int C1, typename T2, int R2>
+
126  inline typename
+
127  boost::enable_if_c< boost::is_same<T1, var>::value ||
+
128  boost::is_same<T2, var>::value, var >::type
+
129  multiply(const Eigen::Matrix<T1, 1, C1>& rv,
+
130  const Eigen::Matrix<T2, R2, 1>& v) {
+
131  if (rv.size() != v.size())
+
132  throw std::domain_error("row vector and vector must be same length "
+
133  "in multiply");
+
134  return dot_product(rv, v);
+
135  }
+
136 
+
137  }
+
138 }
+
139 #endif
+ + + + +
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
Definition: multiply.hpp:21
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
+ +
void domain_error(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw a domain error with a consistently formatted message.
+ +
std::vector< var > to_var(const std::vector< double > &v)
Converts argument to an automatic differentiation variable.
Definition: to_var.hpp:20
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html b/doc/api/html/rev_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html new file mode 100644 index 00000000000..7628f987205 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/multiply_lower_tri_self_transpose.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
multiply_lower_tri_self_transpose.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + +

+Functions

matrix_v stan::math::multiply_lower_tri_self_transpose (const matrix_v &L)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html new file mode 100644 index 00000000000..060a867b771 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2multiply__lower__tri__self__transpose_8hpp_source.html @@ -0,0 +1,181 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/multiply_lower_tri_self_transpose.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+
+
multiply_lower_tri_self_transpose.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_MULTIPLY_LOWER_TRI_SELF_TRANSPOSE_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_MULTIPLY_LOWER_TRI_SELF_TRANSPOSE_HPP
+
3 
+ + + +
7 #include <stan/math/rev/core.hpp>
+ + + + +
12 #include <boost/math/tools/promotion.hpp>
+
13 #include <vector>
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  inline matrix_v
+ +
20  // stan::math::check_square("multiply_lower_tri_self_transpose",
+
21  // L, "L", (double*)0);
+
22  int K = L.rows();
+
23  int J = L.cols();
+
24  matrix_v LLt(K, K);
+
25  if (K == 0) return LLt;
+
26  // if (K == 1) {
+
27  // LLt(0, 0) = L(0, 0) * L(0, 0);
+
28  // return LLt;
+
29  // }
+
30  int Knz;
+
31  if (K >= J)
+
32  Knz = (K-J)*J + (J * (J + 1)) / 2;
+
33  else // if (K < J)
+
34  Knz = (K * (K + 1)) / 2;
+
35  vari** vs
+
36  = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
37  .alloc(Knz * sizeof(vari*)));
+
38  int pos = 0;
+
39  for (int m = 0; m < K; ++m)
+
40  for (int n = 0; n < ((J < (m+1)) ? J : (m+1)); ++n) {
+
41  vs[pos++] = L(m, n).vi_;
+
42  }
+
43  for (int m = 0, mpos=0; m < K; ++m, mpos += (J < m) ? J : m) {
+
44  LLt(m, m) = var(new dot_self_vari(vs + mpos, (J < (m+1)) ? J : (m+1)));
+
45  for (int n = 0, npos = 0; n < m; ++n, npos += (J < n) ? J : n) {
+
46  LLt(m, n)
+
47  = LLt(n, m)
+
48  = var(new dot_product_vari<var, var>(vs + mpos, vs + npos,
+
49  (J < (n+1))?J:(n+1)));
+
50  }
+
51  }
+
52  return LLt;
+
53  }
+
54 
+
55  }
+
56 }
+
57 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
Eigen::Matrix< var, Eigen::Dynamic, Eigen::Dynamic > matrix_v
The type of a matrix holding stan::math::var values.
Definition: typedefs.hpp:21
+
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose(const Eigen::Matrix< fvar< T >, R, C > &m)
+ + + + +
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+ + +
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2quad__form_8hpp.html b/doc/api/html/rev_2mat_2fun_2quad__form_8hpp.html new file mode 100644 index 00000000000..58d63f6e02d --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2quad__form_8hpp.html @@ -0,0 +1,214 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/quad_form.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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template<typename TA , int RA, int CA, typename TB , int RB, int CB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, Eigen::Matrix< var, CB, CB > >::type stan::math::quad_form (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, CB > &B)
 
template<typename TA , int RA, int CA, typename TB , int RB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, var >::type stan::math::quad_form (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, 1 > &B)
 
+

Variable Documentation

+ +
+
+ + + + +
quad_form_vari_alloc<TA, RA, CA, TB, RB, CB>* _impl
+
+ +

Definition at line 115 of file quad_form.hpp.

+ +
+
+ +
+
+ + + + +
bool _sym
+
+ +

Definition at line 48 of file quad_form.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<TA, RA, CA> A_
+
+ +

Definition at line 45 of file quad_form.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<TB, RB, CB> B_
+
+ +

Definition at line 46 of file quad_form.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<var, CB, CB> C_
+
+ +

Definition at line 47 of file quad_form.hpp.

+ +
+
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+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2quad__form_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2quad__form_8hpp_source.html new file mode 100644 index 00000000000..70967bf99bb --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2quad__form_8hpp_source.html @@ -0,0 +1,286 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/quad_form.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
quad_form.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_QUAD_FORM_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_QUAD_FORM_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits.hpp>
+
6 #include <stan/math/rev/core.hpp>
+ + + + + + + + +
15 
+
16 namespace stan {
+
17  namespace math {
+
18  namespace {
+
19  template <typename TA, int RA, int CA, typename TB, int RB, int CB>
+
20  class quad_form_vari_alloc : public chainable_alloc {
+
21  private:
+
22  inline void compute(const Eigen::Matrix<double, RA, CA>& A,
+
23  const Eigen::Matrix<double, RB, CB>& B) {
+
24  Eigen::Matrix<double, CB, CB> Cd(B.transpose()*A*B);
+
25  for (int j = 0; j < C_.cols(); j++) {
+
26  for (int i = 0; i < C_.rows(); i++) {
+
27  if (_sym) {
+
28  C_(i, j) = var(new vari(0.5*(Cd(i, j) + Cd(j, i)), false));
+
29  } else {
+
30  C_(i, j) = var(new vari(Cd(i, j), false));
+
31  }
+
32  }
+
33  }
+
34  }
+
35 
+
36  public:
+
37  quad_form_vari_alloc(const Eigen::Matrix<TA, RA, CA>& A,
+
38  const Eigen::Matrix<TB, RB, CB>& B,
+
39  bool symmetric = false)
+
40  : A_(A), B_(B), C_(B_.cols(), B_.cols()), _sym(symmetric) {
+ +
42  compute(value_of(A), value_of(B));
+
43  }
+
44 
+
45  Eigen::Matrix<TA, RA, CA> A_;
+
46  Eigen::Matrix<TB, RB, CB> B_;
+
47  Eigen::Matrix<var, CB, CB> C_;
+
48  bool _sym;
+
49  };
+
50 
+
51  template <typename TA, int RA, int CA, typename TB, int RB, int CB>
+
52  class quad_form_vari : public vari {
+
53  protected:
+
54  inline void chainA(Eigen::Matrix<double, RA, CA>& A,
+
55  const Eigen::Matrix<double, RB, CB>& Bd,
+
56  const Eigen::Matrix<double, CB, CB>& adjC) {}
+
57  inline void chainB(Eigen::Matrix<double, RB, CB>& B,
+
58  const Eigen::Matrix<double, RA, CA>& Ad,
+
59  const Eigen::Matrix<double, RB, CB>& Bd,
+
60  const Eigen::Matrix<double, CB, CB>& adjC) {}
+
61 
+
62  inline void chainA(Eigen::Matrix<var, RA, CA>& A,
+
63  const Eigen::Matrix<double, RB, CB>& Bd,
+
64  const Eigen::Matrix<double, CB, CB>& adjC) {
+
65  Eigen::Matrix<double, RA, CA> adjA(Bd*adjC*Bd.transpose());
+
66  for (int j = 0; j < A.cols(); j++) {
+
67  for (int i = 0; i < A.rows(); i++) {
+
68  A(i, j).vi_->adj_ += adjA(i, j);
+
69  }
+
70  }
+
71  }
+
72  inline void chainB(Eigen::Matrix<var, RB, CB>& B,
+
73  const Eigen::Matrix<double, RA, CA>& Ad,
+
74  const Eigen::Matrix<double, RB, CB>& Bd,
+
75  const Eigen::Matrix<double, CB, CB>& adjC) {
+
76  Eigen::Matrix<double, RA, CA> adjB(Ad * Bd * adjC.transpose()
+
77  + Ad.transpose()*Bd*adjC);
+
78  for (int j = 0; j < B.cols(); j++)
+
79  for (int i = 0; i < B.rows(); i++)
+
80  B(i, j).vi_->adj_ += adjB(i, j);
+
81  }
+
82 
+
83  inline void chainAB(Eigen::Matrix<TA, RA, CA>& A,
+
84  Eigen::Matrix<TB, RB, CB>& B,
+
85  const Eigen::Matrix<double, RA, CA>& Ad,
+
86  const Eigen::Matrix<double, RB, CB>& Bd,
+
87  const Eigen::Matrix<double, CB, CB>& adjC) {
+
88  chainA(A, Bd, adjC);
+
89  chainB(B, Ad, Bd, adjC);
+
90  }
+
91 
+
92  public:
+
93  quad_form_vari(const Eigen::Matrix<TA, RA, CA>& A,
+
94  const Eigen::Matrix<TB, RB, CB>& B,
+
95  bool symmetric = false)
+
96  : vari(0.0) {
+
97  _impl
+
98  = new quad_form_vari_alloc<TA, RA, CA, TB, RB, CB>(A, B, symmetric);
+
99  }
+
100 
+
101  virtual void chain() {
+
102  using stan::math::value_of;
+
103  Eigen::Matrix<double, CB, CB> adjC(_impl->C_.rows(),
+
104  _impl->C_.cols());
+
105 
+
106  for (int j = 0; j < _impl->C_.cols(); j++)
+
107  for (int i = 0; i < _impl->C_.rows(); i++)
+
108  adjC(i, j) = _impl->C_(i, j).vi_->adj_;
+
109 
+
110  chainAB(_impl->A_, _impl->B_,
+
111  value_of(_impl->A_), value_of(_impl->B_),
+
112  adjC);
+
113  }
+
114 
+
115  quad_form_vari_alloc<TA, RA, CA, TB, RB, CB> *_impl;
+
116  };
+
117  }
+
118 
+
119  template <typename TA, int RA, int CA, typename TB, int RB, int CB>
+
120  inline typename
+
121  boost::enable_if_c< boost::is_same<TA, var>::value ||
+
122  boost::is_same<TB, var>::value,
+
123  Eigen::Matrix<var, CB, CB> >::type
+
124  quad_form(const Eigen::Matrix<TA, RA, CA>& A,
+
125  const Eigen::Matrix<TB, RB, CB>& B) {
+
126  stan::math::check_square("quad_form", "A", A);
+ +
128  "A", A,
+
129  "B", B);
+
130 
+
131  quad_form_vari<TA, RA, CA, TB, RB, CB> *baseVari
+
132  = new quad_form_vari<TA, RA, CA, TB, RB, CB>(A, B);
+
133 
+
134  return baseVari->_impl->C_;
+
135  }
+
136  template <typename TA, int RA, int CA, typename TB, int RB>
+
137  inline typename
+
138  boost::enable_if_c< boost::is_same<TA, var>::value ||
+
139  boost::is_same<TB, var>::value,
+
140  var >::type
+
141  quad_form(const Eigen::Matrix<TA, RA, CA>& A,
+
142  const Eigen::Matrix<TB, RB, 1>& B) {
+
143  stan::math::check_square("quad_form", "A", A);
+ +
145  "A", A,
+
146  "B", B);
+
147 
+
148  quad_form_vari<TA, RA, CA, TB, RB, 1> *baseVari
+
149  = new quad_form_vari<TA, RA, CA, TB, RB, 1>(A, B);
+
150 
+
151  return baseVari->_impl->C_(0, 0);
+
152  }
+
153 
+
154  }
+
155 }
+
156 
+
157 #endif
+
bool _sym
Definition: quad_form.hpp:48
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
Eigen::Matrix< TB, RB, CB > B_
Definition: quad_form.hpp:46
+ +
Eigen::Matrix< TA, RA, CA > A_
Definition: quad_form.hpp:45
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
int cols(const Eigen::Matrix< T, R, C > &m)
Return the number of columns in the specified matrix, vector, or row vector.
Definition: cols.hpp:20
+ + +
Eigen::Matrix< var, CB, CB > C_
Definition: quad_form.hpp:47
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
Eigen::Matrix< T, CB, CB > quad_form(const Eigen::Matrix< T, RA, CA > &A, const Eigen::Matrix< T, RB, CB > &B)
Compute B^T A B.
Definition: quad_form.hpp:21
+
quad_form_vari_alloc< TA, RA, CA, TB, RB, CB > * _impl
Definition: quad_form.hpp:115
+ + +
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2quad__form__sym_8hpp.html b/doc/api/html/rev_2mat_2fun_2quad__form__sym_8hpp.html new file mode 100644 index 00000000000..3680d5b53f7 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2quad__form__sym_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/quad_form_sym.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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quad_form_sym.hpp File Reference
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template<typename TA , int RA, int CA, typename TB , int RB, int CB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, Eigen::Matrix< var, CB, CB > >::type stan::math::quad_form_sym (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, CB > &B)
 
template<typename TA , int RA, int CA, typename TB , int RB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, var >::type stan::math::quad_form_sym (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, 1 > &B)
 
+
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diff --git a/doc/api/html/rev_2mat_2fun_2quad__form__sym_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2quad__form__sym_8hpp_source.html new file mode 100644 index 00000000000..5f40a44a285 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2quad__form__sym_8hpp_source.html @@ -0,0 +1,183 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/quad_form_sym.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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quad_form_sym.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_QUAD_FORM_SYM_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_QUAD_FORM_SYM_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits.hpp>
+
6 #include <stan/math/rev/core.hpp>
+ + + + + + + + + +
16 
+
17 namespace stan {
+
18  namespace math {
+
19 
+
20  template <typename TA, int RA, int CA, typename TB, int RB, int CB>
+
21  inline typename
+
22  boost::enable_if_c< boost::is_same<TA, var>::value ||
+
23  boost::is_same<TB, var>::value,
+
24  Eigen::Matrix<var, CB, CB> >::type
+
25  quad_form_sym(const Eigen::Matrix<TA, RA, CA>& A,
+
26  const Eigen::Matrix<TB, RB, CB>& B) {
+
27  stan::math::check_square("quad_form", "A", A);
+
28  stan::math::check_symmetric("quad_form_sym", "A", A);
+
29  stan::math::check_multiplicable("quad_form_sym",
+
30  "A", A,
+
31  "B", B);
+
32 
+
33  quad_form_vari<TA, RA, CA, TB, RB, CB> *baseVari
+
34  = new quad_form_vari<TA, RA, CA, TB, RB, CB>(A, B, true);
+
35 
+
36  return baseVari->_impl->C_;
+
37  }
+
38  template <typename TA, int RA, int CA, typename TB, int RB>
+
39  inline typename
+
40  boost::enable_if_c< boost::is_same<TA, var>::value ||
+
41  boost::is_same<TB, var>::value,
+
42  var >::type
+
43  quad_form_sym(const Eigen::Matrix<TA, RA, CA>& A,
+
44  const Eigen::Matrix<TB, RB, 1>& B) {
+
45  stan::math::check_square("quad_form", "A", A);
+
46  stan::math::check_symmetric("quad_form_sym", "A", A);
+
47  stan::math::check_multiplicable("quad_form_sym",
+
48  "A", A,
+
49  "B", B);
+
50 
+
51  quad_form_vari<TA, RA, CA, TB, RB, 1> *baseVari
+
52  = new quad_form_vari<TA, RA, CA, TB, RB, 1>(A, B, true);
+
53 
+
54  return baseVari->_impl->C_(0, 0);
+
55  }
+
56  }
+
57 }
+
58 
+
59 #endif
+ + + + + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + +
Eigen::Matrix< fvar< T >, CB, CB > quad_form_sym(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< double, RB, CB > &B)
+
bool check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is symmetric.
+ + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + +
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2rows__dot__product_8hpp.html b/doc/api/html/rev_2mat_2fun_2rows__dot__product_8hpp.html new file mode 100644 index 00000000000..3637231bae1 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2rows__dot__product_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/rows_dot_product.hpp File Reference + + + + + + + + + + +
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template<typename T1 , int R1, int C1, typename T2 , int R2, int C2>
boost::enable_if_c< boost::is_same< T1, var >::value||boost::is_same< T2, var >::value, Eigen::Matrix< var, R1, 1 > >::type stan::math::rows_dot_product (const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
 
+
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diff --git a/doc/api/html/rev_2mat_2fun_2rows__dot__product_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2rows__dot__product_8hpp_source.html new file mode 100644 index 00000000000..1f46c7c7afe --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2rows__dot__product_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/rows_dot_product.hpp Source File + + + + + + + + + + +
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rows_dot_product.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_ROWS_DOT_PRODUCT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_ROWS_DOT_PRODUCT_HPP
+
3 
+ + + + + +
9 #include <stan/math/rev/core.hpp>
+ + + +
13 #include <boost/utility/enable_if.hpp>
+
14 #include <boost/type_traits.hpp>
+
15 #include <vector>
+
16 
+
17 namespace stan {
+
18  namespace math {
+
19 
+
20  template<typename T1, int R1, int C1, typename T2, int R2, int C2>
+
21  inline
+
22  typename boost::enable_if_c<boost::is_same<T1, var>::value ||
+
23  boost::is_same<T2, var>::value,
+
24  Eigen::Matrix<var, R1, 1> >::type
+
25  rows_dot_product(const Eigen::Matrix<T1, R1, C1>& v1,
+
26  const Eigen::Matrix<T2, R2, C2>& v2) {
+ +
28  "v1", v1,
+
29  "v2", v2);
+
30  Eigen::Matrix<var, R1, 1> ret(v1.rows(), 1);
+
31  for (size_type j = 0; j < v1.rows(); ++j) {
+
32  ret(j) = var(new dot_product_vari<T1, T2>(v1.row(j), v2.row(j)));
+
33  }
+
34  return ret;
+
35  }
+
36  }
+
37 }
+
38 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ +
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ + + +
Eigen::Matrix< fvar< T >, R1, 1 > rows_dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2sd_8hpp.html b/doc/api/html/rev_2mat_2fun_2sd_8hpp.html new file mode 100644 index 00000000000..a36c19fb2b6 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2sd_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/sd.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
+
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+ +
+ + +
+
+ +
+
sd.hpp File Reference
+
+
+
#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/mean.hpp>
+#include <stan/math/rev/core.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <cmath>
+#include <vector>
+
+

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var stan::math::sd (const std::vector< var > &v)
 Return the sample standard deviation of the specified standard vector. More...
 
template<int R, int C>
var stan::math::sd (const Eigen::Matrix< var, R, C > &m)
 
+
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2sd_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2sd_8hpp_source.html new file mode 100644 index 00000000000..01faccecbaa --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2sd_8hpp_source.html @@ -0,0 +1,209 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/sd.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
sd.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_SD_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_SD_HPP
+
3 
+ + + +
7 #include <stan/math/rev/core.hpp>
+
8 #include <boost/math/tools/promotion.hpp>
+
9 #include <cmath>
+
10 #include <vector>
+
11 
+
12 namespace stan {
+
13 
+
14  namespace math {
+
15 
+
16  namespace { // anonymous
+
17 
+
18  // if x.size() = N, and x[i] = x[j] =
+
19  // then lim sd(x) -> 0 [ d/dx[n] sd(x) ] = sqrt(N) / N
+
20 
+
21  var calc_sd(size_t size,
+
22  const var* dtrs) {
+
23  using std::sqrt;
+
24  vari** varis
+
25  = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
26  .alloc(size * sizeof(vari*)));
+
27  for (size_t i = 0; i < size; ++i)
+
28  varis[i] = dtrs[i].vi_;
+
29  double sum = 0.0;
+
30  for (size_t i = 0; i < size; ++i)
+
31  sum += dtrs[i].vi_->val_;
+
32  double mean = sum / size;
+
33  double sum_of_squares = 0;
+
34  for (size_t i = 0; i < size; ++i) {
+
35  double diff = dtrs[i].vi_->val_ - mean;
+
36  sum_of_squares += diff * diff;
+
37  }
+
38  double variance = sum_of_squares / (size - 1);
+
39  double sd = sqrt(variance);
+
40  double* partials
+
41  = reinterpret_cast<double*>(ChainableStack::memalloc_
+
42  .alloc(size * sizeof(double)));
+
43  if (sum_of_squares < 1e-20) {
+
44  double grad_limit = 1 / std::sqrt(static_cast<double>(size));
+
45  for (size_t i = 0; i < size; ++i)
+
46  partials[i] = grad_limit;
+
47  } else {
+
48  double multiplier = 1 / (sd * (size - 1));
+
49  for (size_t i = 0; i < size; ++i)
+
50  partials[i] = multiplier * (dtrs[i].vi_->val_ - mean);
+
51  }
+
52  return var(new stored_gradient_vari(sd, size,
+
53  varis, partials));
+
54  }
+
55 
+
56  }
+
57 
+
65  var sd(const std::vector<var>& v) {
+
66  stan::math::check_nonzero_size("sd", "v", v);
+
67  if (v.size() == 1) return 0;
+
68  return calc_sd(v.size(), &v[0]);
+
69  }
+
70 
+
71  /*
+
72  * Return the sample standard deviation of the specified vector,
+
73  * row vector, or matrix. Raise domain error if size is not
+
74  * greater than zero.
+
75  *
+
76  * @tparam R number of rows
+
77  * @tparam C number of columns
+
78  * @param[in] m input matrix
+
79  * @return sample standard deviation of specified matrix
+
80  */
+
81  template <int R, int C>
+
82  var sd(const Eigen::Matrix<var, R, C>& m) {
+
83  stan::math::check_nonzero_size("sd", "m", m);
+
84  if (m.size() == 1) return 0;
+
85  return calc_sd(m.size(), &m(0));
+
86  }
+
87 
+
88  }
+
89 }
+
90 
+
91 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
boost::math::tools::promote_args< T >::type sd(const std::vector< T > &v)
Returns the unbiased sample standard deviation of the coefficients in the specified column vector...
Definition: sd.hpp:22
+
boost::math::tools::promote_args< T >::type variance(const std::vector< T > &v)
Returns the sample variance (divide by length - 1) of the coefficients in the specified standard vect...
Definition: variance.hpp:24
+ +
boost::math::tools::promote_args< T >::type mean(const std::vector< T > &v)
Returns the sample mean (i.e., average) of the coefficients in the specified standard vector...
Definition: mean.hpp:23
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2softmax_8hpp.html b/doc/api/html/rev_2mat_2fun_2softmax_8hpp.html new file mode 100644 index 00000000000..65bd4b8246d --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2softmax_8hpp.html @@ -0,0 +1,191 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/softmax.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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+
softmax.hpp File Reference
+
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Go to the source code of this file.

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+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

Eigen::Matrix< var, Eigen::Dynamic, 1 > stan::math::softmax (const Eigen::Matrix< var, Eigen::Dynamic, 1 > &alpha)
 Return the softmax of the specified Eigen vector. More...
 
+

Variable Documentation

+ +
+
+ + + + +
vari** alpha_
+
+ +

Definition at line 16 of file softmax.hpp.

+ +
+
+ +
+
+ + + + +
const int idx_
+
+ +

Definition at line 19 of file softmax.hpp.

+ +
+
+ +
+
+ + + + +
const int size_
+
+ +

Definition at line 18 of file softmax.hpp.

+ +
+
+ +
+
+ + + + +
const double* softmax_alpha_
+
+ +

Definition at line 17 of file softmax.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2softmax_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2softmax_8hpp_source.html new file mode 100644 index 00000000000..689c25ad92b --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2softmax_8hpp_source.html @@ -0,0 +1,213 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/softmax.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
softmax.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_SOFTMAX_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_SOFTMAX_HPP
+
3 
+ + + +
7 #include <stan/math/rev/core.hpp>
+
8 #include <vector>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class softmax_elt_vari : public vari {
+
15  private:
+
16  vari** alpha_;
+
17  const double* softmax_alpha_;
+
18  const int size_; // array sizes
+
19  const int idx_; // in in softmax output
+
20 
+
21  public:
+
22  softmax_elt_vari(double val,
+
23  vari** alpha,
+
24  const double* softmax_alpha,
+
25  int size,
+
26  int idx)
+
27  : vari(val),
+
28  alpha_(alpha),
+
29  softmax_alpha_(softmax_alpha),
+
30  size_(size),
+
31  idx_(idx) {
+
32  }
+
33  void chain() {
+
34  for (int m = 0; m < size_; ++m) {
+
35  if (m == idx_) {
+
36  alpha_[m]->adj_
+
37  += adj_ * softmax_alpha_[idx_] * (1 - softmax_alpha_[m]);
+
38  } else {
+
39  alpha_[m]->adj_
+
40  -= adj_ * softmax_alpha_[idx_] * softmax_alpha_[m];
+
41  }
+
42  }
+
43  }
+
44  };
+
45  }
+
46 
+
47 
+
58  inline Eigen::Matrix<var, Eigen::Dynamic, 1>
+
59  softmax(const Eigen::Matrix<var, Eigen::Dynamic, 1>& alpha) {
+
60  using Eigen::Matrix;
+
61  using Eigen::Dynamic;
+
62 
+
63  stan::math::check_nonzero_size("softmax", "alpha", alpha);
+
64 
+
65  vari** alpha_vi_array
+
66  = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
67  .alloc(sizeof(vari*) * alpha.size()));
+
68  for (int i = 0; i < alpha.size(); ++i)
+
69  alpha_vi_array[i] = alpha(i).vi_;
+
70 
+
71  Matrix<double, Dynamic, 1> alpha_d(alpha.size());
+
72  for (int i = 0; i < alpha_d.size(); ++i)
+
73  alpha_d(i) = alpha(i).val();
+
74 
+
75  Matrix<double, Dynamic, 1> softmax_alpha_d
+
76  = stan::math::softmax(alpha_d);
+
77 
+
78  double* softmax_alpha_d_array
+
79  = reinterpret_cast<double*>(ChainableStack::memalloc_
+
80  .alloc(sizeof(double) * alpha_d.size()));
+
81  for (int i = 0; i < alpha_d.size(); ++i)
+
82  softmax_alpha_d_array[i] = softmax_alpha_d(i);
+
83 
+
84  Matrix<var, Dynamic, 1> softmax_alpha(alpha.size());
+
85  for (int k = 0; k < softmax_alpha.size(); ++k)
+
86  softmax_alpha(k) = var(new softmax_elt_vari(softmax_alpha_d[k],
+
87  alpha_vi_array,
+
88  softmax_alpha_d_array,
+
89  alpha.size(),
+
90  k));
+
91  return softmax_alpha;
+
92  }
+
93 
+
94 
+
95  }
+
96 }
+
97 
+
98 #endif
+
const int size_
Definition: softmax.hpp:18
+ +
Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > softmax(const Eigen::Matrix< fvar< T >, Eigen::Dynamic, 1 > &alpha)
Definition: softmax.hpp:14
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+ +
const double * softmax_alpha_
Definition: softmax.hpp:17
+
const int idx_
Definition: softmax.hpp:19
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
vari ** alpha_
Definition: softmax.hpp:16
+ +
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2sort__asc_8hpp.html b/doc/api/html/rev_2mat_2fun_2sort__asc_8hpp.html new file mode 100644 index 00000000000..baa54b37f8e --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2sort__asc_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/sort_asc.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+ +
+
sort_asc.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <algorithm>
+#include <functional>
+#include <valarray>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + + +

+Functions

std::vector< var > stan::math::sort_asc (std::vector< var > xs)
 Return the specified standard vector in ascending order with gradients kept. More...
 
template<int R, int C>
Eigen::Matrix< var, R, C > stan::math::sort_asc (Eigen::Matrix< var, R, C > xs)
 Return the specified eigen vector in ascending order with gradients kept. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2sort__asc_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2sort__asc_8hpp_source.html new file mode 100644 index 00000000000..3bd358c4676 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2sort__asc_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/sort_asc.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+ + +
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+
+
+
sort_asc.hpp
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+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_SORT_ASC_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_SORT_ASC_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <algorithm> // std::sort
+
7 #include <functional> // std::greater
+
8 #include <valarray>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
21  inline std::vector<var> sort_asc(std::vector<var> xs) {
+
22  std::sort(xs.begin(), xs.end());
+
23  return xs;
+
24  }
+
25 
+
33  template <int R, int C>
+
34  inline typename Eigen::Matrix<var, R, C>
+
35  sort_asc(Eigen::Matrix<var, R, C> xs) {
+
36  std::sort(xs.data(), xs.data()+xs.size());
+
37  return xs;
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+ + + +
std::vector< fvar< T > > sort_asc(std::vector< fvar< T > > xs)
Definition: sort_asc.hpp:17
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2sort__desc_8hpp.html b/doc/api/html/rev_2mat_2fun_2sort__desc_8hpp.html new file mode 100644 index 00000000000..d3a6a26bd65 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2sort__desc_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/sort_desc.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+
sort_desc.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <algorithm>
+#include <functional>
+#include <valarray>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + + + + + +

+Functions

std::vector< var > stan::math::sort_desc (std::vector< var > xs)
 Return the specified standard vector in descending order with gradients kept. More...
 
template<int R, int C>
Eigen::Matrix< var, R, C > stan::math::sort_desc (Eigen::Matrix< var, R, C > xs)
 Return the specified eigen vector in descending order with gradients kept. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2sort__desc_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2sort__desc_8hpp_source.html new file mode 100644 index 00000000000..346633ac72e --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2sort__desc_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/sort_desc.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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sort_desc.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_SORT_DESC_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_SORT_DESC_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <algorithm> // std::sort
+
7 #include <functional> // std::greater
+
8 #include <valarray>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
21  inline std::vector<var> sort_desc(std::vector<var> xs) {
+
22  std::sort(xs.begin(), xs.end(), std::greater<var>());
+
23  return xs;
+
24  }
+
25 
+
33  template <int R, int C>
+
34  inline typename Eigen::Matrix<var, R, C>
+
35  sort_desc(Eigen::Matrix<var, R, C> xs) {
+
36  std::sort(xs.data(), xs.data()+xs.size(), std::greater<var>());
+
37  return xs;
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+ +
std::vector< fvar< T > > sort_desc(std::vector< fvar< T > > xs)
Definition: sort_desc.hpp:17
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2squared__distance_8hpp.html b/doc/api/html/rev_2mat_2fun_2squared__distance_8hpp.html new file mode 100644 index 00000000000..393667f8207 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2squared__distance_8hpp.html @@ -0,0 +1,189 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/squared_distance.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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squared_distance.hpp File Reference
+
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+ + + + + + + + + + +

+Functions

template<int R1, int C1, int R2, int C2>
var stan::math::squared_distance (const Eigen::Matrix< var, R1, C1 > &v1, const Eigen::Matrix< var, R2, C2 > &v2)
 
template<int R1, int C1, int R2, int C2>
var stan::math::squared_distance (const Eigen::Matrix< var, R1, C1 > &v1, const Eigen::Matrix< double, R2, C2 > &v2)
 
template<int R1, int C1, int R2, int C2>
var stan::math::squared_distance (const Eigen::Matrix< double, R1, C1 > &v1, const Eigen::Matrix< var, R2, C2 > &v2)
 
+

Variable Documentation

+ +
+
+ + + + +
size_t length_
+
+ +

Definition at line 26 of file squared_distance.hpp.

+ +
+
+ +
+
+ + + + +
vari** v1_
+
+ +

Definition at line 24 of file squared_distance.hpp.

+ +
+
+ +
+
+ + + + +
double* v2_
+
+ +

Definition at line 25 of file squared_distance.hpp.

+ +
+
+
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2squared__distance_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2squared__distance_8hpp_source.html new file mode 100644 index 00000000000..ec20cb5f3f6 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2squared__distance_8hpp_source.html @@ -0,0 +1,274 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/squared_distance.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
squared_distance.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_SQUARED_DISTANCE_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_SQUARED_DISTANCE_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + + + + + + + +
14 #include <vector>
+
15 
+
16 namespace stan {
+
17 
+
18  namespace math {
+
19 
+
20  namespace {
+
21 
+
22  class squared_distance_vv_vari : public vari {
+
23  protected:
+
24  vari** v1_;
+
25  vari** v2_;
+
26  size_t length_;
+
27 
+
28  template <int R1, int C1, int R2, int C2>
+
29  inline static double
+
30  var_squared_distance(const Eigen::Matrix<var, R1, C1> &v1,
+
31  const Eigen::Matrix<var, R2, C2> &v2) {
+
32  using Eigen::Matrix;
+ +
34  typedef typename index_type<Matrix<var, R1, R2> >::type idx_t;
+
35  double result = 0;
+
36  for (idx_t i = 0; i < v1.size(); i++) {
+
37  double diff = v1(i).vi_->val_ - v2(i).vi_->val_;
+
38  result += diff*diff;
+
39  }
+
40  return result;
+
41  }
+
42 
+
43  public:
+
44  template<int R1, int C1, int R2, int C2>
+
45  squared_distance_vv_vari(const Eigen::Matrix<var, R1, C1> &v1,
+
46  const Eigen::Matrix<var, R2, C2> &v2)
+
47  : vari(var_squared_distance(v1, v2)), length_(v1.size()) {
+
48  v1_ = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
49  .alloc(length_*sizeof(vari*)));
+
50  for (size_t i = 0; i < length_; i++)
+
51  v1_[i] = v1(i).vi_;
+
52 
+
53  v2_ = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
54  .alloc(length_*sizeof(vari*)));
+
55  for (size_t i = 0; i < length_; i++)
+
56  v2_[i] = v2(i).vi_;
+
57  }
+
58  virtual void chain() {
+
59  for (size_t i = 0; i < length_; i++) {
+
60  double di = 2 * adj_ * (v1_[i]->val_ - v2_[i]->val_);
+
61  v1_[i]->adj_ += di;
+
62  v2_[i]->adj_ -= di;
+
63  }
+
64  }
+
65  };
+
66  class squared_distance_vd_vari : public vari {
+
67  protected:
+
68  vari** v1_;
+
69  double* v2_;
+
70  size_t length_;
+
71 
+
72  template<int R1, int C1, int R2, int C2>
+
73  inline static double
+
74  var_squared_distance(const Eigen::Matrix<var, R1, C1> &v1,
+
75  const Eigen::Matrix<double, R2, C2> &v2) {
+
76  using Eigen::Matrix;
+ +
78  typedef typename index_type<Matrix<double, R1, C1> >::type idx_t;
+
79 
+
80  double result = 0;
+
81  for (idx_t i = 0; i < v1.size(); i++) {
+
82  double diff = v1(i).vi_->val_ - v2(i);
+
83  result += diff*diff;
+
84  }
+
85  return result;
+
86  }
+
87 
+
88  public:
+
89  template<int R1, int C1, int R2, int C2>
+
90  squared_distance_vd_vari(const Eigen::Matrix<var, R1, C1> &v1,
+
91  const Eigen::Matrix<double, R2, C2> &v2)
+
92  : vari(var_squared_distance(v1, v2)), length_(v1.size()) {
+
93  v1_ = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
94  .alloc(length_*sizeof(vari*)));
+
95  for (size_t i = 0; i < length_; i++)
+
96  v1_[i] = v1(i).vi_;
+
97 
+
98  v2_ = reinterpret_cast<double*>(ChainableStack::memalloc_
+
99  .alloc(length_*sizeof(double)));
+
100  for (size_t i = 0; i < length_; i++)
+
101  v2_[i] = v2(i);
+
102  }
+
103  virtual void chain() {
+
104  for (size_t i = 0; i < length_; i++) {
+
105  v1_[i]->adj_ += 2 * adj_ * (v1_[i]->val_ - v2_[i]);
+
106  }
+
107  }
+
108  };
+
109  }
+
110 
+
111  template<int R1, int C1, int R2, int C2>
+
112  inline var squared_distance(const Eigen::Matrix<var, R1, C1>& v1,
+
113  const Eigen::Matrix<var, R2, C2>& v2) {
+
114  stan::math::check_vector("squared_distance", "v1", v1);
+
115  stan::math::check_vector("squared_distance", "v2", v2);
+
116  stan::math::check_matching_sizes("squared_distance",
+
117  "v1", v1,
+
118  "v2", v2);
+
119  return var(new squared_distance_vv_vari(v1, v2));
+
120  }
+
121  template<int R1, int C1, int R2, int C2>
+
122  inline var squared_distance(const Eigen::Matrix<var, R1, C1>& v1,
+
123  const Eigen::Matrix<double, R2, C2>& v2) {
+
124  stan::math::check_vector("squared_distance", "v1", v1);
+
125  stan::math::check_vector("squared_distance", "v2", v2);
+
126  stan::math::check_matching_sizes("squared_distance",
+
127  "v1", v1,
+
128  "v2", v2);
+
129  return var(new squared_distance_vd_vari(v1, v2));
+
130  }
+
131  template<int R1, int C1, int R2, int C2>
+
132  inline var squared_distance(const Eigen::Matrix<double, R1, C1>& v1,
+
133  const Eigen::Matrix<var, R2, C2>& v2) {
+
134  stan::math::check_vector("squared_distance", "v1", v1);
+
135  stan::math::check_vector("squared_distance", "v2", v2);
+
136  stan::math::check_matching_sizes("squared_distance",
+
137  "v1", v1,
+
138  "v2", v2);
+
139  return var(new squared_distance_vd_vari(v2, v1));
+
140  }
+
141  }
+
142 }
+
143 #endif
+ +
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ + + +
boost::math::tools::promote_args< T1, T2 >::type squared_distance(const Eigen::Matrix< T1, R1, C1 > &v1, const Eigen::Matrix< T2, R2, C2 > &v2)
Returns the squared distance between the specified vectors.
+ +
vari ** v1_
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
size_t length_
+ + +
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
+ + +
vari ** v2_
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+ +
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2stan__print_8hpp.html b/doc/api/html/rev_2mat_2fun_2stan__print_8hpp.html new file mode 100644 index 00000000000..ff7f29935fd --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2stan__print_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/stan_print.hpp File Reference + + + + + + + + + + +
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+
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#include <stan/math/rev/core.hpp>
+#include <ostream>
+
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+ + + +

+Functions

void stan::math::stan_print (std::ostream *o, const var &x)
 
+
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2stan__print_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2stan__print_8hpp_source.html new file mode 100644 index 00000000000..afb7214ce58 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2stan__print_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/stan_print.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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stan_print.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_STAN_PRINT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_STAN_PRINT_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <ostream>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  void stan_print(std::ostream* o, const var& x) {
+
11  *o << x.val();
+
12  }
+
13 
+
14  }
+
15 }
+
16 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
void stan_print(std::ostream *o, const T &x)
Definition: stan_print.hpp:12
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2sum_8hpp.html b/doc/api/html/rev_2mat_2fun_2sum_8hpp.html new file mode 100644 index 00000000000..577c06334a8 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2sum_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/sum.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
+ +
+
sum.hpp File Reference
+
+
+ +

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+ + + + + +

+Classes

class  stan::math::sum_eigen_v_vari
 Class for representing sums with constructors for Eigen. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<int R, int C>
var stan::math::sum (const Eigen::Matrix< var, R, C > &m)
 Returns the sum of the coefficients of the specified matrix, column vector or row vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2sum_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2sum_8hpp_source.html new file mode 100644 index 00000000000..71ff25cfc50 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2sum_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/sum.hpp Source File + + + + + + + + + + +
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+
+
sum.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_SUM_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_SUM_HPP
+
3 
+ + +
6 #include <stan/math/rev/core.hpp>
+ +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
17  class sum_eigen_v_vari : public sum_v_vari {
+
18  protected:
+
19  template <typename Derived>
+
20  inline static double sum_of_val(const Eigen::DenseBase<Derived>& v) {
+
21  double result = 0;
+
22  for (int i = 0; i < v.size(); i++)
+
23  result += v(i).vi_->val_;
+
24  return result;
+
25  }
+
26 
+
27  public:
+
28  template <int R1, int C1>
+
29  explicit sum_eigen_v_vari(const Eigen::Matrix<var, R1, C1> &v1)
+
30  : sum_v_vari(sum_of_val(v1),
+
31  reinterpret_cast<vari**>(ChainableStack::memalloc_
+
32  .alloc(v1.size()
+
33  * sizeof(vari*))),
+
34  v1.size()) {
+
35  for (size_t i = 0; i < length_; i++)
+
36  v_[i] = v1(i).vi_;
+
37  }
+
38  };
+
39 
+
49  template <int R, int C>
+
50  inline var sum(const Eigen::Matrix<var, R, C>& m) {
+
51  if (m.size() == 0)
+
52  return 0.0;
+
53  return var(new sum_eigen_v_vari(m));
+
54  }
+
55 
+
56  }
+
57 }
+
58 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + +
sum_eigen_v_vari(const Eigen::Matrix< var, R1, C1 > &v1)
Definition: sum.hpp:29
+ +
static double sum_of_val(const Eigen::DenseBase< Derived > &v)
Definition: sum.hpp:20
+
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ + + +
Class for representing sums with constructors for Eigen.
Definition: sum.hpp:17
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
Class for sums of variables constructed with standard vectors.
Definition: sum.hpp:14
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2tcrossprod_8hpp.html b/doc/api/html/rev_2mat_2fun_2tcrossprod_8hpp.html new file mode 100644 index 00000000000..63cfcf3ceb5 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2tcrossprod_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/tcrossprod.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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+
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+
tcrossprod.hpp File Reference
+
+
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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

matrix_v stan::math::tcrossprod (const matrix_v &M)
 Returns the result of post-multiplying a matrix by its own transpose. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2tcrossprod_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2tcrossprod_8hpp_source.html new file mode 100644 index 00000000000..f3eb33df6b1 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2tcrossprod_8hpp_source.html @@ -0,0 +1,178 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/tcrossprod.hpp Source File + + + + + + + + + + +
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tcrossprod.hpp
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1 #ifndef STAN_MATH_REV_MAT_FUN_TCROSSPROD_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_TCROSSPROD_HPP
+
3 
+ + +
6 #include <stan/math/rev/core.hpp>
+ + + + + +
12 #include <boost/math/tools/promotion.hpp>
+
13 #include <vector>
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
24  inline matrix_v
+
25  tcrossprod(const matrix_v& M) {
+
26  if (M.rows() == 0)
+
27  return matrix_v(0, 0);
+
28  // if (M.rows() == 1)
+
29  // return M * M.transpose();
+
30 
+
31  // WAS JUST THIS
+
32  // matrix_v result(M.rows(), M.rows());
+
33  // return result.setZero().selfadjointView<Eigen::Upper>().rankUpdate(M);
+
34 
+
35  matrix_v MMt(M.rows(), M.rows());
+
36 
+
37  vari** vs
+
38  = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
39  .alloc((M.rows() * M.cols())
+
40  * sizeof(vari*)));
+
41  int pos = 0;
+
42  for (int m = 0; m < M.rows(); ++m)
+
43  for (int n = 0; n < M.cols(); ++n)
+
44  vs[pos++] = M(m, n).vi_;
+
45  for (int m = 0; m < M.rows(); ++m)
+
46  MMt(m, m) = var(new dot_self_vari(vs + m * M.cols(), M.cols()));
+
47  for (int m = 0; m < M.rows(); ++m) {
+
48  for (int n = 0; n < m; ++n) {
+
49  MMt(m, n) = var(new dot_product_vari<var, var>(vs + m * M.cols(),
+
50  vs + n * M.cols(),
+
51  M.cols()));
+
52  MMt(n, m) = MMt(m, n);
+
53  }
+
54  }
+
55  return MMt;
+
56  }
+
57 
+
58  }
+
59 }
+
60 #endif
+ + + + +
The variable implementation base class.
Definition: vari.hpp:30
+
Eigen::Matrix< fvar< T >, R, R > tcrossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: tcrossprod.hpp:17
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
Eigen::Matrix< var, Eigen::Dynamic, Eigen::Dynamic > matrix_v
The type of a matrix holding stan::math::var values.
Definition: typedefs.hpp:21
+ + + + +
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp.html b/doc/api/html/rev_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp.html new file mode 100644 index 00000000000..947ac16464e --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/trace_gen_inv_quad_form_ldlt.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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trace_gen_inv_quad_form_ldlt.hpp File Reference
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 Matrices and templated mathematical functions.
 
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+Functions

template<typename T1 , int R1, int C1, typename T2 , int R2, int C2, typename T3 , int R3, int C3>
boost::enable_if_c< stan::is_var< T1 >::value||stan::is_var< T2 >::value||stan::is_var< T3 >::value, var >::type stan::math::trace_gen_inv_quad_form_ldlt (const Eigen::Matrix< T1, R1, C1 > &D, const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
 Compute the trace of an inverse quadratic form. More...
 
+
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+
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diff --git a/doc/api/html/rev_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp_source.html new file mode 100644 index 00000000000..a5b287f4e4b --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2trace__gen__inv__quad__form__ldlt_8hpp_source.html @@ -0,0 +1,168 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/trace_gen_inv_quad_form_ldlt.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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trace_gen_inv_quad_form_ldlt.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_TRACE_GEN_INV_QUAD_FORM_LDLT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_TRACE_GEN_INV_QUAD_FORM_LDLT_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+ + +
8 #include <boost/utility/enable_if.hpp>
+ + + +
12 
+
13 namespace stan {
+
14  namespace math {
+
15 
+
21  template <typename T1, int R1, int C1, typename T2, int R2, int C2,
+
22  typename T3, int R3, int C3>
+
23  inline typename
+
24  boost::enable_if_c<stan::is_var<T1>::value ||
+ +
26  stan::is_var<T3>::value, var>::type
+
27  trace_gen_inv_quad_form_ldlt(const Eigen::Matrix<T1, R1, C1> &D,
+ +
29  const Eigen::Matrix<T3, R3, C3> &B) {
+
30  stan::math::check_square("trace_gen_inv_quad_form_ldlt", "D", D);
+
31  stan::math::check_multiplicable("trace_gen_inv_quad_form_ldlt",
+
32  "A", A,
+
33  "B", B);
+
34  stan::math::check_multiplicable("trace_gen_inv_quad_form_ldlt",
+
35  "B", B,
+
36  "D", D);
+
37 
+
38  trace_inv_quad_form_ldlt_impl<T2, R2, C2, T3, R3, C3> *_impl
+
39  = new trace_inv_quad_form_ldlt_impl<T2, R2, C2, T3, R3, C3>(D, A, B);
+
40 
+
41  return var(new trace_inv_quad_form_ldlt_vari<T2, R2, C2, T3, R3, C3>
+
42  (_impl));
+
43  }
+
44 
+
45 
+
46  }
+
47 }
+
48 
+
49 #endif
+ + + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value &&!stan::is_var< T3 >::value, typename boost::math::tools::promote_args< T1, T2, T3 >::type >::type trace_gen_inv_quad_form_ldlt(const Eigen::Matrix< T1, R1, C1 > &D, const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
+ + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+
quad_form_vari_alloc< TA, RA, CA, TB, RB, CB > * _impl
Definition: quad_form.hpp:115
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2trace__gen__quad__form_8hpp.html b/doc/api/html/rev_2mat_2fun_2trace__gen__quad__form_8hpp.html new file mode 100644 index 00000000000..49bb17b4b28 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2trace__gen__quad__form_8hpp.html @@ -0,0 +1,197 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/trace_gen_quad_form.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
trace_gen_quad_form.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename TD , int RD, int CD, typename TA , int RA, int CA, typename TB , int RB, int CB>
boost::enable_if_c< boost::is_same< TD, var >::value||boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, var >::type stan::math::trace_gen_quad_form (const Eigen::Matrix< TD, RD, CD > &D, const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, CB > &B)
 
+

Variable Documentation

+ +
+
+ + + + +
trace_gen_quad_form_vari_alloc<TD, RD, CD, TA, RA, CA, TB, RB, CB>* _impl
+
+ +

Definition at line 104 of file trace_gen_quad_form.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<TA, RA, CA> A_
+
+ +

Definition at line 38 of file trace_gen_quad_form.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<TB, RB, CB> B_
+
+ +

Definition at line 39 of file trace_gen_quad_form.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<TD, RD, CD> D_
+
+ +

Definition at line 37 of file trace_gen_quad_form.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2trace__gen__quad__form_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2trace__gen__quad__form_8hpp_source.html new file mode 100644 index 00000000000..34c509f9968 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2trace__gen__quad__form_8hpp_source.html @@ -0,0 +1,267 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/trace_gen_quad_form.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
trace_gen_quad_form.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_TRACE_GEN_QUAD_FORM_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_TRACE_GEN_QUAD_FORM_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits.hpp>
+ + +
8 #include <stan/math/rev/core.hpp>
+ + + + + + +
15 
+
16 namespace stan {
+
17  namespace math {
+
18  namespace {
+
19  template <typename TD, int RD, int CD,
+
20  typename TA, int RA, int CA,
+
21  typename TB, int RB, int CB>
+
22  class trace_gen_quad_form_vari_alloc : public chainable_alloc {
+
23  public:
+
24  trace_gen_quad_form_vari_alloc(const Eigen::Matrix<TD, RD, CD>& D,
+
25  const Eigen::Matrix<TA, RA, CA>& A,
+
26  const Eigen::Matrix<TB, RB, CB>& B)
+
27  : D_(D), A_(A), B_(B)
+
28  { }
+
29 
+
30  double compute() {
+ + +
33  value_of(A_),
+
34  value_of(B_));
+
35  }
+
36 
+
37  Eigen::Matrix<TD, RD, CD> D_;
+
38  Eigen::Matrix<TA, RA, CA> A_;
+
39  Eigen::Matrix<TB, RB, CB> B_;
+
40  };
+
41 
+
42  template <typename TD, int RD, int CD,
+
43  typename TA, int RA, int CA,
+
44  typename TB, int RB, int CB>
+
45  class trace_gen_quad_form_vari : public vari {
+
46  protected:
+
47  static inline void
+
48  computeAdjoints(const double& adj,
+
49  const Eigen::Matrix<double, RD, CD>& D,
+
50  const Eigen::Matrix<double, RA, CA>& A,
+
51  const Eigen::Matrix<double, RB, CB>& B,
+
52  Eigen::Matrix<var, RD, CD> *varD,
+
53  Eigen::Matrix<var, RA, CA> *varA,
+
54  Eigen::Matrix<var, RB, CB> *varB) {
+
55  Eigen::Matrix<double, CA, CB> AtB;
+
56  Eigen::Matrix<double, RA, CB> BD;
+
57  if (varB || varA)
+
58  BD.noalias() = B*D;
+
59  if (varB || varD)
+
60  AtB.noalias() = A.transpose()*B;
+
61 
+
62  if (varB) {
+
63  Eigen::Matrix<double, RB, CB> adjB(adj*(A*BD + AtB*D.transpose()));
+
64  for (int j = 0; j < B.cols(); j++)
+
65  for (int i = 0; i < B.rows(); i++)
+
66  (*varB)(i, j).vi_->adj_ += adjB(i, j);
+
67  }
+
68  if (varA) {
+
69  Eigen::Matrix<double, RA, CA> adjA(adj*(B*BD.transpose()));
+
70  for (int j = 0; j < A.cols(); j++)
+
71  for (int i = 0; i < A.rows(); i++)
+
72  (*varA)(i, j).vi_->adj_ += adjA(i, j);
+
73  }
+
74  if (varD) {
+
75  Eigen::Matrix<double, RD, CD> adjD(adj*(B.transpose()*AtB));
+
76  for (int j = 0; j < D.cols(); j++)
+
77  for (int i = 0; i < D.rows(); i++)
+
78  (*varD)(i, j).vi_->adj_ += adjD(i, j);
+
79  }
+
80  }
+
81 
+
82 
+
83  public:
+
84  explicit
+
85  trace_gen_quad_form_vari(trace_gen_quad_form_vari_alloc
+
86  <TD, RD, CD, TA, RA, CA, TB, RB, CB> *impl)
+
87  : vari(impl->compute()), _impl(impl) { }
+
88 
+
89  virtual void chain() {
+ +
91  computeAdjoints(adj_,
+
92  value_of(_impl->D_),
+
93  value_of(_impl->A_),
+
94  value_of(_impl->B_),
+
95  reinterpret_cast<Eigen::Matrix<var, RD, CD> *>
+
96  (boost::is_same<TD, var>::value?(&_impl->D_):NULL),
+
97  reinterpret_cast<Eigen::Matrix<var, RA, CA> *>
+
98  (boost::is_same<TA, var>::value?(&_impl->A_):NULL),
+
99  reinterpret_cast<Eigen::Matrix<var, RB, CB> *>
+
100  (boost::is_same<TB, var>::value?(&_impl->B_):NULL));
+
101  }
+
102 
+
103  trace_gen_quad_form_vari_alloc<TD, RD, CD, TA, RA, CA, TB, RB, CB>
+ +
105  };
+
106  }
+
107 
+
108  template <typename TD, int RD, int CD,
+
109  typename TA, int RA, int CA,
+
110  typename TB, int RB, int CB>
+
111  inline typename
+
112  boost::enable_if_c< boost::is_same<TD, var>::value ||
+
113  boost::is_same<TA, var>::value ||
+
114  boost::is_same<TB, var>::value,
+
115  var >::type
+
116  trace_gen_quad_form(const Eigen::Matrix<TD, RD, CD>& D,
+
117  const Eigen::Matrix<TA, RA, CA>& A,
+
118  const Eigen::Matrix<TB, RB, CB>& B) {
+
119  stan::math::check_square("trace_gen_quad_form", "A", A);
+
120  stan::math::check_square("trace_gen_quad_form", "D", D);
+
121  stan::math::check_multiplicable("trace_gen_quad_form",
+
122  "A", A,
+
123  "B", B);
+
124  stan::math::check_multiplicable("trace_gen_quad_form",
+
125  "B", B,
+
126  "D", D);
+
127 
+
128  trace_gen_quad_form_vari_alloc<TD, RD, CD, TA, RA, CA, TB, RB, CB>
+
129  *baseVari
+
130  = new trace_gen_quad_form_vari_alloc<TD, RD, CD, TA, RA, CA, TB, RB, CB>
+
131  (D, A, B);
+
132 
+
133  return var(new trace_gen_quad_form_vari
+
134  <TD, RD, CD, TA, RA, CA, TB, RB, CB>(baseVari));
+
135  }
+
136  }
+
137 }
+
138 
+
139 #endif
+
Eigen::Matrix< TB, RB, CB > B_
+ + +
Eigen::Matrix< TA, RA, CA > A_
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
trace_gen_quad_form_vari_alloc< TD, RD, CD, TA, RA, CA, TB, RB, CB > * _impl
+
Eigen::Matrix< TD, RD, CD > D_
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > trace_gen_quad_form(const Eigen::Matrix< fvar< T >, RD, CD > &D, const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+ + +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp.html b/doc/api/html/rev_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp.html new file mode 100644 index 00000000000..4f61ed2a238 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp.html @@ -0,0 +1,264 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/trace_inv_quad_form_ldlt.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
trace_inv_quad_form_ldlt.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename T2 , int R2, int C2, typename T3 , int R3, int C3>
boost::enable_if_c< stan::is_var< T2 >::value||stan::is_var< T3 >::value, var >::type stan::math::trace_inv_quad_form_ldlt (const stan::math::LDLT_factor< T2, R2, C2 > &A, const Eigen::Matrix< T3, R3, C3 > &B)
 Compute the trace of an inverse quadratic form. More...
 
+

Variable Documentation

+ +
+
+ + + + +
trace_inv_quad_form_ldlt_impl<T2, R2, C2, T3, R3, C3>* _impl
+
+ +

Definition at line 161 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
stan::math::LDLT_factor<T2, R2, C2> _ldlt
+
+ +

Definition at line 82 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
double _value
+
+ +

Definition at line 88 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<vari*, R3, C3> _variB
+
+ +

Definition at line 85 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<vari*, Eigen::Dynamic, Eigen::Dynamic> _variD
+
+ +

Definition at line 84 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<double, R3, C3> AinvB_
+
+ +

Definition at line 86 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<double, C3, C3> C_
+
+ +

Definition at line 87 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> D_
+
+ +

Definition at line 83 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+ +
+
+ + + + +
const int Dtype_
+
+ +

Definition at line 81 of file trace_inv_quad_form_ldlt.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp_source.html new file mode 100644 index 00000000000..f3998dfdbcf --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2trace__inv__quad__form__ldlt_8hpp_source.html @@ -0,0 +1,319 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/trace_inv_quad_form_ldlt.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
trace_inv_quad_form_ldlt.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_TRACE_INV_QUAD_FORM_LDLT_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_TRACE_INV_QUAD_FORM_LDLT_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+ + +
8 #include <boost/utility/enable_if.hpp>
+ + +
11 
+
12 namespace stan {
+
13  namespace math {
+
14  namespace {
+
15  template <typename T2, int R2, int C2, typename T3, int R3, int C3>
+
16  class trace_inv_quad_form_ldlt_impl : public chainable_alloc {
+
17  protected:
+
18  inline void initializeB(const Eigen::Matrix<var, R3, C3> &B,
+
19  bool haveD) {
+
20  Eigen::Matrix<double, R3, C3> Bd(B.rows(), B.cols());
+
21  _variB.resize(B.rows(), B.cols());
+
22  for (int j = 0; j < B.cols(); j++) {
+
23  for (int i = 0; i < B.rows(); i++) {
+
24  _variB(i, j) = B(i, j).vi_;
+
25  Bd(i, j) = B(i, j).val();
+
26  }
+
27  }
+
28  AinvB_ = _ldlt.solve(Bd);
+
29  if (haveD)
+
30  C_.noalias() = Bd.transpose()*AinvB_;
+
31  else
+
32  _value = (Bd.transpose()*AinvB_).trace();
+
33  }
+
34  inline void initializeB(const Eigen::Matrix<double, R3, C3> &B,
+
35  bool haveD) {
+
36  AinvB_ = _ldlt.solve(B);
+
37  if (haveD)
+
38  C_.noalias() = B.transpose()*AinvB_;
+
39  else
+
40  _value = (B.transpose()*AinvB_).trace();
+
41  }
+
42 
+
43  template<int R1, int C1>
+
44  inline void initializeD(const Eigen::Matrix<var, R1, C1> &D) {
+
45  D_.resize(D.rows(), D.cols());
+
46  _variD.resize(D.rows(), D.cols());
+
47  for (int j = 0; j < D.cols(); j++) {
+
48  for (int i = 0; i < D.rows(); i++) {
+
49  _variD(i, j) = D(i, j).vi_;
+
50  D_(i, j) = D(i, j).val();
+
51  }
+
52  }
+
53  }
+
54  template<int R1, int C1>
+
55  inline void initializeD(const Eigen::Matrix<double, R1, C1> &D) {
+
56  D_ = D;
+
57  }
+
58 
+
59  public:
+
60  template<typename T1, int R1, int C1>
+
61  trace_inv_quad_form_ldlt_impl(const Eigen::Matrix<T1, R1, C1> &D,
+ +
63  &A,
+
64  const Eigen::Matrix<T3, R3, C3> &B)
+
65  : Dtype_(stan::is_var<T1>::value),
+
66  _ldlt(A) {
+
67  initializeB(B, true);
+
68  initializeD(D);
+
69 
+
70  _value = (D_*C_).trace();
+
71  }
+
72 
+
73  trace_inv_quad_form_ldlt_impl(const stan::math::LDLT_factor<T2, R2, C2>
+
74  &A,
+
75  const Eigen::Matrix<T3, R3, C3> &B)
+
76  : Dtype_(2),
+
77  _ldlt(A) {
+
78  initializeB(B, false);
+
79  }
+
80 
+
81  const int Dtype_; // 0 = double, 1 = var, 2 = missing
+ +
83  Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> D_;
+
84  Eigen::Matrix<vari*, Eigen::Dynamic, Eigen::Dynamic> _variD;
+
85  Eigen::Matrix<vari*, R3, C3> _variB;
+
86  Eigen::Matrix<double, R3, C3> AinvB_;
+
87  Eigen::Matrix<double, C3, C3> C_;
+
88  double _value;
+
89  };
+
90 
+
91  template <typename T2, int R2, int C2, typename T3, int R3, int C3>
+
92  class trace_inv_quad_form_ldlt_vari : public vari {
+
93  protected:
+
94  static inline
+
95  void
+
96  chainA(const double &adj,
+
97  trace_inv_quad_form_ldlt_impl<double, R2, C2, T3, R3, C3>
+
98  *impl) {
+
99  }
+
100  static inline
+
101  void
+
102  chainB(const double &adj,
+
103  trace_inv_quad_form_ldlt_impl<T2, R2, C2, double, R3, C3>
+
104  *impl) {
+
105  }
+
106 
+
107  static inline
+
108  void
+
109  chainA(const double &adj,
+
110  trace_inv_quad_form_ldlt_impl<var, R2, C2, T3, R3, C3> *impl) {
+
111  Eigen::Matrix<double, R2, C2> aA;
+
112 
+
113  if (impl->Dtype_ != 2)
+
114  aA.noalias() = -adj * (impl->AinvB_ * impl->D_.transpose()
+
115  * impl->AinvB_.transpose());
+
116  else
+
117  aA.noalias() = -adj*(impl->AinvB_ * impl->AinvB_.transpose());
+
118 
+
119  for (int j = 0; j < aA.cols(); j++)
+
120  for (int i = 0; i < aA.rows(); i++)
+
121  impl->_ldlt._alloc->_variA(i, j)->adj_ += aA(i, j);
+
122  }
+
123  static inline
+
124  void
+
125  chainB(const double &adj,
+
126  trace_inv_quad_form_ldlt_impl<T2, R2, C2, var, R3, C3> *impl) {
+
127  Eigen::Matrix<double, R3, C3> aB;
+
128 
+
129  if (impl->Dtype_ != 2)
+
130  aB.noalias() = adj*impl->AinvB_*(impl->D_ + impl->D_.transpose());
+
131  else
+
132  aB.noalias() = 2*adj*impl->AinvB_;
+
133 
+
134  for (int j = 0; j < aB.cols(); j++)
+
135  for (int i = 0; i < aB.rows(); i++)
+
136  impl->_variB(i, j)->adj_ += aB(i, j);
+
137  }
+
138 
+
139  public:
+
140  explicit trace_inv_quad_form_ldlt_vari
+
141  (trace_inv_quad_form_ldlt_impl<T2, R2, C2, T3, R3, C3> *impl)
+
142  : vari(impl->_value), _impl(impl)
+
143  { }
+
144 
+
145  virtual void chain() {
+
146  // F = trace(D * B' * inv(A) * B)
+
147  // aA = -aF * inv(A') * B * D' * B' * inv(A')
+
148  // aB = aF*(inv(A) * B * D + inv(A') * B * D')
+
149  // aD = aF*(B' * inv(A) * B)
+
150  chainA(adj_, _impl);
+
151 
+
152  chainB(adj_, _impl);
+
153 
+
154  if (_impl->Dtype_ == 1) {
+
155  for (int j = 0; j < _impl->_variD.cols(); j++)
+
156  for (int i = 0; i < _impl->_variD.rows(); i++)
+
157  _impl->_variD(i, j)->adj_ += adj_*_impl->C_(i, j);
+
158  }
+
159  }
+
160 
+
161  trace_inv_quad_form_ldlt_impl<T2, R2, C2, T3, R3, C3> *_impl;
+
162  };
+
163 
+
164  }
+
165 
+
166 
+
172  template <typename T2, int R2, int C2, typename T3, int R3, int C3>
+
173  inline typename
+
174  boost::enable_if_c<stan::is_var<T2>::value ||
+ +
176  var>::type
+ +
178  const Eigen::Matrix<T3, R3, C3> &B) {
+
179  stan::math::check_multiplicable("trace_inv_quad_form_ldlt",
+
180  "A", A,
+
181  "B", B);
+
182 
+
183  trace_inv_quad_form_ldlt_impl<T2, R2, C2, T3, R3, C3> *_impl
+
184  = new trace_inv_quad_form_ldlt_impl<T2, R2, C2, T3, R3, C3>(A, B);
+
185 
+
186  return var(new trace_inv_quad_form_ldlt_vari<T2, R2, C2, T3, R3, C3>
+
187  (_impl));
+
188  }
+
189 
+
190  }
+
191 }
+
192 
+
193 #endif
+ + + + + +
Eigen::Matrix< vari *, Eigen::Dynamic, Eigen::Dynamic > _variD
+
const int Dtype_
+
Eigen::Matrix< double, C3, C3 > C_
+
double _value
+
boost::enable_if_c<!stan::is_var< T1 >::value &&!stan::is_var< T2 >::value, typename boost::math::tools::promote_args< T1, T2 >::type >::type trace_inv_quad_form_ldlt(const stan::math::LDLT_factor< T1, R2, C2 > &A, const Eigen::Matrix< T2, R3, C3 > &B)
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > D_
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+
stan::math::LDLT_factor< T2, R2, C2 > _ldlt
+ + +
Eigen::Matrix< double, R3, C3 > AinvB_
+
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+ +
Eigen::Matrix< vari *, R3, C3 > _variB
+
trace_inv_quad_form_ldlt_impl< T2, R2, C2, T3, R3, C3 > * _impl
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2trace__quad__form_8hpp.html b/doc/api/html/rev_2mat_2fun_2trace__quad__form_8hpp.html new file mode 100644 index 00000000000..1f1df4fecdf --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2trace__quad__form_8hpp.html @@ -0,0 +1,183 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/trace_quad_form.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
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+
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+Namespaces

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+ + + + +

+Functions

template<typename TA , int RA, int CA, typename TB , int RB, int CB>
boost::enable_if_c< boost::is_same< TA, var >::value||boost::is_same< TB, var >::value, var >::type stan::math::trace_quad_form (const Eigen::Matrix< TA, RA, CA > &A, const Eigen::Matrix< TB, RB, CB > &B)
 
+

Variable Documentation

+ +
+
+ + + + +
trace_quad_form_vari_alloc<TA, RA, CA, TB, RB, CB>* _impl
+
+ +

Definition at line 89 of file trace_quad_form.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<TA, RA, CA> A_
+
+ +

Definition at line 33 of file trace_quad_form.hpp.

+ +
+
+ +
+
+ + + + +
Eigen::Matrix<TB, RB, CB> B_
+
+ +

Definition at line 34 of file trace_quad_form.hpp.

+ +
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+
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diff --git a/doc/api/html/rev_2mat_2fun_2trace__quad__form_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2trace__quad__form_8hpp_source.html new file mode 100644 index 00000000000..b8fe2d6ba3f --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2trace__quad__form_8hpp_source.html @@ -0,0 +1,240 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/trace_quad_form.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
+ + +
+ +
+ + +
+
+
+
trace_quad_form.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_TRACE_QUAD_FORM_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_TRACE_QUAD_FORM_HPP
+
3 
+
4 #include <boost/utility/enable_if.hpp>
+
5 #include <boost/type_traits.hpp>
+
6 #include <stan/math/rev/core.hpp>
+ + + + + + + + +
15 
+
16 namespace stan {
+
17  namespace math {
+
18  namespace {
+
19  template <typename TA, int RA, int CA, typename TB, int RB, int CB>
+
20  class trace_quad_form_vari_alloc : public chainable_alloc {
+
21  public:
+
22  trace_quad_form_vari_alloc(const Eigen::Matrix<TA, RA, CA>& A,
+
23  const Eigen::Matrix<TB, RB, CB>& B)
+
24  : A_(A), B_(B)
+
25  { }
+
26 
+
27  double compute() {
+ + +
30  value_of(B_));
+
31  }
+
32 
+
33  Eigen::Matrix<TA, RA, CA> A_;
+
34  Eigen::Matrix<TB, RB, CB> B_;
+
35  };
+
36 
+
37  template <typename TA, int RA, int CA, typename TB, int RB, int CB>
+
38  class trace_quad_form_vari : public vari {
+
39  protected:
+
40  static inline void chainA(Eigen::Matrix<double, RA, CA>& A,
+
41  const Eigen::Matrix<double, RB, CB>& Bd,
+
42  const double& adjC) {}
+
43  static inline void chainB(Eigen::Matrix<double, RB, CB>& B,
+
44  const Eigen::Matrix<double, RA, CA>& Ad,
+
45  const Eigen::Matrix<double, RB, CB>& Bd,
+
46  const double& adjC) {}
+
47 
+
48  static inline void chainA(Eigen::Matrix<var, RA, CA>& A,
+
49  const Eigen::Matrix<double, RB, CB>& Bd,
+
50  const double& adjC) {
+
51  Eigen::Matrix<double, RA, CA> adjA(adjC*Bd*Bd.transpose());
+
52  for (int j = 0; j < A.cols(); j++)
+
53  for (int i = 0; i < A.rows(); i++)
+
54  A(i, j).vi_->adj_ += adjA(i, j);
+
55  }
+
56  static inline void chainB(Eigen::Matrix<var, RB, CB>& B,
+
57  const Eigen::Matrix<double, RA, CA>& Ad,
+
58  const Eigen::Matrix<double, RB, CB>& Bd,
+
59  const double& adjC) {
+
60  Eigen::Matrix<double, RA, CA> adjB(adjC*(Ad + Ad.transpose())*Bd);
+
61  for (int j = 0; j < B.cols(); j++)
+
62  for (int i = 0; i < B.rows(); i++)
+
63  B(i, j).vi_->adj_ += adjB(i, j);
+
64  }
+
65 
+
66  inline void chainAB(Eigen::Matrix<TA, RA, CA>& A,
+
67  Eigen::Matrix<TB, RB, CB>& B,
+
68  const Eigen::Matrix<double, RA, CA>& Ad,
+
69  const Eigen::Matrix<double, RB, CB>& Bd,
+
70  const double& adjC) {
+
71  chainA(A, Bd, adjC);
+
72  chainB(B, Ad, Bd, adjC);
+
73  }
+
74 
+
75 
+
76  public:
+
77  explicit
+
78  trace_quad_form_vari
+
79  (trace_quad_form_vari_alloc<TA, RA, CA, TB, RB, CB> *impl)
+
80  : vari(impl->compute()), _impl(impl) { }
+
81 
+
82  virtual void chain() {
+ +
84  chainAB(_impl->A_, _impl->B_,
+
85  value_of(_impl->A_), value_of(_impl->B_),
+
86  adj_);
+
87  }
+
88 
+
89  trace_quad_form_vari_alloc<TA, RA, CA, TB, RB, CB> *_impl;
+
90  };
+
91  }
+
92 
+
93  template <typename TA, int RA, int CA, typename TB, int RB, int CB>
+
94  inline typename
+
95  boost::enable_if_c< boost::is_same<TA, var>::value ||
+
96  boost::is_same<TB, var>::value,
+
97  var >::type
+
98  trace_quad_form(const Eigen::Matrix<TA, RA, CA>& A,
+
99  const Eigen::Matrix<TB, RB, CB>& B) {
+
100  stan::math::check_square("trace_quad_form", "A", A);
+
101  stan::math::check_multiplicable("trace_quad_form",
+
102  "A", A,
+
103  "B", B);
+
104 
+
105  trace_quad_form_vari_alloc<TA, RA, CA, TB, RB, CB> *baseVari
+
106  = new trace_quad_form_vari_alloc<TA, RA, CA, TB, RB, CB>(A, B);
+
107 
+
108  return var(new trace_quad_form_vari<TA, RA, CA, TB, RB, CB>(baseVari));
+
109  }
+
110  }
+
111 }
+
112 
+
113 #endif
+ + +
fvar< T > trace_quad_form(const Eigen::Matrix< fvar< T >, RA, CA > &A, const Eigen::Matrix< fvar< T >, RB, CB > &B)
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
Eigen::Matrix< TA, RA, CA > A_
+ +
bool check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Return true if the matrices can be multiplied.
+ +
Eigen::Matrix< TB, RB, CB > B_
+ +
trace_quad_form_vari_alloc< TA, RA, CA, TB, RB, CB > * _impl
+ +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2typedefs_8hpp.html b/doc/api/html/rev_2mat_2fun_2typedefs_8hpp.html new file mode 100644 index 00000000000..9a8148da80f --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2typedefs_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/typedefs.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+ +
+
typedefs.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Typedefs

typedef Eigen::Matrix< var, Eigen::Dynamic, Eigen::Dynamic > stan::math::matrix_v
 The type of a matrix holding stan::math::var values. More...
 
typedef Eigen::Matrix< var, Eigen::Dynamic, 1 > stan::math::vector_v
 The type of a (column) vector holding stan::math::var values. More...
 
typedef Eigen::Matrix< var, 1, Eigen::Dynamic > stan::math::row_vector_v
 The type of a row vector holding stan::math::var values. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2typedefs_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2typedefs_8hpp_source.html new file mode 100644 index 00000000000..21c41527010 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2typedefs_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/typedefs.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
typedefs.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_TYPEDEFS_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_TYPEDEFS_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11  typedef
+
12  Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>::Index
+
13  size_type;
+
14 
+
19  typedef
+
20  Eigen::Matrix<var, Eigen::Dynamic, Eigen::Dynamic>
+ +
22 
+
27  typedef
+
28  Eigen::Matrix<var, Eigen::Dynamic, 1>
+ +
30 
+
35  typedef
+
36  Eigen::Matrix<var, 1, Eigen::Dynamic>
+ +
38 
+
39  }
+
40 }
+
41 #endif
+ +
Eigen::Matrix< var, Eigen::Dynamic, 1 > vector_v
The type of a (column) vector holding stan::math::var values.
Definition: typedefs.hpp:29
+ +
Eigen::Matrix< var, Eigen::Dynamic, Eigen::Dynamic > matrix_v
The type of a matrix holding stan::math::var values.
Definition: typedefs.hpp:21
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+ +
Eigen::Matrix< var, 1, Eigen::Dynamic > row_vector_v
The type of a row vector holding stan::math::var values.
Definition: typedefs.hpp:37
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2unit__vector__constrain_8hpp.html b/doc/api/html/rev_2mat_2fun_2unit__vector__constrain_8hpp.html new file mode 100644 index 00000000000..1cd4ba89beb --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2unit__vector__constrain_8hpp.html @@ -0,0 +1,213 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/unit_vector_constrain.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
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unit_vector_constrain.hpp File Reference
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 Matrices and templated mathematical functions.
 
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+Functions

template<int R, int C>
Eigen::Matrix< var, R, C > stan::math::unit_vector_constrain (const Eigen::Matrix< var, R, C > &y)
 Return the unit length vector corresponding to the free vector y. More...
 
template<int R, int C>
Eigen::Matrix< var, R, C > stan::math::unit_vector_constrain (const Eigen::Matrix< var, R, C > &y, var &lp)
 Return the unit length vector corresponding to the free vector y. More...
 
+

Variable Documentation

+ +
+
+ + + + +
const int idx_
+
+ +

Definition at line 22 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+ + + + +
const double norm_
+
+ +

Definition at line 23 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+ + + + +
const int size_
+
+ +

Definition at line 21 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+ + + + +
const double* unit_vector_y_
+
+ +

Definition at line 20 of file unit_vector_constrain.hpp.

+ +
+
+ +
+
+ + + + +
vari** y_
+
+ +

Definition at line 19 of file unit_vector_constrain.hpp.

+ +
+
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+
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diff --git a/doc/api/html/rev_2mat_2fun_2unit__vector__constrain_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2unit__vector__constrain_8hpp_source.html new file mode 100644 index 00000000000..f9d5b1d9399 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2unit__vector__constrain_8hpp_source.html @@ -0,0 +1,237 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/unit_vector_constrain.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+
+ + +
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+ + +
+
+
+
unit_vector_constrain.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_UNIT_VECTOR_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_UNIT_VECTOR_CONSTRAIN_HPP
+
3 
+ + + + + +
9 #include <stan/math/rev/core.hpp>
+ +
11 #include <cmath>
+
12 
+
13 namespace stan {
+
14  namespace math {
+
15 
+
16  namespace {
+
17  class unit_vector_elt_vari : public vari {
+
18  private:
+
19  vari** y_;
+
20  const double* unit_vector_y_;
+
21  const int size_;
+
22  const int idx_;
+
23  const double norm_;
+
24 
+
25  public:
+
26  unit_vector_elt_vari(double val,
+
27  vari** y,
+
28  const double* unit_vector_y,
+
29  int size,
+
30  int idx,
+
31  const double norm)
+
32  : vari(val),
+
33  y_(y),
+
34  unit_vector_y_(unit_vector_y),
+
35  size_(size),
+
36  idx_(idx),
+
37  norm_(norm) {
+
38  }
+
39  void chain() {
+
40  const double cubed_norm = norm_ * norm_ * norm_;
+
41  for (int m = 0; m < size_; ++m) {
+
42  y_[m]->adj_
+
43  -= adj_ * unit_vector_y_[m] * unit_vector_y_[idx_] / cubed_norm;
+
44  if (m == idx_)
+
45  y_[m]->adj_ += adj_ / norm_;
+
46  }
+
47  }
+
48  };
+
49  }
+
50 
+
51 
+
52  // Unit vector
+
53 
+
62  template <int R, int C>
+
63  Eigen::Matrix<var, R, C>
+
64  unit_vector_constrain(const Eigen::Matrix<var, R, C>& y) {
+
65  stan::math::check_vector("unit_vector", "y", y);
+
66  stan::math::check_nonzero_size("unit_vector", "y", y);
+
67 
+
68  vari** y_vi_array
+
69  = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
70  .alloc(sizeof(vari*) * y.size()));
+
71  for (int i = 0; i < y.size(); ++i)
+
72  y_vi_array[i] = y.coeff(i).vi_;
+
73 
+
74  Eigen::VectorXd y_d(y.size());
+
75  for (int i = 0; i < y.size(); ++i)
+
76  y_d.coeffRef(i) = y.coeff(i).val();
+
77 
+
78 
+
79  const double norm = y_d.norm();
+
80  stan::math::check_positive_finite("unit_vector", "norm", norm);
+
81  Eigen::VectorXd unit_vector_d = y_d / norm;
+
82 
+
83  double* unit_vector_y_d_array
+
84  = reinterpret_cast<double*>(ChainableStack::memalloc_
+
85  .alloc(sizeof(double) * y_d.size()));
+
86  for (int i = 0; i < y_d.size(); ++i)
+
87  unit_vector_y_d_array[i] = unit_vector_d.coeff(i);
+
88 
+
89  Eigen::Matrix<var, R, C> unit_vector_y(y.size());
+
90  for (int k = 0; k < y.size(); ++k)
+
91  unit_vector_y.coeffRef(k)
+
92  = var(new unit_vector_elt_vari(unit_vector_d[k],
+
93  y_vi_array,
+
94  unit_vector_y_d_array,
+
95  y.size(),
+
96  k,
+
97  norm));
+
98  return unit_vector_y;
+
99  }
+
100 
+
110  template <int R, int C>
+
111  Eigen::Matrix<var, R, C>
+
112  unit_vector_constrain(const Eigen::Matrix<var, R, C>& y, var &lp) {
+
113  Eigen::Matrix<var, R, C> x = unit_vector_constrain(y);
+
114  lp -= 0.5 * stan::math::dot_self(y);
+
115  return x;
+
116  }
+
117 
+
118  }
+
119 
+
120 }
+
121 
+
122 #endif
+ +
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
+ + +
vari ** y_
+ +
The variable implementation base class.
Definition: vari.hpp:30
+
const double * unit_vector_y_
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > dot_self(const Eigen::Matrix< fvar< T >, R, C > &v)
Definition: dot_self.hpp:16
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+ +
Eigen::Matrix< fvar< T >, R, C > unit_vector_constrain(const Eigen::Matrix< fvar< T >, R, C > &y)
+ + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
const double norm_
+
const int size_
+ + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+
const int idx_
+
+
+
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diff --git a/doc/api/html/rev_2mat_2fun_2variance_8hpp.html b/doc/api/html/rev_2mat_2fun_2variance_8hpp.html new file mode 100644 index 00000000000..2b53c3c3442 --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2variance_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/variance.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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variance.hpp File Reference
+
+
+
#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/fun/mean.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/arr/err/check_nonzero_size.hpp>
+#include <vector>
+
+

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

var stan::math::variance (const std::vector< var > &v)
 Return the sample variance of the specified standard vector. More...
 
template<int R, int C>
var stan::math::variance (const Eigen::Matrix< var, R, C > &m)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2fun_2variance_8hpp_source.html b/doc/api/html/rev_2mat_2fun_2variance_8hpp_source.html new file mode 100644 index 00000000000..1757be073ae --- /dev/null +++ b/doc/api/html/rev_2mat_2fun_2variance_8hpp_source.html @@ -0,0 +1,193 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/fun/variance.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
variance.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUN_VARIANCE_HPP
+
2 #define STAN_MATH_REV_MAT_FUN_VARIANCE_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + +
7 #include <stan/math/rev/core.hpp>
+ +
9 #include <vector>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15  namespace { // anonymous
+
16 
+
17  var calc_variance(size_t size,
+
18  const var* dtrs) {
+
19  vari** varis = reinterpret_cast<vari**>(ChainableStack::memalloc_
+
20  .alloc(size * sizeof(vari*)));
+
21  for (size_t i = 0; i < size; ++i)
+
22  varis[i] = dtrs[i].vi_;
+
23  double sum = 0.0;
+
24  for (size_t i = 0; i < size; ++i)
+
25  sum += dtrs[i].vi_->val_;
+
26  double mean = sum / size;
+
27  double sum_of_squares = 0;
+
28  for (size_t i = 0; i < size; ++i) {
+
29  double diff = dtrs[i].vi_->val_ - mean;
+
30  sum_of_squares += diff * diff;
+
31  }
+
32  double variance = sum_of_squares / (size - 1);
+
33  double* partials
+
34  = reinterpret_cast<double*>(ChainableStack::memalloc_
+
35  .alloc(size * sizeof(double)));
+
36  double two_over_size_m1 = 2 / (size - 1);
+
37  for (size_t i = 0; i < size; ++i)
+
38  partials[i] = two_over_size_m1 * (dtrs[i].vi_->val_ - mean);
+
39  return var(new stored_gradient_vari(variance, size,
+
40  varis, partials));
+
41  }
+
42 
+
43  }
+
44 
+
52  var variance(const std::vector<var>& v) {
+
53  stan::math::check_nonzero_size("variance", "v", v);
+
54  if (v.size() == 1) return 0;
+
55  return calc_variance(v.size(), &v[0]);
+
56  }
+
57 
+
58  /*
+
59  * Return the sample variance of the specified vector, row vector,
+
60  * or matrix. Raise domain error if size is not greater than
+
61  * zero.
+
62  *
+
63  * @tparam R number of rows
+
64  * @tparam C number of columns
+
65  * @param[in] m input matrix
+
66  * @return sample variance of specified matrix
+
67  */
+
68  template <int R, int C>
+
69  var variance(const Eigen::Matrix<var, R, C>& m) {
+
70  stan::math::check_nonzero_size("variance", "m", m);
+
71  if (m.size() == 1) return 0;
+
72  return calc_variance(m.size(), &m(0));
+
73  }
+
74 
+
75  }
+
76 }
+
77 
+
78 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool check_nonzero_size(const char *function, const char *name, const T_y &y)
Return true if the specified matrix/vector is of non-zero size.
+
boost::math::tools::promote_args< T >::type variance(const std::vector< T > &v)
Returns the sample variance (divide by length - 1) of the coefficients in the specified standard vect...
Definition: variance.hpp:24
+ +
boost::math::tools::promote_args< T >::type mean(const std::vector< T > &v)
Returns the sample mean (i.e., average) of the coefficients in the specified standard vector...
Definition: mean.hpp:23
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+ +
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2functor_2gradient_8hpp.html b/doc/api/html/rev_2mat_2functor_2gradient_8hpp.html new file mode 100644 index 00000000000..4f929ee5912 --- /dev/null +++ b/doc/api/html/rev_2mat_2functor_2gradient_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/gradient.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
gradient.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stdexcept>
+
+

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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename F >
void stan::math::gradient (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &fx, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad_fx)
 Calculate the value and the gradient of the specified function at the specified argument. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2functor_2gradient_8hpp_source.html b/doc/api/html/rev_2mat_2functor_2gradient_8hpp_source.html new file mode 100644 index 00000000000..3972ca41ff2 --- /dev/null +++ b/doc/api/html/rev_2mat_2functor_2gradient_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/gradient.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
gradient.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUNCTOR_GRADIENT_HPP
+
2 #define STAN_MATH_REV_MAT_FUNCTOR_GRADIENT_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+
6 #include <stdexcept>
+
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
41  template <typename F>
+
42  void
+
43  gradient(const F& f,
+
44  const Eigen::Matrix<double, Eigen::Dynamic, 1>& x,
+
45  double& fx,
+
46  Eigen::Matrix<double, Eigen::Dynamic, 1>& grad_fx) {
+
47  using stan::math::var;
+
48  start_nested();
+
49  try {
+
50  Eigen::Matrix<var, Eigen::Dynamic, 1> x_var(x.size());
+
51  for (int i = 0; i < x.size(); ++i)
+
52  x_var(i) = x(i);
+
53  var fx_var = f(x_var);
+
54  fx = fx_var.val();
+
55  grad_fx.resize(x.size());
+
56  stan::math::grad(fx_var.vi_);
+
57  for (int i = 0; i < x.size(); ++i)
+
58  grad_fx(i) = x_var(i).adj();
+
59  } catch (const std::exception& /*e*/) {
+ +
61  throw;
+
62  }
+ +
64  }
+
65  } // namespace math
+
66 } // namespace stan
+
67 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
void gradient(const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, T &fx, Eigen::Matrix< T, Eigen::Dynamic, 1 > &grad_fx)
Calculate the value and the gradient of the specified function at the specified argument.
Definition: gradient.hpp:41
+
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2functor_2jacobian_8hpp.html b/doc/api/html/rev_2mat_2functor_2jacobian_8hpp.html new file mode 100644 index 00000000000..487ca4eed67 --- /dev/null +++ b/doc/api/html/rev_2mat_2functor_2jacobian_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/jacobian.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
+
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+ + +
+
+ +
+
jacobian.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stdexcept>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename F >
void stan::math::jacobian (const F &f, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, Eigen::Matrix< double, Eigen::Dynamic, 1 > &fx, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &J)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2functor_2jacobian_8hpp_source.html b/doc/api/html/rev_2mat_2functor_2jacobian_8hpp_source.html new file mode 100644 index 00000000000..21950f321f8 --- /dev/null +++ b/doc/api/html/rev_2mat_2functor_2jacobian_8hpp_source.html @@ -0,0 +1,167 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/functor/jacobian.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+
jacobian.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_FUNCTOR_JACOBIAN_HPP
+
2 #define STAN_MATH_REV_MAT_FUNCTOR_JACOBIAN_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+
6 #include <stdexcept>
+
7 #include <vector>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  template <typename F>
+
14  void
+
15  jacobian(const F& f,
+
16  const Eigen::Matrix<double, Eigen::Dynamic, 1>& x,
+
17  Eigen::Matrix<double, Eigen::Dynamic, 1>& fx,
+
18  Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& J) {
+
19  using Eigen::Matrix;
+
20  using Eigen::Dynamic;
+
21  using stan::math::var;
+
22  start_nested();
+
23  try {
+
24  Matrix<var, Dynamic, 1> x_var(x.size());
+
25  for (int k = 0; k < x.size(); ++k)
+
26  x_var(k) = x(k);
+
27  Matrix<var, Dynamic, 1> fx_var = f(x_var);
+
28  fx.resize(fx_var.size());
+
29  for (int i = 0; i < fx_var.size(); ++i)
+
30  fx(i) = fx_var(i).val();
+
31  J.resize(fx_var.size(), x.size());
+
32  for (int i = 0; i < fx_var.size(); ++i) {
+
33  if (i > 0)
+ +
35  grad(fx_var(i).vi_);
+
36  for (int k = 0; k < x.size(); ++k)
+
37  J(i, k) = x_var(k).adj();
+
38  }
+
39  } catch (const std::exception& e) {
+ +
41  throw;
+
42  }
+ +
44  }
+
45 
+
46  }
+
47 }
+
48 #endif
+ + +
static void set_zero_all_adjoints_nested()
Reset all adjoint values in the top nested portion of the stack to zero.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+
void jacobian(const F &f, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x, Eigen::Matrix< T, Eigen::Dynamic, 1 > &fx, Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &J)
Definition: jacobian.hpp:14
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
static void recover_memory_nested()
Recover only the memory used for the top nested call.
+
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2vectorize_2apply__scalar__unary_8hpp.html b/doc/api/html/rev_2mat_2vectorize_2apply__scalar__unary_8hpp.html new file mode 100644 index 00000000000..1ecf4b81efc --- /dev/null +++ b/doc/api/html/rev_2mat_2vectorize_2apply__scalar__unary_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/vectorize/apply_scalar_unary.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+ +
+
apply_scalar_unary.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + +

+Classes

struct  stan::math::apply_scalar_unary< F, stan::math::var >
 Template specialization to var for vectorizing a unary scalar function. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html b/doc/api/html/rev_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html new file mode 100644 index 00000000000..2d4771c02e5 --- /dev/null +++ b/doc/api/html/rev_2mat_2vectorize_2apply__scalar__unary_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/mat/vectorize/apply_scalar_unary.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
apply_scalar_unary.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_MAT_VECTORIZE_APPLY_UNARY_SCALAR_HPP
+
2 #define STAN_MATH_REV_MAT_VECTORIZE_APPLY_UNARY_SCALAR_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
19  template <typename F>
+ + +
25 
+
32  static inline return_t apply(const stan::math::var& x) {
+
33  return F::fun(x);
+
34  }
+
35  };
+
36 
+
37  }
+
38 }
+
39 #endif
+
stan::math::var return_t
Function return type, which is var.
+
static return_t apply(const stan::math::var &x)
Apply the function specified by F to the specified argument.
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
Base template class for vectorization of unary scalar functions defined by a template class F to a sc...
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2mat_8hpp.html b/doc/api/html/rev_2mat_8hpp.html new file mode 100644 index 00000000000..bae50cd63de --- /dev/null +++ b/doc/api/html/rev_2mat_8hpp.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/rev/mat.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+
+
mat.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/scal/meta/is_var.hpp>
+#include <stan/math/rev/scal/meta/partials_type.hpp>
+#include <stan/math/prim/mat.hpp>
+#include <stan/math/rev/arr.hpp>
+#include <stan/math/rev/mat/fun/cholesky_decompose.hpp>
+#include <stan/math/rev/mat/fun/columns_dot_product.hpp>
+#include <stan/math/rev/mat/fun/columns_dot_self.hpp>
+#include <stan/math/rev/mat/fun/crossprod.hpp>
+#include <stan/math/rev/mat/fun/determinant.hpp>
+#include <stan/math/rev/mat/fun/divide.hpp>
+#include <stan/math/rev/mat/fun/dot_product.hpp>
+#include <stan/math/rev/mat/fun/dot_self.hpp>
+#include <stan/math/rev/mat/fun/Eigen_NumTraits.hpp>
+#include <stan/math/rev/mat/fun/grad.hpp>
+#include <stan/math/rev/mat/fun/initialize_variable.hpp>
+#include <stan/math/rev/mat/fun/LDLT_alloc.hpp>
+#include <stan/math/rev/mat/fun/LDLT_factor.hpp>
+#include <stan/math/rev/mat/fun/log_determinant.hpp>
+#include <stan/math/rev/mat/fun/log_determinant_ldlt.hpp>
+#include <stan/math/rev/mat/fun/log_determinant_spd.hpp>
+#include <stan/math/rev/mat/fun/log_softmax.hpp>
+#include <stan/math/rev/mat/fun/log_sum_exp.hpp>
+#include <stan/math/rev/mat/fun/mdivide_left.hpp>
+#include <stan/math/rev/mat/fun/mdivide_left_ldlt.hpp>
+#include <stan/math/rev/mat/fun/mdivide_left_spd.hpp>
+#include <stan/math/rev/mat/fun/mdivide_left_tri.hpp>
+#include <stan/math/rev/mat/fun/multiply.hpp>
+#include <stan/math/rev/mat/fun/multiply_lower_tri_self_transpose.hpp>
+#include <stan/math/rev/mat/fun/quad_form.hpp>
+#include <stan/math/rev/mat/fun/quad_form_sym.hpp>
+#include <stan/math/rev/mat/fun/rows_dot_product.hpp>
+#include <stan/math/rev/mat/fun/sd.hpp>
+#include <stan/math/rev/mat/fun/softmax.hpp>
+#include <stan/math/rev/mat/fun/sort_asc.hpp>
+#include <stan/math/rev/mat/fun/sort_desc.hpp>
+#include <stan/math/rev/mat/fun/squared_distance.hpp>
+#include <stan/math/rev/mat/fun/stan_print.hpp>
+#include <stan/math/rev/mat/fun/sum.hpp>
+#include <stan/math/rev/mat/fun/tcrossprod.hpp>
+#include <stan/math/rev/mat/fun/to_var.hpp>
+#include <stan/math/rev/mat/fun/trace_gen_inv_quad_form_ldlt.hpp>
+#include <stan/math/rev/mat/fun/trace_gen_quad_form.hpp>
+#include <stan/math/rev/mat/fun/trace_inv_quad_form_ldlt.hpp>
+#include <stan/math/rev/mat/fun/trace_quad_form.hpp>
+#include <stan/math/rev/mat/fun/typedefs.hpp>
+#include <stan/math/rev/mat/fun/variance.hpp>
+#include <stan/math/rev/mat/functor/gradient.hpp>
+#include <stan/math/rev/mat/functor/jacobian.hpp>
+#include <stan/math/rev/mat/functor/ode_system.hpp>
+#include <stan/math/rev/mat/functor/cvodes_utils.hpp>
+#include <stan/math/rev/mat/functor/cvodes_ode_data.hpp>
+#include <stan/math/rev/mat/functor/integrate_ode_bdf.hpp>
+
+

Go to the source code of this file.

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diff --git a/doc/api/html/rev_2mat_8hpp_source.html b/doc/api/html/rev_2mat_8hpp_source.html new file mode 100644 index 00000000000..cc9fc07aafb --- /dev/null +++ b/doc/api/html/rev_2mat_8hpp_source.html @@ -0,0 +1,222 @@ + + + + + + +Stan Math Library: stan/math/rev/mat.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_MAT_HPP
+
2 #define STAN_MATH_REV_MAT_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 
+
8 #include <stan/math/prim/mat.hpp>
+
9 #include <stan/math/rev/arr.hpp>
+
10 
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59 
+
60 #endif
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diff --git a/doc/api/html/rev_2scal_2fun_2_phi_8hpp.html b/doc/api/html/rev_2scal_2fun_2_phi_8hpp.html new file mode 100644 index 00000000000..07eca64d59e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2_phi_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/Phi.hpp File Reference + + + + + + + + + + +
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var stan::math::Phi (const stan::math::var &a)
 The unit normal cumulative density function for variables (stan). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2_phi_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2_phi_8hpp_source.html new file mode 100644 index 00000000000..98dde694591 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2_phi_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/Phi.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_PHI_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_PHI_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class Phi_vari : public op_v_vari {
+
12  public:
+
13  explicit Phi_vari(vari* avi) :
+
14  op_v_vari(stan::math::Phi(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  static const double NEG_HALF = -0.5;
+
18  avi_->adj_ += adj_
+ +
20  * std::exp(NEG_HALF * avi_->val_ * avi_->val_);
+
21  }
+
22  };
+
23  }
+
24 
+
66  inline var Phi(const stan::math::var& a) {
+
67  return var(new Phi_vari(a.vi_));
+
68  }
+
69 
+
70  }
+
71 }
+
72 #endif
+
const double INV_SQRT_TWO_PI
Definition: constants.hpp:166
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > Phi(const fvar< T > &x)
Definition: Phi.hpp:14
+ +
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2_phi__approx_8hpp.html b/doc/api/html/rev_2scal_2fun_2_phi__approx_8hpp.html new file mode 100644 index 00000000000..dd31d5e5dd7 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2_phi__approx_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/Phi_approx.hpp File Reference + + + + + + + + + + +
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var stan::math::Phi_approx (const stan::math::var &a)
 Approximation of the unit normal CDF for variables (stan). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2_phi__approx_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2_phi__approx_8hpp_source.html new file mode 100644 index 00000000000..f6dbea59f7e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2_phi__approx_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/Phi_approx.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_PHI_APPROX_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_PHI_APPROX_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
47  inline var Phi_approx(const stan::math::var& a) {
+
48  // return inv_logit(0.07056 * pow(a, 3.0) + 1.5976 * a);
+
49 
+
50  double av = a.vi_->val_;
+
51  double av_squared = av * av;
+
52  double av_cubed = av * av_squared;
+
53  double f = stan::math::inv_logit(0.07056 * av_cubed + 1.5976 * av);
+
54  double da = f * (1 - f) * (3.0 * 0.07056 * av_squared + 1.5976);
+
55  return var(new precomp_v_vari(f, a.vi_, da));
+
56  }
+
57 
+
58  }
+
59 }
+
60 #endif
+ + +
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
boost::math::tools::promote_args< T >::type Phi_approx(T x)
Approximation of the unit normal CDF.
Definition: Phi_approx.hpp:23
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
+
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diff --git a/doc/api/html/rev_2scal_2fun_2abs_8hpp.html b/doc/api/html/rev_2scal_2fun_2abs_8hpp.html new file mode 100644 index 00000000000..56f86617b59 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2abs_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/abs.hpp File Reference + + + + + + + + + + +
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var stan::math::abs (const var &a)
 Return the absolute value of the variable (std). More...
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2abs_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2abs_8hpp_source.html new file mode 100644 index 00000000000..bbed5afde03 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2abs_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/abs.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_ABS_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ABS_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
35  inline var abs(const var& a) {
+
36  return fabs(a);
+
37  }
+
38 
+
39  }
+
40 }
+
41 #endif
+
fvar< T > abs(const fvar< T > &x)
Definition: abs.hpp:15
+
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
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diff --git a/doc/api/html/rev_2scal_2fun_2acos_8hpp.html b/doc/api/html/rev_2scal_2fun_2acos_8hpp.html new file mode 100644 index 00000000000..a23495f1fbf --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2acos_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/acos.hpp File Reference + + + + + + + + + + +
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+#include <cmath>
+#include <valarray>
+
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var stan::math::acos (const var &a)
 Return the principal value of the arc cosine of a variable, in radians (cmath). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2acos_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2acos_8hpp_source.html new file mode 100644 index 00000000000..ec1798ec994 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2acos_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/acos.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_ACOS_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ACOS_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 #include <valarray>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class acos_vari : public op_v_vari {
+
13  public:
+
14  explicit acos_vari(vari* avi) :
+
15  op_v_vari(std::acos(avi->val_), avi) {
+
16  }
+
17  void chain() {
+
18  avi_->adj_ -= adj_ / std::sqrt(1.0 - (avi_->val_ * avi_->val_));
+
19  }
+
20  };
+
21  }
+
22 
+
59  inline var acos(const var& a) {
+
60  return var(new acos_vari(a.vi_));
+
61  }
+
62 
+
63  }
+
64 }
+
65 #endif
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > acos(const fvar< T > &x)
Definition: acos.hpp:14
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2acosh_8hpp.html b/doc/api/html/rev_2scal_2fun_2acosh_8hpp.html new file mode 100644 index 00000000000..351bf795371 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2acosh_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/acosh.hpp File Reference + + + + + + + + + + +
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#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <cmath>
+
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var stan::math::acosh (const var &a)
 The inverse hyperbolic cosine function for variables (C99). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2acosh_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2acosh_8hpp_source.html new file mode 100644 index 00000000000..1bfd818844e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2acosh_8hpp_source.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/acosh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_ACOSH_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ACOSH_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <cmath>
+
8 
+
9 #ifdef _MSC_VER
+
10 #include <boost/math/special_functions/acosh.hpp>
+
11 using boost::math::acosh;
+
12 #endif
+
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  namespace {
+
18  class acosh_vari : public op_v_vari {
+
19  public:
+
20  acosh_vari(double val, vari* avi) :
+
21  op_v_vari(val, avi) {
+
22  }
+
23  void chain() {
+
24  avi_->adj_ += adj_ / std::sqrt(avi_->val_ * avi_->val_ - 1.0);
+
25  }
+
26  };
+
27  }
+
28 
+
68  inline var acosh(const var& a) {
+
69  if (boost::math::isinf(a.val()) && a > 0.0)
+
70  return var(new acosh_vari(a.val(), a.vi_));
+
71  return var(new acosh_vari(::acosh(a.val()), a.vi_));
+
72  }
+
73 
+
74  }
+
75 }
+
76 #endif
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+
var acosh(const var &a)
The inverse hyperbolic cosine function for variables (C99).
Definition: acosh.hpp:68
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
fvar< T > acosh(const fvar< T > &x)
Definition: acosh.hpp:14
+
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diff --git a/doc/api/html/rev_2scal_2fun_2as__bool_8hpp.html b/doc/api/html/rev_2scal_2fun_2as__bool_8hpp.html new file mode 100644 index 00000000000..0b47e8b77a4 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2as__bool_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/as_bool.hpp File Reference + + + + + + + + + + +
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int stan::math::as_bool (const var &v)
 Return 1 if the argument is unequal to zero and 0 otherwise. More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2as__bool_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2as__bool_8hpp_source.html new file mode 100644 index 00000000000..61be2ce9f63 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2as__bool_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/as_bool.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_AS_BOOL_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_AS_BOOL_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
15  inline int as_bool(const var& v) {
+
16  return 0.0 != v.vi_->val_;
+
17  }
+
18 
+
19  }
+
20 }
+
21 #endif
+ +
bool as_bool(const T x)
Return 1 if the argument is unequal to zero and 0 otherwise.
Definition: as_bool.hpp:14
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
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+
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diff --git a/doc/api/html/rev_2scal_2fun_2asin_8hpp.html b/doc/api/html/rev_2scal_2fun_2asin_8hpp.html new file mode 100644 index 00000000000..53f9b1e17b4 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2asin_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/asin.hpp File Reference + + + + + + + + + + +
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var stan::math::asin (const var &a)
 Return the principal value of the arc sine, in radians, of the specified variable (cmath). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2asin_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2asin_8hpp_source.html new file mode 100644 index 00000000000..ec1ee36f3c2 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2asin_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/asin.hpp Source File + + + + + + + + + + +
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+
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+
asin.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_ASIN_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ASIN_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class asin_vari : public op_v_vari {
+
12  public:
+
13  explicit asin_vari(vari* avi) :
+
14  op_v_vari(std::asin(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ / std::sqrt(1.0 - (avi_->val_ * avi_->val_));
+
18  }
+
19  };
+
20  }
+
21 
+
58  inline var asin(const var& a) {
+
59  return var(new asin_vari(a.vi_));
+
60  }
+
61 
+
62  }
+
63 }
+
64 #endif
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > asin(const fvar< T > &x)
Definition: asin.hpp:12
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2asinh_8hpp.html b/doc/api/html/rev_2scal_2fun_2asinh_8hpp.html new file mode 100644 index 00000000000..47732aa20d7 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2asinh_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/asinh.hpp File Reference + + + + + + + + + + +
+
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+
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+ +
+
asinh.hpp File Reference
+
+
+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <cmath>
+#include <valarray>
+
+

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var stan::math::asinh (const var &a)
 The inverse hyperbolic sine function for variables (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2asinh_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2asinh_8hpp_source.html new file mode 100644 index 00000000000..38a536c14d5 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2asinh_8hpp_source.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/asinh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_ASINH_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ASINH_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <cmath>
+
8 #include <valarray>
+
9 
+
10 #ifdef _MSC_VER
+
11 #include <boost/math/special_functions/asinh.hpp>
+
12 using boost::math::asinh;
+
13 #endif
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  namespace {
+
19  class asinh_vari : public op_v_vari {
+
20  public:
+
21  asinh_vari(double val, vari* avi) :
+
22  op_v_vari(val, avi) {
+
23  }
+
24  void chain() {
+
25  avi_->adj_ += adj_ / std::sqrt(avi_->val_ * avi_->val_ + 1.0);
+
26  }
+
27  };
+
28  }
+
29 
+
67  inline var asinh(const var& a) {
+
68  if (boost::math::isinf(a.val()))
+
69  return var(new asinh_vari(a.val(), a.vi_));
+
70  return var(new asinh_vari(::asinh(a.val()), a.vi_));
+
71  }
+
72 
+
73  }
+
74 }
+
75 #endif
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+
fvar< T > asinh(const fvar< T > &x)
Definition: asinh.hpp:13
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
var asinh(const var &a)
The inverse hyperbolic sine function for variables (C99).
Definition: asinh.hpp:67
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2atan2_8hpp.html b/doc/api/html/rev_2scal_2fun_2atan2_8hpp.html new file mode 100644 index 00000000000..513f3f856c4 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2atan2_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/atan2.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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+
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+
+ +
+
atan2.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <cmath>
+#include <valarray>
+
+

Go to the source code of this file.

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 Matrices and templated mathematical functions.
 
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+Functions

var stan::math::atan2 (const var &a, const var &b)
 Return the principal value of the arc tangent, in radians, of the first variable divided by the second (cmath). More...
 
var stan::math::atan2 (const var &a, const double b)
 Return the principal value of the arc tangent, in radians, of the first variable divided by the second scalar (cmath). More...
 
var stan::math::atan2 (const double a, const var &b)
 Return the principal value of the arc tangent, in radians, of the first scalar divided by the second variable (cmath). More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2atan2_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2atan2_8hpp_source.html new file mode 100644 index 00000000000..1c647d0ebda --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2atan2_8hpp_source.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/atan2.hpp Source File + + + + + + + + + + +
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atan2.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_ATAN2_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ATAN2_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 #include <valarray>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class atan2_vv_vari : public op_vv_vari {
+
13  public:
+
14  atan2_vv_vari(vari* avi, vari* bvi) :
+
15  op_vv_vari(std::atan2(avi->val_, bvi->val_), avi, bvi) {
+
16  }
+
17  void chain() {
+
18  double a_sq_plus_b_sq = (avi_->val_ * avi_->val_)
+
19  + (bvi_->val_ * bvi_->val_);
+
20  avi_->adj_ += adj_ * bvi_->val_ / a_sq_plus_b_sq;
+
21  bvi_->adj_ -= adj_ * avi_->val_ / a_sq_plus_b_sq;
+
22  }
+
23  };
+
24 
+
25  class atan2_vd_vari : public op_vd_vari {
+
26  public:
+
27  atan2_vd_vari(vari* avi, double b) :
+
28  op_vd_vari(std::atan2(avi->val_, b), avi, b) {
+
29  }
+
30  void chain() {
+
31  double a_sq_plus_b_sq = (avi_->val_ * avi_->val_) + (bd_ * bd_);
+
32  avi_->adj_ += adj_ * bd_ / a_sq_plus_b_sq;
+
33  }
+
34  };
+
35 
+
36  class atan2_dv_vari : public op_dv_vari {
+
37  public:
+
38  atan2_dv_vari(double a, vari* bvi) :
+
39  op_dv_vari(std::atan2(a, bvi->val_), a, bvi) {
+
40  }
+
41  void chain() {
+
42  double a_sq_plus_b_sq = (ad_ * ad_) + (bvi_->val_ * bvi_->val_);
+
43  bvi_->adj_ -= adj_ * ad_ / a_sq_plus_b_sq;
+
44  }
+
45  };
+
46  }
+
47 
+
62  inline var atan2(const var& a, const var& b) {
+
63  return var(new atan2_vv_vari(a.vi_, b.vi_));
+
64  }
+
65 
+
78  inline var atan2(const var& a, const double b) {
+
79  return var(new atan2_vd_vari(a.vi_, b));
+
80  }
+
81 
+
119  inline var atan2(const double a, const var& b) {
+
120  return var(new atan2_dv_vari(a, b.vi_));
+
121  }
+
122 
+
123  }
+
124 }
+
125 #endif
+ + +
fvar< T > atan2(const fvar< T > &x1, const fvar< T > &x2)
Definition: atan2.hpp:12
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2atan_8hpp.html b/doc/api/html/rev_2scal_2fun_2atan_8hpp.html new file mode 100644 index 00000000000..64c71f86e72 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2atan_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/atan.hpp File Reference + + + + + + + + + + +
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atan.hpp File Reference
+
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+
#include <stan/math/rev/core.hpp>
+#include <cmath>
+#include <valarray>
+
+

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

var stan::math::atan (const var &a)
 Return the principal value of the arc tangent, in radians, of the specified variable (cmath). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2atan_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2atan_8hpp_source.html new file mode 100644 index 00000000000..4c3f5acf025 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2atan_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/atan.hpp Source File + + + + + + + + + + +
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+
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atan.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_ATAN_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ATAN_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 #include <valarray>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class atan_vari : public op_v_vari {
+
13  public:
+
14  explicit atan_vari(vari* avi) :
+
15  op_v_vari(std::atan(avi->val_), avi) {
+
16  }
+
17  void chain() {
+
18  avi_->adj_ += adj_ / (1.0 + (avi_->val_ * avi_->val_));
+
19  }
+
20  };
+
21  }
+
22 
+
55  inline var atan(const var& a) {
+
56  return var(new atan_vari(a.vi_));
+
57  }
+
58 
+
59  }
+
60 }
+
61 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > atan(const fvar< T > &x)
Definition: atan.hpp:12
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2atanh_8hpp.html b/doc/api/html/rev_2scal_2fun_2atanh_8hpp.html new file mode 100644 index 00000000000..ca46c66668d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2atanh_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/atanh.hpp File Reference + + + + + + + + + + +
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+
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+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <cmath>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

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 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

var stan::math::atanh (const var &a)
 The inverse hyperbolic tangent function for variables (C99). More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2atanh_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2atanh_8hpp_source.html new file mode 100644 index 00000000000..e42554e41b6 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2atanh_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/atanh.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_ATANH_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ATANH_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+
6 #include <cmath>
+
7 #include <limits>
+
8 
+
9 #ifdef _MSC_VER
+
10 #include <boost/math/special_functions/atanh.hpp>
+
11 using boost::math::atanh;
+
12 #endif
+
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  namespace {
+
18  class atanh_vari : public op_v_vari {
+
19  public:
+
20  atanh_vari(double val, vari* avi) :
+
21  op_v_vari(val, avi) {
+
22  }
+
23  void chain() {
+
24  avi_->adj_ += adj_ / (1.0 - avi_->val_ * avi_->val_);
+
25  }
+
26  };
+
27  }
+
28 
+
70  inline var atanh(const var& a) {
+
71  if (a == 1.0)
+
72  return var(new atanh_vari(std::numeric_limits<double>::infinity(),
+
73  a.vi_));
+
74  if (a == -1.0)
+
75  return var(new atanh_vari(-std::numeric_limits<double>::infinity(),
+
76  a.vi_));
+
77  return var(new atanh_vari(::atanh(a.val()), a.vi_));
+
78  }
+
79 
+
80  }
+
81 }
+
82 #endif
+ +
fvar< T > atanh(const fvar< T > &x)
Definition: atanh.hpp:13
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
var atanh(const var &a)
The inverse hyperbolic tangent function for variables (C99).
Definition: atanh.hpp:70
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2bessel__first__kind_8hpp.html b/doc/api/html/rev_2scal_2fun_2bessel__first__kind_8hpp.html new file mode 100644 index 00000000000..08e24d6c50a --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2bessel__first__kind_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/bessel_first_kind.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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var stan::math::bessel_first_kind (const int &v, const var &a)
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2bessel__first__kind_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2bessel__first__kind_8hpp_source.html new file mode 100644 index 00000000000..5166dc8c8f5 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2bessel__first__kind_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/bessel_first_kind.hpp Source File + + + + + + + + + + +
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+
+
bessel_first_kind.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_BESSEL_FIRST_KIND_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_BESSEL_FIRST_KIND_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12 
+
13  class bessel_first_kind_dv_vari : public op_dv_vari {
+
14  public:
+
15  bessel_first_kind_dv_vari(int a, vari* bvi) :
+
16  op_dv_vari(stan::math::bessel_first_kind(a, bvi->val_), a, bvi) {
+
17  }
+
18  void chain() {
+
19  bvi_->adj_ += adj_
+
20  * (ad_ * stan::math::bessel_first_kind(ad_, bvi_->val_)
+
21  / bvi_->val_
+
22  - stan::math::bessel_first_kind(ad_ + 1, bvi_->val_));
+
23  }
+
24  };
+
25  }
+
26 
+
27  inline var bessel_first_kind(const int& v,
+
28  const var& a) {
+
29  return var(new bessel_first_kind_dv_vari(v, a.vi_));
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+ +
fvar< T > bessel_first_kind(int v, const fvar< T > &z)
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
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diff --git a/doc/api/html/rev_2scal_2fun_2bessel__second__kind_8hpp.html b/doc/api/html/rev_2scal_2fun_2bessel__second__kind_8hpp.html new file mode 100644 index 00000000000..11ec33e3041 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2bessel__second__kind_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/bessel_second_kind.hpp File Reference + + + + + + + + + + +
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var stan::math::bessel_second_kind (const int &v, const var &a)
 
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diff --git a/doc/api/html/rev_2scal_2fun_2bessel__second__kind_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2bessel__second__kind_8hpp_source.html new file mode 100644 index 00000000000..496422dac8f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2bessel__second__kind_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/bessel_second_kind.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_BESSEL_SECOND_KIND_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_BESSEL_SECOND_KIND_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12 
+
13  class bessel_second_kind_dv_vari : public op_dv_vari {
+
14  public:
+
15  bessel_second_kind_dv_vari(int a, vari* bvi) :
+
16  op_dv_vari(stan::math::bessel_second_kind(a, bvi->val_), a, bvi) {
+
17  }
+
18  void chain() {
+
19  bvi_->adj_ += adj_
+
20  * (ad_ * stan::math::bessel_second_kind(ad_, bvi_->val_)
+
21  / bvi_->val_
+
22  - stan::math::bessel_second_kind(ad_ + 1, bvi_->val_));
+
23  }
+
24  };
+
25  }
+
26 
+
27  inline var bessel_second_kind(const int& v,
+
28  const var& a) {
+
29  return var(new bessel_second_kind_dv_vari(v, a.vi_));
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > bessel_second_kind(int v, const fvar< T > &z)
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
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diff --git a/doc/api/html/rev_2scal_2fun_2binary__log__loss_8hpp.html b/doc/api/html/rev_2scal_2fun_2binary__log__loss_8hpp.html new file mode 100644 index 00000000000..c792c6bf894 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2binary__log__loss_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/binary_log_loss.hpp File Reference + + + + + + + + + + +
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var stan::math::binary_log_loss (const int y, const stan::math::var &y_hat)
 The log loss function for variables (stan). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2binary__log__loss_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2binary__log__loss_8hpp_source.html new file mode 100644 index 00000000000..7d729fc119c --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2binary__log__loss_8hpp_source.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/binary_log_loss.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_BINARY_LOG_LOSS_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_BINARY_LOG_LOSS_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <valarray>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class binary_log_loss_1_vari : public op_v_vari {
+
14  public:
+
15  explicit binary_log_loss_1_vari(vari* avi) :
+
16  op_v_vari(-std::log(avi->val_), avi) {
+
17  }
+
18  void chain() {
+
19  avi_->adj_ -= adj_ / avi_->val_;
+
20  }
+
21  };
+
22 
+
23  class binary_log_loss_0_vari : public op_v_vari {
+
24  public:
+
25  explicit binary_log_loss_0_vari(vari* avi) :
+
26  op_v_vari(-stan::math::log1p(-avi->val_), avi) {
+
27  }
+
28  void chain() {
+
29  avi_->adj_ += adj_ / (1.0 - avi_->val_);
+
30  }
+
31  };
+
32  }
+
33 
+
68  inline var binary_log_loss(const int y, const stan::math::var& y_hat) {
+
69  if (y == 0)
+
70  return var(new binary_log_loss_0_vari(y_hat.vi_));
+
71  else
+
72  return var(new binary_log_loss_1_vari(y_hat.vi_));
+
73  }
+
74 
+
75  }
+
76 }
+
77 #endif
+ + +
fvar< T > binary_log_loss(const int y, const fvar< T > &y_hat)
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ +
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diff --git a/doc/api/html/rev_2scal_2fun_2cbrt_8hpp.html b/doc/api/html/rev_2scal_2fun_2cbrt_8hpp.html new file mode 100644 index 00000000000..68b7ab3e2ac --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2cbrt_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/cbrt.hpp File Reference + + + + + + + + + + +
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#include <math.h>
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+
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var stan::math::cbrt (const var &a)
 Returns the cube root of the specified variable (C99). More...
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2cbrt_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2cbrt_8hpp_source.html new file mode 100644 index 00000000000..b505a432f7a --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2cbrt_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/cbrt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_CBRT_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_CBRT_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 #ifdef _MSC_VER
+
8 #include <boost/math/special_functions/cbrt.hpp>
+ +
10 #endif
+
11 
+
12 
+
13 namespace stan {
+
14  namespace math {
+
15 
+
16  namespace {
+
17  class cbrt_vari : public op_v_vari {
+
18  public:
+
19  explicit cbrt_vari(vari* avi) :
+
20  op_v_vari(::cbrt(avi->val_), avi) {
+
21  }
+
22  void chain() {
+
23  avi_->adj_ += adj_ / (3.0 * val_ * val_);
+
24  }
+
25  };
+
26  }
+
27 
+
56  inline var cbrt(const var& a) {
+
57  return var(new cbrt_vari(a.vi_));
+
58  }
+
59 
+
60  }
+
61 }
+
62 #endif
+ + +
fvar< T > cbrt(const fvar< T > &x)
Definition: cbrt.hpp:14
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
var cbrt(const var &a)
Returns the cube root of the specified variable (C99).
Definition: cbrt.hpp:56
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2ceil_8hpp.html b/doc/api/html/rev_2scal_2fun_2ceil_8hpp.html new file mode 100644 index 00000000000..691c92dd49f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2ceil_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/ceil.hpp File Reference + + + + + + + + + + +
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#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/meta/likely.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <cmath>
+#include <limits>
+
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var stan::math::ceil (const var &a)
 Return the ceiling of the specified variable (cmath). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2ceil_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2ceil_8hpp_source.html new file mode 100644 index 00000000000..cd5285e9aee --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2ceil_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/ceil.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_CEIL_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_CEIL_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <cmath>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class ceil_vari : public op_v_vari {
+
15  public:
+
16  explicit ceil_vari(vari* avi) :
+
17  op_v_vari(std::ceil(avi->val_), avi) {
+
18  }
+
19  void chain() {
+
20  if (unlikely(boost::math::isnan(avi_->val_)))
+
21  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
22  }
+
23  };
+
24  }
+
25 
+
60  inline var ceil(const var& a) {
+
61  return var(new ceil_vari(a.vi_));
+
62  }
+
63 
+
64  }
+
65 }
+
66 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > ceil(const fvar< T > &x)
Definition: ceil.hpp:11
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2cos_8hpp.html b/doc/api/html/rev_2scal_2fun_2cos_8hpp.html new file mode 100644 index 00000000000..0baa6eb1de6 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2cos_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/cos.hpp File Reference + + + + + + + + + + +
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+
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var stan::math::cos (const var &a)
 Return the cosine of a radian-scaled variable (cmath). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2cos_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2cos_8hpp_source.html new file mode 100644 index 00000000000..53d52a88512 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2cos_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/cos.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_COS_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_COS_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class cos_vari : public op_v_vari {
+
12  public:
+
13  explicit cos_vari(vari* avi) :
+
14  op_v_vari(std::cos(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ -= adj_ * std::sin(avi_->val_);
+
18  }
+
19  };
+
20  }
+
21 
+
49  inline var cos(const var& a) {
+
50  return var(new cos_vari(a.vi_));
+
51  }
+
52 
+
53  }
+
54 }
+
55 #endif
+
fvar< T > cos(const fvar< T > &x)
Definition: cos.hpp:13
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > sin(const fvar< T > &x)
Definition: sin.hpp:14
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2cosh_8hpp.html b/doc/api/html/rev_2scal_2fun_2cosh_8hpp.html new file mode 100644 index 00000000000..966e3ee55fd --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2cosh_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/cosh.hpp File Reference + + + + + + + + + + +
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+#include <cmath>
+#include <valarray>
+
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var stan::math::cosh (const var &a)
 Return the hyperbolic cosine of the specified variable (cmath). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2cosh_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2cosh_8hpp_source.html new file mode 100644 index 00000000000..893a61e403f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2cosh_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/cosh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_COSH_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_COSH_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 #include <valarray>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class cosh_vari : public op_v_vari {
+
13  public:
+
14  explicit cosh_vari(vari* avi) :
+
15  op_v_vari(std::cosh(avi->val_), avi) {
+
16  }
+
17  void chain() {
+
18  avi_->adj_ += adj_ * std::sinh(avi_->val_);
+
19  }
+
20  };
+
21  }
+
22 
+
50  inline var cosh(const var& a) {
+
51  return var(new cosh_vari(a.vi_));
+
52  }
+
53 
+
54  }
+
55 }
+
56 #endif
+ +
fvar< T > cosh(const fvar< T > &x)
Definition: cosh.hpp:13
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > sinh(const fvar< T > &x)
Definition: sinh.hpp:14
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2digamma_8hpp.html b/doc/api/html/rev_2scal_2fun_2digamma_8hpp.html new file mode 100644 index 00000000000..5c1834d21e8 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2digamma_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/digamma.hpp File Reference + + + + + + + + + + +
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+
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+
#include <boost/math/special_functions/zeta.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/trigamma.hpp>
+#include <stan/math/prim/scal/fun/digamma.hpp>
+
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var stan::math::digamma (const stan::math::var &a)
 
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diff --git a/doc/api/html/rev_2scal_2fun_2digamma_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2digamma_8hpp_source.html new file mode 100644 index 00000000000..59fa2e34a58 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2digamma_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/digamma.hpp Source File + + + + + + + + + + +
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digamma.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_DIGAMMA_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_DIGAMMA_HPP
+
3 
+
4 #include <boost/math/special_functions/zeta.hpp>
+
5 #include <stan/math/rev/core.hpp>
+ + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class digamma_vari : public op_v_vari {
+
14  public:
+
15  explicit digamma_vari(vari* avi) :
+
16  op_v_vari(digamma(avi->val_), avi) {
+
17  }
+
18  void chain() {
+
19  avi_->adj_ += adj_ * trigamma(avi_->val_);
+
20  }
+
21  };
+
22  }
+
23 
+
24  inline var digamma(const stan::math::var& a) {
+
25  return var(new digamma_vari(a.vi_));
+
26  }
+
27 
+
28  }
+
29 }
+
30 #endif
+
T trigamma(T x)
Definition: trigamma.hpp:50
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2erf_8hpp.html b/doc/api/html/rev_2scal_2fun_2erf_8hpp.html new file mode 100644 index 00000000000..29cf4ea3ff9 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2erf_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/erf.hpp File Reference + + + + + + + + + + +
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erf.hpp File Reference
+
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+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <cmath>
+#include <valarray>
+
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var stan::math::erf (const var &a)
 The error function for variables (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2erf_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2erf_8hpp_source.html new file mode 100644 index 00000000000..465bee88bad --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2erf_8hpp_source.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/erf.hpp Source File + + + + + + + + + + +
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erf.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_ERF_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ERF_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+ +
7 #include <cmath>
+
8 #include <valarray>
+
9 
+
10 #ifdef _MSC_VER
+
11 #include <boost/math/special_functions/erf.hpp>
+
12 using boost::math::erf;
+
13 #endif
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  namespace {
+
19  class erf_vari : public op_v_vari {
+
20  public:
+
21  explicit erf_vari(vari* avi) :
+
22  op_v_vari(::erf(avi->val_), avi) {
+
23  }
+
24  void chain() {
+
25  avi_->adj_ += adj_ * stan::math::TWO_OVER_SQRT_PI
+
26  * std::exp(- avi_->val_ * avi_->val_);
+
27  }
+
28  };
+
29  }
+
30 
+
68  inline var erf(const var& a) {
+
69  return var(new erf_vari(a.vi_));
+
70  }
+
71 
+
72  }
+
73 }
+
74 #endif
+
var erf(const var &a)
The error function for variables (C99).
Definition: erf.hpp:68
+ + +
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double TWO_OVER_SQRT_PI
Definition: constants.hpp:161
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2erfc_8hpp.html b/doc/api/html/rev_2scal_2fun_2erfc_8hpp.html new file mode 100644 index 00000000000..4612bc2236b --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2erfc_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/erfc.hpp File Reference + + + + + + + + + + +
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erfc.hpp File Reference
+
+
+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <cmath>
+#include <valarray>
+
+

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+Functions

var stan::math::erfc (const var &a)
 The complementary error function for variables (C99). More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2erfc_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2erfc_8hpp_source.html new file mode 100644 index 00000000000..7aa78d8e5af --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2erfc_8hpp_source.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/erfc.hpp Source File + + + + + + + + + + +
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erfc.hpp
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+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_ERFC_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ERFC_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+ +
7 #include <cmath>
+
8 #include <valarray>
+
9 
+
10 #ifdef _MSC_VER
+
11 #include <boost/math/special_functions/erf.hpp>
+
12 using boost::math::erfc;
+
13 #endif
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  namespace {
+
19  class erfc_vari : public op_v_vari {
+
20  public:
+
21  explicit erfc_vari(vari* avi) :
+
22  op_v_vari(::erfc(avi->val_), avi) {
+
23  }
+
24  void chain() {
+
25  avi_->adj_ += adj_ * stan::math::NEG_TWO_OVER_SQRT_PI
+
26  * std::exp(- avi_->val_ * avi_->val_);
+
27  }
+
28  };
+
29  }
+
30 
+
68  inline var erfc(const var& a) {
+
69  return var(new erfc_vari(a.vi_));
+
70  }
+
71 
+
72  }
+
73 }
+
74 #endif
+ + +
var erfc(const var &a)
The complementary error function for variables (C99).
Definition: erfc.hpp:68
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
const double NEG_TWO_OVER_SQRT_PI
Definition: constants.hpp:163
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2exp2_8hpp.html b/doc/api/html/rev_2scal_2fun_2exp2_8hpp.html new file mode 100644 index 00000000000..6fca7c005f8 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2exp2_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/exp2.hpp File Reference + + + + + + + + + + +
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exp2.hpp File Reference
+
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+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <cmath>
+#include <valarray>
+
+

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var stan::math::exp2 (const var &a)
 Exponentiation base 2 function for variables (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2exp2_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2exp2_8hpp_source.html new file mode 100644 index 00000000000..31cee0d8f57 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2exp2_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/exp2.hpp Source File + + + + + + + + + + +
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exp2.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_EXP2_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_EXP2_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <cmath>
+
7 #include <valarray>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class exp2_vari : public op_v_vari {
+
14  public:
+
15  explicit exp2_vari(vari* avi) :
+
16  op_v_vari(std::pow(2.0, avi->val_), avi) {
+
17  }
+
18  void chain() {
+
19  avi_->adj_ += adj_ * val_ * stan::math::LOG_2;
+
20  }
+
21  };
+
22  }
+
23 
+
52  inline var exp2(const var& a) {
+
53  return var(new exp2_vari(a.vi_));
+
54  }
+
55 
+
56  }
+
57 }
+
58 #endif
+
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:33
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > exp2(const fvar< T > &x)
Definition: exp2.hpp:14
+ +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2exp_8hpp.html b/doc/api/html/rev_2scal_2fun_2exp_8hpp.html new file mode 100644 index 00000000000..5dcf50de7f4 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2exp_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/exp.hpp File Reference + + + + + + + + + + +
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exp.hpp File Reference
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+
#include <stan/math/rev/core.hpp>
+#include <cmath>
+
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var stan::math::exp (const var &a)
 Return the exponentiation of the specified variable (cmath). More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2exp_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2exp_8hpp_source.html new file mode 100644 index 00000000000..a5f1fd93aaa --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2exp_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/exp.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_EXP_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_EXP_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class exp_vari : public op_v_vari {
+
12  public:
+
13  explicit exp_vari(vari* avi) :
+
14  op_v_vari(std::exp(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ * val_;
+
18  }
+
19  };
+
20  }
+
21 
+
44  inline var exp(const var& a) {
+
45  return var(new exp_vari(a.vi_));
+
46  }
+
47 
+
48  }
+
49 }
+
50 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2expm1_8hpp.html b/doc/api/html/rev_2scal_2fun_2expm1_8hpp.html new file mode 100644 index 00000000000..12c34f7fbb5 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2expm1_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/expm1.hpp File Reference + + + + + + + + + + +
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expm1.hpp File Reference
+
+
+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <cmath>
+#include <valarray>
+
+

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var stan::math::expm1 (const stan::math::var &a)
 The exponentiation of the specified variable minus 1 (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2expm1_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2expm1_8hpp_source.html new file mode 100644 index 00000000000..3213d9471a9 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2expm1_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/expm1.hpp Source File + + + + + + + + + + +
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expm1.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_EXPM1_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_EXPM1_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+ +
7 #include <cmath>
+
8 #include <valarray>
+
9 
+
10 #ifdef _MSC_VER
+
11 #include <boost/math/special_functions/expm1.hpp>
+
12 using boost::math::expm1;
+
13 #endif
+
14 
+
15 namespace stan {
+
16  namespace math {
+
17 
+
18  namespace {
+
19  class expm1_vari : public op_v_vari {
+
20  public:
+
21  explicit expm1_vari(vari* avi) :
+
22  op_v_vari(::expm1(avi->val_), avi) {
+
23  }
+
24  void chain() {
+
25  avi_->adj_ += adj_ * (val_ + 1.0);
+
26  }
+
27  };
+
28  }
+
29 
+
57  inline var expm1(const stan::math::var& a) {
+
58  return var(new expm1_vari(a.vi_));
+
59  }
+
60 
+
61  }
+
62 }
+
63 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
var expm1(const stan::math::var &a)
The exponentiation of the specified variable minus 1 (C99).
Definition: expm1.hpp:57
+
fvar< T > expm1(const fvar< T > &x)
Definition: expm1.hpp:12
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fabs_8hpp.html b/doc/api/html/rev_2scal_2fun_2fabs_8hpp.html new file mode 100644 index 00000000000..53fa1aa7041 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fabs_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fabs.hpp File Reference + + + + + + + + + + +
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+Functions

var stan::math::fabs (const var &a)
 Return the absolute value of the variable (cmath). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fabs_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2fabs_8hpp_source.html new file mode 100644 index 00000000000..436fa65a10d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fabs_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fabs.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_FABS_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_FABS_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
50  inline var fabs(const var& a) {
+ +
52  // cut-and-paste from abs()
+
53  if (a.val() > 0.0)
+
54  return a;
+
55  else if (a.val() < 0.0)
+
56  return var(new neg_vari(a.vi_));
+
57  else if (a.val() == 0)
+
58  return var(new vari(0));
+
59  else
+ +
61  }
+
62 
+
63  }
+
64 }
+
65 #endif
+ +
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ +
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2falling__factorial_8hpp.html b/doc/api/html/rev_2scal_2fun_2falling__factorial_8hpp.html new file mode 100644 index 00000000000..130a9ee578d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2falling__factorial_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/falling_factorial.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
falling_factorial.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/falling_factorial.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

var stan::math::falling_factorial (const var &a, const double &b)
 
var stan::math::falling_factorial (const var &a, const var &b)
 
var stan::math::falling_factorial (const double &a, const var &b)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2falling__factorial_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2falling__factorial_8hpp_source.html new file mode 100644 index 00000000000..dd5031c1b71 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2falling__factorial_8hpp_source.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/falling_factorial.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
falling_factorial.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_FALLING_FACTORIAL_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_FALLING_FACTORIAL_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <boost/math/special_functions/digamma.hpp>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12 
+
13  class falling_factorial_vv_vari : public op_vv_vari {
+
14  public:
+
15  falling_factorial_vv_vari(vari* avi, vari* bvi) :
+
16  op_vv_vari(stan::math::falling_factorial(avi->val_, bvi->val_),
+
17  avi, bvi) {
+
18  }
+
19  void chain() {
+
20  avi_->adj_ += adj_
+
21  * val_
+
22  * (boost::math::digamma(avi_->val_ + 1)
+
23  - boost::math::digamma(avi_->val_ - bvi_->val_ + 1));
+
24  bvi_->adj_ += adj_
+
25  * val_
+
26  * boost::math::digamma(avi_->val_ - bvi_->val_ + 1);
+
27  }
+
28  };
+
29 
+
30  class falling_factorial_vd_vari : public op_vd_vari {
+
31  public:
+
32  falling_factorial_vd_vari(vari* avi, double b) :
+
33  op_vd_vari(stan::math::falling_factorial(avi->val_, b), avi, b) {
+
34  }
+
35  void chain() {
+
36  avi_->adj_ += adj_
+
37  * val_
+
38  * (boost::math::digamma(avi_->val_ + 1)
+
39  - boost::math::digamma(avi_->val_ - bd_ + 1));
+
40  }
+
41  };
+
42 
+
43  class falling_factorial_dv_vari : public op_dv_vari {
+
44  public:
+
45  falling_factorial_dv_vari(double a, vari* bvi) :
+
46  op_dv_vari(stan::math::falling_factorial(a, bvi->val_), a, bvi) {
+
47  }
+
48  void chain() {
+
49  bvi_->adj_ += adj_
+
50  * val_
+
51  * boost::math::digamma(ad_ - bvi_->val_ + 1);
+
52  }
+
53  };
+
54  }
+
55 
+
56  inline var falling_factorial(const var& a,
+
57  const double& b) {
+
58  return var(new falling_factorial_vd_vari(a.vi_, b));
+
59  }
+
60 
+
61  inline var falling_factorial(const var& a,
+
62  const var& b) {
+
63  return var(new falling_factorial_vv_vari(a.vi_, b.vi_));
+
64  }
+
65 
+
66  inline var falling_factorial(const double& a,
+
67  const var& b) {
+
68  return var(new falling_factorial_dv_vari(a, b.vi_));
+
69  }
+
70  }
+
71 }
+
72 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > falling_factorial(const fvar< T > &x, const fvar< T > &n)
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fdim_8hpp.html b/doc/api/html/rev_2scal_2fun_2fdim_8hpp.html new file mode 100644 index 00000000000..973f8a3d5d2 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fdim_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fdim.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
fdim.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/prim/scal/meta/likely.hpp>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::fdim (const stan::math::var &a, const stan::math::var &b)
 Return the positive difference between the first variable's the value and the second's (C99). More...
 
var stan::math::fdim (const double &a, const stan::math::var &b)
 Return the positive difference between the first value and the value of the second variable (C99). More...
 
var stan::math::fdim (const stan::math::var &a, const double &b)
 Return the positive difference between the first variable's value and the second value (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fdim_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2fdim_8hpp_source.html new file mode 100644 index 00000000000..d7d6c6eac24 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fdim_8hpp_source.html @@ -0,0 +1,202 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fdim.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
fdim.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_FDIM_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_FDIM_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <boost/math/special_functions/fpclassify.hpp>
+ +
7 #include <limits>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class fdim_vv_vari : public op_vv_vari {
+
14  public:
+
15  fdim_vv_vari(vari* avi, vari* bvi) :
+
16  op_vv_vari(avi->val_ - bvi->val_, avi, bvi) {
+
17  }
+
18  void chain() {
+
19  if (unlikely(boost::math::isnan(avi_->val_)
+
20  || boost::math::isnan(bvi_->val_))) {
+
21  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
22  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
23  } else {
+
24  avi_->adj_ += adj_;
+
25  bvi_->adj_ -= adj_;
+
26  }
+
27  }
+
28  };
+
29 
+
30  class fdim_vd_vari : public op_vd_vari {
+
31  public:
+
32  fdim_vd_vari(vari* avi, double b) :
+
33  op_vd_vari(avi->val_ - b, avi, b) {
+
34  }
+
35  void chain() {
+
36  if (unlikely(boost::math::isnan(avi_->val_)
+
37  || boost::math::isnan(bd_)))
+
38  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
39  else
+
40  avi_->adj_ += adj_;
+
41  }
+
42  };
+
43 
+
44  class fdim_dv_vari : public op_dv_vari {
+
45  public:
+
46  fdim_dv_vari(double a, vari* bvi) :
+
47  op_dv_vari(a - bvi->val_, a, bvi) {
+
48  }
+
49  void chain() {
+
50  if (unlikely(boost::math::isnan(bvi_->val_)
+
51  || boost::math::isnan(ad_)))
+
52  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
53  else
+
54  bvi_->adj_ -= adj_;
+
55  }
+
56  };
+
57  }
+
58 
+
110  inline var fdim(const stan::math::var& a,
+
111  const stan::math::var& b) {
+
112  if (!(a.vi_->val_ <= b.vi_->val_))
+
113  return var(new fdim_vv_vari(a.vi_, b.vi_));
+
114  else
+
115  return var(new vari(0.0));
+
116  }
+
117 
+
135  inline var fdim(const double& a,
+
136  const stan::math::var& b) {
+
137  return a <= b.vi_->val_
+
138  ? var(new vari(0.0))
+
139  : var(new fdim_dv_vari(a, b.vi_));
+
140  }
+
141 
+
158  inline var fdim(const stan::math::var& a,
+
159  const double& b) {
+
160  return a.vi_->val_ <= b
+
161  ? var(new vari(0.0))
+
162  : var(new fdim_vd_vari(a.vi_, b));
+
163  }
+
164 
+
165  }
+
166 }
+
167 #endif
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
fvar< T > fdim(const fvar< T > &x1, const fvar< T > &x2)
Definition: fdim.hpp:11
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2floor_8hpp.html b/doc/api/html/rev_2scal_2fun_2floor_8hpp.html new file mode 100644 index 00000000000..f8679bb5575 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2floor_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/floor.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
floor.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/prim/scal/meta/likely.hpp>
+#include <cmath>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

var stan::math::floor (const var &a)
 Return the floor of the specified variable (cmath). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2floor_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2floor_8hpp_source.html new file mode 100644 index 00000000000..52df90c743e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2floor_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/floor.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
floor.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_FLOOR_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_FLOOR_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <boost/math/special_functions/fpclassify.hpp>
+ +
7 #include <cmath>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class floor_vari : public op_v_vari {
+
15  public:
+
16  explicit floor_vari(vari* avi) :
+
17  op_v_vari(std::floor(avi->val_), avi) {
+
18  }
+
19  void chain() {
+
20  if (unlikely(boost::math::isnan(avi_->val_)))
+
21  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
22  }
+
23  };
+
24  }
+
25 
+
60  inline var floor(const var& a) {
+
61  return var(new floor_vari(a.vi_));
+
62  }
+
63 
+
64  }
+
65 }
+
66 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > floor(const fvar< T > &x)
Definition: floor.hpp:11
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fma_8hpp.html b/doc/api/html/rev_2scal_2fun_2fma_8hpp.html new file mode 100644 index 00000000000..2c5f836746e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fma_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fma.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
fma.hpp File Reference
+
+
+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/prim/scal/meta/likely.hpp>
+#include <valarray>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + + + + + + + + + + + + +

+Functions

var stan::math::fma (const stan::math::var &a, const stan::math::var &b, const stan::math::var &c)
 The fused multiply-add function for three variables (C99). More...
 
var stan::math::fma (const stan::math::var &a, const stan::math::var &b, const double &c)
 The fused multiply-add function for two variables and a value (C99). More...
 
var stan::math::fma (const stan::math::var &a, const double &b, const stan::math::var &c)
 The fused multiply-add function for a variable, value, and variable (C99). More...
 
var stan::math::fma (const stan::math::var &a, const double &b, const double &c)
 The fused multiply-add function for a variable and two values (C99). More...
 
var stan::math::fma (const double &a, const stan::math::var &b, const double &c)
 The fused multiply-add function for a value, variable, and value (C99). More...
 
var stan::math::fma (const double &a, const double &b, const stan::math::var &c)
 The fused multiply-add function for two values and a variable, and value (C99). More...
 
var stan::math::fma (const double &a, const stan::math::var &b, const stan::math::var &c)
 The fused multiply-add function for a value and two variables (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fma_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2fma_8hpp_source.html new file mode 100644 index 00000000000..f385c0250df --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fma_8hpp_source.html @@ -0,0 +1,278 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fma.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
fma.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_FMA_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_FMA_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+ +
7 #include <boost/math/special_functions/fpclassify.hpp>
+ +
9 #include <valarray>
+
10 #include <limits>
+
11 
+
12 #ifdef _MSC_VER
+
13 template<typename T>
+
14 T fma(T x, T y, T z) {
+
15  return x*y+z;
+
16 }
+
17 #endif
+
18 
+
19 namespace stan {
+
20  namespace math {
+
21 
+
22  namespace {
+
23  class fma_vvv_vari : public op_vvv_vari {
+
24  public:
+
25  fma_vvv_vari(vari* avi, vari* bvi, vari* cvi) :
+
26  op_vvv_vari(::fma(avi->val_, bvi->val_, cvi->val_),
+
27  avi, bvi, cvi) {
+
28  }
+
29  void chain() {
+
30  if (unlikely(boost::math::isnan(avi_->val_)
+
31  || boost::math::isnan(bvi_->val_)
+
32  || boost::math::isnan(cvi_->val_))) {
+
33  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
34  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
35  cvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
36  } else {
+
37  avi_->adj_ += adj_ * bvi_->val_;
+
38  bvi_->adj_ += adj_ * avi_->val_;
+
39  cvi_->adj_ += adj_;
+
40  }
+
41  }
+
42  };
+
43 
+
44  class fma_vvd_vari : public op_vvd_vari {
+
45  public:
+
46  fma_vvd_vari(vari* avi, vari* bvi, double c) :
+
47  op_vvd_vari(::fma(avi->val_, bvi->val_, c),
+
48  avi, bvi, c) {
+
49  }
+
50  void chain() {
+
51  if (unlikely(boost::math::isnan(avi_->val_)
+
52  || boost::math::isnan(bvi_->val_)
+
53  || boost::math::isnan(cd_))) {
+
54  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
55  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
56  } else {
+
57  avi_->adj_ += adj_ * bvi_->val_;
+
58  bvi_->adj_ += adj_ * avi_->val_;
+
59  }
+
60  }
+
61  };
+
62 
+
63  class fma_vdv_vari : public op_vdv_vari {
+
64  public:
+
65  fma_vdv_vari(vari* avi, double b, vari* cvi) :
+
66  op_vdv_vari(::fma(avi->val_ , b, cvi->val_),
+
67  avi, b, cvi) {
+
68  }
+
69  void chain() {
+
70  if (unlikely(boost::math::isnan(avi_->val_)
+
71  || boost::math::isnan(cvi_->val_)
+
72  || boost::math::isnan(bd_))) {
+
73  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
74  cvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
75  } else {
+
76  avi_->adj_ += adj_ * bd_;
+
77  cvi_->adj_ += adj_;
+
78  }
+
79  }
+
80  };
+
81 
+
82  class fma_vdd_vari : public op_vdd_vari {
+
83  public:
+
84  fma_vdd_vari(vari* avi, double b, double c) :
+
85  op_vdd_vari(::fma(avi->val_ , b, c),
+
86  avi, b, c) {
+
87  }
+
88  void chain() {
+
89  if (unlikely(boost::math::isnan(avi_->val_)
+
90  || boost::math::isnan(bd_)
+
91  || boost::math::isnan(cd_)))
+
92  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
93  else
+
94  avi_->adj_ += adj_ * bd_;
+
95  }
+
96  };
+
97 
+
98  class fma_ddv_vari : public op_ddv_vari {
+
99  public:
+
100  fma_ddv_vari(double a, double b, vari* cvi) :
+
101  op_ddv_vari(::fma(a, b, cvi->val_),
+
102  a, b, cvi) {
+
103  }
+
104  void chain() {
+
105  if (unlikely(boost::math::isnan(cvi_->val_)
+
106  || boost::math::isnan(ad_)
+
107  || boost::math::isnan(bd_)))
+
108  cvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
109  else
+
110  cvi_->adj_ += adj_;
+
111  }
+
112  };
+
113  }
+
114 
+
136  inline var fma(const stan::math::var& a,
+
137  const stan::math::var& b,
+
138  const stan::math::var& c) {
+
139  return var(new fma_vvv_vari(a.vi_, b.vi_, c.vi_));
+
140  }
+
141 
+
161  inline var fma(const stan::math::var& a,
+
162  const stan::math::var& b,
+
163  const double& c) {
+
164  return var(new fma_vvd_vari(a.vi_, b.vi_, c));
+
165  }
+
166 
+
186  inline var fma(const stan::math::var& a,
+
187  const double& b,
+
188  const stan::math::var& c) {
+
189  return var(new fma_vdv_vari(a.vi_, b, c.vi_));
+
190  }
+
191 
+
209  inline var fma(const stan::math::var& a,
+
210  const double& b,
+
211  const double& c) {
+
212  return var(new fma_vdd_vari(a.vi_, b, c));
+
213  }
+
214 
+
232  inline var fma(const double& a,
+
233  const stan::math::var& b,
+
234  const double& c) {
+
235  return var(new fma_vdd_vari(b.vi_, a, c));
+
236  }
+
237 
+
255  inline var fma(const double& a,
+
256  const double& b,
+
257  const stan::math::var& c) {
+
258  return var(new fma_ddv_vari(a, b, c.vi_));
+
259  }
+
260 
+
280  inline var fma(const double& a,
+
281  const stan::math::var& b,
+
282  const stan::math::var& c) {
+
283  return var(new fma_vdv_vari(b.vi_, a, c.vi_)); // a-b symmetry
+
284  }
+
285 
+
286  }
+
287 }
+
288 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
fvar< typename stan::return_type< T1, T2, T3 >::type > fma(const fvar< T1 > &x1, const fvar< T2 > &x2, const fvar< T3 > &x3)
The fused multiply-add operation (C99).
Definition: fma.hpp:61
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
var fma(const double &a, const stan::math::var &b, const stan::math::var &c)
The fused multiply-add function for a value and two variables (C99).
Definition: fma.hpp:280
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2fmax_8hpp.html b/doc/api/html/rev_2scal_2fun_2fmax_8hpp.html new file mode 100644 index 00000000000..004fa2df1aa --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fmax_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fmax.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+ +
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fmax.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/scal/fun/is_nan.hpp>
+#include <stan/math/prim/scal/fun/is_nan.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/likely.hpp>
+
+

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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::fmax (const stan::math::var &a, const stan::math::var &b)
 Returns the maximum of the two variable arguments (C99). More...
 
var stan::math::fmax (const stan::math::var &a, const double &b)
 Returns the maximum of the variable and scalar, promoting the scalar to a variable if it is larger (C99). More...
 
var stan::math::fmax (const double &a, const stan::math::var &b)
 Returns the maximum of a scalar and variable, promoting the scalar to a variable if it is larger (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fmax_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2fmax_8hpp_source.html new file mode 100644 index 00000000000..3c251ccb3b4 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fmax_8hpp_source.html @@ -0,0 +1,193 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fmax.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
fmax.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_FMAX_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_FMAX_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <boost/math/special_functions/fpclassify.hpp>
+ + +
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
63  inline var fmax(const stan::math::var& a,
+
64  const stan::math::var& b) {
+ +
66  if (unlikely(is_nan(a))) {
+
67  if (unlikely(is_nan(b)))
+
68  return var(new precomp_vv_vari(NOT_A_NUMBER,
+
69  a.vi_, b.vi_,
+ +
71 
+
72  return b;
+
73  }
+
74 
+
75  if (unlikely(is_nan(b)))
+
76  return a;
+
77 
+
78  return a > b ? a : b;
+
79  }
+
80 
+
95  inline var fmax(const stan::math::var& a,
+
96  const double& b) {
+ +
98  if (unlikely(is_nan(a))) {
+
99  if (unlikely(is_nan(b)))
+ +
101  a.vi_,
+ +
103 
+
104  return var(b);
+
105  }
+
106 
+
107  if (unlikely(is_nan(b)))
+
108  return a;
+
109 
+
110  return a >= b ? a : var(b);
+
111  }
+
112 
+
127  inline var fmax(const double& a,
+
128  const stan::math::var& b) {
+ +
130  if (unlikely(is_nan(b))) {
+
131  if (unlikely(is_nan(a)))
+ +
133  b.vi_,
+ +
135  return var(a);
+
136  }
+
137 
+
138  if (unlikely(is_nan(a)))
+
139  return b;
+
140 
+
141  return a > b ? var(a) : b;
+
142  }
+
143 
+
144  }
+
145 }
+
146 #endif
+ +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + + +
int is_nan(const fvar< T > &x)
Returns 1 if the input's value is NaN and 0 otherwise.
Definition: is_nan.hpp:22
+
fvar< T > fmax(const fvar< T > &x1, const fvar< T > &x2)
Definition: fmax.hpp:13
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fmin_8hpp.html b/doc/api/html/rev_2scal_2fun_2fmin_8hpp.html new file mode 100644 index 00000000000..5c70713eec6 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fmin_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fmin.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
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+ +
+ + +
+
+ +
+
fmin.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/meta/likely.hpp>
+#include <stan/math/rev/scal/fun/is_nan.hpp>
+#include <stan/math/prim/scal/fun/is_nan.hpp>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::fmin (const stan::math::var &a, const stan::math::var &b)
 Returns the minimum of the two variable arguments (C99). More...
 
var stan::math::fmin (const stan::math::var &a, double b)
 Returns the minimum of the variable and scalar, promoting the scalar to a variable if it is larger (C99). More...
 
var stan::math::fmin (double a, const stan::math::var &b)
 Returns the minimum of a scalar and variable, promoting the scalar to a variable if it is larger (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fmin_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2fmin_8hpp_source.html new file mode 100644 index 00000000000..733333270d5 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fmin_8hpp_source.html @@ -0,0 +1,192 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fmin.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
fmin.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_FMIN_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_FMIN_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <boost/math/special_functions/fpclassify.hpp>
+ + + + +
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
59  inline var fmin(const stan::math::var& a,
+
60  const stan::math::var& b) {
+ +
62  if (unlikely(is_nan(a))) {
+
63  if (unlikely(is_nan(b)))
+
64  return var(new precomp_vv_vari(NOT_A_NUMBER,
+
65  a.vi_, b.vi_,
+ +
67  return b;
+
68  }
+
69 
+
70  if (unlikely(is_nan(b)))
+
71  return a;
+
72 
+
73  return a < b ? a : b;
+
74  }
+
75 
+
89  inline var fmin(const stan::math::var& a,
+
90  double b) {
+ +
92  if (unlikely(is_nan(a))) {
+
93  if (unlikely(is_nan(b)))
+
94  return var(new precomp_v_vari(NOT_A_NUMBER,
+
95  a.vi_,
+
96  NOT_A_NUMBER));
+
97  return var(b);
+
98  }
+
99 
+
100  if (unlikely(is_nan(b)))
+
101  return a;
+
102 
+
103  return a <= b ? a : var(b);
+
104  }
+
105 
+
120  inline var fmin(double a,
+
121  const stan::math::var& b) {
+ +
123  if (unlikely(is_nan(b))) {
+
124  if (unlikely(is_nan(a)))
+
125  return var(new precomp_v_vari(NOT_A_NUMBER,
+
126  b.vi_,
+
127  NOT_A_NUMBER));
+
128 
+
129  return var(a);
+
130  }
+
131 
+
132  if (unlikely(is_nan(a)))
+
133  return b;
+
134 
+
135  return b <= a ? b : var(a);
+
136  }
+
137 
+
138  }
+
139 }
+
140 #endif
+
fvar< T > fmin(const fvar< T > &x1, const fvar< T > &x2)
Definition: fmin.hpp:13
+ +
const double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition: constants.hpp:56
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + + +
int is_nan(const fvar< T > &x)
Returns 1 if the input's value is NaN and 0 otherwise.
Definition: is_nan.hpp:22
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fmod_8hpp.html b/doc/api/html/rev_2scal_2fun_2fmod_8hpp.html new file mode 100644 index 00000000000..fece557e348 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fmod_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fmod.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
fmod.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <cmath>
+#include <limits>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::fmod (const var &a, const var &b)
 Return the floating point remainder after dividing the first variable by the second (cmath). More...
 
var stan::math::fmod (const var &a, const double b)
 Return the floating point remainder after dividing the the first variable by the second scalar (cmath). More...
 
var stan::math::fmod (const double a, const var &b)
 Return the floating point remainder after dividing the first scalar by the second variable (cmath). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2fmod_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2fmod_8hpp_source.html new file mode 100644 index 00000000000..a86bd4e67da --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2fmod_8hpp_source.html @@ -0,0 +1,192 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/fmod.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + + + + + +
+
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+ +
+ + +
+
+
+
fmod.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_FMOD_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_FMOD_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <boost/math/special_functions/fpclassify.hpp>
+
6 #include <cmath>
+
7 #include <limits>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class fmod_vv_vari : public op_vv_vari {
+
14  public:
+
15  fmod_vv_vari(vari* avi, vari* bvi) :
+
16  op_vv_vari(std::fmod(avi->val_, bvi->val_), avi, bvi) {
+
17  }
+
18  void chain() {
+
19  if (unlikely(boost::math::isnan(avi_->val_)
+
20  || boost::math::isnan(bvi_->val_))) {
+
21  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
22  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
23  } else {
+
24  avi_->adj_ += adj_;
+
25  bvi_->adj_ -= adj_ * static_cast<int>(avi_->val_ / bvi_->val_);
+
26  }
+
27  }
+
28  };
+
29 
+
30  class fmod_vd_vari : public op_vd_vari {
+
31  public:
+
32  fmod_vd_vari(vari* avi, double b) :
+
33  op_vd_vari(std::fmod(avi->val_, b), avi, b) {
+
34  }
+
35  void chain() {
+
36  if (unlikely(boost::math::isnan(avi_->val_)
+
37  || boost::math::isnan(bd_)))
+
38  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
39  else
+
40  avi_->adj_ += adj_;
+
41  }
+
42  };
+
43 
+
44  class fmod_dv_vari : public op_dv_vari {
+
45  public:
+
46  fmod_dv_vari(double a, vari* bvi) :
+
47  op_dv_vari(std::fmod(a, bvi->val_), a, bvi) {
+
48  }
+
49  void chain() {
+
50  if (unlikely(boost::math::isnan(bvi_->val_)
+
51  || boost::math::isnan(ad_))) {
+
52  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
53  } else {
+
54  int d = static_cast<int>(ad_ / bvi_->val_);
+
55  bvi_->adj_ -= adj_ * d;
+
56  }
+
57  }
+
58  };
+
59  }
+
60 
+
103  inline var fmod(const var& a, const var& b) {
+
104  return var(new fmod_vv_vari(a.vi_, b.vi_));
+
105  }
+
106 
+
120  inline var fmod(const var& a, const double b) {
+
121  return var(new fmod_vd_vari(a.vi_, b));
+
122  }
+
123 
+
137  inline var fmod(const double a, const var& b) {
+
138  return var(new fmod_dv_vari(a, b.vi_));
+
139  }
+
140 
+
141  }
+
142 }
+
143 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > fmod(const fvar< T > &x1, const fvar< T > &x2)
Definition: fmod.hpp:16
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2gamma__p_8hpp.html b/doc/api/html/rev_2scal_2fun_2gamma__p_8hpp.html new file mode 100644 index 00000000000..0a2444a6555 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2gamma__p_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/gamma_p.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ +
+
gamma_p.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/gamma_p.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+#include <valarray>
+
+

Go to the source code of this file.

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+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

var stan::math::gamma_p (const stan::math::var &a, const stan::math::var &b)
 
var stan::math::gamma_p (const stan::math::var &a, const double &b)
 
var stan::math::gamma_p (const double &a, const stan::math::var &b)
 
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diff --git a/doc/api/html/rev_2scal_2fun_2gamma__p_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2gamma__p_8hpp_source.html new file mode 100644 index 00000000000..1b298ad3f02 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2gamma__p_8hpp_source.html @@ -0,0 +1,243 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/gamma_p.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
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+
+
+
gamma_p.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_GAMMA_P_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_GAMMA_P_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <boost/math/special_functions/gamma.hpp>
+
7 #include <boost/math/special_functions/digamma.hpp>
+
8 #include <valarray>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class gamma_p_vv_vari : public op_vv_vari {
+
15  public:
+
16  gamma_p_vv_vari(vari* avi, vari* bvi) :
+
17  op_vv_vari(stan::math::gamma_p(avi->val_, bvi->val_),
+
18  avi, bvi) {
+
19  }
+
20  void chain() {
+
21  // return zero derivative as gamma_p is flat
+
22  // to machine precision for b / a > 10
+
23  if (std::fabs(bvi_->val_ / avi_->val_) > 10 ) return;
+
24 
+
25  double u = stan::math::gamma_p(avi_->val_, bvi_->val_);
+
26 
+
27  double S = 0.0;
+
28  double s = 1.0;
+
29  double l = std::log(bvi_->val_);
+
30  double g = boost::math::tgamma(avi_->val_);
+
31  double dig = boost::math::digamma(avi_->val_);
+
32 
+
33  int k = 0;
+
34  double delta = s / (avi_->val_ * avi_->val_);
+
35 
+
36  while (std::fabs(delta) > 1e-6) {
+
37  S += delta;
+
38  ++k;
+
39  s *= -bvi_->val_ / k;
+
40  delta = s / ((k + avi_->val_) * (k + avi_->val_));
+
41  }
+
42 
+
43 
+
44  avi_->adj_ -= adj_ * ((u) * (dig - l)
+
45  + std::exp(avi_->val_ * l) * S / g);
+
46  bvi_->adj_ += adj_ * (std::exp(-bvi_->val_)
+
47  * std::pow(bvi_->val_, avi_->val_ - 1.0) / g);
+
48  }
+
49  };
+
50 
+
51  class gamma_p_vd_vari : public op_vd_vari {
+
52  public:
+
53  gamma_p_vd_vari(vari* avi, double b) :
+
54  op_vd_vari(stan::math::gamma_p(avi->val_, b),
+
55  avi, b) {
+
56  }
+
57  void chain() {
+
58  // return zero derivative as gamma_p is flat
+
59  // to machine precision for b / a > 10
+
60  if (std::fabs(bd_ / avi_->val_) > 10)
+
61  return;
+
62 
+
63  double u = stan::math::gamma_p(avi_->val_, bd_);
+
64 
+
65  double S = 0.0;
+
66  double s = 1.0;
+
67  double l = std::log(bd_);
+
68  double g = boost::math::tgamma(avi_->val_);
+
69  double dig = boost::math::digamma(avi_->val_);
+
70 
+
71  int k = 0;
+
72  double delta = s / (avi_->val_ * avi_->val_);
+
73 
+
74  while (std::fabs(delta) > 1e-6) {
+
75  S += delta;
+
76  ++k;
+
77  s *= -bd_ / k;
+
78  delta = s / ((k + avi_->val_) * (k + avi_->val_));
+
79  }
+
80 
+
81  avi_->adj_ -= adj_ * ((u) * (dig - l)
+
82  + std::exp(avi_->val_ * l) * S / g);
+
83  }
+
84  };
+
85 
+
86  class gamma_p_dv_vari : public op_dv_vari {
+
87  public:
+
88  gamma_p_dv_vari(double a, vari* bvi) :
+
89  op_dv_vari(stan::math::gamma_p(a, bvi->val_),
+
90  a, bvi) {
+
91  }
+
92  void chain() {
+
93  // return zero derivative as gamma_p is flat to
+
94  // machine precision for b / a > 10
+
95  if (std::fabs(bvi_->val_ / ad_) > 10 )
+
96  return;
+
97  bvi_->adj_ += adj_
+
98  * (std::exp(-bvi_->val_) * std::pow(bvi_->val_, ad_ - 1.0)
+
99  / boost::math::tgamma(ad_));
+
100  }
+
101  };
+
102  }
+
103 
+
104  inline var gamma_p(const stan::math::var& a,
+
105  const stan::math::var& b) {
+
106  return var(new gamma_p_vv_vari(a.vi_, b.vi_));
+
107  }
+
108 
+
109  inline var gamma_p(const stan::math::var& a,
+
110  const double& b) {
+
111  return var(new gamma_p_vd_vari(a.vi_, b));
+
112  }
+
113 
+
114  inline var gamma_p(const double& a,
+
115  const stan::math::var& b) {
+
116  return var(new gamma_p_dv_vari(a, b.vi_));
+
117  }
+
118 
+
119  }
+
120 }
+
121 #endif
+ +
fvar< T > fabs(const fvar< T > &x)
Definition: fabs.hpp:14
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_p.hpp:15
+ +
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2gamma__q_8hpp.html b/doc/api/html/rev_2scal_2fun_2gamma__q_8hpp.html new file mode 100644 index 00000000000..21049be1fec --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2gamma__q_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/gamma_q.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+
+ +
+
gamma_q.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/gamma_q.hpp>
+#include <stan/math/prim/scal/fun/grad_reg_inc_gamma.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+#include <valarray>
+
+

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+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

var stan::math::gamma_q (const stan::math::var &a, const stan::math::var &b)
 
var stan::math::gamma_q (const stan::math::var &a, const double &b)
 
var stan::math::gamma_q (const double &a, const stan::math::var &b)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2gamma__q_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2gamma__q_8hpp_source.html new file mode 100644 index 00000000000..706a57f3b98 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2gamma__q_8hpp_source.html @@ -0,0 +1,194 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/gamma_q.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
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+
+
+
gamma_q.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_GAMMA_Q_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_GAMMA_Q_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <boost/math/special_functions/gamma.hpp>
+
8 #include <boost/math/special_functions/digamma.hpp>
+
9 #include <valarray>
+
10 
+
11 namespace stan {
+
12  namespace math {
+
13 
+
14  namespace {
+
15  class gamma_q_vv_vari : public op_vv_vari {
+
16  public:
+
17  gamma_q_vv_vari(vari* avi, vari* bvi) :
+
18  op_vv_vari(stan::math::gamma_q(avi->val_, bvi->val_),
+
19  avi, bvi) {
+
20  }
+
21  void chain() {
+
22  avi_->adj_ += adj_
+
23  * stan::math::grad_reg_inc_gamma(avi_->val_, bvi_->val_,
+
24  boost::math::tgamma(avi_->val_),
+
25  boost::math::digamma(avi_->val_));
+
26  bvi_->adj_ -= adj_
+
27  * boost::math::gamma_p_derivative(avi_->val_, bvi_->val_);
+
28  }
+
29  };
+
30 
+
31  class gamma_q_vd_vari : public op_vd_vari {
+
32  public:
+
33  gamma_q_vd_vari(vari* avi, double b) :
+
34  op_vd_vari(stan::math::gamma_q(avi->val_, b),
+
35  avi, b) {
+
36  }
+
37  void chain() {
+
38  avi_->adj_ += adj_
+
39  * stan::math::grad_reg_inc_gamma(avi_->val_, bd_,
+
40  boost::math::tgamma(avi_->val_),
+
41  boost::math::digamma(avi_->val_));
+
42  }
+
43  };
+
44 
+
45  class gamma_q_dv_vari : public op_dv_vari {
+
46  public:
+
47  gamma_q_dv_vari(double a, vari* bvi) :
+
48  op_dv_vari(stan::math::gamma_q(a, bvi->val_),
+
49  a, bvi) {
+
50  }
+
51  void chain() {
+
52  bvi_->adj_ -= adj_
+
53  * boost::math::gamma_p_derivative(ad_, bvi_->val_);
+
54  }
+
55  };
+
56  }
+
57 
+
58  inline var gamma_q(const stan::math::var& a,
+
59  const stan::math::var& b) {
+
60  return var(new gamma_q_vv_vari(a.vi_, b.vi_));
+
61  }
+
62 
+
63  inline var gamma_q(const stan::math::var& a,
+
64  const double& b) {
+
65  return var(new gamma_q_vd_vari(a.vi_, b));
+
66  }
+
67 
+
68  inline var gamma_q(const double& a,
+
69  const stan::math::var& b) {
+
70  return var(new gamma_q_dv_vari(a, b.vi_));
+
71  }
+
72 
+
73  }
+
74 }
+
75 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2grad__inc__beta_8hpp.html b/doc/api/html/rev_2scal_2fun_2grad__inc__beta_8hpp.html new file mode 100644 index 00000000000..814ff32aa4f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2grad__inc__beta_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/grad_inc_beta.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+
grad_inc_beta.hpp File Reference
+
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 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + +

+Functions

void stan::math::grad_inc_beta (var &g1, var &g2, const var &a, const var &b, const var &z)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2grad__inc__beta_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2grad__inc__beta_8hpp_source.html new file mode 100644 index 00000000000..e0ae40a8ec0 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2grad__inc__beta_8hpp_source.html @@ -0,0 +1,170 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/grad_inc_beta.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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grad_inc_beta.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_GRAD_INC_BETA_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_GRAD_INC_BETA_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+ + + + + + + + + +
15 #include <cmath>
+
16 
+
17 namespace stan {
+
18  namespace math {
+
19 
+
20  // Gradient of the incomplete beta function beta(a, b, z)
+
21  // with respect to the first two arguments, using the
+
22  // equivalence to a hypergeometric function.
+
23  // See http://dlmf.nist.gov/8.17#ii
+
24  void grad_inc_beta(var& g1, var& g2,
+
25  const var& a, const var& b, const var& z) {
+
26  var c1 = log(z);
+
27  var c2 = log1m(z);
+
28  var c3 = exp(lbeta(a, b)) * inc_beta(a, b, z);
+
29  var C = exp(a * c1 + b * c2) / a;
+
30  var dF1 = 0;
+
31  var dF2 = 0;
+
32  if (value_of(value_of(C)))
+
33  grad_2F1(dF1, dF2, a + b, var(1.0), a + 1, z);
+
34  g1 = (c1 - 1.0 / a) * c3 + C * (dF1 + dF2);
+
35  g2 = c2 * c3 + C * dF1;
+
36  }
+
37 
+
38  }
+
39 }
+
40 #endif
+ + + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+ +
void grad_inc_beta(stan::math::fvar< T > &g1, stan::math::fvar< T > &g2, stan::math::fvar< T > a, stan::math::fvar< T > b, stan::math::fvar< T > z)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ + + + + + + + +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
void grad_2F1(T &gradA, T &gradC, T a, T b, T c, T z, T precision=1e-6)
Definition: grad_2F1.hpp:13
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2hypot_8hpp.html b/doc/api/html/rev_2scal_2fun_2hypot_8hpp.html new file mode 100644 index 00000000000..067bbec20e7 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2hypot_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/hypot.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
hypot.hpp File Reference
+
+
+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <cmath>
+#include <valarray>
+
+

Go to the source code of this file.

+ + + + + + + +

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 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::hypot (const var &a, const var &b)
 Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99). More...
 
var stan::math::hypot (const var &a, double b)
 Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99). More...
 
var stan::math::hypot (double a, const var &b)
 Returns the length of the hypoteneuse of a right triangle with sides of the specified lengths (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2hypot_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2hypot_8hpp_source.html new file mode 100644 index 00000000000..50464385b61 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2hypot_8hpp_source.html @@ -0,0 +1,165 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/hypot.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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hypot.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_HYPOT_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_HYPOT_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+
6 #include <cmath>
+
7 #include <valarray>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class hypot_vv_vari : public op_vv_vari {
+
14  public:
+
15  hypot_vv_vari(vari* avi, vari* bvi) :
+
16  op_vv_vari(::hypot(avi->val_, bvi->val_),
+
17  avi, bvi) {
+
18  }
+
19  void chain() {
+
20  avi_->adj_ += adj_ * avi_->val_ / val_;
+
21  bvi_->adj_ += adj_ * bvi_->val_ / val_;
+
22  }
+
23  };
+
24 
+
25  class hypot_vd_vari : public op_v_vari {
+
26  public:
+
27  hypot_vd_vari(vari* avi, double b) :
+
28  op_v_vari(::hypot(avi->val_, b),
+
29  avi) {
+
30  }
+
31  void chain() {
+
32  avi_->adj_ += adj_ * avi_->val_ / val_;
+
33  }
+
34  };
+
35  }
+
36 
+
53  inline var hypot(const var& a, const var& b) {
+
54  return var(new hypot_vv_vari(a.vi_, b.vi_));
+
55  }
+
56 
+
71  inline var hypot(const var& a, double b) {
+
72  return var(new hypot_vd_vari(a.vi_, b));
+
73  }
+
74 
+
116  inline var hypot(double a, const var& b) {
+
117  return var(new hypot_vd_vari(b.vi_, a));
+
118  }
+
119 
+
120  }
+
121 }
+
122 #endif
+ +
fvar< T > hypot(const fvar< T > &x1, const fvar< T > &x2)
Definition: hypot.hpp:13
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2ibeta_8hpp.html b/doc/api/html/rev_2scal_2fun_2ibeta_8hpp.html new file mode 100644 index 00000000000..9d7d0ebce4c --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2ibeta_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/ibeta.hpp File Reference + + + + + + + + + + +
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ibeta.hpp File Reference
+
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+
#include <boost/math/special_functions/digamma.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/ibeta.hpp>
+
+

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var stan::math::ibeta (const var &a, const var &b, const var &x)
 The normalized incomplete beta function of a, b, and x. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2ibeta_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2ibeta_8hpp_source.html new file mode 100644 index 00000000000..d3812861616 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2ibeta_8hpp_source.html @@ -0,0 +1,349 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/ibeta.hpp Source File + + + + + + + + + + +
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ibeta.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_IBETA_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_IBETA_HPP
+
3 
+
4 #include <boost/math/special_functions/digamma.hpp>
+
5 #include <boost/math/special_functions/gamma.hpp>
+
6 #include <stan/math/rev/core.hpp>
+ +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
18  double ibeta_hypergeometric_helper(double a, double b, double z,
+
19  double precision = 1e-8,
+
20  double max_steps = 1000) {
+
21  double val = 0;
+
22  double diff = 1;
+
23  double k = 0;
+
24  double a_2 = a*a;
+
25  double bprod = 1;
+
26  while (std::abs(diff) > precision
+
27  && ++k < max_steps
+
28  && !std::isnan(diff)) {
+
29  val += diff;
+
30  bprod *= b+k-1.0;
+
31  diff = a_2 * std::pow(a+k, -2) * bprod * std::pow(z, k)
+
32  / boost::math::tgamma(k+1);
+
33  }
+
34  return val;
+
35  }
+
36 
+
37  class ibeta_vvv_vari : public op_vvv_vari {
+
38  public:
+
39  ibeta_vvv_vari(vari* avi, vari* bvi, vari* xvi) :
+
40  op_vvv_vari(stan::math::ibeta(avi->val_, bvi->val_, xvi->val_),
+
41  avi, bvi, xvi) {
+
42  }
+
43  void chain() {
+
44  double a = avi_->val_;
+
45  double b = bvi_->val_;
+
46  double c = cvi_->val_;
+
47 
+
48  using std::sin;
+
49  using std::pow;
+
50  using std::log;
+ +
52  using boost::math::tgamma;
+ +
54  using boost::math::ibeta;
+
55  using stan::math::ibeta_hypergeometric_helper;
+
56  avi_->adj_ += adj_ *
+
57  (log(c) - digamma(a) + digamma(a+b)) * val_
+
58  - tgamma(a) * tgamma(a+b) / tgamma(b) * pow(c, a)
+
59  / tgamma(1+a) / tgamma(1+a)
+
60  * ibeta_hypergeometric_helper(a, 1-b, c);
+
61  bvi_->adj_ += adj_ *
+
62  (tgamma(b) * tgamma(a+b) / tgamma(a) * pow(1-c, b)
+
63  * ibeta_hypergeometric_helper(b, 1-a, 1-c)
+
64  / tgamma(b+1) / tgamma(b+1)
+
65  + ibeta(b, a, 1-c) * (digamma(b) - digamma(a+b) - log(1-c)));
+
66  cvi_->adj_ += adj_ *
+
67  boost::math::ibeta_derivative(a, b, c);
+
68  }
+
69  };
+
70  class ibeta_vvd_vari : public op_vvd_vari {
+
71  public:
+
72  ibeta_vvd_vari(vari* avi, vari* bvi, double x) :
+
73  op_vvd_vari(stan::math::ibeta(avi->val_, bvi->val_, x), avi, bvi, x) {
+
74  }
+
75  void chain() {
+
76  double a = avi_->val_;
+
77  double b = bvi_->val_;
+
78  double c = cd_;
+
79 
+
80  using std::sin;
+
81  using std::pow;
+
82  using std::log;
+ +
84  using boost::math::tgamma;
+ +
86  using boost::math::ibeta;
+
87  using stan::math::ibeta_hypergeometric_helper;
+
88  avi_->adj_ += adj_ *
+
89  (log(c) - digamma(a) + digamma(a+b)) * val_ -
+
90  tgamma(a) * tgamma(a+b) / tgamma(b) * pow(c, a)
+
91  / tgamma(1+a) / tgamma(1+a)
+
92  * ibeta_hypergeometric_helper(a, 1-b, c);
+
93  bvi_->adj_ += adj_ *
+
94  (tgamma(b) * tgamma(a+b) / tgamma(a) * pow(1-c, b)
+
95  * ibeta_hypergeometric_helper(b, 1-a, 1-c)
+
96  / tgamma(b+1) / tgamma(b+1)
+
97  + ibeta(b, a, 1-c) * (digamma(b) - digamma(a+b) - log(1-c)));
+
98  }
+
99  };
+
100  class ibeta_vdv_vari : public op_vdv_vari {
+
101  public:
+
102  ibeta_vdv_vari(vari* avi, double b, vari* xvi) :
+
103  op_vdv_vari(stan::math::ibeta(avi->val_, b, xvi->val_), avi, b, xvi) {
+
104  }
+
105  void chain() {
+
106  double a = avi_->val_;
+
107  double b = bd_;
+
108  double c = cvi_->val_;
+
109 
+
110  using std::sin;
+
111  using std::pow;
+
112  using std::log;
+ +
114  using boost::math::tgamma;
+
115  using boost::math::digamma;
+
116  using boost::math::ibeta;
+
117  using stan::math::ibeta_hypergeometric_helper;
+
118  avi_->adj_ += adj_ *
+
119  (log(c) - digamma(a) + digamma(a+b)) * val_
+
120  - tgamma(a) * tgamma(a+b) / tgamma(b) * pow(c, a)
+
121  / tgamma(1+a) / tgamma(1+a)
+
122  * ibeta_hypergeometric_helper(a, 1-b, c);
+
123  cvi_->adj_ += adj_ *
+
124  boost::math::ibeta_derivative(a, b, c);
+
125  }
+
126  };
+
127  class ibeta_vdd_vari : public op_vdd_vari {
+
128  public:
+
129  ibeta_vdd_vari(vari* avi, double b, double x) :
+
130  op_vdd_vari(stan::math::ibeta(avi->val_, b, x), avi, b, x) {
+
131  }
+
132  void chain() {
+
133  double a = avi_->val_;
+
134  double b = bd_;
+
135  double c = cd_;
+
136 
+
137  using std::sin;
+
138  using std::pow;
+
139  using std::log;
+ +
141  using boost::math::tgamma;
+
142  using boost::math::digamma;
+
143  using boost::math::ibeta;
+
144  using stan::math::ibeta_hypergeometric_helper;
+
145  avi_->adj_ += adj_ *
+
146  (log(c) - digamma(a) + digamma(a+b)) * val_
+
147  - tgamma(a) * tgamma(a+b) / tgamma(b) * pow(c, a)
+
148  / tgamma(1+a) / tgamma(1+a)
+
149  * ibeta_hypergeometric_helper(a, 1-b, c);
+
150  }
+
151  };
+
152  class ibeta_dvv_vari : public op_dvv_vari {
+
153  public:
+
154  ibeta_dvv_vari(double a, vari* bvi, vari* xvi) :
+
155  op_dvv_vari(stan::math::ibeta(a, bvi->val_, xvi->val_), a, bvi, xvi) {
+
156  }
+
157  void chain() {
+
158  double a = ad_;
+
159  double b = bvi_->val_;
+
160  double c = cvi_->val_;
+
161 
+
162  using std::sin;
+
163  using std::pow;
+
164  using std::log;
+ +
166  using boost::math::tgamma;
+
167  using boost::math::digamma;
+
168  using boost::math::ibeta;
+
169  using stan::math::ibeta_hypergeometric_helper;
+
170  bvi_->adj_ += adj_ *
+
171  (tgamma(b) * tgamma(a+b) / tgamma(a) * pow(1-c, b)
+
172  * ibeta_hypergeometric_helper(b, 1-a, 1-c)
+
173  / tgamma(b+1) / tgamma(b+1)
+
174  + ibeta(b, a, 1-c) * (digamma(b) - digamma(a+b) - log(1-c)));
+
175  cvi_->adj_ += adj_ *
+
176  boost::math::ibeta_derivative(a, b, c);
+
177  }
+
178  };
+
179  class ibeta_dvd_vari : public op_dvd_vari {
+
180  public:
+
181  ibeta_dvd_vari(double a, vari* bvi, double x) :
+
182  op_dvd_vari(stan::math::ibeta(a, bvi->val_, x), a, bvi, x) {
+
183  }
+
184  void chain() {
+
185  double a = ad_;
+
186  double b = bvi_->val_;
+
187  double c = cd_;
+
188 
+
189  using std::sin;
+
190  using std::pow;
+
191  using std::log;
+ +
193  using boost::math::tgamma;
+
194  using boost::math::digamma;
+
195  using boost::math::ibeta;
+
196  using stan::math::ibeta_hypergeometric_helper;
+
197  bvi_->adj_ += adj_ *
+
198  (tgamma(b) * tgamma(a+b) / tgamma(a) * pow(1-c, b)
+
199  * ibeta_hypergeometric_helper(b, 1-a, 1-c)
+
200  / tgamma(b+1) / tgamma(b+1)
+
201  + ibeta(b, a, 1-c) * (digamma(b) - digamma(a+b) - log(1-c)));
+
202  }
+
203  };
+
204  class ibeta_ddv_vari : public op_ddv_vari {
+
205  public:
+
206  ibeta_ddv_vari(double a, double b, vari* xvi) :
+
207  op_ddv_vari(stan::math::ibeta(a, b, xvi->val_), a, b, xvi) {
+
208  }
+
209  void chain() {
+
210  double a = ad_;
+
211  double b = bd_;
+
212  double c = cvi_->val_;
+
213 
+
214  cvi_->adj_ += adj_ *
+
215  boost::math::ibeta_derivative(a, b, c);
+
216  }
+
217  };
+
218  }
+
219 
+
238  inline var ibeta(const var& a,
+
239  const var& b,
+
240  const var& x) {
+
241  return var(new ibeta_vvv_vari(a.vi_, b.vi_, x.vi_));
+
242  }
+
243 
+
244  }
+
245 }
+
246 #endif
+
fvar< T > abs(const fvar< T > &x)
Definition: abs.hpp:15
+ +
double ibeta(const double a, const double b, const double x)
The normalized incomplete beta function of a, b, and x.
Definition: ibeta.hpp:23
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
int isnan(const stan::math::var &a)
Checks if the given number is NaN.
Definition: std_isnan.hpp:18
+
fvar< T > sin(const fvar< T > &x)
Definition: sin.hpp:14
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
double e()
Return the base of the natural logarithm.
Definition: constants.hpp:95
+
var ibeta(const var &a, const var &b, const var &x)
The normalized incomplete beta function of a, b, and x.
Definition: ibeta.hpp:238
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2if__else_8hpp.html b/doc/api/html/rev_2scal_2fun_2if__else_8hpp.html new file mode 100644 index 00000000000..45ddc09d255 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2if__else_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/if_else.hpp File Reference + + + + + + + + + + +
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if_else.hpp File Reference
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var stan::math::if_else (bool c, const var &y_true, const var &y_false)
 If the specified condition is true, return the first variable, otherwise return the second variable. More...
 
var stan::math::if_else (bool c, double y_true, const var &y_false)
 If the specified condition is true, return a new variable constructed from the first scalar, otherwise return the second variable. More...
 
var stan::math::if_else (bool c, const var &y_true, const double y_false)
 If the specified condition is true, return the first variable, otherwise return a new variable constructed from the second scalar. More...
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2if__else_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2if__else_8hpp_source.html new file mode 100644 index 00000000000..77559d5d989 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2if__else_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/if_else.hpp Source File + + + + + + + + + + +
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if_else.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_IF_ELSE_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_IF_ELSE_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
17  inline var if_else(bool c, const var& y_true, const var&y_false) {
+
18  return c ? y_true : y_false;
+
19  }
+
29  inline var if_else(bool c, double y_true, const var& y_false) {
+
30  if (c)
+
31  return var(y_true);
+
32  else
+
33  return y_false;
+
34  }
+
44  inline var if_else(bool c, const var& y_true, const double y_false) {
+
45  if (c)
+
46  return y_true;
+
47  else
+
48  return var(y_false);
+
49  }
+
50 
+
51  }
+
52 }
+
53 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
boost::math::tools::promote_args< T_true, T_false >::type if_else(const bool c, const T_true y_true, const T_false y_false)
Return the second argument if the first argument is true and otherwise return the second argument...
Definition: if_else.hpp:25
+
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diff --git a/doc/api/html/rev_2scal_2fun_2inc__beta_8hpp.html b/doc/api/html/rev_2scal_2fun_2inc__beta_8hpp.html new file mode 100644 index 00000000000..d07f8cdf24e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inc__beta_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inc_beta.hpp File Reference + + + + + + + + + + +
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var stan::math::inc_beta (const stan::math::var &a, const stan::math::var &b, const stan::math::var &c)
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2inc__beta_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2inc__beta_8hpp_source.html new file mode 100644 index 00000000000..5798366cb43 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inc__beta_8hpp_source.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inc_beta.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_INC_BETA_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_INC_BETA_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + + + +
10 #include <valarray>
+
11 
+
12 namespace stan {
+
13  namespace math {
+
14 
+
15  namespace {
+
16 
+
17  class inc_beta_vvv_vari : public op_vvv_vari {
+
18  public:
+
19  inc_beta_vvv_vari(vari* avi, vari* bvi, vari* cvi) :
+
20  op_vvv_vari(stan::math::inc_beta(avi->val_, bvi->val_, cvi->val_),
+
21  avi, bvi, cvi) {
+
22  }
+
23  void chain() {
+
24  using stan::math::digamma;
+
25  using stan::math::lbeta;
+
26 
+
27  double d_a; double d_b;
+
28  stan::math::grad_reg_inc_beta(d_a, d_b, avi_->val_, bvi_->val_,
+
29  cvi_->val_, digamma(avi_->val_),
+
30  digamma(bvi_->val_),
+
31  digamma(avi_->val_ + bvi_->val_),
+
32  std::exp(lbeta(avi_->val_,
+
33  bvi_->val_)));
+
34 
+
35  avi_->adj_ += adj_ * d_a;
+
36  bvi_->adj_ += adj_ * d_b;
+
37  cvi_->adj_ += adj_ * std::pow((1-cvi_->val_), bvi_->val_-1)
+
38  * std::pow(cvi_->val_, avi_->val_-1)
+
39  / std::exp(stan::math::lbeta(avi_->val_, bvi_->val_));
+
40  }
+
41  };
+
42 
+
43  }
+
44 
+
45  inline var inc_beta(const stan::math::var& a,
+
46  const stan::math::var& b,
+
47  const stan::math::var& c) {
+
48  return var(new inc_beta_vvv_vari(a.vi_, b.vi_, c.vi_));
+
49  }
+
50 
+
51  }
+
52 }
+
53 #endif
+ + +
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2inv_8hpp.html b/doc/api/html/rev_2scal_2fun_2inv_8hpp.html new file mode 100644 index 00000000000..5e13e486825 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv.hpp File Reference + + + + + + + + + + +
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#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/inv.hpp>
+#include <valarray>
+
+

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var stan::math::inv (const var &a)
 

+\[ \mbox{inv}(x) = \begin{cases} \frac{1}{x} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/rev_2scal_2fun_2inv_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2inv_8hpp_source.html new file mode 100644 index 00000000000..cb775b6e660 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_INV_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_INV_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <valarray>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class inv_vari : public op_v_vari {
+
13  public:
+
14  explicit inv_vari(vari* avi) :
+
15  op_v_vari(stan::math::inv(avi->val_), avi) {
+
16  }
+
17  void chain() {
+
18  avi_->adj_ -= adj_ / (avi_->val_ * avi_->val_);
+
19  }
+
20  };
+
21  }
+
22 
+
42  inline var inv(const var& a) {
+
43  return var(new inv_vari(a.vi_));
+
44  }
+
45 
+
46  }
+
47 }
+
48 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > inv(const fvar< T > &x)
Definition: inv.hpp:15
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2inv___phi_8hpp.html b/doc/api/html/rev_2scal_2fun_2inv___phi_8hpp.html new file mode 100644 index 00000000000..707a46e0519 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv___phi_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_Phi.hpp File Reference + + + + + + + + + + +
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var stan::math::inv_Phi (const stan::math::var &p)
 The inverse of unit normal cumulative density function. More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2inv___phi_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2inv___phi_8hpp_source.html new file mode 100644 index 00000000000..b44e77b20ac --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv___phi_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_Phi.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_INV_PHI_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_INV_PHI_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class inv_Phi_vari : public op_v_vari {
+
14  public:
+
15  explicit inv_Phi_vari(vari* avi) :
+
16  op_v_vari(stan::math::inv_Phi(avi->val_), avi) {
+
17  }
+
18  void chain() {
+
19  static const double NEG_HALF = -0.5;
+
20  avi_->adj_ += adj_
+ +
22  / std::exp(NEG_HALF * val_ * val_);
+
23  }
+
24  };
+
25  }
+
26 
+
37  inline var inv_Phi(const stan::math::var& p) {
+
38  return var(new inv_Phi_vari(p.vi_));
+
39  }
+
40 
+
41  }
+
42 }
+
43 #endif
+ +
fvar< T > inv_Phi(const fvar< T > &p)
Definition: inv_Phi.hpp:15
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double SQRT_2_TIMES_SQRT_PI
Definition: constants.hpp:158
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
+
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diff --git a/doc/api/html/rev_2scal_2fun_2inv__cloglog_8hpp.html b/doc/api/html/rev_2scal_2fun_2inv__cloglog_8hpp.html new file mode 100644 index 00000000000..e1bfb3cd74e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv__cloglog_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_cloglog.hpp File Reference + + + + + + + + + + +
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var stan::math::inv_cloglog (const stan::math::var &a)
 Return the inverse complementary log-log function applied specified variable (stan). More...
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2inv__cloglog_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2inv__cloglog_8hpp_source.html new file mode 100644 index 00000000000..c8ed217622d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv__cloglog_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_cloglog.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_INV_CLOGLOG_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_INV_CLOGLOG_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class inv_cloglog_vari : public op_v_vari {
+
12  public:
+
13  explicit inv_cloglog_vari(vari* avi) :
+
14  op_v_vari(stan::math::inv_cloglog(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ * std::exp(avi_->val_ - std::exp(avi_->val_));
+
18  }
+
19  };
+
20  }
+
21 
+
36  inline var inv_cloglog(const stan::math::var& a) {
+
37  return var(new inv_cloglog_vari(a.vi_));
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > inv_cloglog(const fvar< T > &x)
Definition: inv_cloglog.hpp:15
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2inv__logit_8hpp.html b/doc/api/html/rev_2scal_2fun_2inv__logit_8hpp.html new file mode 100644 index 00000000000..fe84de551e3 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv__logit_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_logit.hpp File Reference + + + + + + + + + + +
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var stan::math::inv_logit (const stan::math::var &a)
 The inverse logit function for variables (stan). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2inv__logit_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2inv__logit_8hpp_source.html new file mode 100644 index 00000000000..bf14cf4e5b6 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv__logit_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_logit.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_INV_LOGIT_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_INV_LOGIT_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class inv_logit_vari : public op_v_vari {
+
12  public:
+
13  explicit inv_logit_vari(vari* avi) :
+
14  op_v_vari(stan::math::inv_logit(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ * val_ * (1.0 - val_);
+
18  }
+
19  };
+
20  }
+
21 
+
34  inline var inv_logit(const stan::math::var& a) {
+
35  return var(new inv_logit_vari(a.vi_));
+
36  }
+
37 
+
38  }
+
39 }
+
40 #endif
+ + +
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2inv__sqrt_8hpp.html b/doc/api/html/rev_2scal_2fun_2inv__sqrt_8hpp.html new file mode 100644 index 00000000000..2e2dc5fa6b8 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv__sqrt_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_sqrt.hpp File Reference + + + + + + + + + + +
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#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/inv_sqrt.hpp>
+#include <valarray>
+
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var stan::math::inv_sqrt (const var &a)
 

+\[ \mbox{inv\_sqrt}(x) = \begin{cases} \frac{1}{\sqrt{x}} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/rev_2scal_2fun_2inv__sqrt_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2inv__sqrt_8hpp_source.html new file mode 100644 index 00000000000..59de76cfe8b --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv__sqrt_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_sqrt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_INV_SQRT_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_INV_SQRT_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <valarray>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class inv_sqrt_vari : public op_v_vari {
+
13  public:
+
14  explicit inv_sqrt_vari(vari* avi) :
+
15  op_v_vari(stan::math::inv_sqrt(avi->val_), avi) {
+
16  }
+
17  void chain() {
+
18  avi_->adj_ -= 0.5 * adj_ / (avi_->val_ * std::sqrt(avi_->val_));
+
19  }
+
20  };
+
21  }
+
22 
+
42  inline var inv_sqrt(const var& a) {
+
43  return var(new inv_sqrt_vari(a.vi_));
+
44  }
+
45 
+
46  }
+
47 }
+
48 #endif
+ +
fvar< T > inv_sqrt(const fvar< T > &x)
Definition: inv_sqrt.hpp:15
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2inv__square_8hpp.html b/doc/api/html/rev_2scal_2fun_2inv__square_8hpp.html new file mode 100644 index 00000000000..f8e84ae7be2 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv__square_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_square.hpp File Reference + + + + + + + + + + +
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+
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+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/inv_square.hpp>
+#include <valarray>
+
+

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var stan::math::inv_square (const var &a)
 

+\[ \mbox{inv\_square}(x) = \begin{cases} \frac{1}{x^2} & \mbox{if } -\infty\leq x \leq \infty \\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/rev_2scal_2fun_2inv__square_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2inv__square_8hpp_source.html new file mode 100644 index 00000000000..76cfa9ddf65 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2inv__square_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/inv_square.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_INV_SQUARE_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_INV_SQUARE_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <valarray>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class inv_square_vari : public op_v_vari {
+
13  public:
+
14  explicit inv_square_vari(vari* avi) :
+
15  op_v_vari(stan::math::inv_square(avi->val_), avi) {
+
16  }
+
17  void chain() {
+
18  avi_->adj_ -= 2 * adj_ / (avi_->val_ * avi_->val_ * avi_->val_);
+
19  }
+
20  };
+
21  }
+
22 
+
42  inline var inv_square(const var& a) {
+
43  return var(new inv_square_vari(a.vi_));
+
44  }
+
45 
+
46  }
+
47 }
+
48 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > inv_square(const fvar< T > &x)
Definition: inv_square.hpp:15
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2is__inf_8hpp.html b/doc/api/html/rev_2scal_2fun_2is__inf_8hpp.html new file mode 100644 index 00000000000..e76b2bab23d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2is__inf_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/is_inf.hpp File Reference + + + + + + + + + + +
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int stan::math::is_inf (const var &v)
 Returns 1 if the input's value is infinite and 0 otherwise. More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2is__inf_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2is__inf_8hpp_source.html new file mode 100644 index 00000000000..d8a94a497c4 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2is__inf_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/is_inf.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_IS_INF_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_IS_INF_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
21  inline
+
22  int
+
23  is_inf(const var& v) {
+
24  return stan::math::is_inf(v.val());
+
25  }
+
26 
+
27  }
+
28 }
+
29 
+
30 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
int is_inf(const fvar< T > &x)
Returns 1 if the input's value is infinite and 0 otherwise.
Definition: is_inf.hpp:22
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2is__nan_8hpp.html b/doc/api/html/rev_2scal_2fun_2is__nan_8hpp.html new file mode 100644 index 00000000000..1a4c02cabcf --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2is__nan_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/is_nan.hpp File Reference + + + + + + + + + + +
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bool stan::math::is_nan (const var &v)
 Returns 1 if the input's value is NaN and 0 otherwise. More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2is__nan_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2is__nan_8hpp_source.html new file mode 100644 index 00000000000..17db93d140f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2is__nan_8hpp_source.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/is_nan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_IS_NAN_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_IS_NAN_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
21  inline bool is_nan(const var& v) {
+
22  return stan::math::is_nan(v.val());
+
23  }
+
24 
+
25  }
+
26 }
+
27 
+
28 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
int is_nan(const fvar< T > &x)
Returns 1 if the input's value is NaN and 0 otherwise.
Definition: is_nan.hpp:22
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2is__uninitialized_8hpp.html b/doc/api/html/rev_2scal_2fun_2is__uninitialized_8hpp.html new file mode 100644 index 00000000000..2fe981d03cc --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2is__uninitialized_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/is_uninitialized.hpp File Reference + + + + + + + + + + +
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bool stan::math::is_uninitialized (var x)
 Returns true if the specified variable is uninitialized. More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2is__uninitialized_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2is__uninitialized_8hpp_source.html new file mode 100644 index 00000000000..72098b9843b --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2is__uninitialized_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/is_uninitialized.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_IS_UNINITIALIZED_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_IS_UNINITIALIZED_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
23  inline bool is_uninitialized(var x) {
+
24  return x.is_uninitialized();
+
25  }
+
26 
+
27  }
+
28 }
+
29 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool is_uninitialized(T x)
Returns true if the specified variable is uninitialized.
+
bool is_uninitialized()
Return true if this variable has been declared, but not been defined.
Definition: var.hpp:54
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2lgamma_8hpp.html b/doc/api/html/rev_2scal_2fun_2lgamma_8hpp.html new file mode 100644 index 00000000000..86f59983a5c --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2lgamma_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/lgamma.hpp File Reference + + + + + + + + + + +
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+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+#include <valarray>
+
+

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var stan::math::lgamma (const stan::math::var &a)
 The log gamma function for variables (C99). More...
 
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2lgamma_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2lgamma_8hpp_source.html new file mode 100644 index 00000000000..d48ea908b4f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2lgamma_8hpp_source.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/lgamma.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LGAMMA_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LGAMMA_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <boost/math/special_functions/digamma.hpp>
+
7 #include <boost/math/special_functions/gamma.hpp>
+
8 #include <valarray>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class lgamma_vari : public op_v_vari {
+
15  public:
+
16  lgamma_vari(double value, vari* avi) :
+
17  op_v_vari(value, avi) {
+
18  }
+
19  void chain() {
+
20  avi_->adj_ += adj_ * boost::math::digamma(avi_->val_);
+
21  }
+
22  };
+
23  }
+
24 
+
35  inline var lgamma(const stan::math::var& a) {
+
36  double lgamma_a = boost::math::lgamma(a.val());
+
37  return var(new lgamma_vari(lgamma_a, a.vi_));
+
38  }
+
39 
+
40  }
+
41 }
+
42 #endif
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
var lgamma(const stan::math::var &a)
The log gamma function for variables (C99).
Definition: lgamma.hpp:35
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2lmgamma_8hpp.html b/doc/api/html/rev_2scal_2fun_2lmgamma_8hpp.html new file mode 100644 index 00000000000..4e9829a58db --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2lmgamma_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/lmgamma.hpp File Reference + + + + + + + + + + +
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var stan::math::lmgamma (int a, const stan::math::var &b)
 
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2lmgamma_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2lmgamma_8hpp_source.html new file mode 100644 index 00000000000..92b45e1a1bc --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2lmgamma_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/lmgamma.hpp Source File + + + + + + + + + + +
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lmgamma.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_LMGAMMA_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LMGAMMA_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + +
8 #include <valarray>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class lmgamma_dv_vari : public op_dv_vari {
+
15  public:
+
16  lmgamma_dv_vari(int a, vari* bvi) :
+
17  op_dv_vari(stan::math::lmgamma(a, bvi->val_), a, bvi) {
+
18  }
+
19  void chain() {
+
20  double deriv = 0;
+
21  for (int i = 1; i < ad_ + 1; i++)
+
22  deriv += stan::math::digamma(bvi_->val_ + (1.0 - i) / 2.0);
+
23  bvi_->adj_ += adj_ * deriv;
+
24  }
+
25  };
+
26  }
+
27 
+
28  inline var lmgamma(int a, const stan::math::var& b) {
+
29  return var(new lmgamma_dv_vari(a, b.vi_));
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
fvar< typename stan::return_type< T, int >::type > lmgamma(int x1, const fvar< T > &x2)
Definition: lmgamma.hpp:16
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log10_8hpp.html b/doc/api/html/rev_2scal_2fun_2log10_8hpp.html new file mode 100644 index 00000000000..c4bc24a4c21 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log10_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log10.hpp File Reference + + + + + + + + + + +
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#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <cmath>
+
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var stan::math::log10 (const var &a)
 Return the base 10 log of the specified variable (cmath). More...
 
+

Variable Documentation

+ +
+
+ + + + +
const double exp_val_
+
+ +

Definition at line 14 of file log10.hpp.

+ +
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diff --git a/doc/api/html/rev_2scal_2fun_2log10_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log10_8hpp_source.html new file mode 100644 index 00000000000..ec158167484 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log10_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log10.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG10_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG10_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <cmath>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class log10_vari : public op_v_vari {
+
13  public:
+
14  const double exp_val_;
+
15  explicit log10_vari(vari* avi) :
+
16  op_v_vari(std::log10(avi->val_), avi),
+
17  exp_val_(avi->val_) {
+
18  }
+
19  void chain() {
+
20  avi_->adj_ += adj_ / (stan::math::LOG_10 * exp_val_);
+
21  }
+
22  };
+
23  }
+
24 
+
54  inline var log10(const var& a) {
+
55  return var(new log10_vari(a.vi_));
+
56  }
+
57 
+
58  }
+
59 }
+
60 #endif
+ + + +
const double LOG_10
The natural logarithm of 10, .
Definition: constants.hpp:39
+
fvar< T > log10(const fvar< T > &x)
Definition: log10.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
const double exp_val_
Definition: log10.hpp:14
+ +
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log1m_8hpp.html b/doc/api/html/rev_2scal_2fun_2log1m_8hpp.html new file mode 100644 index 00000000000..de86f775592 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log1m_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log1m.hpp File Reference + + + + + + + + + + +
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var stan::math::log1m (const stan::math::var &a)
 The log (1 - x) function for variables. More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2log1m_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log1m_8hpp_source.html new file mode 100644 index 00000000000..968e5f9fffd --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log1m_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log1m.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG1M_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG1M_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class log1m_vari : public op_v_vari {
+
12  public:
+
13  explicit log1m_vari(vari* avi) :
+
14  op_v_vari(stan::math::log1p(-avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ / (avi_->val_ - 1);
+
18  }
+
19  };
+
20  }
+
21 
+
32  inline var log1m(const stan::math::var& a) {
+
33  return var(new log1m_vari(a.vi_));
+
34  }
+
35 
+
36  }
+
37 }
+
38 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log1m__exp_8hpp.html b/doc/api/html/rev_2scal_2fun_2log1m__exp_8hpp.html new file mode 100644 index 00000000000..7c36479efdc --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log1m__exp_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log1m_exp.hpp File Reference + + + + + + + + + + +
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var stan::math::log1m_exp (const stan::math::var &a)
 Return the log of 1 minus the exponential of the specified variable. More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2log1m__exp_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log1m__exp_8hpp_source.html new file mode 100644 index 00000000000..73e6e23369e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log1m__exp_8hpp_source.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log1m_exp.hpp Source File + + + + + + + + + + +
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log1m_exp.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG1M_EXP_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG1M_EXP_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <cmath>
+
8 
+
9 #ifdef _MSC_VER
+
10 #include <boost/math/special_functions/expm1.hpp>
+
11 using boost::math::expm1;
+
12 #endif
+
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  namespace {
+
18  class log1m_exp_v_vari : public op_v_vari {
+
19  public:
+
20  explicit log1m_exp_v_vari(vari* avi) :
+
21  op_v_vari(stan::math::log1m_exp(avi->val_),
+
22  avi) {
+
23  }
+
24  void chain() {
+
25  // derivative of
+
26  // log(1-exp(x)) = -exp(x)/(1-exp(x))
+
27  // = -1/(exp(-x)-1)
+
28  // = -1/expm1(-x)
+
29  avi_->adj_ -= adj_ / ::expm1(-(avi_->val_));
+
30  }
+
31  };
+
32  }
+
33 
+
38  inline var log1m_exp(const stan::math::var& a) {
+
39  return var(new log1m_exp_v_vari(a.vi_));
+
40  }
+
41 
+
42  }
+
43 }
+
44 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > expm1(const fvar< T > &x)
Definition: expm1.hpp:12
+
fvar< T > log1m_exp(const fvar< T > &x)
Definition: log1m_exp.hpp:16
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log1p_8hpp.html b/doc/api/html/rev_2scal_2fun_2log1p_8hpp.html new file mode 100644 index 00000000000..f210c8b33c7 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log1p_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log1p.hpp File Reference + + + + + + + + + + +
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var stan::math::log1p (const stan::math::var &a)
 The log (1 + x) function for variables (C99). More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log1p_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log1p_8hpp_source.html new file mode 100644 index 00000000000..ee54d8c3b77 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log1p_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log1p.hpp Source File + + + + + + + + + + +
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log1p.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG1P_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG1P_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <valarray>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class log1p_vari : public op_v_vari {
+
14  public:
+
15  explicit log1p_vari(vari* avi) :
+
16  op_v_vari(stan::math::log1p(avi->val_), avi) {
+
17  }
+
18  void chain() {
+
19  avi_->adj_ += adj_ / (1 + avi_->val_);
+
20  }
+
21  };
+
22  }
+
23 
+
34  inline var log1p(const stan::math::var& a) {
+
35  return var(new log1p_vari(a.vi_));
+
36  }
+
37 
+
38  }
+
39 }
+
40 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+ +
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log1p__exp_8hpp.html b/doc/api/html/rev_2scal_2fun_2log1p__exp_8hpp.html new file mode 100644 index 00000000000..a7b4995a0f2 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log1p__exp_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log1p_exp.hpp File Reference + + + + + + + + + + +
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log1p_exp.hpp File Reference
+
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+Functions

var stan::math::log1p_exp (const stan::math::var &a)
 Return the log of 1 plus the exponential of the specified variable. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2log1p__exp_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log1p__exp_8hpp_source.html new file mode 100644 index 00000000000..7b6302823ad --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log1p__exp_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log1p_exp.hpp Source File + + + + + + + + + + +
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+
log1p_exp.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG1P_EXP_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG1P_EXP_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class log1p_exp_v_vari : public op_v_vari {
+
13  public:
+
14  explicit log1p_exp_v_vari(vari* avi) :
+
15  op_v_vari(stan::math::log1p_exp(avi->val_),
+
16  avi) {
+
17  }
+
18  void chain() {
+
19  avi_->adj_ += adj_ * calculate_chain(avi_->val_, val_);
+
20  }
+
21  };
+
22  }
+
23 
+
28  inline var log1p_exp(const stan::math::var& a) {
+
29  return var(new log1p_exp_v_vari(a.vi_));
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
double calculate_chain(const double &x, const double &val)
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
fvar< T > log1p_exp(const fvar< T > &x)
Definition: log1p_exp.hpp:13
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2log2_8hpp.html b/doc/api/html/rev_2scal_2fun_2log2_8hpp.html new file mode 100644 index 00000000000..0d42ec46f77 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log2_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log2.hpp File Reference + + + + + + + + + + +
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var stan::math::log2 (const stan::math::var &a)
 Returns the base 2 logarithm of the specified variable (C99). More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log2_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log2_8hpp_source.html new file mode 100644 index 00000000000..762fe1bc79d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log2_8hpp_source.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log2.hpp Source File + + + + + + + + + + +
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log2.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG2_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG2_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12  class log2_vari : public op_v_vari {
+
13  public:
+
14  explicit log2_vari(vari* avi) :
+
15  op_v_vari(stan::math::log2(avi->val_), avi) {
+
16  }
+
17  void chain() {
+
18  avi_->adj_ += adj_ / (stan::math::LOG_2 * avi_->val_);
+
19  }
+
20  };
+
21  }
+
22 
+
53  inline var log2(const stan::math::var& a) {
+
54  return var(new log2_vari(a.vi_));
+
55  }
+
56 
+
57  }
+
58 }
+
59 #endif
+
const double LOG_2
The natural logarithm of 2, .
Definition: constants.hpp:33
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ + +
fvar< T > log2(const fvar< T > &x)
Definition: log2.hpp:17
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2log_8hpp.html b/doc/api/html/rev_2scal_2fun_2log_8hpp.html new file mode 100644 index 00000000000..7be414a7e53 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
log.hpp File Reference
+
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+
#include <stan/math/rev/core.hpp>
+#include <cmath>
+
+

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var stan::math::log (const var &a)
 Return the natural log of the specified variable (cmath). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2log_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log_8hpp_source.html new file mode 100644 index 00000000000..bb84a1efb9d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log.hpp Source File + + + + + + + + + + +
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log.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class log_vari : public op_v_vari {
+
12  public:
+
13  explicit log_vari(vari* avi) :
+
14  op_v_vari(std::log(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ / avi_->val_;
+
18  }
+
19  };
+
20  }
+
21 
+
50  inline var log(const var& a) {
+
51  return var(new log_vari(a.vi_));
+
52  }
+
53 
+
54  }
+
55 }
+
56 #endif
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log__diff__exp_8hpp.html b/doc/api/html/rev_2scal_2fun_2log__diff__exp_8hpp.html new file mode 100644 index 00000000000..bca7617c441 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__diff__exp_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_diff_exp.hpp File Reference + + + + + + + + + + +
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var stan::math::log_diff_exp (const stan::math::var &a, const stan::math::var &b)
 Returns the log sum of exponentials. More...
 
var stan::math::log_diff_exp (const stan::math::var &a, const double &b)
 Returns the log sum of exponentials. More...
 
var stan::math::log_diff_exp (const double &a, const stan::math::var &b)
 Returns the log sum of exponentials. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2log__diff__exp_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log__diff__exp_8hpp_source.html new file mode 100644 index 00000000000..106a0d09801 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__diff__exp_8hpp_source.html @@ -0,0 +1,184 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_diff_exp.hpp Source File + + + + + + + + + + +
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log_diff_exp.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG_DIFF_EXP_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG_DIFF_EXP_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <cmath>
+
8 
+
9 #ifdef _MSC_VER
+
10 #include <boost/math/special_functions/expm1.hpp>
+
11 using boost::math::expm1;
+
12 #endif
+
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  namespace {
+
18  class log_diff_exp_vv_vari : public op_vv_vari {
+
19  public:
+
20  log_diff_exp_vv_vari(vari* avi, vari* bvi) :
+
21  op_vv_vari(stan::math::log_diff_exp(avi->val_, bvi->val_),
+
22  avi, bvi) {
+
23  }
+
24  void chain() {
+
25  avi_->adj_ += adj_ * calculate_chain(avi_->val_, val_);
+
26  bvi_->adj_ -= adj_ / ::expm1(avi_->val_ - bvi_->val_);
+
27  }
+
28  };
+
29  class log_diff_exp_vd_vari : public op_vd_vari {
+
30  public:
+
31  log_diff_exp_vd_vari(vari* avi, double b) :
+
32  op_vd_vari(stan::math::log_diff_exp(avi->val_, b),
+
33  avi, b) {
+
34  }
+
35  void chain() {
+
36  avi_->adj_ += adj_ * calculate_chain(avi_->val_, val_);
+
37  }
+
38  };
+
39  class log_diff_exp_dv_vari : public op_dv_vari {
+
40  public:
+
41  log_diff_exp_dv_vari(double a, vari* bvi) :
+
42  op_dv_vari(stan::math::log_diff_exp(a, bvi->val_),
+
43  a, bvi) {
+
44  }
+
45  void chain() {
+
46  bvi_->adj_ -= adj_ / ::expm1(ad_ - bvi_->val_);
+
47  }
+
48  };
+
49  }
+
50 
+
54  inline var log_diff_exp(const stan::math::var& a,
+
55  const stan::math::var& b) {
+
56  return var(new log_diff_exp_vv_vari(a.vi_, b.vi_));
+
57  }
+
61  inline var log_diff_exp(const stan::math::var& a,
+
62  const double& b) {
+
63  return var(new log_diff_exp_vd_vari(a.vi_, b));
+
64  }
+
68  inline var log_diff_exp(const double& a,
+
69  const stan::math::var& b) {
+
70  return var(new log_diff_exp_dv_vari(a, b.vi_));
+
71  }
+
72 
+
73  }
+
74 }
+
75 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > log_diff_exp(const fvar< T > &x1, const fvar< T > &x2)
+
fvar< T > expm1(const fvar< T > &x)
Definition: expm1.hpp:12
+
double calculate_chain(const double &x, const double &val)
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log__falling__factorial_8hpp.html b/doc/api/html/rev_2scal_2fun_2log__falling__factorial_8hpp.html new file mode 100644 index 00000000000..1fce6eae37a --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__falling__factorial_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_falling_factorial.hpp File Reference + + + + + + + + + + +
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log_falling_factorial.hpp File Reference
+
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+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/log_falling_factorial.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
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var stan::math::log_falling_factorial (const var &a, const double &b)
 
var stan::math::log_falling_factorial (const var &a, const var &b)
 
var stan::math::log_falling_factorial (const double &a, const var &b)
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log__falling__factorial_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log__falling__factorial_8hpp_source.html new file mode 100644 index 00000000000..bfa89a41d4c --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__falling__factorial_8hpp_source.html @@ -0,0 +1,202 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_falling_factorial.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
log_falling_factorial.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG_FALLING_FACTORIAL_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG_FALLING_FACTORIAL_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <boost/math/special_functions/digamma.hpp>
+
7 #include <boost/math/special_functions/fpclassify.hpp>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14 
+
15  class log_falling_factorial_vv_vari : public op_vv_vari {
+
16  public:
+
17  log_falling_factorial_vv_vari(vari* avi, vari* bvi) :
+
18  op_vv_vari(stan::math::log_falling_factorial(avi->val_, bvi->val_),
+
19  avi, bvi) {
+
20  }
+
21  void chain() {
+
22  if (unlikely(boost::math::isnan(avi_->val_)
+
23  || boost::math::isnan(bvi_->val_))) {
+
24  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
25  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
26  } else {
+
27  avi_->adj_ += adj_
+
28  * (boost::math::digamma(avi_->val_ + 1)
+
29  - boost::math::digamma(avi_->val_ - bvi_->val_ + 1));
+
30  bvi_->adj_ += adj_
+
31  * boost::math::digamma(avi_->val_ - bvi_->val_ + 1);
+
32  }
+
33  }
+
34  };
+
35 
+
36  class log_falling_factorial_vd_vari : public op_vd_vari {
+
37  public:
+
38  log_falling_factorial_vd_vari(vari* avi, double b) :
+
39  op_vd_vari(stan::math::log_falling_factorial(avi->val_, b), avi, b) {
+
40  }
+
41  void chain() {
+
42  if (unlikely(boost::math::isnan(avi_->val_)
+
43  || boost::math::isnan(bd_)))
+
44  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
45  else
+
46  avi_->adj_ += adj_
+
47  * (boost::math::digamma(avi_->val_ + 1)
+
48  - boost::math::digamma(avi_->val_ - bd_ + 1));
+
49  }
+
50  };
+
51 
+
52  class log_falling_factorial_dv_vari : public op_dv_vari {
+
53  public:
+
54  log_falling_factorial_dv_vari(double a, vari* bvi) :
+
55  op_dv_vari(stan::math::log_falling_factorial(a, bvi->val_), a, bvi) {
+
56  }
+
57  void chain() {
+ +
59  || boost::math::isnan(bvi_->val_)))
+
60  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
61  else
+
62  bvi_->adj_ += adj_
+
63  * boost::math::digamma(ad_ - bvi_->val_ + 1);
+
64  }
+
65  };
+
66  }
+
67 
+
68  inline var log_falling_factorial(const var& a,
+
69  const double& b) {
+
70  return var(new log_falling_factorial_vd_vari(a.vi_, b));
+
71  }
+
72 
+
73  inline var log_falling_factorial(const var& a,
+
74  const var& b) {
+
75  return var(new log_falling_factorial_vv_vari(a.vi_, b.vi_));
+
76  }
+
77 
+
78  inline var log_falling_factorial(const double& a,
+
79  const var& b) {
+
80  return var(new log_falling_factorial_dv_vari(a, b.vi_));
+
81  }
+
82  }
+
83 }
+
84 #endif
+ +
fvar< T > log_falling_factorial(const fvar< T > &x, const fvar< T > &n)
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2log__mix_8hpp.html b/doc/api/html/rev_2scal_2fun_2log__mix_8hpp.html new file mode 100644 index 00000000000..98f65740284 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__mix_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_mix.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
log_mix.hpp File Reference
+
+
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Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

void stan::math::log_mix_partial_helper (const double &theta_val, const double &lambda1_val, const double &lambda2_val, double &one_m_exp_lam2_m_lam1, double &one_m_t_prod_exp_lam2_m_lam1, double &one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1)
 
template<typename T_theta , typename T_lambda1 , typename T_lambda2 >
return_type< T_theta, T_lambda1, T_lambda2 >::type stan::math::log_mix (const T_theta &theta, const T_lambda1 &lambda1, const T_lambda2 &lambda2)
 Return the log mixture density with specified mixing proportion and log densities and its derivative at each. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2log__mix_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log__mix_8hpp_source.html new file mode 100644 index 00000000000..dc5ca4bfbdf --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__mix_8hpp_source.html @@ -0,0 +1,241 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_mix.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
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+ +
+ + +
+
+
+
log_mix.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG_MIX_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG_MIX_HPP
+
3 
+ + + + + + + + +
12 #include <cmath>
+
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
17 
+
18  /* Computes shared terms in log_mix partial derivative calculations
+
19  *
+
20  * @param[in] theta_val value of mixing proportion theta.
+
21  * @param[in] lambda1_val value of log density multiplied by theta.
+
22  * @param[in] lambda2_val value of log density multiplied by 1 - theta.
+
23  * @param[out] one_m_exp_lam2_m_lam1 shared term in deriv calculation.
+
24  * @param[out] one_m_t_prod_exp_lam2_m_lam1 shared term in deriv calculation.
+
25  * @param[out] one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1 shared term in deriv calculation.
+
26  */
+
27  inline void
+
28  log_mix_partial_helper(const double& theta_val,
+
29  const double& lambda1_val,
+
30  const double& lambda2_val,
+
31  double& one_m_exp_lam2_m_lam1,
+
32  double& one_m_t_prod_exp_lam2_m_lam1,
+
33  double& one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1) {
+
34  using std::exp;
+
35  double lam2_m_lam1 = lambda2_val - lambda1_val;
+
36  double exp_lam2_m_lam1 = exp(lam2_m_lam1);
+
37  one_m_exp_lam2_m_lam1 = 1 - exp_lam2_m_lam1;
+
38  double one_m_t = 1 - theta_val;
+
39  one_m_t_prod_exp_lam2_m_lam1 = one_m_t * exp_lam2_m_lam1;
+
40  one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1
+
41  = 1 / (theta_val + one_m_t_prod_exp_lam2_m_lam1);
+
42  }
+
43 
+
83  template <typename T_theta,
+
84  typename T_lambda1,
+
85  typename T_lambda2>
+
86  inline
+ +
88  log_mix(const T_theta& theta,
+
89  const T_lambda1& lambda1,
+
90  const T_lambda2& lambda2) {
+
91  using std::log;
+
92  using stan::math::log_mix;
+
93  using stan::math::log1m;
+ +
95 
+ +
97  operands_and_partials(theta, lambda1, lambda2);
+
98 
+
99  double theta_double = value_of(theta);
+
100  const double lambda1_double = value_of(lambda1);
+
101  const double lambda2_double = value_of(lambda2);
+
102 
+
103  double log_mix_function_value
+
104  = log_mix(theta_double, lambda1_double, lambda2_double);
+
105 
+
106  double one_m_exp_lam2_m_lam1(0.0);
+
107  double one_m_t_prod_exp_lam2_m_lam1(0.0);
+
108  double one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1(0.0);
+
109 
+
110  if (lambda1 > lambda2) {
+
111  log_mix_partial_helper(theta_double,
+
112  lambda1_double,
+
113  lambda2_double,
+
114  one_m_exp_lam2_m_lam1,
+
115  one_m_t_prod_exp_lam2_m_lam1,
+
116  one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1);
+
117  } else {
+
118  log_mix_partial_helper(1.0 - theta_double,
+
119  lambda2_double,
+
120  lambda1_double,
+
121  one_m_exp_lam2_m_lam1,
+
122  one_m_t_prod_exp_lam2_m_lam1,
+
123  one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1);
+
124  one_m_exp_lam2_m_lam1 = -one_m_exp_lam2_m_lam1;
+
125  theta_double = one_m_t_prod_exp_lam2_m_lam1;
+
126  one_m_t_prod_exp_lam2_m_lam1 = 1.0 - value_of(theta);
+
127  }
+
128 
+ +
130  operands_and_partials.d_x1[0]
+
131  = one_m_exp_lam2_m_lam1
+
132  * one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1;
+ +
134  operands_and_partials.d_x2[0]
+
135  = theta_double
+
136  * one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1;
+ +
138  operands_and_partials.d_x3[0]
+
139  = one_m_t_prod_exp_lam2_m_lam1
+
140  * one_d_t_plus_one_m_t_prod_exp_lam2_m_lam1;
+
141 
+
142  return operands_and_partials.value(log_mix_function_value);
+
143  }
+
144 
+
145  } // namespace math
+
146 
+
147 } // namespace stan
+
148 
+
149 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+ + + + +
void log_mix_partial_helper(const T_theta &theta, const T_lambda1 &lambda1, const T_lambda2 &lambda2, typename boost::math::tools::promote_args< T_theta, T_lambda1, T_lambda2 >::type(&partials_array)[N])
Definition: log_mix.hpp:29
+ +
fvar< T > log_mix(const fvar< T > &theta, const fvar< T > &lambda1, const fvar< T > &lambda2)
Return the log mixture density with specified mixing proportion and log densities and its derivative ...
Definition: log_mix.hpp:117
+ +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2log__rising__factorial_8hpp.html b/doc/api/html/rev_2scal_2fun_2log__rising__factorial_8hpp.html new file mode 100644 index 00000000000..5554b49568e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__rising__factorial_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_rising_factorial.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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log_rising_factorial.hpp File Reference
+
+
+ +

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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

var stan::math::log_rising_factorial (const var &a, const double &b)
 
var stan::math::log_rising_factorial (const var &a, const var &b)
 
var stan::math::log_rising_factorial (const double &a, const var &b)
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log__rising__factorial_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log__rising__factorial_8hpp_source.html new file mode 100644 index 00000000000..1dbc0c539b0 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__rising__factorial_8hpp_source.html @@ -0,0 +1,183 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_rising_factorial.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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log_rising_factorial.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG_RISING_FACTORIAL_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG_RISING_FACTORIAL_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + +
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13 
+
14  class log_rising_factorial_vv_vari : public op_vv_vari {
+
15  public:
+
16  log_rising_factorial_vv_vari(vari* avi, vari* bvi) :
+
17  op_vv_vari(stan::math::log_rising_factorial(avi->val_, bvi->val_),
+
18  avi, bvi) {
+
19  }
+
20  void chain() {
+
21  avi_->adj_ += adj_ * (digamma(avi_->val_ + bvi_->val_)
+
22  - digamma(avi_->val_));
+
23  bvi_->adj_ += adj_ * digamma(avi_->val_ + bvi_->val_);
+
24  }
+
25  };
+
26 
+
27  class log_rising_factorial_vd_vari : public op_vd_vari {
+
28  public:
+
29  log_rising_factorial_vd_vari(vari* avi, double b) :
+
30  op_vd_vari(stan::math::log_rising_factorial(avi->val_, b), avi, b) {
+
31  }
+
32  void chain() {
+
33  avi_->adj_ += adj_ * (digamma(avi_->val_ + bd_)
+
34  - digamma(avi_->val_));
+
35  }
+
36  };
+
37 
+
38  class log_rising_factorial_dv_vari : public op_dv_vari {
+
39  public:
+
40  log_rising_factorial_dv_vari(double a, vari* bvi) :
+
41  op_dv_vari(stan::math::log_rising_factorial(a, bvi->val_), a, bvi) {
+
42  }
+
43  void chain() {
+
44  bvi_->adj_ += adj_ * digamma(bvi_->val_ + ad_);
+
45  }
+
46  };
+
47  }
+
48 
+
49  inline var log_rising_factorial(const var& a,
+
50  const double& b) {
+
51  return var(new log_rising_factorial_vd_vari(a.vi_, b));
+
52  }
+
53 
+
54  inline var log_rising_factorial(const var& a,
+
55  const var& b) {
+
56  return var(new log_rising_factorial_vv_vari(a.vi_, b.vi_));
+
57  }
+
58 
+
59  inline var log_rising_factorial(const double& a,
+
60  const var& b) {
+
61  return var(new log_rising_factorial_dv_vari(a, b.vi_));
+
62  }
+
63  }
+
64 }
+
65 #endif
+ + + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > log_rising_factorial(const fvar< T > &x, const fvar< T > &n)
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log__sum__exp_8hpp.html b/doc/api/html/rev_2scal_2fun_2log__sum__exp_8hpp.html new file mode 100644 index 00000000000..9a9354171a8 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__sum__exp_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_sum_exp.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
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var stan::math::log_sum_exp (const stan::math::var &a, const stan::math::var &b)
 Returns the log sum of exponentials. More...
 
var stan::math::log_sum_exp (const stan::math::var &a, const double &b)
 Returns the log sum of exponentials. More...
 
var stan::math::log_sum_exp (const double &a, const stan::math::var &b)
 Returns the log sum of exponentials. More...
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2log__sum__exp_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2log__sum__exp_8hpp_source.html new file mode 100644 index 00000000000..8d9dfd45433 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2log__sum__exp_8hpp_source.html @@ -0,0 +1,179 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/log_sum_exp.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+
log_sum_exp.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_LOG_SUM_EXP_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_LOG_SUM_EXP_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12 
+
13  class log_sum_exp_vv_vari : public op_vv_vari {
+
14  public:
+
15  log_sum_exp_vv_vari(vari* avi, vari* bvi) :
+
16  op_vv_vari(stan::math::log_sum_exp(avi->val_, bvi->val_),
+
17  avi, bvi) {
+
18  }
+
19  void chain() {
+
20  avi_->adj_ += adj_ * calculate_chain(avi_->val_, val_);
+
21  bvi_->adj_ += adj_ * calculate_chain(bvi_->val_, val_);
+
22  }
+
23  };
+
24  class log_sum_exp_vd_vari : public op_vd_vari {
+
25  public:
+
26  log_sum_exp_vd_vari(vari* avi, double b) :
+
27  op_vd_vari(stan::math::log_sum_exp(avi->val_, b),
+
28  avi, b) {
+
29  }
+
30  void chain() {
+
31  avi_->adj_ += adj_ * calculate_chain(avi_->val_, val_);
+
32  }
+
33  };
+
34  class log_sum_exp_dv_vari : public op_dv_vari {
+
35  public:
+
36  log_sum_exp_dv_vari(double a, vari* bvi) :
+
37  op_dv_vari(stan::math::log_sum_exp(a, bvi->val_),
+
38  a, bvi) {
+
39  }
+
40  void chain() {
+
41  bvi_->adj_ += adj_ * calculate_chain(bvi_->val_, val_);
+
42  }
+
43  };
+
44 
+
45  }
+
46 
+
50  inline var log_sum_exp(const stan::math::var& a,
+
51  const stan::math::var& b) {
+
52  return var(new log_sum_exp_vv_vari(a.vi_, b.vi_));
+
53  }
+
57  inline var log_sum_exp(const stan::math::var& a,
+
58  const double& b) {
+
59  return var(new log_sum_exp_vd_vari(a.vi_, b));
+
60  }
+
64  inline var log_sum_exp(const double& a,
+
65  const stan::math::var& b) {
+
66  return var(new log_sum_exp_dv_vari(a, b.vi_));
+
67  }
+
68 
+
69  }
+
70 }
+
71 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > log_sum_exp(const std::vector< fvar< T > > &v)
Definition: log_sum_exp.hpp:14
+ +
double calculate_chain(const double &x, const double &val)
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2modified__bessel__first__kind_8hpp.html b/doc/api/html/rev_2scal_2fun_2modified__bessel__first__kind_8hpp.html new file mode 100644 index 00000000000..d92dac5a832 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2modified__bessel__first__kind_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/modified_bessel_first_kind.hpp File Reference + + + + + + + + + + +
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var stan::math::modified_bessel_first_kind (const int &v, const var &a)
 
+
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+
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diff --git a/doc/api/html/rev_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html new file mode 100644 index 00000000000..d8f3c52fac2 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2modified__bessel__first__kind_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/modified_bessel_first_kind.hpp Source File + + + + + + + + + + +
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modified_bessel_first_kind.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_MODIFIED_BESSEL_FIRST_KIND_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_MODIFIED_BESSEL_FIRST_KIND_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11 
+
12  class modified_bessel_first_kind_dv_vari : public op_dv_vari {
+
13  public:
+
14  modified_bessel_first_kind_dv_vari(int a, vari* bvi) :
+
15  op_dv_vari(stan::math::modified_bessel_first_kind(a, bvi->val_),
+
16  a, bvi) {
+
17  }
+
18  void chain() {
+
19  bvi_->adj_ += adj_
+
20  * (-ad_ * stan::math::modified_bessel_first_kind(ad_, bvi_->val_)
+
21  / bvi_->val_
+
22  + stan::math::modified_bessel_first_kind(ad_ - 1, bvi_->val_));
+
23  }
+
24  };
+
25  }
+
26 
+
27  inline var modified_bessel_first_kind(const int& v,
+
28  const var& a) {
+
29  return var(new modified_bessel_first_kind_dv_vari(v, a.vi_));
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > modified_bessel_first_kind(int v, const fvar< T > &z)
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2modified__bessel__second__kind_8hpp.html b/doc/api/html/rev_2scal_2fun_2modified__bessel__second__kind_8hpp.html new file mode 100644 index 00000000000..fdf68433e9d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2modified__bessel__second__kind_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/modified_bessel_second_kind.hpp File Reference + + + + + + + + + + +
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+Functions

var stan::math::modified_bessel_second_kind (const int &v, const var &a)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html new file mode 100644 index 00000000000..161beaaf80e --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2modified__bessel__second__kind_8hpp_source.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/modified_bessel_second_kind.hpp Source File + + + + + + + + + + +
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modified_bessel_second_kind.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_MODIFIED_BESSEL_SECOND_KIND_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_MODIFIED_BESSEL_SECOND_KIND_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11 
+
12  class modified_bessel_second_kind_dv_vari : public op_dv_vari {
+
13  public:
+
14  modified_bessel_second_kind_dv_vari(int a, vari* bvi) :
+
15  op_dv_vari(stan::math::modified_bessel_second_kind(a, bvi->val_),
+
16  a, bvi) {
+
17  }
+
18  void chain() {
+
19  bvi_->adj_ -= adj_
+
20  * (ad_ * stan::math::modified_bessel_second_kind(ad_, bvi_->val_)
+
21  / bvi_->val_
+
22  + stan::math::modified_bessel_second_kind(ad_ - 1, bvi_->val_));
+
23  }
+
24  };
+
25  }
+
26 
+
27  inline var modified_bessel_second_kind(const int& v,
+
28  const var& a) {
+
29  return var(new modified_bessel_second_kind_dv_vari(v, a.vi_));
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+
fvar< T > modified_bessel_second_kind(int v, const fvar< T > &z)
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2multiply__log_8hpp.html b/doc/api/html/rev_2scal_2fun_2multiply__log_8hpp.html new file mode 100644 index 00000000000..037abae7159 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2multiply__log_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/multiply_log.hpp File Reference + + + + + + + + + + +
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+ +
+
multiply_log.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/scal/fun/log.hpp>
+#include <stan/math/prim/scal/fun/multiply_log.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
+

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+ + + + + + + + + + +

+Functions

var stan::math::multiply_log (const var &a, const var &b)
 Return the value of a*log(b). More...
 
var stan::math::multiply_log (const var &a, const double b)
 Return the value of a*log(b). More...
 
var stan::math::multiply_log (const double a, const var &b)
 Return the value of a*log(b). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2multiply__log_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2multiply__log_8hpp_source.html new file mode 100644 index 00000000000..20083fcf3d3 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2multiply__log_8hpp_source.html @@ -0,0 +1,195 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/multiply_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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+
multiply_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_MULTIPLY_LOG_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_MULTIPLY_LOG_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + +
7 #include <boost/math/special_functions/fpclassify.hpp>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class multiply_log_vv_vari : public op_vv_vari {
+
15  public:
+
16  multiply_log_vv_vari(vari* avi, vari* bvi) :
+
17  op_vv_vari(stan::math::multiply_log(avi->val_, bvi->val_), avi, bvi) {
+
18  }
+
19  void chain() {
+
20  using std::log;
+
21  if (unlikely(boost::math::isnan(avi_->val_)
+
22  || boost::math::isnan(bvi_->val_))) {
+
23  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
24  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
25  } else {
+
26  avi_->adj_ += adj_ * log(bvi_->val_);
+
27  if (bvi_->val_ == 0.0 && avi_->val_ == 0)
+
28  bvi_->adj_ += adj_ * std::numeric_limits<double>::infinity();
+
29  else
+
30  bvi_->adj_ += adj_ * avi_->val_ / bvi_->val_;
+
31  }
+
32  }
+
33  };
+
34  class multiply_log_vd_vari : public op_vd_vari {
+
35  public:
+
36  multiply_log_vd_vari(vari* avi, double b) :
+
37  op_vd_vari(stan::math::multiply_log(avi->val_, b), avi, b) {
+
38  }
+
39  void chain() {
+
40  using std::log;
+
41  if (unlikely(boost::math::isnan(avi_->val_)
+
42  || boost::math::isnan(bd_)))
+
43  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
44  else
+
45  avi_->adj_ += adj_ * log(bd_);
+
46  }
+
47  };
+
48  class multiply_log_dv_vari : public op_dv_vari {
+
49  public:
+
50  multiply_log_dv_vari(double a, vari* bvi) :
+
51  op_dv_vari(stan::math::multiply_log(a, bvi->val_), a, bvi) {
+
52  }
+
53  void chain() {
+
54  if (bvi_->val_ == 0.0 && ad_ == 0.0)
+
55  bvi_->adj_ += adj_ * std::numeric_limits<double>::infinity();
+
56  else
+
57  bvi_->adj_ += adj_ * ad_ / bvi_->val_;
+
58  }
+
59  };
+
60  }
+
61 
+
74  inline var multiply_log(const var& a, const var& b) {
+
75  return var(new multiply_log_vv_vari(a.vi_, b.vi_));
+
76  }
+
87  inline var multiply_log(const var& a, const double b) {
+
88  return var(new multiply_log_vd_vari(a.vi_, b));
+
89  }
+
101  inline var multiply_log(const double a, const var& b) {
+
102  if (a == 1.0)
+
103  return log(b);
+
104  return var(new multiply_log_dv_vari(a, b.vi_));
+
105  }
+
106 
+
107  }
+
108 }
+
109 #endif
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+ + +
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2owens__t_8hpp.html b/doc/api/html/rev_2scal_2fun_2owens__t_8hpp.html new file mode 100644 index 00000000000..b2ca4b432f4 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2owens__t_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/owens_t.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
owens_t.hpp File Reference
+
+
+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/constants.hpp>
+#include <stan/math/prim/scal/fun/square.hpp>
+#include <boost/math/special_functions/owens_t.hpp>
+#include <cmath>
+
+

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+ + + + + + + +

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 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::owens_t (const var &h, const var &a)
 The Owen's T function of h and a. More...
 
var stan::math::owens_t (const var &h, double a)
 The Owen's T function of h and a. More...
 
var stan::math::owens_t (double h, const var &a)
 The Owen's T function of h and a. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2owens__t_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2owens__t_8hpp_source.html new file mode 100644 index 00000000000..d8a3276ef6c --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2owens__t_8hpp_source.html @@ -0,0 +1,198 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/owens_t.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+
+
owens_t.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_OWENS_T_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_OWENS_T_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+ + +
8 #include <boost/math/special_functions/owens_t.hpp>
+
9 #include <cmath>
+
10 
+
11 #ifdef _MSC_VER
+
12 #include <boost/math/special_functions/erf.hpp>
+
13 using boost::math::erf;
+
14 #endif
+
15 
+
16 namespace stan {
+
17  namespace math {
+
18 
+
19  namespace {
+
20  class owens_t_vv_vari : public op_vv_vari {
+
21  public:
+
22  owens_t_vv_vari(vari* avi, vari* bvi) :
+
23  op_vv_vari(boost::math::owens_t(avi->val_, bvi->val_), avi, bvi) {
+
24  }
+
25  void chain() {
+
26  const double neg_avi_sq_div_2 = -square(avi_->val_) * 0.5;
+
27  const double one_p_bvi_sq = 1.0 + square(bvi_->val_);
+
28 
+
29  avi_->adj_ += adj_ * ::erf(bvi_->val_ * avi_->val_ * INV_SQRT_2)
+
30  * std::exp(neg_avi_sq_div_2) * INV_SQRT_TWO_PI * -0.5;
+
31  bvi_->adj_ += adj_ * std::exp(neg_avi_sq_div_2 * one_p_bvi_sq)
+
32  / (one_p_bvi_sq * 2.0 * pi());
+
33  }
+
34  };
+
35 
+
36  class owens_t_vd_vari : public op_vd_vari {
+
37  public:
+
38  owens_t_vd_vari(vari* avi, double b) :
+
39  op_vd_vari(boost::math::owens_t(avi->val_, b), avi, b) {
+
40  }
+
41  void chain() {
+
42  avi_->adj_ += adj_ * ::erf(bd_ * avi_->val_ * INV_SQRT_2)
+
43  * std::exp(-square(avi_->val_) * 0.5)
+
44  * INV_SQRT_TWO_PI * -0.5;
+
45  }
+
46  };
+
47 
+
48  class owens_t_dv_vari : public op_dv_vari {
+
49  public:
+
50  owens_t_dv_vari(double a, vari* bvi) :
+
51  op_dv_vari(boost::math::owens_t(a, bvi->val_), a, bvi) {
+
52  }
+
53  void chain() {
+
54  const double one_p_bvi_sq = 1.0 + square(bvi_->val_);
+
55  bvi_->adj_ += adj_ * std::exp(-0.5 * square(ad_) * one_p_bvi_sq)
+
56  / (one_p_bvi_sq * 2.0 * pi());
+
57  }
+
58  };
+
59  }
+
60 
+
71  inline var owens_t(const var& h, const var& a) {
+
72  return var(new owens_t_vv_vari(h.vi_, a.vi_));
+
73  }
+
74 
+
85  inline var owens_t(const var& h, double a) {
+
86  return var(new owens_t_vd_vari(h.vi_, a));
+
87  }
+
88 
+
99  inline var owens_t(double h, const var& a) {
+
100  return var(new owens_t_dv_vari(h, a.vi_));
+
101  }
+
102 
+
103  }
+
104 }
+
105 #endif
+
const double INV_SQRT_TWO_PI
Definition: constants.hpp:166
+ +
Reimplementing boost functionality.
+ + +
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
fvar< T > owens_t(const fvar< T > &x1, const fvar< T > &x2)
Definition: owens_t.hpp:14
+
const double INV_SQRT_2
The value of 1 over the square root of 2, .
Definition: constants.hpp:27
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2pow_8hpp.html b/doc/api/html/rev_2scal_2fun_2pow_8hpp.html new file mode 100644 index 00000000000..a7caa1ea051 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2pow_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/pow.hpp File Reference + + + + + + + + + + +
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+
+ +
+
pow.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/scal/fun/sqrt.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <cmath>
+#include <limits>
+
+

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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + + + + +

+Functions

var stan::math::pow (const var &base, const var &exponent)
 Return the base raised to the power of the exponent (cmath). More...
 
var stan::math::pow (const var &base, const double exponent)
 Return the base variable raised to the power of the exponent scalar (cmath). More...
 
var stan::math::pow (const double base, const var &exponent)
 Return the base scalar raised to the power of the exponent variable (cmath). More...
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2pow_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2pow_8hpp_source.html new file mode 100644 index 00000000000..dce4afeeca8 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2pow_8hpp_source.html @@ -0,0 +1,205 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/pow.hpp Source File + + + + + + + + + + +
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pow.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_POW_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_POW_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <cmath>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  namespace {
+
14  class pow_vv_vari : public op_vv_vari {
+
15  public:
+
16  pow_vv_vari(vari* avi, vari* bvi) :
+
17  op_vv_vari(std::pow(avi->val_, bvi->val_), avi, bvi) {
+
18  }
+
19  void chain() {
+
20  if (unlikely(boost::math::isnan(avi_->val_)
+
21  || boost::math::isnan(bvi_->val_))) {
+
22  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
23  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
24  } else {
+
25  if (avi_->val_ == 0.0) return; // partials zero, avoids 0 & log(0)
+
26  avi_->adj_ += adj_ * bvi_->val_ * val_ / avi_->val_;
+
27  bvi_->adj_ += adj_ * std::log(avi_->val_) * val_;
+
28  }
+
29  }
+
30  };
+
31 
+
32  class pow_vd_vari : public op_vd_vari {
+
33  public:
+
34  pow_vd_vari(vari* avi, double b) :
+
35  op_vd_vari(std::pow(avi->val_, b), avi, b) {
+
36  }
+
37  void chain() {
+
38  if (unlikely(boost::math::isnan(avi_->val_)
+
39  || boost::math::isnan(bd_))) {
+
40  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
41  } else {
+
42  if (avi_->val_ == 0.0) return; // partials zero, avoids 0 & log(0)
+
43  avi_->adj_ += adj_ * bd_ * val_ / avi_->val_;
+
44  }
+
45  }
+
46  };
+
47 
+
48  class pow_dv_vari : public op_dv_vari {
+
49  public:
+
50  pow_dv_vari(double a, vari* bvi) :
+
51  op_dv_vari(std::pow(a, bvi->val_), a, bvi) {
+
52  }
+
53  void chain() {
+
54  if (unlikely(boost::math::isnan(bvi_->val_)
+
55  || boost::math::isnan(ad_))) {
+
56  bvi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
57  } else {
+
58  if (ad_ == 0.0) return; // partials zero, avoids 0 & log(0)
+
59  bvi_->adj_ += adj_ * std::log(ad_) * val_;
+
60  }
+
61  }
+
62  };
+
63  }
+
64 
+
103  inline var pow(const var& base, const var& exponent) {
+
104  return var(new pow_vv_vari(base.vi_, exponent.vi_));
+
105  }
+
106 
+
119  inline var pow(const var& base, const double exponent) {
+
120  if (exponent == 0.5)
+
121  return sqrt(base);
+
122  if (exponent == 1.0)
+
123  return base;
+
124  if (exponent == 2.0)
+
125  return base * base; // FIXME: use square()
+
126  return var(new pow_vd_vari(base.vi_, exponent));
+
127  }
+
128 
+
141  inline var pow(const double base, const var& exponent) {
+
142  return var(new pow_dv_vari(base, exponent.vi_));
+
143  }
+
144 
+
145  }
+
146 }
+
147 #endif
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2primitive__value_8hpp.html b/doc/api/html/rev_2scal_2fun_2primitive__value_8hpp.html new file mode 100644 index 00000000000..3a2365905e2 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2primitive__value_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/primitive_value.hpp File Reference + + + + + + + + + + +
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+ + + + +

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double stan::math::primitive_value (const var &v)
 Return the primitive double value for the specified auto-diff variable. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2primitive__value_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2primitive__value_8hpp_source.html new file mode 100644 index 00000000000..fe9418e459b --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2primitive__value_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/primitive_value.hpp Source File + + + + + + + + + + +
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primitive_value.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_PRIMITIVE_VALUE_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_PRIMITIVE_VALUE_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
17  inline double primitive_value(const var& v) {
+
18  return v.val();
+
19  }
+
20 
+
21  }
+
22 }
+
23 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
double primitive_value(const fvar< T > &v)
Return the primitive value of the specified forward-mode autodiff variable.
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2rising__factorial_8hpp.html b/doc/api/html/rev_2scal_2fun_2rising__factorial_8hpp.html new file mode 100644 index 00000000000..940c0ab316f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2rising__factorial_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/rising_factorial.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+ +
+
rising_factorial.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <stan/math/prim/scal/fun/rising_factorial.hpp>
+#include <boost/math/special_functions/digamma.hpp>
+
+

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

var stan::math::rising_factorial (const var &a, const double &b)
 
var stan::math::rising_factorial (const var &a, const var &b)
 
var stan::math::rising_factorial (const double &a, const var &b)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2rising__factorial_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2rising__factorial_8hpp_source.html new file mode 100644 index 00000000000..9de187011da --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2rising__factorial_8hpp_source.html @@ -0,0 +1,186 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/rising_factorial.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+
+
rising_factorial.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_RISING_FACTORIAL_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_RISING_FACTORIAL_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 #include <boost/math/special_functions/digamma.hpp>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  namespace {
+
12 
+
13  class rising_factorial_vv_vari : public op_vv_vari {
+
14  public:
+
15  rising_factorial_vv_vari(vari* avi, vari* bvi) :
+
16  op_vv_vari(stan::math::rising_factorial(avi->val_, bvi->val_),
+
17  avi, bvi) {
+
18  }
+
19  void chain() {
+
20  avi_->adj_ += adj_
+
21  * stan::math::rising_factorial(avi_->val_, bvi_->val_)
+
22  * (boost::math::digamma(avi_->val_ + bvi_->val_)
+
23  - boost::math::digamma(avi_->val_));
+
24  bvi_->adj_ += adj_
+
25  * stan::math::rising_factorial(avi_->val_, bvi_->val_)
+
26  * boost::math::digamma(bvi_->val_ + avi_->val_);
+
27  }
+
28  };
+
29 
+
30  class rising_factorial_vd_vari : public op_vd_vari {
+
31  public:
+
32  rising_factorial_vd_vari(vari* avi, double b) :
+
33  op_vd_vari(stan::math::rising_factorial(avi->val_, b), avi, b) {
+
34  }
+
35  void chain() {
+
36  avi_->adj_ += adj_ * stan::math::rising_factorial(avi_->val_, bd_)
+
37  * (boost::math::digamma(avi_->val_ + bd_)
+
38  - boost::math::digamma(avi_->val_));
+
39  }
+
40  };
+
41 
+
42  class rising_factorial_dv_vari : public op_dv_vari {
+
43  public:
+
44  rising_factorial_dv_vari(double a, vari* bvi) :
+
45  op_dv_vari(stan::math::rising_factorial(a, bvi->val_), a, bvi) {
+
46  }
+
47  void chain() {
+
48  bvi_->adj_ += adj_ * stan::math::rising_factorial(ad_, bvi_->val_)
+
49  * boost::math::digamma(bvi_->val_ + ad_);
+
50  }
+
51  };
+
52  }
+
53 
+
54  inline var rising_factorial(const var& a,
+
55  const double& b) {
+
56  return var(new rising_factorial_vd_vari(a.vi_, b));
+
57  }
+
58 
+
59  inline var rising_factorial(const var& a,
+
60  const var& b) {
+
61  return var(new rising_factorial_vv_vari(a.vi_, b.vi_));
+
62  }
+
63 
+
64  inline var rising_factorial(const double& a,
+
65  const var& b) {
+
66  return var(new rising_factorial_dv_vari(a, b.vi_));
+
67  }
+
68  }
+
69 }
+
70 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > rising_factorial(const fvar< T > &x, const fvar< T > &n)
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2round_8hpp.html b/doc/api/html/rev_2scal_2fun_2round_8hpp.html new file mode 100644 index 00000000000..bffc9ceae4f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2round_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/round.hpp File Reference + + + + + + + + + + +
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+
round.hpp File Reference
+
+
+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
+

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+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

var stan::math::round (const var &a)
 Returns the rounded form of the specified variable (C99). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2round_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2round_8hpp_source.html new file mode 100644 index 00000000000..eba1c10248f --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2round_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/round.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
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+
+
round.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_ROUND_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_ROUND_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <limits>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
12  namespace {
+
13  class round_vari : public op_v_vari {
+
14  public:
+
15  explicit round_vari(vari* avi) :
+
16  op_v_vari(::round(avi->val_), avi) {
+
17  }
+
18  void chain() {
+
19  if (unlikely(boost::math::isnan(avi_->val_)))
+
20  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
21  }
+
22  };
+
23  }
+
24 
+
57  inline var round(const var& a) {
+
58  return var(new round_vari(a.vi_));
+
59  }
+
60 
+
61  }
+
62 }
+
63 #endif
+ + +
fvar< T > round(const fvar< T > &x)
Definition: round.hpp:11
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2sin_8hpp.html b/doc/api/html/rev_2scal_2fun_2sin_8hpp.html new file mode 100644 index 00000000000..e3ae18ffddb --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2sin_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/sin.hpp File Reference + + + + + + + + + + +
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sin.hpp File Reference
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#include <stan/math/rev/core.hpp>
+#include <cmath>
+
+

Go to the source code of this file.

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+Functions

var stan::math::sin (const var &a)
 Return the sine of a radian-scaled variable (cmath). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2sin_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2sin_8hpp_source.html new file mode 100644 index 00000000000..31127c372b0 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2sin_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/sin.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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sin.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_SIN_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_SIN_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class sin_vari : public op_v_vari {
+
12  public:
+
13  explicit sin_vari(vari* avi) :
+
14  op_v_vari(std::sin(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ * std::cos(avi_->val_);
+
18  }
+
19  };
+
20  }
+
21 
+
49  inline var sin(const var& a) {
+
50  return var(new sin_vari(a.vi_));
+
51  }
+
52 
+
53  }
+
54 }
+
55 #endif
+
fvar< T > cos(const fvar< T > &x)
Definition: cos.hpp:13
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > sin(const fvar< T > &x)
Definition: sin.hpp:14
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2sinh_8hpp.html b/doc/api/html/rev_2scal_2fun_2sinh_8hpp.html new file mode 100644 index 00000000000..858117cdaf8 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2sinh_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/sinh.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
sinh.hpp File Reference
+
+
+
#include <stan/math/rev/core.hpp>
+#include <valarray>
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var stan::math::sinh (const var &a)
 Return the hyperbolic sine of the specified variable (cmath). More...
 
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diff --git a/doc/api/html/rev_2scal_2fun_2sinh_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2sinh_8hpp_source.html new file mode 100644 index 00000000000..ff59b5e6ba2 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2sinh_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/sinh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_SINH_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_SINH_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <valarray>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class sinh_vari : public op_v_vari {
+
12  public:
+
13  explicit sinh_vari(vari* avi) :
+
14  op_v_vari(std::sinh(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ * std::cosh(avi_->val_);
+
18  }
+
19  };
+
20  }
+
21 
+
49  inline var sinh(const var& a) {
+
50  return var(new sinh_vari(a.vi_));
+
51  }
+
52 
+
53  }
+
54 }
+
55 #endif
+ +
fvar< T > cosh(const fvar< T > &x)
Definition: cosh.hpp:13
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > sinh(const fvar< T > &x)
Definition: sinh.hpp:14
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2sqrt_8hpp.html b/doc/api/html/rev_2scal_2fun_2sqrt_8hpp.html new file mode 100644 index 00000000000..fc7361252ff --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2sqrt_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/sqrt.hpp File Reference + + + + + + + + + + +
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#include <stan/math/rev/core.hpp>
+#include <cmath>
+
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var stan::math::sqrt (const var &a)
 Return the square root of the specified variable (cmath). More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2sqrt_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2sqrt_8hpp_source.html new file mode 100644 index 00000000000..e36ce2038fc --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2sqrt_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/sqrt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_SQRT_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_SQRT_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class sqrt_vari : public op_v_vari {
+
12  public:
+
13  explicit sqrt_vari(vari* avi) :
+
14  op_v_vari(std::sqrt(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ / (2.0 * val_);
+
18  }
+
19  };
+
20  }
+
21 
+
50  inline var sqrt(const var& a) {
+
51  return var(new sqrt_vari(a.vi_));
+
52  }
+
53 
+
54  }
+
55 }
+
56 #endif
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2square_8hpp.html b/doc/api/html/rev_2scal_2fun_2square_8hpp.html new file mode 100644 index 00000000000..f30bfef8411 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2square_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/square.hpp File Reference + + + + + + + + + + +
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var stan::math::square (const var &x)
 Return the square of the input variable. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2square_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2square_8hpp_source.html new file mode 100644 index 00000000000..ac68e180a66 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2square_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/square.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_SQUARE_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_SQUARE_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  namespace {
+
10  class square_vari : public op_v_vari {
+
11  public:
+
12  explicit square_vari(vari* avi) :
+
13  op_v_vari(avi->val_ * avi->val_, avi) {
+
14  }
+
15  void chain() {
+
16  avi_->adj_ += adj_ * 2.0 * avi_->val_;
+
17  }
+
18  };
+
19  }
+
20 
+
46  inline var square(const var& x) {
+
47  return var(new square_vari(x.vi_));
+
48  }
+
49 
+
50  }
+
51 }
+
52 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2step_8hpp.html b/doc/api/html/rev_2scal_2fun_2step_8hpp.html new file mode 100644 index 00000000000..40148f43a1c --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2step_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/step.hpp File Reference + + + + + + + + + + +
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var stan::math::step (const stan::math::var &a)
 Return the step, or heaviside, function applied to the specified variable (stan). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2step_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2step_8hpp_source.html new file mode 100644 index 00000000000..4cbdb1647a0 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2step_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/step.hpp Source File + + + + + + + + + + +
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step.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_STEP_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_STEP_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
25  inline var step(const stan::math::var& a) {
+
26  return var(new vari(a.vi_->val_ < 0.0 ? 0.0 : 1.0));
+
27  }
+
28 
+
29  }
+
30 }
+
31 #endif
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
int step(const T y)
The step, or Heaviside, function.
Definition: step.hpp:29
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2tan_8hpp.html b/doc/api/html/rev_2scal_2fun_2tan_8hpp.html new file mode 100644 index 00000000000..c90227da85a --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2tan_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/tan.hpp File Reference + + + + + + + + + + +
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+
#include <stan/math/rev/core.hpp>
+#include <cmath>
+
+

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var stan::math::tan (const var &a)
 Return the tangent of a radian-scaled variable (cmath). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2tan_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2tan_8hpp_source.html new file mode 100644 index 00000000000..2ed8367a50d --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2tan_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/tan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_TAN_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_TAN_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class tan_vari : public op_v_vari {
+
12  public:
+
13  explicit tan_vari(vari* avi) :
+
14  op_v_vari(std::tan(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ * (1.0 + val_ * val_);
+
18  }
+
19  };
+
20  }
+
21 
+
49  inline var tan(const var& a) {
+
50  return var(new tan_vari(a.vi_));
+
51  }
+
52 
+
53  }
+
54 }
+
55 #endif
+ + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > tan(const fvar< T > &x)
Definition: tan.hpp:14
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2tanh_8hpp.html b/doc/api/html/rev_2scal_2fun_2tanh_8hpp.html new file mode 100644 index 00000000000..91330442cce --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2tanh_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/tanh.hpp File Reference + + + + + + + + + + +
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#include <stan/math/rev/core.hpp>
+#include <cmath>
+
+

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var stan::math::tanh (const var &a)
 Return the hyperbolic tangent of the specified variable (cmath). More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2tanh_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2tanh_8hpp_source.html new file mode 100644 index 00000000000..2e16b5bcee3 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2tanh_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/tanh.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_TANH_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_TANH_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 #include <cmath>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class tanh_vari : public op_v_vari {
+
12  public:
+
13  explicit tanh_vari(vari* avi) :
+
14  op_v_vari(std::tanh(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  double cosh = std::cosh(avi_->val_);
+
18  avi_->adj_ += adj_ / (cosh * cosh);
+
19  }
+
20  };
+
21  }
+
22 
+
50  inline var tanh(const var& a) {
+
51  return var(new tanh_vari(a.vi_));
+
52  }
+
53 
+
54  }
+
55 }
+
56 #endif
+ +
fvar< T > cosh(const fvar< T > &x)
Definition: cosh.hpp:13
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > tanh(const fvar< T > &x)
Definition: tanh.hpp:14
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2tgamma_8hpp.html b/doc/api/html/rev_2scal_2fun_2tgamma_8hpp.html new file mode 100644 index 00000000000..c3e33ef90a5 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2tgamma_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/tgamma.hpp File Reference + + + + + + + + + + +
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tgamma.hpp File Reference
+
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+
#include <boost/math/special_functions/digamma.hpp>
+#include <stan/math/rev/core.hpp>
+
+

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var stan::math::tgamma (const stan::math::var &a)
 Return the Gamma function applied to the specified variable (C99). More...
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2tgamma_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2tgamma_8hpp_source.html new file mode 100644 index 00000000000..9ca401a46bb --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2tgamma_8hpp_source.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/tgamma.hpp Source File + + + + + + + + + + +
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tgamma.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_TGAMMA_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_TGAMMA_HPP
+
3 
+
4 #include <boost/math/special_functions/digamma.hpp>
+
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  namespace {
+
11  class tgamma_vari : public op_v_vari {
+
12  public:
+
13  explicit tgamma_vari(vari* avi) :
+
14  op_v_vari(boost::math::tgamma(avi->val_), avi) {
+
15  }
+
16  void chain() {
+
17  avi_->adj_ += adj_ * val_ * boost::math::digamma(avi_->val_);
+
18  }
+
19  };
+
20  }
+
21 
+
65  inline var tgamma(const stan::math::var& a) {
+
66  return var(new tgamma_vari(a.vi_));
+
67  }
+
68 
+
69  }
+
70 }
+
71 #endif
+ +
Reimplementing boost functionality.
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2trunc_8hpp.html b/doc/api/html/rev_2scal_2fun_2trunc_8hpp.html new file mode 100644 index 00000000000..edb35e16b99 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2trunc_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/trunc.hpp File Reference + + + + + + + + + + +
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+
+
+
#include <math.h>
+#include <stan/math/rev/core.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <limits>
+
+

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var stan::math::trunc (const var &a)
 Returns the truncatation of the specified variable (C99). More...
 
+
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diff --git a/doc/api/html/rev_2scal_2fun_2trunc_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2trunc_8hpp_source.html new file mode 100644 index 00000000000..0bac5105f41 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2trunc_8hpp_source.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/trunc.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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trunc.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_TRUNC_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_TRUNC_HPP
+
3 
+
4 #include <math.h>
+
5 #include <stan/math/rev/core.hpp>
+
6 #include <boost/math/special_functions/fpclassify.hpp>
+
7 #include <limits>
+
8 
+
9 #ifdef _MSC_VER
+
10 #include <boost/math/special_functions/trunc.hpp>
+
11 using boost::math::trunc;
+
12 #endif
+
13 
+
14 namespace stan {
+
15  namespace math {
+
16 
+
17  namespace {
+
18  class trunc_vari : public op_v_vari {
+
19  public:
+
20  explicit trunc_vari(vari* avi) :
+
21  op_v_vari(::trunc(avi->val_), avi) {
+
22  }
+
23  void chain() {
+
24  if (unlikely(boost::math::isnan(avi_->val_)))
+
25  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
+
26  }
+
27  };
+
28  }
+
29 
+
60  inline var trunc(const var& a) {
+
61  return var(new trunc_vari(a.vi_));
+
62  }
+
63 
+
64  }
+
65 }
+
66 #endif
+
var trunc(const var &a)
Returns the truncatation of the specified variable (C99).
Definition: trunc.hpp:60
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
fvar< T > trunc(const fvar< T > &x)
Definition: trunc.hpp:12
+
bool isnan(const stan::math::var &v)
Checks if the given number is NaN.
Definition: boost_isnan.hpp:22
+
#define unlikely(x)
Definition: likely.hpp:9
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2value__of_8hpp.html b/doc/api/html/rev_2scal_2fun_2value__of_8hpp.html new file mode 100644 index 00000000000..7fc54eafb07 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2value__of_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/value_of.hpp File Reference + + + + + + + + + + +
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double stan::math::value_of (const var &v)
 Return the value of the specified variable. More...
 
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2value__of_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2value__of_8hpp_source.html new file mode 100644 index 00000000000..1ee6c5f8cf7 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2value__of_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/value_of.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_VALUE_OF_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_VALUE_OF_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
22  inline double value_of(const var& v) {
+
23  return v.vi_->val_;
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
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diff --git a/doc/api/html/rev_2scal_2fun_2value__of__rec_8hpp.html b/doc/api/html/rev_2scal_2fun_2value__of__rec_8hpp.html new file mode 100644 index 00000000000..2a92460a0fc --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2value__of__rec_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/value_of_rec.hpp File Reference + + + + + + + + + + +
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+Functions

double stan::math::value_of_rec (const var &v)
 Return the value of the specified variable. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/rev_2scal_2fun_2value__of__rec_8hpp_source.html b/doc/api/html/rev_2scal_2fun_2value__of__rec_8hpp_source.html new file mode 100644 index 00000000000..6049b4ffb32 --- /dev/null +++ b/doc/api/html/rev_2scal_2fun_2value__of__rec_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/value_of_rec.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_FUN_VALUE_OF_REC_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_VALUE_OF_REC_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
15  inline double value_of_rec(const var& v) {
+
16  return v.vi_->val_;
+
17  }
+
18 
+
19  }
+
20 }
+
21 #endif
+ + +
double value_of_rec(const fvar< T > &v)
Return the value of the specified variable.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+
+
+
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diff --git a/doc/api/html/rev_2scal_2meta_2_operands_and_partials_8hpp.html b/doc/api/html/rev_2scal_2meta_2_operands_and_partials_8hpp.html new file mode 100644 index 00000000000..b4927008134 --- /dev/null +++ b/doc/api/html/rev_2scal_2meta_2_operands_and_partials_8hpp.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/meta/OperandsAndPartials.hpp File Reference + + + + + + + + + + +
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OperandsAndPartials.hpp File Reference
+
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+ + + + + +

+Classes

struct  stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >
 This class builds partial derivatives with respect to a set of operands. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+

Variable Documentation

+ +
+
+ + + + +
const size_t N_
+
+ +

Definition at line 18 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+ + + + +
vari** operands_
+
+ +

Definition at line 19 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+ + + + +
double* partials_
+
+ +

Definition at line 20 of file OperandsAndPartials.hpp.

+ +
+
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diff --git a/doc/api/html/rev_2scal_2meta_2_operands_and_partials_8hpp_source.html b/doc/api/html/rev_2scal_2meta_2_operands_and_partials_8hpp_source.html new file mode 100644 index 00000000000..54bdb7019f0 --- /dev/null +++ b/doc/api/html/rev_2scal_2meta_2_operands_and_partials_8hpp_source.html @@ -0,0 +1,291 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/meta/OperandsAndPartials.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+
OperandsAndPartials.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_META_OPERANDSANDPARTIALS_HPP
+
2 #define STAN_MATH_REV_SCAL_META_OPERANDSANDPARTIALS_HPP
+
3 
+ + + + +
8 #include <stan/math/rev/core.hpp>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+
13  // These are helpers to the OperandsAndPartials specialization for
+
14  // stan::math::var
+
15  namespace {
+
16  class partials_vari : public vari {
+
17  private:
+
18  const size_t N_;
+
19  vari** operands_;
+
20  double* partials_;
+
21  public:
+
22  partials_vari(double value,
+
23  size_t N,
+
24  vari** operands, double* partials)
+
25  : vari(value),
+
26  N_(N),
+
27  operands_(operands),
+
28  partials_(partials) { }
+
29  void chain() {
+
30  for (size_t n = 0; n < N_; ++n)
+
31  operands_[n]->adj_ += adj_ * partials_[n];
+
32  }
+
33  };
+
34 
+
35  var partials_to_var(double logp, size_t nvaris,
+
36  vari** all_varis,
+
37  double* all_partials) {
+
38  return var(new partials_vari(logp, nvaris, all_varis,
+
39  all_partials));
+
40  }
+
41 
+
42  template<typename T,
+
43  bool is_vec = is_vector<T>::value,
+
44  bool is_const = is_constant_struct<T>::value>
+
45  struct set_varis {
+
46  inline size_t set(vari** /*varis*/, const T& /*x*/) {
+
47  return 0U;
+
48  }
+
49  };
+
50  template<typename T>
+
51  struct set_varis<T, true, false> {
+
52  inline size_t set(vari** varis, const T& x) {
+
53  for (size_t n = 0; n < length(x); n++)
+
54  varis[n] = x[n].vi_;
+
55  return length(x);
+
56  }
+
57  };
+
58  template<>
+
59  struct set_varis<var, false, false> {
+
60  inline size_t set(vari** varis, const var& x) {
+
61  varis[0] = x.vi_;
+
62  return (1);
+
63  }
+
64  };
+
65  }
+
66 
+
89  template<typename T1, typename T2, typename T3,
+
90  typename T4, typename T5, typename T6>
+
91  struct OperandsAndPartials<T1, T2, T3, T4, T5, T6, stan::math::var> {
+
92  size_t nvaris;
+ +
94  double* all_partials;
+
95 
+
96  VectorView<double,
+ + +
99  VectorView<double,
+ + +
102  VectorView<double,
+ + +
105  VectorView<double,
+ + +
108  VectorView<double,
+ + +
111  VectorView<double,
+ + +
114 
+
125  OperandsAndPartials(const T1& x1 = 0, const T2& x2 = 0, const T3& x3 = 0,
+
126  const T4& x4 = 0, const T5& x5 = 0, const T6& x6 = 0)
+
127  : nvaris(!is_constant_struct<T1>::value * length(x1) +
+
128  !is_constant_struct<T2>::value * length(x2) +
+
129  !is_constant_struct<T3>::value * length(x3) +
+
130  !is_constant_struct<T4>::value * length(x4) +
+
131  !is_constant_struct<T5>::value * length(x5) +
+
132  !is_constant_struct<T6>::value * length(x6)),
+
133  // TODO(carpenter): replace with array allocation fun
+
134  all_varis(static_cast<vari**>
+
135  (vari::operator new
+
136  (sizeof(vari*) * nvaris))),
+
137  all_partials(static_cast<double*>
+
138  (vari::operator new
+
139  (sizeof(double) * nvaris))),
+
140  d_x1(all_partials),
+
141  d_x2(all_partials
+
142  + (!is_constant_struct<T1>::value) * length(x1)),
+
143  d_x3(all_partials
+
144  + (!is_constant_struct<T1>::value) * length(x1)
+
145  + (!is_constant_struct<T2>::value) * length(x2)),
+
146  d_x4(all_partials
+
147  + (!is_constant_struct<T1>::value) * length(x1)
+
148  + (!is_constant_struct<T2>::value) * length(x2)
+
149  + (!is_constant_struct<T3>::value) * length(x3)),
+
150  d_x5(all_partials
+
151  + (!is_constant_struct<T1>::value) * length(x1)
+
152  + (!is_constant_struct<T2>::value) * length(x2)
+
153  + (!is_constant_struct<T3>::value) * length(x3)
+
154  + (!is_constant_struct<T4>::value) * length(x4)),
+
155  d_x6(all_partials
+
156  + (!is_constant_struct<T1>::value) * length(x1)
+
157  + (!is_constant_struct<T2>::value) * length(x2)
+
158  + (!is_constant_struct<T3>::value) * length(x3)
+
159  + (!is_constant_struct<T4>::value) * length(x4)
+
160  + (!is_constant_struct<T5>::value) * length(x5)) {
+
161  size_t base = 0;
+ +
163  base += set_varis<T1>().set(&all_varis[base], x1);
+ +
165  base += set_varis<T2>().set(&all_varis[base], x2);
+ +
167  base += set_varis<T3>().set(&all_varis[base], x3);
+ +
169  base += set_varis<T4>().set(&all_varis[base], x4);
+ +
171  base += set_varis<T5>().set(&all_varis[base], x5);
+ +
173  set_varis<T6>().set(&all_varis[base], x6);
+
174  std::fill(all_partials, all_partials+nvaris, 0);
+
175  }
+
176 
+ +
186  return partials_to_var(value, nvaris, all_varis,
+
187  all_partials);
+
188  }
+
189  };
+
190 
+
191  }
+
192 }
+
193 #endif
+ + + +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
VectorView< double, is_vector< T4 >::value, is_constant_struct< T4 >::value > d_x4
+
The variable implementation base class.
Definition: vari.hpp:30
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
stan::math::var value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari ** operands_
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
double * partials_
+
VectorView< double, is_vector< T1 >::value, is_constant_struct< T1 >::value > d_x1
+
const size_t N_
+
This class builds partial derivatives with respect to a set of operands.
+ +
OperandsAndPartials(const T1 &x1=0, const T2 &x2=0, const T3 &x3=0, const T4 &x4=0, const T5 &x5=0, const T6 &x6=0)
Constructor.
+
VectorView< double, is_vector< T5 >::value, is_constant_struct< T5 >::value > d_x5
+ + +
VectorView< double, is_vector< T2 >::value, is_constant_struct< T2 >::value > d_x2
+
void fill(std::vector< T > &x, const S &y)
Fill the specified container with the specified value.
Definition: fill.hpp:22
+
VectorView< double, is_vector< T3 >::value, is_constant_struct< T3 >::value > d_x3
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ + +
VectorView< double, is_vector< T6 >::value, is_constant_struct< T6 >::value > d_x6
+
+
+
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diff --git a/doc/api/html/rev_2scal_2meta_2is__var_8hpp.html b/doc/api/html/rev_2scal_2meta_2is__var_8hpp.html new file mode 100644 index 00000000000..bac8a5483f7 --- /dev/null +++ b/doc/api/html/rev_2scal_2meta_2is__var_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/meta/is_var.hpp File Reference + + + + + + + + + + +
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struct  stan::is_var< stan::math::var >
 
+ + + +

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diff --git a/doc/api/html/rev_2scal_2meta_2is__var_8hpp_source.html b/doc/api/html/rev_2scal_2meta_2is__var_8hpp_source.html new file mode 100644 index 00000000000..48d280b9e10 --- /dev/null +++ b/doc/api/html/rev_2scal_2meta_2is__var_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/meta/is_var.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_META_IS_VAR_HPP
+
2 #define STAN_MATH_REV_SCAL_META_IS_VAR_HPP
+
3 
+ +
5 #include <stan/math/rev/core.hpp>
+
6 
+
7 namespace stan {
+
8 
+
9  template <>
+
10  struct is_var<stan::math::var> {
+
11  enum { value = true };
+
12  };
+
13 
+
14 }
+
15 #endif
+
16 
+ + + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
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diff --git a/doc/api/html/rev_2scal_2meta_2partials__type_8hpp.html b/doc/api/html/rev_2scal_2meta_2partials__type_8hpp.html new file mode 100644 index 00000000000..9ba63be5396 --- /dev/null +++ b/doc/api/html/rev_2scal_2meta_2partials__type_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/meta/partials_type.hpp File Reference + + + + + + + + + + +
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partials_type.hpp File Reference
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diff --git a/doc/api/html/rev_2scal_2meta_2partials__type_8hpp_source.html b/doc/api/html/rev_2scal_2meta_2partials__type_8hpp_source.html new file mode 100644 index 00000000000..d83e79116d8 --- /dev/null +++ b/doc/api/html/rev_2scal_2meta_2partials__type_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/meta/partials_type.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_META_PARTIALS_TYPE_HPP
+
2 #define STAN_MATH_REV_SCAL_META_PARTIALS_TYPE_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ +
6 
+
7 namespace stan {
+
8 
+
9  template <>
+ +
11  typedef double type;
+
12  };
+
13 
+
14 }
+
15 #endif
+
16 
+ + + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
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diff --git a/doc/api/html/rev_2scal_8hpp.html b/doc/api/html/rev_2scal_8hpp.html new file mode 100644 index 00000000000..871c8d262cc --- /dev/null +++ b/doc/api/html/rev_2scal_8hpp.html @@ -0,0 +1,204 @@ + + + + + + +Stan Math Library: stan/math/rev/scal.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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scal.hpp File Reference
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+
#include <stan/math/rev/core.hpp>
+#include <stan/math/rev/scal/meta/is_var.hpp>
+#include <stan/math/rev/scal/meta/partials_type.hpp>
+#include <stan/math/rev/scal/meta/OperandsAndPartials.hpp>
+#include <stan/math/prim/scal.hpp>
+#include <stan/math/rev/scal/fun/abs.hpp>
+#include <stan/math/rev/scal/fun/acos.hpp>
+#include <stan/math/rev/scal/fun/acosh.hpp>
+#include <stan/math/rev/scal/fun/as_bool.hpp>
+#include <stan/math/rev/scal/fun/asin.hpp>
+#include <stan/math/rev/scal/fun/asinh.hpp>
+#include <stan/math/rev/scal/fun/atan.hpp>
+#include <stan/math/rev/scal/fun/atan2.hpp>
+#include <stan/math/rev/scal/fun/atanh.hpp>
+#include <stan/math/rev/scal/fun/bessel_first_kind.hpp>
+#include <stan/math/rev/scal/fun/bessel_second_kind.hpp>
+#include <stan/math/rev/scal/fun/binary_log_loss.hpp>
+#include <stan/math/rev/scal/fun/boost_fpclassify.hpp>
+#include <stan/math/rev/scal/fun/boost_isfinite.hpp>
+#include <stan/math/rev/scal/fun/boost_isinf.hpp>
+#include <stan/math/rev/scal/fun/boost_isnan.hpp>
+#include <stan/math/rev/scal/fun/boost_isnormal.hpp>
+#include <stan/math/rev/scal/fun/calculate_chain.hpp>
+#include <stan/math/rev/scal/fun/cbrt.hpp>
+#include <stan/math/rev/scal/fun/ceil.hpp>
+#include <stan/math/rev/scal/fun/cos.hpp>
+#include <stan/math/rev/scal/fun/cosh.hpp>
+#include <stan/math/rev/scal/fun/digamma.hpp>
+#include <stan/math/rev/scal/fun/erf.hpp>
+#include <stan/math/rev/scal/fun/erfc.hpp>
+#include <stan/math/rev/scal/fun/exp.hpp>
+#include <stan/math/rev/scal/fun/exp2.hpp>
+#include <stan/math/rev/scal/fun/expm1.hpp>
+#include <stan/math/rev/scal/fun/fabs.hpp>
+#include <stan/math/rev/scal/fun/falling_factorial.hpp>
+#include <stan/math/rev/scal/fun/fdim.hpp>
+#include <stan/math/rev/scal/fun/floor.hpp>
+#include <stan/math/rev/scal/fun/fma.hpp>
+#include <stan/math/rev/scal/fun/fmax.hpp>
+#include <stan/math/rev/scal/fun/fmin.hpp>
+#include <stan/math/rev/scal/fun/fmod.hpp>
+#include <stan/math/rev/scal/fun/gamma_p.hpp>
+#include <stan/math/rev/scal/fun/gamma_q.hpp>
+#include <stan/math/rev/scal/fun/grad_inc_beta.hpp>
+#include <stan/math/rev/scal/fun/hypot.hpp>
+#include <stan/math/rev/scal/fun/ibeta.hpp>
+#include <stan/math/rev/scal/fun/if_else.hpp>
+#include <stan/math/rev/scal/fun/inc_beta.hpp>
+#include <stan/math/rev/scal/fun/inv.hpp>
+#include <stan/math/rev/scal/fun/inv_cloglog.hpp>
+#include <stan/math/rev/scal/fun/inv_logit.hpp>
+#include <stan/math/rev/scal/fun/inv_Phi.hpp>
+#include <stan/math/rev/scal/fun/inv_sqrt.hpp>
+#include <stan/math/rev/scal/fun/inv_square.hpp>
+#include <stan/math/rev/scal/fun/is_inf.hpp>
+#include <stan/math/rev/scal/fun/is_nan.hpp>
+#include <stan/math/rev/scal/fun/is_uninitialized.hpp>
+#include <stan/math/rev/scal/fun/lgamma.hpp>
+#include <stan/math/rev/scal/fun/lmgamma.hpp>
+#include <stan/math/rev/scal/fun/log.hpp>
+#include <stan/math/rev/scal/fun/log10.hpp>
+#include <stan/math/rev/scal/fun/log1m.hpp>
+#include <stan/math/rev/scal/fun/log1m_exp.hpp>
+#include <stan/math/rev/scal/fun/log1p.hpp>
+#include <stan/math/rev/scal/fun/log1p_exp.hpp>
+#include <stan/math/rev/scal/fun/log2.hpp>
+#include <stan/math/rev/scal/fun/log_diff_exp.hpp>
+#include <stan/math/rev/scal/fun/log_falling_factorial.hpp>
+#include <stan/math/rev/scal/fun/log_mix.hpp>
+#include <stan/math/rev/scal/fun/log_rising_factorial.hpp>
+#include <stan/math/rev/scal/fun/log_sum_exp.hpp>
+#include <stan/math/rev/scal/fun/modified_bessel_first_kind.hpp>
+#include <stan/math/rev/scal/fun/modified_bessel_second_kind.hpp>
+#include <stan/math/rev/scal/fun/multiply_log.hpp>
+#include <stan/math/rev/scal/fun/owens_t.hpp>
+#include <stan/math/rev/scal/fun/Phi.hpp>
+#include <stan/math/rev/scal/fun/Phi_approx.hpp>
+#include <stan/math/rev/scal/fun/pow.hpp>
+#include <stan/math/rev/scal/fun/primitive_value.hpp>
+#include <stan/math/rev/scal/fun/rising_factorial.hpp>
+#include <stan/math/rev/scal/fun/round.hpp>
+#include <stan/math/rev/scal/fun/sin.hpp>
+#include <stan/math/rev/scal/fun/sinh.hpp>
+#include <stan/math/rev/scal/fun/sqrt.hpp>
+#include <stan/math/rev/scal/fun/square.hpp>
+#include <stan/math/rev/scal/fun/step.hpp>
+#include <stan/math/rev/scal/fun/tan.hpp>
+#include <stan/math/rev/scal/fun/tanh.hpp>
+#include <stan/math/rev/scal/fun/to_var.hpp>
+#include <stan/math/rev/scal/fun/tgamma.hpp>
+#include <stan/math/rev/scal/fun/trunc.hpp>
+#include <stan/math/rev/scal/fun/value_of.hpp>
+#include <stan/math/rev/scal/fun/value_of_rec.hpp>
+
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diff --git a/doc/api/html/rev_2scal_8hpp_source.html b/doc/api/html/rev_2scal_8hpp_source.html new file mode 100644 index 00000000000..0dd25fb813b --- /dev/null +++ b/doc/api/html/rev_2scal_8hpp_source.html @@ -0,0 +1,302 @@ + + + + + + +Stan Math Library: stan/math/rev/scal.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_SCAL_HPP
+
2 #define STAN_MATH_REV_SCAL_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+ + + +
8 
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10 
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99 
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100 #endif
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diff --git a/doc/api/html/row_8hpp.html b/doc/api/html/row_8hpp.html new file mode 100644 index 00000000000..f17540d4300 --- /dev/null +++ b/doc/api/html/row_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/row.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::row (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i)
 Return the specified row of the specified matrix, using start-at-1 indexing. More...
 
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diff --git a/doc/api/html/row_8hpp_source.html b/doc/api/html/row_8hpp_source.html new file mode 100644 index 00000000000..fac2020cda9 --- /dev/null +++ b/doc/api/html/row_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/row.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_ROW_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ROW_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
22  template <typename T>
+
23  inline
+
24  Eigen::Matrix<T, 1, Eigen::Dynamic>
+
25  row(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m,
+
26  size_t i) {
+
27  stan::math::check_row_index("row", "j", m, i);
+
28 
+
29  return m.row(i - 1);
+
30  }
+
31 
+
32  }
+
33 }
+
34 #endif
+ +
bool check_row_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
Return true if the specified index is a valid row of the matrix.
+ +
Eigen::Matrix< T, 1, Eigen::Dynamic > row(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i)
Return the specified row of the specified matrix, using start-at-1 indexing.
Definition: row.hpp:25
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diff --git a/doc/api/html/rows_8hpp.html b/doc/api/html/rows_8hpp.html new file mode 100644 index 00000000000..672be4dc9bd --- /dev/null +++ b/doc/api/html/rows_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rows.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
int stan::math::rows (const Eigen::Matrix< T, R, C > &m)
 Return the number of rows in the specified matrix, vector, or row vector. More...
 
+
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diff --git a/doc/api/html/rows_8hpp_source.html b/doc/api/html/rows_8hpp_source.html new file mode 100644 index 00000000000..f2de21f64a8 --- /dev/null +++ b/doc/api/html/rows_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/rows.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_ROWS_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_ROWS_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
19  template <typename T, int R, int C>
+
20  inline int rows(const Eigen::Matrix<T, R, C>& m) {
+
21  return m.rows();
+
22  }
+
23 
+
24  }
+
25 }
+
26 #endif
+
int rows(const Eigen::Matrix< T, R, C > &m)
Return the number of rows in the specified matrix, vector, or row vector.
Definition: rows.hpp:20
+ + +
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diff --git a/doc/api/html/scal_2fun_2fill_8hpp.html b/doc/api/html/scal_2fun_2fill_8hpp.html new file mode 100644 index 00000000000..893cc390c03 --- /dev/null +++ b/doc/api/html/scal_2fun_2fill_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/fill.hpp File Reference + + + + + + + + + + +
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template<typename T , typename S >
void stan::math::fill (T &x, const S &y)
 Fill the specified container with the specified value. More...
 
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diff --git a/doc/api/html/scal_2fun_2fill_8hpp_source.html b/doc/api/html/scal_2fun_2fill_8hpp_source.html new file mode 100644 index 00000000000..0a69192fe3b --- /dev/null +++ b/doc/api/html/scal_2fun_2fill_8hpp_source.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/fill.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_FILL_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_FILL_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
17  template <typename T, typename S>
+
18  void fill(T& x, const S& y) {
+
19  x = y;
+
20  }
+
21 
+
22  }
+
23 }
+
24 #endif
+ +
void fill(std::vector< T > &x, const S &y)
Fill the specified container with the specified value.
Definition: fill.hpp:22
+
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diff --git a/doc/api/html/scal_2fun_2promote__scalar_8hpp.html b/doc/api/html/scal_2fun_2promote__scalar_8hpp.html new file mode 100644 index 00000000000..e6cbe2734c2 --- /dev/null +++ b/doc/api/html/scal_2fun_2promote__scalar_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/promote_scalar.hpp File Reference + + + + + + + + + + +
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struct  stan::math::promote_scalar_struct< T, S >
 General struct to hold static function for promoting underlying scalar types. More...
 
struct  stan::math::promote_scalar_struct< T, T >
 Struct to hold static function for promoting underlying scalar types. More...
 
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template<typename T , typename S >
promote_scalar_type< T, S >::type stan::math::promote_scalar (const S &x)
 This is the top-level function to call to promote the scalar types of an input of type S to type T. More...
 
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diff --git a/doc/api/html/scal_2fun_2promote__scalar_8hpp_source.html b/doc/api/html/scal_2fun_2promote__scalar_8hpp_source.html new file mode 100644 index 00000000000..00211104fd8 --- /dev/null +++ b/doc/api/html/scal_2fun_2promote__scalar_8hpp_source.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/promote_scalar.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_PROMOTE_SCALAR_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_PROMOTE_SCALAR_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
18  template <typename T, typename S>
+ +
31  static T apply(S x) {
+
32  return T(x);
+
33  }
+
34  };
+
35 
+
43  template <typename T>
+
44  struct promote_scalar_struct<T, T> {
+
51  static T apply(const T& x) {
+
52  return x;
+
53  }
+
54  };
+
55 
+
65  template <typename T, typename S>
+
66  typename promote_scalar_type<T, S>::type
+
67  promote_scalar(const S& x) {
+ +
69  }
+
70 
+
71  }
+
72 }
+
73 #endif
+ + +
static T apply(const T &x)
Return the unmodified input.
+
promote_scalar_type< T, S >::type promote_scalar(const S &x)
This is the top-level function to call to promote the scalar types of an input of type S to type T...
+
General struct to hold static function for promoting underlying scalar types.
+ +
static T apply(S x)
Return the value of the input argument promoted to the type specified by the template parameter...
+
+
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diff --git a/doc/api/html/scal_2fun_2promote__scalar__type_8hpp.html b/doc/api/html/scal_2fun_2promote__scalar__type_8hpp.html new file mode 100644 index 00000000000..d93bf3c07bf --- /dev/null +++ b/doc/api/html/scal_2fun_2promote__scalar__type_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/promote_scalar_type.hpp File Reference + + + + + + + + + + +
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struct  stan::math::promote_scalar_type< T, S >
 Template metaprogram to calculate a type for converting a convertible type. More...
 
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+Namespaces

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 Matrices and templated mathematical functions.
 
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diff --git a/doc/api/html/scal_2fun_2promote__scalar__type_8hpp_source.html b/doc/api/html/scal_2fun_2promote__scalar__type_8hpp_source.html new file mode 100644 index 00000000000..00792e36368 --- /dev/null +++ b/doc/api/html/scal_2fun_2promote__scalar__type_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/promote_scalar_type.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_PROMOTE_SCALAR_TYPE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_PROMOTE_SCALAR_TYPE_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
14  template <typename T, typename S>
+ +
19  typedef T type;
+
20  };
+
21 
+
22  }
+
23 }
+
24 #endif
+ +
Template metaprogram to calculate a type for converting a convertible type.
+ +
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diff --git a/doc/api/html/scal_2fun_2to__fvar_8hpp.html b/doc/api/html/scal_2fun_2to__fvar_8hpp.html new file mode 100644 index 00000000000..05c67d71190 --- /dev/null +++ b/doc/api/html/scal_2fun_2to__fvar_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/to_fvar.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+ + + + + + + +

+Functions

template<typename T >
fvar< T > stan::math::to_fvar (const T &x)
 
template<typename T >
fvar< T > stan::math::to_fvar (const fvar< T > &x)
 
+
+
+
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diff --git a/doc/api/html/scal_2fun_2to__fvar_8hpp_source.html b/doc/api/html/scal_2fun_2to__fvar_8hpp_source.html new file mode 100644 index 00000000000..5ea494d23a0 --- /dev/null +++ b/doc/api/html/scal_2fun_2to__fvar_8hpp_source.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/fwd/scal/fun/to_fvar.hpp Source File + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
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+
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+
to_fvar.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_TO_FVAR_HPP
+
2 #define STAN_MATH_FWD_SCAL_FUN_TO_FVAR_HPP
+
3 
+
4 #include <stan/math/fwd/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  template<typename T>
+
10  inline
+
11  fvar<T>
+
12  to_fvar(const T& x) {
+
13  return fvar<T>(x);
+
14  }
+
15 
+
16  template<typename T>
+
17  inline
+
18  fvar<T>
+
19  to_fvar(const fvar<T>& x) {
+
20  return x;
+
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ + +
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Definition: to_fvar.hpp:14
+ +
+
+
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diff --git a/doc/api/html/scal_2fun_2to__var_8hpp.html b/doc/api/html/scal_2fun_2to__var_8hpp.html new file mode 100644 index 00000000000..dd66064601b --- /dev/null +++ b/doc/api/html/scal_2fun_2to__var_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/to_var.hpp File Reference + + + + + + + + + + +
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+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

var stan::math::to_var (const double &x)
 Converts argument to an automatic differentiation variable. More...
 
var stan::math::to_var (const var &x)
 Converts argument to an automatic differentiation variable. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scal_2fun_2to__var_8hpp_source.html b/doc/api/html/scal_2fun_2to__var_8hpp_source.html new file mode 100644 index 00000000000..fbe83e7a0e5 --- /dev/null +++ b/doc/api/html/scal_2fun_2to__var_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/scal/fun/to_var.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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+
to_var.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_SCAL_FUN_TO_VAR_HPP
+
2 #define STAN_MATH_REV_SCAL_FUN_TO_VAR_HPP
+
3 
+
4 #include <stan/math/rev/core.hpp>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
17  inline var to_var(const double& x) {
+
18  return var(x);
+
19  }
+
20 
+
29  inline var to_var(const var& x) {
+
30  return x;
+
31  }
+
32 
+
33  }
+
34 }
+
35 #endif
+ + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
std::vector< var > to_var(const std::vector< double > &v)
Converts argument to an automatic differentiation variable.
Definition: to_var.hpp:20
+
+
+
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diff --git a/doc/api/html/scal_2meta_2_vector_builder_helper_8hpp.html b/doc/api/html/scal_2meta_2_vector_builder_helper_8hpp.html new file mode 100644 index 00000000000..63de6494e14 --- /dev/null +++ b/doc/api/html/scal_2meta_2_vector_builder_helper_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/VectorBuilderHelper.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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+
VectorBuilderHelper.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/contains_vector.hpp>
+#include <stdexcept>
+
+

Go to the source code of this file.

+ + + + + + + +

+Classes

class  stan::VectorBuilderHelper< T1, used, is_vec >
 VectorBuilder allocates type T1 values to be used as intermediate values. More...
 
class  stan::VectorBuilderHelper< T1, true, false >
 
+ + + +

+Namespaces

 stan
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scal_2meta_2_vector_builder_helper_8hpp_source.html b/doc/api/html/scal_2meta_2_vector_builder_helper_8hpp_source.html new file mode 100644 index 00000000000..3684a6307d7 --- /dev/null +++ b/doc/api/html/scal_2meta_2_vector_builder_helper_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/VectorBuilderHelper.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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+
+
+
VectorBuilderHelper.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_VECTORBUILDER_HELPER_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_VECTORBUILDER_HELPER_HPP
+
3 
+ +
5 #include <stdexcept>
+
6 
+
7 namespace stan {
+
8 
+
24  template<typename T1, bool used, bool is_vec>
+ +
26  public:
+
27  explicit VectorBuilderHelper(size_t /* n */) { }
+
28 
+
29  T1& operator[](size_t /* i */) {
+
30  throw std::logic_error("used is false. this should never be called");
+
31  }
+
32 
+
33  typedef T1 type;
+
34 
+
35  inline type& data() {
+
36  throw std::logic_error("used is false. this should never be called");
+
37  }
+
38  };
+
39 
+
40  template<typename T1>
+
41  class VectorBuilderHelper<T1, true, false> {
+
42  private:
+
43  T1 x_;
+
44  public:
+
45  explicit VectorBuilderHelper(size_t /* n */) : x_(0.0) { }
+
46  T1& operator[](size_t /* i */) {
+
47  return x_;
+
48  }
+
49 
+
50  typedef T1 type;
+
51 
+
52  inline type& data() {
+
53  return x_;
+
54  }
+
55  };
+
56 
+
57 }
+
58 #endif
+ + + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scal_2meta_2_vector_view_8hpp.html b/doc/api/html/scal_2meta_2_vector_view_8hpp.html new file mode 100644 index 00000000000..020aef2448e --- /dev/null +++ b/doc/api/html/scal_2meta_2_vector_view_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/VectorView.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
VectorView.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/scalar_type.hpp>
+#include <stan/math/prim/scal/meta/is_vector_like.hpp>
+#include <boost/type_traits.hpp>
+#include <stdexcept>
+
+

Go to the source code of this file.

+ + + + + + + + + + + +

+Classes

class  stan::VectorView< T, is_array, throw_if_accessed >
 VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[]. More...
 
class  stan::VectorView< T, is_array, true >
 
class  stan::VectorView< T, false, false >
 
class  stan::VectorView< T, true, false >
 
+ + + +

+Namespaces

 stan
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scal_2meta_2_vector_view_8hpp_source.html b/doc/api/html/scal_2meta_2_vector_view_8hpp_source.html new file mode 100644 index 00000000000..ac0710c7966 --- /dev/null +++ b/doc/api/html/scal_2meta_2_vector_view_8hpp_source.html @@ -0,0 +1,245 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/VectorView.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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+
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+
+
+
VectorView.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_VECTORVIEW_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_VECTORVIEW_HPP
+
3 
+ + +
6 #include <boost/type_traits.hpp>
+
7 #include <stdexcept>
+
8 
+
9 namespace stan {
+
10 
+
45  template <typename T,
+
46  bool is_array = stan::is_vector_like<T>::value,
+
47  bool throw_if_accessed = false>
+
48  class VectorView {
+
49  public:
+
50  typedef typename
+
51  boost::conditional<boost::is_const<T>::value,
+
52  typename boost::add_const<
+
53  typename scalar_type<T>::type>::type,
+
54  typename scalar_type<T>::type>::type scalar_t;
+
55 
+
56  template <typename X>
+
57  explicit VectorView(X x) {
+
58  throw std::logic_error("VectorView: the default template "
+
59  "specialization not implemented");
+
60  }
+
61 
+
62  scalar_t& operator[](int i) {
+
63  throw std::logic_error("VectorView: the default template "
+
64  "specialization not implemented");
+
65  }
+
66 
+
67  scalar_t& operator[](int i) const {
+
68  throw std::logic_error("VectorView: the default template "
+
69  "specialization not implemented");
+
70  }
+
71  };
+
72 
+
73 
+
74  template <typename T, bool is_array>
+
75  class VectorView<T, is_array, true> {
+
76  public:
+
77  typedef typename
+
78  boost::conditional<boost::is_const<T>::value,
+
79  typename boost::add_const<
+
80  typename scalar_type<T>::type>::type,
+
81  typename scalar_type<T>::type>::type scalar_t;
+
82  VectorView() { }
+
83 
+
84  template <typename X>
+
85  explicit VectorView(X x) { }
+
86 
+
87  scalar_t& operator[](int i) {
+
88  throw std::logic_error("VectorView: this cannot be accessed");
+
89  }
+
90 
+
91  scalar_t& operator[](int i) const {
+
92  throw std::logic_error("VectorView: this cannot be accessed");
+
93  }
+
94  };
+
95 
+
96  // this covers non-vectors: double
+
97  template <typename T>
+
98  class VectorView<T, false, false> {
+
99  public:
+
100  typedef typename
+
101  boost::conditional<boost::is_const<T>::value,
+
102  typename boost::add_const<
+
103  typename scalar_type<T>::type>::type,
+ +
105 
+
106  explicit VectorView(scalar_t& x) : x_(&x) { }
+
107 
+
108  explicit VectorView(scalar_t* x) : x_(x) { }
+
109 
+
110  scalar_t& operator[](int i) {
+
111  return *x_;
+
112  }
+
113 
+
114  scalar_t& operator[](int i) const {
+
115  return *x_;
+
116  }
+
117  private:
+
118  scalar_t* x_;
+
119  };
+
120 
+
121 
+
122  // this covers raw memory: double*
+
123  template <typename T>
+
124  class VectorView<T, true, false> {
+
125  public:
+
126  typedef typename
+
127  boost::conditional<boost::is_const<T>::value,
+
128  typename boost::add_const<
+
129  typename scalar_type<T>::type>::type,
+ +
131 
+
132  explicit VectorView(scalar_t* x) : x_(x) { }
+
133 
+
134  scalar_t& operator[](int i) {
+
135  return x_[i];
+
136  }
+
137 
+
138  scalar_t& operator[](int i) const {
+
139  return x_[i];
+
140  }
+
141 
+
142  private:
+
143  scalar_t* x_;
+
144  };
+
145 }
+
146 #endif
+
boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
Definition: VectorView.hpp:81
+
scalar_t & operator[](int i)
Definition: VectorView.hpp:62
+ + +
Template metaprogram indicates whether a type is vector_like.
+ + +
boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
Definition: VectorView.hpp:54
+ +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+
scalar_t & operator[](int i) const
Definition: VectorView.hpp:67
+ + +
boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
Definition: VectorView.hpp:130
+
scalar_t & operator[](int i) const
Definition: VectorView.hpp:138
+
boost::conditional< boost::is_const< T >::value, typename boost::add_const< typename scalar_type< T >::type >::type, typename scalar_type< T >::type >::type scalar_t
Definition: VectorView.hpp:104
+ +
scalar_t & operator[](int i) const
Definition: VectorView.hpp:91
+ + + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
scalar_t & operator[](int i) const
Definition: VectorView.hpp:114
+ +
+
+
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diff --git a/doc/api/html/scal_2meta_2container__view_8hpp.html b/doc/api/html/scal_2meta_2container__view_8hpp.html new file mode 100644 index 00000000000..275d1d507fa --- /dev/null +++ b/doc/api/html/scal_2meta_2container__view_8hpp.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/container_view.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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+ +
+
container_view.hpp File Reference
+
+
+
#include <stan/math/prim/scal/meta/scalar_type.hpp>
+#include <stdexcept>
+
+

Go to the source code of this file.

+ + + + + + + + + + + +

+Classes

class  stan::math::container_view< T1, T2 >
 Primary template class for container view of array y with same structure as T1 and size as x. More...
 
struct  stan::math::dummy
 Empty struct for use in boost::condtional<is_constant_struct<T1>::value, T1, dummy>::type as false condtion for safe indexing. More...
 
class  stan::math::container_view< dummy, T2 >
 Dummy type specialization, used in conjunction with struct dummy as described above. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scal_2meta_2container__view_8hpp_source.html b/doc/api/html/scal_2meta_2container__view_8hpp_source.html new file mode 100644 index 00000000000..7b140c04071 --- /dev/null +++ b/doc/api/html/scal_2meta_2container__view_8hpp_source.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/container_view.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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container_view.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_CONTAINER_VIEW_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_CONTAINER_VIEW_HPP
+
3 
+ +
5 #include <stdexcept>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11 
+
21  template <typename T1, typename T2>
+ +
23  public:
+
30  container_view(const T1& x, T2* y) : y_(y) { }
+
31 
+
40  T2& operator[](int i) {
+
41  return y_[0];
+
42  }
+
43  private:
+
44  T2* y_;
+
45  };
+
46 
+
53  struct dummy { };
+
54 
+
62  template <typename T2>
+
63  class container_view<dummy, T2> {
+
64  public:
+ +
66  template <typename T1>
+
67 
+
74  container_view(const T1& x, scalar_t* y) { }
+
75 
+
82  scalar_t operator[](int n) const {
+
83  throw std::out_of_range("can't access dummy elements.");
+
84  }
+
85  };
+
86  }
+
87 }
+
88 
+
89 #endif
+
container_view(const T1 &x, T2 *y)
Constructor.
+ +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+
Empty struct for use in boost::condtional::value, T1, dummy>::type as false co...
+
stan::scalar_type< T2 >::type scalar_t
+
T2 & operator[](int i)
operator[](int i) returns reference to view, indexed by i Specialization handle appropriate broadcast...
+
scalar_t operator[](int n) const
operator[](int i) throws exception
+
container_view(const T1 &x, scalar_t *y)
Nothing initialized.
+
void out_of_range(const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
Throw an out_of_range exception with a consistently formatted message.
+ +
Primary template class for container view of array y with same structure as T1 and size as x...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scal_2meta_2get_8hpp.html b/doc/api/html/scal_2meta_2get_8hpp.html new file mode 100644 index 00000000000..5b6723494f4 --- /dev/null +++ b/doc/api/html/scal_2meta_2get_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/get.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
get.hpp File Reference
+
+
+
#include <cmath>
+#include <cstddef>
+
+

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+ + + + +

+Namespaces

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+ + + + +

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template<typename T >
stan::get (const T &x, size_t n)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scal_2meta_2get_8hpp_source.html b/doc/api/html/scal_2meta_2get_8hpp_source.html new file mode 100644 index 00000000000..d67904e9093 --- /dev/null +++ b/doc/api/html/scal_2meta_2get_8hpp_source.html @@ -0,0 +1,126 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/get.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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get.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_META_GET_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_GET_HPP
+
3 
+
4 #include <cmath>
+
5 #include <cstddef>
+
6 
+
7 namespace stan {
+
8 
+
9  template <typename T>
+
10  inline T get(const T& x, size_t n) {
+
11  return x;
+
12  }
+
13 
+
14 }
+
15 #endif
+
16 
+ +
+
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diff --git a/doc/api/html/scal_2meta_2index__type_8hpp.html b/doc/api/html/scal_2meta_2index__type_8hpp.html new file mode 100644 index 00000000000..73da3430b03 --- /dev/null +++ b/doc/api/html/scal_2meta_2index__type_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/index_type.hpp File Reference + + + + + + + + + + +
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struct  stan::math::index_type< T >
 Primary template class for the metaprogram to compute the index type of a container. More...
 
struct  stan::math::index_type< const T >
 Template class for metaprogram to compute the type of indexes used in a constant container type. More...
 
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+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
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diff --git a/doc/api/html/scal_2meta_2index__type_8hpp_source.html b/doc/api/html/scal_2meta_2index__type_8hpp_source.html new file mode 100644 index 00000000000..80352330643 --- /dev/null +++ b/doc/api/html/scal_2meta_2index__type_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/index_type.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_INDEX_TYPE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_INDEX_TYPE_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  namespace math {
+
7 
+
18  template <typename T>
+
19  struct index_type {
+
20  };
+
21 
+
22 
+
29  template <typename T>
+
30  struct index_type<const T> {
+
31  typedef typename index_type<T>::type type;
+
32  };
+
33 
+
34  }
+
35 }
+
36 
+
37 
+
38 #endif
+ +
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
index_type< T >::type type
Definition: index_type.hpp:31
+
+
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diff --git a/doc/api/html/scal_2meta_2is__constant__struct_8hpp.html b/doc/api/html/scal_2meta_2is__constant__struct_8hpp.html new file mode 100644 index 00000000000..2530951c537 --- /dev/null +++ b/doc/api/html/scal_2meta_2is__constant__struct_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_constant_struct.hpp File Reference + + + + + + + + + + +
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struct  stan::is_constant_struct< T >
 Metaprogram to determine if a type has a base scalar type that can be assigned to type double. More...
 
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+Namespaces

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diff --git a/doc/api/html/scal_2meta_2is__constant__struct_8hpp_source.html b/doc/api/html/scal_2meta_2is__constant__struct_8hpp_source.html new file mode 100644 index 00000000000..27df7557d80 --- /dev/null +++ b/doc/api/html/scal_2meta_2is__constant__struct_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_constant_struct.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_IS_CONSTANT_STRUCT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_IS_CONSTANT_STRUCT_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
12  template <typename T>
+ + +
15  };
+
16 
+
17 }
+
18 #endif
+
Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the ...
Definition: is_constant.hpp:22
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
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diff --git a/doc/api/html/scal_2meta_2is__vector_8hpp.html b/doc/api/html/scal_2meta_2is__vector_8hpp.html new file mode 100644 index 00000000000..de4d089e108 --- /dev/null +++ b/doc/api/html/scal_2meta_2is__vector_8hpp.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_vector.hpp File Reference + + + + + + + + + + +
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struct  stan::is_vector< T >
 
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diff --git a/doc/api/html/scal_2meta_2is__vector_8hpp_source.html b/doc/api/html/scal_2meta_2is__vector_8hpp_source.html new file mode 100644 index 00000000000..5b4b2163adf --- /dev/null +++ b/doc/api/html/scal_2meta_2is__vector_8hpp_source.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_vector.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_IS_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_IS_VECTOR_HPP
+
3 
+
4 namespace stan {
+
5 
+
6  // FIXME: use boost::type_traits::remove_all_extents to
+
7  // extend to array/ptr types
+
8 
+
9  template <typename T>
+
10  struct is_vector {
+
11  enum { value = 0 };
+
12  typedef T type;
+
13  };
+
14 }
+
15 #endif
+
16 
+ + + + +
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diff --git a/doc/api/html/scal_2meta_2is__vector__like_8hpp.html b/doc/api/html/scal_2meta_2is__vector__like_8hpp.html new file mode 100644 index 00000000000..0b452fc6f18 --- /dev/null +++ b/doc/api/html/scal_2meta_2is__vector__like_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_vector_like.hpp File Reference + + + + + + + + + + +
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struct  stan::is_vector_like< T >
 Template metaprogram indicates whether a type is vector_like. More...
 
struct  stan::is_vector_like< T * >
 Template metaprogram indicates whether a type is vector_like. More...
 
struct  stan::is_vector_like< const T >
 Template metaprogram indicates whether a type is vector_like. More...
 
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+Namespaces

 stan
 
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diff --git a/doc/api/html/scal_2meta_2is__vector__like_8hpp_source.html b/doc/api/html/scal_2meta_2is__vector__like_8hpp_source.html new file mode 100644 index 00000000000..44ec7933f7b --- /dev/null +++ b/doc/api/html/scal_2meta_2is__vector__like_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/is_vector_like.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_IS_VECTOR_LIKE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_IS_VECTOR_LIKE_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
20  template <typename T>
+
21  struct is_vector_like {
+ +
23  };
+
24 
+
35  template <typename T>
+
36  struct is_vector_like<T*> {
+
37  enum { value = true };
+
38  };
+
39 
+
40 
+
53  template <typename T>
+
54  struct is_vector_like<const T> {
+ +
56  };
+
57 }
+
58 #endif
+
59 
+
Template metaprogram indicates whether a type is vector_like.
+ + + + +
+
+
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diff --git a/doc/api/html/scal_2meta_2length_8hpp.html b/doc/api/html/scal_2meta_2length_8hpp.html new file mode 100644 index 00000000000..5032c8a96f1 --- /dev/null +++ b/doc/api/html/scal_2meta_2length_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/length.hpp File Reference + + + + + + + + + + +
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length.hpp File Reference
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#include <cstdlib>
+
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template<typename T >
size_t stan::length (const T &)
 
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diff --git a/doc/api/html/scal_2meta_2length_8hpp_source.html b/doc/api/html/scal_2meta_2length_8hpp_source.html new file mode 100644 index 00000000000..8a19c5a367c --- /dev/null +++ b/doc/api/html/scal_2meta_2length_8hpp_source.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/length.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_LENGTH_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_LENGTH_HPP
+
3 
+
4 #include <cstdlib>
+
5 
+
6 namespace stan {
+
7 
+
8  template <typename T>
+
9  size_t length(const T& /*x*/) {
+
10  return 1U;
+
11  }
+
12 }
+
13 #endif
+
14 
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
+
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diff --git a/doc/api/html/scal_2meta_2length__mvt_8hpp.html b/doc/api/html/scal_2meta_2length__mvt_8hpp.html new file mode 100644 index 00000000000..1ea5dcbba71 --- /dev/null +++ b/doc/api/html/scal_2meta_2length__mvt_8hpp.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/length_mvt.hpp File Reference + + + + + + + + + + +
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template<typename T >
size_t stan::length_mvt (const T &)
 
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diff --git a/doc/api/html/scal_2meta_2length__mvt_8hpp_source.html b/doc/api/html/scal_2meta_2length__mvt_8hpp_source.html new file mode 100644 index 00000000000..061fae76a03 --- /dev/null +++ b/doc/api/html/scal_2meta_2length__mvt_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/length_mvt.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_LENGTH_MVT_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_LENGTH_MVT_HPP
+
3 
+
4 #include <stdexcept>
+
5 
+
6 namespace stan {
+
7 
+
8  template <typename T>
+
9  size_t length_mvt(const T& ) {
+
10  throw std::out_of_range("length_mvt passed to an unrecognized type.");
+
11  return 1U;
+
12  }
+
13 
+
14 }
+
15 #endif
+
16 
+ +
void out_of_range(const char *function, const int max, const int index, const char *msg1="", const char *msg2="")
Throw an out_of_range exception with a consistently formatted message.
+
size_t length_mvt(const Eigen::Matrix< T, R, C > &)
Definition: length_mvt.hpp:12
+
+
+
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diff --git a/doc/api/html/scal_2meta_2scalar__type_8hpp.html b/doc/api/html/scal_2meta_2scalar__type_8hpp.html new file mode 100644 index 00000000000..747db9b2c41 --- /dev/null +++ b/doc/api/html/scal_2meta_2scalar__type_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/scalar_type.hpp File Reference + + + + + + + + + + +
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struct  stan::scalar_type< T >
 Metaprogram structure to determine the base scalar type of a template argument. More...
 
struct  stan::scalar_type< T * >
 
+ + + +

+Namespaces

 stan
 
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diff --git a/doc/api/html/scal_2meta_2scalar__type_8hpp_source.html b/doc/api/html/scal_2meta_2scalar__type_8hpp_source.html new file mode 100644 index 00000000000..99ed53dde2d --- /dev/null +++ b/doc/api/html/scal_2meta_2scalar__type_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/scalar_type.hpp Source File + + + + + + + + + + +
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scalar_type.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_META_SCALAR_TYPE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_SCALAR_TYPE_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace {
+
10  template <bool is_vec, typename T>
+
11  struct scalar_type_helper {
+
12  typedef T type;
+
13  };
+
14 
+
15  template <typename T>
+
16  struct scalar_type_helper<true, T> {
+
17  typedef typename
+
18  scalar_type_helper<is_vector<typename
+ +
20  typename stan::math::value_type<T>::type>::type
+
21  type;
+
22  };
+
23  }
+
24 
+
33  template <typename T>
+
34  struct scalar_type {
+
35  typedef typename scalar_type_helper<is_vector<T>::value, T>::type type;
+
36  };
+
37 
+
38  template <typename T>
+
39  struct scalar_type<T*> {
+
40  typedef typename scalar_type<T>::type type;
+
41  };
+
42 
+
43 }
+
44 #endif
+
scalar_type< T >::type type
Definition: scalar_type.hpp:40
+
Metaprogram structure to determine the base scalar type of a template argument.
Definition: scalar_type.hpp:34
+ + +
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+ +
Primary template class for metaprogram to compute the type of values stored in a container.
Definition: value_type.hpp:18
+
+
+
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diff --git a/doc/api/html/scal_2meta_2value__type_8hpp.html b/doc/api/html/scal_2meta_2value__type_8hpp.html new file mode 100644 index 00000000000..05856db91fa --- /dev/null +++ b/doc/api/html/scal_2meta_2value__type_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/value_type.hpp File Reference + + + + + + + + + + +
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+Classes

struct  stan::math::value_type< T >
 Primary template class for metaprogram to compute the type of values stored in a container. More...
 
struct  stan::math::value_type< const T >
 Template class for metaprogram to compute the type of values stored in a constant container. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
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diff --git a/doc/api/html/scal_2meta_2value__type_8hpp_source.html b/doc/api/html/scal_2meta_2value__type_8hpp_source.html new file mode 100644 index 00000000000..155a85bdf39 --- /dev/null +++ b/doc/api/html/scal_2meta_2value__type_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/value_type.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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1 #ifndef STAN_MATH_PRIM_SCAL_META_VALUE_TYPE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_VALUE_TYPE_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
17  template <typename T>
+
18  struct value_type {
+
19  };
+
20 
+
27  template <typename T>
+
28  struct value_type<const T> {
+
29  typedef typename value_type<T>::type type;
+
30  };
+
31 
+
32  }
+
33 }
+
34 #endif
+
value_type< T >::type type
Definition: value_type.hpp:29
+ +
Primary template class for metaprogram to compute the type of values stored in a container.
Definition: value_type.hpp:18
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scalar__type__pre_8hpp.html b/doc/api/html/scalar__type__pre_8hpp.html new file mode 100644 index 00000000000..02e4d548f13 --- /dev/null +++ b/doc/api/html/scalar__type__pre_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/scalar_type_pre.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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scalar_type_pre.hpp File Reference
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struct  stan::scalar_type_pre< T >
 Metaprogram structure to determine the type of first container of the base scalar type of a template argument. More...
 
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diff --git a/doc/api/html/scalar__type__pre_8hpp_source.html b/doc/api/html/scalar__type__pre_8hpp_source.html new file mode 100644 index 00000000000..6283c7a82ea --- /dev/null +++ b/doc/api/html/scalar__type__pre_8hpp_source.html @@ -0,0 +1,155 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/scalar_type_pre.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
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+ + +
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+
scalar_type_pre.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_META_SCALAR_TYPE_PRE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_SCALAR_TYPE_PRE_HPP
+
3 
+ + +
6 
+
7 namespace stan {
+
8 
+
9  namespace {
+
10  template <bool is_vec, typename T, typename T_container>
+
11  struct scalar_type_helper_pre {
+
12  typedef T_container type;
+
13  };
+
14 
+
15  template <typename T, typename T_container>
+
16  struct scalar_type_helper_pre<true, T, T_container> {
+
17  typedef typename
+
18  scalar_type_helper_pre<is_vector<typename stan::math::value_type<T>::type>
+
19  ::value,
+ +
21  typename
+ +
23  type;
+
24  };
+
25  }
+
26 
+
33  template <typename T>
+
34  struct scalar_type_pre {
+
35  typedef typename
+
36  scalar_type_helper_pre<is_vector
+
37  <typename stan::math::value_type<T>::type>::value,
+ + +
40  };
+
41 
+
42 
+
43 }
+
44 #endif
+
45 
+
scalar_type_helper_pre< is_vector< typename stan::math::value_type< T >::type >::value, typename stan::math::value_type< T >::type, T >::type type
+ + + + +
Metaprogram structure to determine the type of first container of the base scalar type of a template ...
+
Primary template class for metaprogram to compute the type of values stored in a container.
Definition: value_type.hpp:18
+
+
+
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diff --git a/doc/api/html/scaled__add_8hpp.html b/doc/api/html/scaled__add_8hpp.html new file mode 100644 index 00000000000..62644ae96db --- /dev/null +++ b/doc/api/html/scaled__add_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/scaled_add.hpp File Reference + + + + + + + + + + +
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scaled_add.hpp File Reference
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#include <vector>
+#include <cstddef>
+
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void stan::math::scaled_add (std::vector< double > &x, const std::vector< double > &y, const double lambda)
 
+
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diff --git a/doc/api/html/scaled__add_8hpp_source.html b/doc/api/html/scaled__add_8hpp_source.html new file mode 100644 index 00000000000..051c71f2ba8 --- /dev/null +++ b/doc/api/html/scaled__add_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/scaled_add.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_SCALED_ADD_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_SCALED_ADD_HPP
+
3 
+
4 #include <vector>
+
5 #include <cstddef>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  // x <- x + lambda * y
+
11  inline void scaled_add(std::vector<double>& x,
+
12  const std::vector<double>& y,
+
13  const double lambda) {
+
14  for (size_t i = 0; i < x.size(); ++i)
+
15  x[i] += lambda * y[i];
+
16  }
+
17 
+
18  }
+
19 }
+
20 
+
21 #endif
+ +
void scaled_add(std::vector< double > &x, const std::vector< double > &y, const double lambda)
Definition: scaled_add.hpp:11
+
+
+
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diff --git a/doc/api/html/scaled__inv__chi__square__ccdf__log_8hpp.html b/doc/api/html/scaled__inv__chi__square__ccdf__log_8hpp.html new file mode 100644 index 00000000000..7f11fda0edb --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__ccdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_ccdf_log.hpp File Reference + + + + + + + + + + +
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scaled_inv_chi_square_ccdf_log.hpp File Reference
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+Functions

template<typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type stan::math::scaled_inv_chi_square_ccdf_log (const T_y &y, const T_dof &nu, const T_scale &s)
 
+
+
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scaled__inv__chi__square__ccdf__log_8hpp_source.html b/doc/api/html/scaled__inv__chi__square__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..1563105cbdf --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__ccdf__log_8hpp_source.html @@ -0,0 +1,299 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_ccdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
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+
reverse mode automatic differentiation
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+
scaled_inv_chi_square_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/chi_squared_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <limits>
+
25 #include <cmath>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_y, typename T_dof, typename T_scale>
+
32  typename return_type<T_y, T_dof, T_scale>::type
+
33  scaled_inv_chi_square_ccdf_log(const T_y& y, const T_dof& nu,
+
34  const T_scale& s) {
+ +
36  T_partials_return;
+
37 
+
38  // Size checks
+
39  if (!(stan::length(y) && stan::length(nu) && stan::length(s)))
+
40  return 0.0;
+
41 
+
42  static const char* function("stan::math::scaled_inv_chi_square_ccdf_log");
+
43 
+ + + + + +
49  using std::exp;
+
50 
+
51  T_partials_return P(0.0);
+
52 
+
53  check_not_nan(function, "Random variable", y);
+
54  check_nonnegative(function, "Random variable", y);
+
55  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
56  check_positive_finite(function, "Scale parameter", s);
+
57  check_consistent_sizes(function,
+
58  "Random variable", y,
+
59  "Degrees of freedom parameter", nu,
+
60  "Scale parameter", s);
+
61 
+
62  // Wrap arguments in vectors
+
63  VectorView<const T_y> y_vec(y);
+
64  VectorView<const T_dof> nu_vec(nu);
+ +
66  size_t N = max_size(y, nu, s);
+
67 
+ +
69  operands_and_partials(y, nu, s);
+
70 
+
71  // Explicit return for extreme values
+
72  // The gradients are technically ill-defined, but treated as zero
+
73  for (size_t i = 0; i < stan::length(y); i++) {
+
74  if (value_of(y_vec[i]) == 0)
+
75  return operands_and_partials.value(0.0);
+
76  }
+
77 
+
78  // Compute cdf_log and its gradients
+
79  using stan::math::gamma_q;
+
80  using stan::math::digamma;
+
81  using boost::math::tgamma;
+
82  using std::exp;
+
83  using std::pow;
+
84  using std::log;
+
85 
+
86  // Cache a few expensive function calls if nu is a parameter
+ +
88  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
90  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
91 
+ +
93  for (size_t i = 0; i < stan::length(nu); i++) {
+
94  const T_partials_return half_nu_dbl = 0.5 * value_of(nu_vec[i]);
+
95  gamma_vec[i] = tgamma(half_nu_dbl);
+
96  digamma_vec[i] = digamma(half_nu_dbl);
+
97  }
+
98  }
+
99 
+
100  // Compute vectorized cdf_log and gradient
+
101  for (size_t n = 0; n < N; n++) {
+
102  // Explicit results for extreme values
+
103  // The gradients are technically ill-defined, but treated as zero
+
104  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
105  return operands_and_partials.value(stan::math::negative_infinity());
+
106  }
+
107 
+
108  // Pull out values
+
109  const T_partials_return y_dbl = value_of(y_vec[n]);
+
110  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
111  const T_partials_return half_nu_dbl = 0.5 * value_of(nu_vec[n]);
+
112  const T_partials_return s_dbl = value_of(s_vec[n]);
+
113  const T_partials_return half_s2_overx_dbl = 0.5 * s_dbl * s_dbl
+
114  * y_inv_dbl;
+
115  const T_partials_return half_nu_s2_overx_dbl
+
116  = 2.0 * half_nu_dbl * half_s2_overx_dbl;
+
117 
+
118  // Compute
+
119  const T_partials_return Pn = 1.0 - gamma_q(half_nu_dbl,
+
120  half_nu_s2_overx_dbl);
+
121  const T_partials_return gamma_p_deriv = exp(-half_nu_s2_overx_dbl)
+
122  * pow(half_nu_s2_overx_dbl, half_nu_dbl-1) / tgamma(half_nu_dbl);
+
123 
+
124  P += log(Pn);
+
125 
+ +
127  operands_and_partials.d_x1[n] -= half_nu_s2_overx_dbl * y_inv_dbl
+
128  * gamma_p_deriv / Pn;
+ +
130  operands_and_partials.d_x2[n]
+
131  -= (0.5 * stan::math::grad_reg_inc_gamma(half_nu_dbl,
+
132  half_nu_s2_overx_dbl,
+
133  gamma_vec[n],
+
134  digamma_vec[n])
+
135  - half_s2_overx_dbl * gamma_p_deriv)
+
136  / Pn;
+ +
138  operands_and_partials.d_x3[n] += 2.0 * half_nu_dbl * s_dbl * y_inv_dbl
+
139  * gamma_p_deriv / Pn;
+
140  }
+
141 
+
142  return operands_and_partials.value(P);
+
143  }
+
144  }
+
145 }
+
146 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ +
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_ccdf_log(const T_y &y, const T_dof &nu, const T_scale &s)
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/scaled__inv__chi__square__cdf_8hpp.html b/doc/api/html/scaled__inv__chi__square__cdf_8hpp.html new file mode 100644 index 00000000000..cef0c0dcfbb --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__cdf_8hpp.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_cdf.hpp File Reference + + + + + + + + + + +
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+Functions

template<typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type stan::math::scaled_inv_chi_square_cdf (const T_y &y, const T_dof &nu, const T_scale &s)
 The CDF of a scaled inverse chi-squared density for y with the specified degrees of freedom parameter and scale parameter. More...
 
+
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diff --git a/doc/api/html/scaled__inv__chi__square__cdf_8hpp_source.html b/doc/api/html/scaled__inv__chi__square__cdf_8hpp_source.html new file mode 100644 index 00000000000..f276aff5eac --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__cdf_8hpp_source.html @@ -0,0 +1,315 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_cdf.hpp Source File + + + + + + + + + + +
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scaled_inv_chi_square_cdf.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/chi_squared_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <limits>
+
25 #include <cmath>
+
26 
+
27 
+
28 namespace stan {
+
29 
+
30  namespace math {
+
31 
+
46  template <typename T_y, typename T_dof, typename T_scale>
+
47  typename return_type<T_y, T_dof, T_scale>::type
+
48  scaled_inv_chi_square_cdf(const T_y& y, const T_dof& nu,
+
49  const T_scale& s) {
+ +
51  T_partials_return;
+
52 
+
53  // Size checks
+
54  if (!(stan::length(y) && stan::length(nu) && stan::length(s)))
+
55  return 1.0;
+
56 
+
57  static const char* function("stan::math::scaled_inv_chi_square_cdf");
+
58 
+ + + + + +
64  using std::exp;
+
65 
+
66  T_partials_return P(1.0);
+
67 
+
68  check_not_nan(function, "Random variable", y);
+
69  check_nonnegative(function, "Random variable", y);
+
70  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
71  check_positive_finite(function, "Scale parameter", s);
+
72  check_consistent_sizes(function,
+
73  "Random variable", y,
+
74  "Degrees of freedom parameter", nu,
+
75  "Scale parameter", s);
+
76 
+
77  // Wrap arguments in vectors
+
78  VectorView<const T_y> y_vec(y);
+
79  VectorView<const T_dof> nu_vec(nu);
+ +
81  size_t N = max_size(y, nu, s);
+
82 
+ +
84  operands_and_partials(y, nu, s);
+
85 
+
86  // Explicit return for extreme values
+
87  // The gradients are technically ill-defined, but treated as zero
+
88 
+
89  for (size_t i = 0; i < stan::length(y); i++) {
+
90  if (value_of(y_vec[i]) == 0)
+
91  return operands_and_partials.value(0.0);
+
92  }
+
93 
+
94  // Compute CDF and its gradients
+
95  using stan::math::gamma_q;
+
96  using stan::math::digamma;
+
97  using boost::math::tgamma;
+
98  using std::exp;
+
99  using std::pow;
+
100 
+
101  // Cache a few expensive function calls if nu is a parameter
+ +
103  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
105  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
106 
+ +
108  for (size_t i = 0; i < stan::length(nu); i++) {
+
109  const T_partials_return half_nu_dbl = 0.5 * value_of(nu_vec[i]);
+
110  gamma_vec[i] = tgamma(half_nu_dbl);
+
111  digamma_vec[i] = digamma(half_nu_dbl);
+
112  }
+
113  }
+
114 
+
115  // Compute vectorized CDF and gradient
+
116  for (size_t n = 0; n < N; n++) {
+
117  // Explicit results for extreme values
+
118  // The gradients are technically ill-defined, but treated as zero
+
119  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
120  continue;
+
121  }
+
122 
+
123  // Pull out values
+
124  const T_partials_return y_dbl = value_of(y_vec[n]);
+
125  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
126  const T_partials_return half_nu_dbl = 0.5 * value_of(nu_vec[n]);
+
127  const T_partials_return s_dbl = value_of(s_vec[n]);
+
128  const T_partials_return half_s2_overx_dbl = 0.5 * s_dbl * s_dbl
+
129  * y_inv_dbl;
+
130  const T_partials_return half_nu_s2_overx_dbl
+
131  = 2.0 * half_nu_dbl * half_s2_overx_dbl;
+
132 
+
133  // Compute
+
134  const T_partials_return Pn = gamma_q(half_nu_dbl, half_nu_s2_overx_dbl);
+
135  const T_partials_return gamma_p_deriv = exp(-half_nu_s2_overx_dbl)
+
136  * pow(half_nu_s2_overx_dbl, half_nu_dbl-1) / tgamma(half_nu_dbl);
+
137 
+
138  P *= Pn;
+
139 
+ +
141  operands_and_partials.d_x1[n] += half_nu_s2_overx_dbl * y_inv_dbl
+
142  * gamma_p_deriv / Pn;
+
143 
+
144 
+
145 
+ +
147  operands_and_partials.d_x2[n]
+
148  += (0.5 * stan::math::grad_reg_inc_gamma(half_nu_dbl,
+
149  half_nu_s2_overx_dbl,
+
150  gamma_vec[n],
+
151  digamma_vec[n])
+
152  - half_s2_overx_dbl * gamma_p_deriv)
+
153  / Pn;
+
154 
+ +
156  operands_and_partials.d_x3[n]
+
157  += - 2.0 * half_nu_dbl * s_dbl * y_inv_dbl
+
158  * gamma_p_deriv / Pn;
+
159  }
+
160 
+ +
162  for (size_t n = 0; n < stan::length(y); ++n)
+
163  operands_and_partials.d_x1[n] *= P;
+
164  }
+ +
166  for (size_t n = 0; n < stan::length(nu); ++n)
+
167  operands_and_partials.d_x2[n] *= P;
+
168  }
+ +
170  for (size_t n = 0; n < stan::length(s); ++n)
+
171  operands_and_partials.d_x3[n] *= P;
+
172  }
+
173 
+
174  return operands_and_partials.value(P);
+
175  }
+
176  }
+
177 }
+
178 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_cdf(const T_y &y, const T_dof &nu, const T_scale &s)
The CDF of a scaled inverse chi-squared density for y with the specified degrees of freedom parameter...
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scaled__inv__chi__square__cdf__log_8hpp.html b/doc/api/html/scaled__inv__chi__square__cdf__log_8hpp.html new file mode 100644 index 00000000000..048b090b2c2 --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__cdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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scaled_inv_chi_square_cdf_log.hpp File Reference
+
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+ +

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+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type stan::math::scaled_inv_chi_square_cdf_log (const T_y &y, const T_dof &nu, const T_scale &s)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scaled__inv__chi__square__cdf__log_8hpp_source.html b/doc/api/html/scaled__inv__chi__square__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..ae5cc0ed429 --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__cdf__log_8hpp_source.html @@ -0,0 +1,299 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+
+
scaled_inv_chi_square_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/chi_squared_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <limits>
+
25 #include <cmath>
+
26 
+
27 
+
28 namespace stan {
+
29 
+
30  namespace math {
+
31 
+
32  template <typename T_y, typename T_dof, typename T_scale>
+
33  typename return_type<T_y, T_dof, T_scale>::type
+
34  scaled_inv_chi_square_cdf_log(const T_y& y, const T_dof& nu,
+
35  const T_scale& s) {
+ +
37  T_partials_return;
+
38 
+
39  // Size checks
+
40  if (!(stan::length(y) && stan::length(nu) && stan::length(s)))
+
41  return 0.0;
+
42 
+
43  static const char* function("stan::math::scaled_inv_chi_square_cdf_log");
+
44 
+ + + + + +
50  using std::exp;
+
51 
+
52  T_partials_return P(0.0);
+
53 
+
54  check_not_nan(function, "Random variable", y);
+
55  check_nonnegative(function, "Random variable", y);
+
56  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
57  check_positive_finite(function, "Scale parameter", s);
+
58  check_consistent_sizes(function,
+
59  "Random variable", y,
+
60  "Degrees of freedom parameter", nu,
+
61  "Scale parameter", s);
+
62 
+
63  // Wrap arguments in vectors
+
64  VectorView<const T_y> y_vec(y);
+
65  VectorView<const T_dof> nu_vec(nu);
+ +
67  size_t N = max_size(y, nu, s);
+
68 
+ +
70  operands_and_partials(y, nu, s);
+
71 
+
72  // Explicit return for extreme values
+
73  // The gradients are technically ill-defined, but treated as zero
+
74  for (size_t i = 0; i < stan::length(y); i++) {
+
75  if (value_of(y_vec[i]) == 0)
+
76  return operands_and_partials.value(stan::math::negative_infinity());
+
77  }
+
78 
+
79  // Compute cdf_log and its gradients
+
80  using stan::math::gamma_q;
+
81  using stan::math::digamma;
+
82  using boost::math::tgamma;
+
83  using std::exp;
+
84  using std::pow;
+
85  using std::log;
+
86 
+
87  // Cache a few expensive function calls if nu is a parameter
+ +
89  T_partials_return, T_dof> gamma_vec(stan::length(nu));
+ +
91  T_partials_return, T_dof> digamma_vec(stan::length(nu));
+
92 
+ +
94  for (size_t i = 0; i < stan::length(nu); i++) {
+
95  const T_partials_return half_nu_dbl = 0.5 * value_of(nu_vec[i]);
+
96  gamma_vec[i] = tgamma(half_nu_dbl);
+
97  digamma_vec[i] = digamma(half_nu_dbl);
+
98  }
+
99  }
+
100 
+
101  // Compute vectorized cdf_log and gradient
+
102  for (size_t n = 0; n < N; n++) {
+
103  // Explicit results for extreme values
+
104  // The gradients are technically ill-defined, but treated as zero
+
105  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
106  continue;
+
107  }
+
108 
+
109  // Pull out values
+
110  const T_partials_return y_dbl = value_of(y_vec[n]);
+
111  const T_partials_return y_inv_dbl = 1.0 / y_dbl;
+
112  const T_partials_return half_nu_dbl = 0.5 * value_of(nu_vec[n]);
+
113  const T_partials_return s_dbl = value_of(s_vec[n]);
+
114  const T_partials_return half_s2_overx_dbl = 0.5 * s_dbl * s_dbl
+
115  * y_inv_dbl;
+
116  const T_partials_return half_nu_s2_overx_dbl
+
117  = 2.0 * half_nu_dbl * half_s2_overx_dbl;
+
118 
+
119  // Compute
+
120  const T_partials_return Pn = gamma_q(half_nu_dbl, half_nu_s2_overx_dbl);
+
121  const T_partials_return gamma_p_deriv = exp(-half_nu_s2_overx_dbl)
+
122  * pow(half_nu_s2_overx_dbl, half_nu_dbl-1) / tgamma(half_nu_dbl);
+
123 
+
124  P += log(Pn);
+
125 
+ +
127  operands_and_partials.d_x1[n] += half_nu_s2_overx_dbl * y_inv_dbl
+
128  * gamma_p_deriv / Pn;
+ +
130  operands_and_partials.d_x2[n]
+
131  += (0.5 * stan::math::grad_reg_inc_gamma(half_nu_dbl,
+
132  half_nu_s2_overx_dbl,
+
133  gamma_vec[n],
+
134  digamma_vec[n])
+
135  - half_s2_overx_dbl * gamma_p_deriv)
+
136  / Pn;
+ +
138  operands_and_partials.d_x3[n] += - 2.0 * half_nu_dbl * s_dbl
+
139  * y_inv_dbl * gamma_p_deriv / Pn;
+
140  }
+
141 
+
142  return operands_and_partials.value(P);
+
143  }
+
144  }
+
145 }
+
146 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
T grad_reg_inc_gamma(T a, T z, T g, T dig, T precision=1e-6)
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
fvar< T > tgamma(const fvar< T > &x)
Definition: tgamma.hpp:15
+
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_cdf_log(const T_y &y, const T_dof &nu, const T_scale &s)
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
fvar< T > gamma_q(const fvar< T > &x1, const fvar< T > &x2)
Definition: gamma_q.hpp:15
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scaled__inv__chi__square__log_8hpp.html b/doc/api/html/scaled__inv__chi__square__log_8hpp.html new file mode 100644 index 00000000000..7f7abbd3f1e --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__log_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_log.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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scaled_inv_chi_square_log.hpp File Reference
+
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Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type stan::math::scaled_inv_chi_square_log (const T_y &y, const T_dof &nu, const T_scale &s)
 The log of a scaled inverse chi-squared density for y with the specified degrees of freedom parameter and scale parameter. More...
 
template<typename T_y , typename T_dof , typename T_scale >
return_type< T_y, T_dof, T_scale >::type stan::math::scaled_inv_chi_square_log (const T_y &y, const T_dof &nu, const T_scale &s)
 
+
+
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diff --git a/doc/api/html/scaled__inv__chi__square__log_8hpp_source.html b/doc/api/html/scaled__inv__chi__square__log_8hpp_source.html new file mode 100644 index 00000000000..bb149b408bb --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__log_8hpp_source.html @@ -0,0 +1,312 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_log.hpp Source File + + + + + + + + + + +
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scaled_inv_chi_square_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/chi_squared_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <cmath>
+
25 
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
50  template <bool propto,
+
51  typename T_y, typename T_dof, typename T_scale>
+
52  typename return_type<T_y, T_dof, T_scale>::type
+
53  scaled_inv_chi_square_log(const T_y& y, const T_dof& nu, const T_scale& s) {
+
54  static const char* function("stan::math::scaled_inv_chi_square_log");
+ +
56  T_partials_return;
+
57 
+ + + + +
62 
+
63  // check if any vectors are zero length
+
64  if (!(stan::length(y)
+
65  && stan::length(nu)
+
66  && stan::length(s)))
+
67  return 0.0;
+
68 
+
69  T_partials_return logp(0.0);
+
70  check_not_nan(function, "Random variable", y);
+
71  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
72  check_positive_finite(function, "Scale parameter", s);
+
73  check_consistent_sizes(function,
+
74  "Random variable", y,
+
75  "Degrees of freedom parameter", nu,
+
76  "Scale parameter", s);
+
77 
+
78  // check if no variables are involved and prop-to
+ +
80  return 0.0;
+
81 
+
82  VectorView<const T_y> y_vec(y);
+
83  VectorView<const T_dof> nu_vec(nu);
+ +
85  size_t N = max_size(y, nu, s);
+
86 
+
87  for (size_t n = 0; n < N; n++) {
+
88  if (value_of(y_vec[n]) <= 0)
+
89  return LOG_ZERO;
+
90  }
+
91 
+
92  using stan::math::lgamma;
+
93  using stan::math::digamma;
+
94  using stan::math::square;
+
95  using std::log;
+
96 
+ +
98  T_partials_return, T_dof> half_nu(length(nu));
+
99  for (size_t i = 0; i < length(nu); i++)
+ +
101  half_nu[i] = 0.5 * value_of(nu_vec[i]);
+
102 
+ +
104  T_partials_return, T_y> log_y(length(y));
+
105  for (size_t i = 0; i < length(y); i++)
+ +
107  log_y[i] = log(value_of(y_vec[i]));
+
108 
+ +
110  T_partials_return, T_y> inv_y(length(y));
+
111  for (size_t i = 0; i < length(y); i++)
+ +
113  inv_y[i] = 1.0 / value_of(y_vec[i]);
+
114 
+ +
116  T_partials_return, T_scale> log_s(length(s));
+
117  for (size_t i = 0; i < length(s); i++)
+ +
119  log_s[i] = log(value_of(s_vec[i]));
+
120 
+ +
122  T_partials_return, T_dof> log_half_nu(length(nu));
+ +
124  T_partials_return, T_dof> lgamma_half_nu(length(nu));
+ +
126  T_partials_return, T_dof>
+
127  digamma_half_nu_over_two(length(nu));
+
128  for (size_t i = 0; i < length(nu); i++) {
+ +
130  lgamma_half_nu[i] = lgamma(half_nu[i]);
+ +
132  log_half_nu[i] = log(half_nu[i]);
+ +
134  digamma_half_nu_over_two[i] = digamma(half_nu[i]) * 0.5;
+
135  }
+
136 
+ +
138  operands_and_partials(y, nu, s);
+
139  for (size_t n = 0; n < N; n++) {
+
140  const T_partials_return s_dbl = value_of(s_vec[n]);
+
141  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+ +
143  logp += half_nu[n] * log_half_nu[n] - lgamma_half_nu[n];
+ +
145  logp += nu_dbl * log_s[n];
+ +
147  logp -= (half_nu[n]+1.0) * log_y[n];
+ +
149  logp -= half_nu[n] * s_dbl*s_dbl * inv_y[n];
+
150 
+ +
152  operands_and_partials.d_x1[n]
+
153  += -(half_nu[n] + 1.0) * inv_y[n]
+
154  + half_nu[n] * s_dbl*s_dbl * inv_y[n]*inv_y[n];
+
155  }
+ +
157  operands_and_partials.d_x2[n]
+
158  += 0.5 * log_half_nu[n] + 0.5
+
159  - digamma_half_nu_over_two[n]
+
160  + log_s[n]
+
161  - 0.5 * log_y[n]
+
162  - 0.5* s_dbl*s_dbl * inv_y[n];
+
163  }
+ +
165  operands_and_partials.d_x3[n]
+
166  += nu_dbl / s_dbl - nu_dbl * inv_y[n] * s_dbl;
+
167  }
+
168  }
+
169  return operands_and_partials.value(logp);
+
170  }
+
171 
+
172  template <typename T_y, typename T_dof, typename T_scale>
+
173  inline
+ +
175  scaled_inv_chi_square_log(const T_y& y, const T_dof& nu, const T_scale& s) {
+
176  return scaled_inv_chi_square_log<false>(y, nu, s);
+
177  }
+
178  }
+
179 }
+
180 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
return_type< T_y, T_dof, T_scale >::type scaled_inv_chi_square_log(const T_y &y, const T_dof &nu, const T_scale &s)
The log of a scaled inverse chi-squared density for y with the specified degrees of freedom parameter...
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+ +
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
+
+
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diff --git a/doc/api/html/scaled__inv__chi__square__rng_8hpp.html b/doc/api/html/scaled__inv__chi__square__rng_8hpp.html new file mode 100644 index 00000000000..a0e87ac891c --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__rng_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_rng.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
scaled_inv_chi_square_rng.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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+ + + + +

+Functions

template<class RNG >
double stan::math::scaled_inv_chi_square_rng (const double nu, const double s, RNG &rng)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/scaled__inv__chi__square__rng_8hpp_source.html b/doc/api/html/scaled__inv__chi__square__rng_8hpp_source.html new file mode 100644 index 00000000000..82615457c84 --- /dev/null +++ b/doc/api/html/scaled__inv__chi__square__rng_8hpp_source.html @@ -0,0 +1,175 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/scaled_inv_chi_square_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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scaled_inv_chi_square_rng.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SCALED_INV_CHI_SQUARE_RNG_HPP
+
3 
+
4 #include <boost/random/chi_squared_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + +
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <class RNG>
+
27  inline double
+
28  scaled_inv_chi_square_rng(const double nu,
+
29  const double s,
+
30  RNG& rng) {
+
31  using boost::variate_generator;
+
32  using boost::random::chi_squared_distribution;
+
33 
+
34  static const char* function("stan::math::scaled_inv_chi_square_rng");
+
35 
+ +
37 
+
38  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
39  check_positive_finite(function, "Scale parameter", s);
+
40 
+
41  variate_generator<RNG&, chi_squared_distribution<> >
+
42  chi_square_rng(rng, chi_squared_distribution<>(nu));
+
43  return nu * s / chi_square_rng();
+
44  }
+
45  }
+
46 }
+
47 #endif
+ +
double scaled_inv_chi_square_rng(const double nu, const double s, RNG &rng)
+ +
double chi_square_rng(const double nu, RNG &rng)
+ + + + + + + + + + + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
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segment.hpp File Reference
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::segment (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t i, size_t n)
 Return the specified number of elements as a vector starting from the specified element - 1 of the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::segment (const Eigen::Matrix< T, 1, Eigen::Dynamic > &v, size_t i, size_t n)
 
template<typename T >
std::vector< T > stan::math::segment (const std::vector< T > &sv, size_t i, size_t n)
 
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diff --git a/doc/api/html/segment_8hpp_source.html b/doc/api/html/segment_8hpp_source.html new file mode 100644 index 00000000000..18cabe8455e --- /dev/null +++ b/doc/api/html/segment_8hpp_source.html @@ -0,0 +1,181 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/segment.hpp Source File + + + + + + + + + + +
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segment.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SEGMENT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SEGMENT_HPP
+
3 
+ + + +
7 #include <vector>
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
16  template <typename T>
+
17  inline
+
18  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
19  segment(const Eigen::Matrix<T, Eigen::Dynamic, 1>& v,
+
20  size_t i, size_t n) {
+
21  stan::math::check_greater("segment", "n", i, 0.0);
+
22  stan::math::check_less_or_equal("segment", "n", i,
+
23  static_cast<size_t>(v.rows()));
+
24  if (n != 0) {
+
25  stan::math::check_greater("segment", "n", i+n-1, 0.0);
+
26  stan::math::check_less_or_equal("segment", "n", i+n-1,
+
27  static_cast<size_t>(v.rows()));
+
28  }
+
29  return v.segment(i-1, n);
+
30  }
+
31 
+
32  template <typename T>
+
33  inline
+
34  Eigen::Matrix<T, 1, Eigen::Dynamic>
+
35  segment(const Eigen::Matrix<T, 1, Eigen::Dynamic>& v,
+
36  size_t i, size_t n) {
+
37  stan::math::check_greater("segment", "n", i, 0.0);
+
38  stan::math::check_less_or_equal("segment", "n", i,
+
39  static_cast<size_t>(v.cols()));
+
40  if (n != 0) {
+
41  stan::math::check_greater("segment", "n", i+n-1, 0.0);
+
42  stan::math::check_less_or_equal("segment", "n", i + n - 1,
+
43  static_cast<size_t>(v.cols()));
+
44  }
+
45 
+
46  return v.segment(i-1, n);
+
47  }
+
48 
+
49 
+
50  template <typename T>
+
51  std::vector<T>
+
52  segment(const std::vector<T>& sv,
+
53  size_t i, size_t n) {
+
54  stan::math::check_greater("segment", "i", i, 0.0);
+
55  stan::math::check_less_or_equal("segment", "i", i, sv.size());
+
56  if (n != 0) {
+
57  stan::math::check_greater("segment", "i+n-1", i + n - 1, 0.0);
+
58  stan::math::check_less_or_equal("segment", "i+n-1", i + n - 1,
+
59  static_cast<size_t>(sv.size()));
+
60  }
+
61  std::vector<T> s;
+
62  for (size_t j = 0; j < n; ++j)
+
63  s.push_back(sv[i + j - 1]);
+
64  return s;
+
65  }
+
66 
+
67  }
+
68 }
+
69 #endif
+ + + + +
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > segment(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t i, size_t n)
Return the specified number of elements as a vector starting from the specified element - 1 of the sp...
Definition: segment.hpp:19
+
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
+
+
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diff --git a/doc/api/html/seq__view_8hpp.html b/doc/api/html/seq__view_8hpp.html new file mode 100644 index 00000000000..96c992c0c0f --- /dev/null +++ b/doc/api/html/seq__view_8hpp.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/seq_view.hpp File Reference + + + + + + + + + + +
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+ + + + + + + +
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diff --git a/doc/api/html/seq__view_8hpp_source.html b/doc/api/html/seq__view_8hpp_source.html new file mode 100644 index 00000000000..547944854e1 --- /dev/null +++ b/doc/api/html/seq__view_8hpp_source.html @@ -0,0 +1,346 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/meta/seq_view.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_META_SEQ_VIEW_HPP
+
2 #define STAN_MATH_PRIM_MAT_META_SEQ_VIEW_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+
11 
+
12  template <typename T>
+
13  struct store_type {
+
14  typedef const T& type;
+
15  };
+
16  template <>
+
17  struct store_type<double> {
+
18  typedef const double type;
+
19  };
+
20  template <>
+
21  struct store_type<int> {
+
22  typedef const int type;
+
23  };
+
24 
+
25 
+
26  template <typename T>
+
27  struct pass_type {
+
28  typedef const T& type;
+
29  };
+
30  template <>
+
31  struct pass_type<double> {
+
32  typedef double type;
+
33  };
+
34  template <>
+
35  struct pass_type<int> {
+
36  typedef int type;
+
37  };
+
38 
+
39 
+
40  // S assignable to T
+
41  template <typename T, typename S>
+
42  class seq_view {
+
43  private:
+
44  typename store_type<S>::type x_;
+
45  public:
+
46  explicit seq_view(typename pass_type<S>::type x)
+
47  : x_(x) {
+
48  }
+
49  inline typename pass_type<T>::type
+
50  operator[](int n) const {
+
51  return x_;
+
52  }
+
53  int size() const {
+
54  return 1;
+
55  }
+
56  };
+
57 
+
58  template <typename T, typename S>
+
59  class seq_view<T, Eigen::Matrix<S, Eigen::Dynamic, 1> > {
+
60  private:
+ +
62  public:
+
63  explicit seq_view(typename
+
64  pass_type<Eigen::Matrix<S, Eigen::Dynamic, 1> >::type x)
+
65  : x_(x) {
+
66  }
+
67  inline typename pass_type<T>::type
+
68  operator[](int n) const {
+
69  return x_(n);
+
70  }
+
71  int size() const {
+
72  return x_.size();
+
73  }
+
74  };
+
75 
+
76 
+
77  template <typename T, typename S>
+
78  class seq_view<T, Eigen::Matrix<S, 1, Eigen::Dynamic> > {
+
79  private:
+ +
81  public:
+
82  explicit seq_view(typename pass_type
+
83  <Eigen::Matrix<S, 1, Eigen::Dynamic> >::type x)
+
84  : x_(x) {
+
85  }
+
86  inline typename pass_type<T>::type
+
87  operator[](int n) const {
+
88  return x_(n);
+
89  }
+
90  int size() const {
+
91  return x_.size();
+
92  }
+
93  };
+
94 
+
95 
+
96 
+
97  // row-major order of returns to match std::vector
+
98  template <typename T, typename S>
+
99  class seq_view<T, Eigen::Matrix<S, Eigen::Dynamic, Eigen::Dynamic> > {
+
100  private:
+
101  typename store_type<Eigen::Matrix
+
102  <S, Eigen::Dynamic, Eigen::Dynamic> >::type x_;
+
103  public:
+
104  explicit
+
105  seq_view(typename pass_type<Eigen::Matrix
+
106  <S, Eigen::Dynamic, Eigen::Dynamic> >::type x)
+
107  : x_(x) {
+
108  }
+
109  inline typename pass_type<T>::type
+
110  operator[](int n) const {
+
111  return x_(n / x_.cols(), n % x_.cols());
+
112  }
+
113  int size() const {
+
114  return x_.size();
+
115  }
+
116  };
+
117 
+
118  // question is how expensive the ctor is
+
119  template <typename T, typename S>
+
120  class seq_view<T, std::vector<S> > {
+
121  private:
+
122  typename store_type<std::vector<S> >::type x_;
+
123  const size_t elt_size_;
+
124  public:
+
125  explicit seq_view(typename pass_type<std::vector<S> >::type x)
+
126  : x_(x),
+
127  elt_size_(x_.size() == 0 ? 0 : seq_view<T, S>(x_[0]).size()) {
+
128  }
+
129  inline typename pass_type<T>::type
+
130  operator[](int n) const {
+
131  return seq_view<T, S>(x_[n / elt_size_])[n % elt_size_];
+
132  }
+
133  int size() const {
+
134  return x_.size() * elt_size_;
+
135  }
+
136  };
+
137 
+
138  // BELOW HERE JUST FOR EFFICIENCY
+
139 
+
140  template <typename T>
+
141  class seq_view<T, std::vector<T> > {
+
142  private:
+
143  typename store_type<std::vector<T> >::type x_;
+
144  public:
+
145  explicit seq_view(typename pass_type<std::vector<T> >::type x)
+
146  : x_(x) {
+
147  }
+
148  inline typename pass_type<T>::type
+
149  operator[](int n) const {
+
150  return x_[n];
+
151  }
+
152  int size() const {
+
153  return x_.size();
+
154  }
+
155  };
+
156 
+
157  // if vector of S with S assignable to T, also works
+
158  // use enable_if? (and disable_if for the general case)
+
159  template <typename T>
+
160  class seq_view<T, std::vector<std::vector<T> > > {
+
161  private:
+
162  typename store_type<std::vector<std::vector<T> > >::type x_;
+
163  const size_t cols_;
+
164  public:
+
165  explicit seq_view(typename pass_type
+
166  <std::vector<std::vector<T> > >::type x)
+
167  : x_(x),
+
168  cols_(x_.size() == 0 ? 0 : x_[0].size()) { }
+
169  inline typename pass_type<T>::type
+
170  operator[](int n) const {
+
171  return x_[n / cols_][n % cols_];
+
172  }
+
173  int size() const {
+
174  return x_.size() * cols_;
+
175  }
+
176  };
+
177 
+
178  template <>
+
179  class seq_view<double, std::vector<int> > {
+
180  private:
+
181  store_type<std::vector<int> >::type x_;
+
182  public:
+
183  explicit seq_view(pass_type<std::vector<int> >::type x)
+
184  : x_(x) {
+
185  }
+
186  inline pass_type<double>::type operator[](int n) const {
+
187  return x_[n];
+
188  }
+
189  int size() const {
+
190  return x_.size();
+
191  }
+
192  };
+
193 
+
194 
+
195 
+
196 
+
197  }
+
198 }
+
199 
+
200 #endif
+ +
pass_type< T >::type operator[](int n) const
Definition: seq_view.hpp:130
+
int size() const
Definition: seq_view.hpp:53
+ + + + +
seq_view(typename pass_type< Eigen::Matrix< S, 1, Eigen::Dynamic > >::type x)
Definition: seq_view.hpp:82
+
seq_view(typename pass_type< S >::type x)
Definition: seq_view.hpp:46
+
(Expert) Numerical traits for algorithmic differentiation variables.
+ + + + +
seq_view(typename pass_type< Eigen::Matrix< S, Eigen::Dynamic, 1 > >::type x)
Definition: seq_view.hpp:63
+ + +
pass_type< double >::type operator[](int n) const
Definition: seq_view.hpp:186
+
seq_view(typename pass_type< std::vector< S > >::type x)
Definition: seq_view.hpp:125
+ +
seq_view(pass_type< std::vector< int > >::type x)
Definition: seq_view.hpp:183
+ + +
seq_view(typename pass_type< std::vector< std::vector< T > > >::type x)
Definition: seq_view.hpp:165
+ +
pass_type< T >::type operator[](int n) const
Definition: seq_view.hpp:149
+ + + + + +
seq_view(typename pass_type< Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >::type x)
Definition: seq_view.hpp:105
+ + + +
seq_view(typename pass_type< std::vector< T > >::type x)
Definition: seq_view.hpp:145
+
pass_type< T >::type operator[](int n) const
Definition: seq_view.hpp:50
+
+
+
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diff --git a/doc/api/html/set__zero__all__adjoints_8hpp.html b/doc/api/html/set__zero__all__adjoints_8hpp.html new file mode 100644 index 00000000000..b04b326dc59 --- /dev/null +++ b/doc/api/html/set__zero__all__adjoints_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/core/set_zero_all_adjoints.hpp File Reference + + + + + + + + + + +
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static void stan::math::set_zero_all_adjoints ()
 Reset all adjoint values in the stack to zero. More...
 
+
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+
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diff --git a/doc/api/html/set__zero__all__adjoints_8hpp_source.html b/doc/api/html/set__zero__all__adjoints_8hpp_source.html new file mode 100644 index 00000000000..bc9eb03816f --- /dev/null +++ b/doc/api/html/set__zero__all__adjoints_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/set_zero_all_adjoints.hpp Source File + + + + + + + + + + +
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set_zero_all_adjoints.hpp
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1 #ifndef STAN_MATH_REV_CORE_SET_ZERO_ALL_ADJOINTS_HPP
+
2 #define STAN_MATH_REV_CORE_SET_ZERO_ALL_ADJOINTS_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
14  static void set_zero_all_adjoints() {
+
15  for (size_t i = 0; i < ChainableStack::var_stack_.size(); ++i)
+
16  ChainableStack::var_stack_[i]->set_zero_adjoint();
+
17  for (size_t i = 0; i < ChainableStack::var_nochain_stack_.size(); ++i)
+
18  ChainableStack::var_nochain_stack_[i]->set_zero_adjoint();
+
19  }
+
20 
+
21  }
+
22 }
+
23 #endif
+ + +
static void set_zero_all_adjoints()
Reset all adjoint values in the stack to zero.
+
static std::vector< ChainableT * > var_nochain_stack_
+ + +
static std::vector< ChainableT * > var_stack_
+
+
+
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diff --git a/doc/api/html/set__zero__all__adjoints__nested_8hpp.html b/doc/api/html/set__zero__all__adjoints__nested_8hpp.html new file mode 100644 index 00000000000..5da686e0837 --- /dev/null +++ b/doc/api/html/set__zero__all__adjoints__nested_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/rev/core/set_zero_all_adjoints_nested.hpp File Reference + + + + + + + + + + +
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static void stan::math::set_zero_all_adjoints_nested ()
 Reset all adjoint values in the top nested portion of the stack to zero. More...
 
+
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+
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diff --git a/doc/api/html/set__zero__all__adjoints__nested_8hpp_source.html b/doc/api/html/set__zero__all__adjoints__nested_8hpp_source.html new file mode 100644 index 00000000000..d7be7758c8e --- /dev/null +++ b/doc/api/html/set__zero__all__adjoints__nested_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/rev/core/set_zero_all_adjoints_nested.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_SET_ZERO_ALL_ADJOINTS_NESTED_HPP
+
2 #define STAN_MATH_REV_CORE_SET_ZERO_ALL_ADJOINTS_NESTED_HPP
+
3 
+ + + + +
8 #include <stdexcept>
+
9 
+
10 namespace stan {
+
11  namespace math {
+
12 
+ +
18  if (empty_nested())
+
19  throw std::logic_error("empty_nested() must be false before calling"
+
20  " set_zero_all_adjoints_nested()");
+
21  size_t start1 = ChainableStack::nested_var_stack_sizes_.back();
+
22  // avoid wrap with unsigned when start1 == 0
+
23  for (size_t i = (start1 == 0U) ? 0U : (start1 - 1);
+
24  i < ChainableStack::var_stack_.size(); ++i)
+
25  ChainableStack::var_stack_[i]->set_zero_adjoint();
+
26 
+ +
28  for (size_t i = (start2 == 0U) ? 0U : (start2 - 1);
+
29  i < ChainableStack::var_nochain_stack_.size(); ++i) {
+
30  ChainableStack::var_nochain_stack_[i]->set_zero_adjoint();
+
31  }
+
32  }
+
33 
+
34  }
+
35 }
+
36 #endif
+
static bool empty_nested()
Return true if there is no nested autodiff being executed.
+ + +
static void set_zero_all_adjoints_nested()
Reset all adjoint values in the top nested portion of the stack to zero.
+ +
static std::vector< ChainableT * > var_nochain_stack_
+
static std::vector< size_t > nested_var_nochain_stack_sizes_
+ +
static std::vector< size_t > nested_var_stack_sizes_
+ +
static std::vector< ChainableT * > var_stack_
+
+
+
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diff --git a/doc/api/html/sign_8hpp.html b/doc/api/html/sign_8hpp.html new file mode 100644 index 00000000000..38b17f1fb6b --- /dev/null +++ b/doc/api/html/sign_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/sign.hpp File Reference + + + + + + + + + + +
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template<typename T >
int stan::math::sign (const T &z)
 
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diff --git a/doc/api/html/sign_8hpp_source.html b/doc/api/html/sign_8hpp_source.html new file mode 100644 index 00000000000..dc88a7a1d0c --- /dev/null +++ b/doc/api/html/sign_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/sign.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_SIGN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_SIGN_HPP
+
3 
+
4 namespace stan {
+
5  namespace math {
+
6 
+
7  // returns 1 if NaN is passed in.
+
8  template<typename T>
+
9  inline int sign(const T& z) {
+
10  return (z == 0) ? 0 : z < 0 ? -1 : 1;
+
11  }
+
12  }
+
13 }
+
14 
+
15 #endif
+
16 
+ +
int sign(const T &z)
Definition: sign.hpp:9
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diff --git a/doc/api/html/simplex__constrain_8hpp.html b/doc/api/html/simplex__constrain_8hpp.html new file mode 100644 index 00000000000..2aab899f15f --- /dev/null +++ b/doc/api/html/simplex__constrain_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/simplex_constrain.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::simplex_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
 Return the simplex corresponding to the specified free vector. More...
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::simplex_constrain (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y, T &lp)
 Return the simplex corresponding to the specified free vector and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
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diff --git a/doc/api/html/simplex__constrain_8hpp_source.html b/doc/api/html/simplex__constrain_8hpp_source.html new file mode 100644 index 00000000000..fca6eba111d --- /dev/null +++ b/doc/api/html/simplex__constrain_8hpp_source.html @@ -0,0 +1,202 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/simplex_constrain.hpp Source File + + + + + + + + + + +
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+
+
simplex_constrain.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_SIMPLEX_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SIMPLEX_CONSTRAIN_HPP
+
3 
+ + + + + + +
10 #include <cmath>
+
11 
+
12 namespace stan {
+
13 
+
14  namespace math {
+
15 
+
28  template <typename T>
+
29  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
30  simplex_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& y) {
+
31  // cut & paste simplex_constrain(Eigen::Matrix, T) w/o Jacobian
+
32  using Eigen::Matrix;
+
33  using Eigen::Dynamic;
+ + +
36  using stan::math::logit;
+
37  using stan::math::log1m;
+
38  using std::log;
+
39  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
40 
+
41 
+
42  int Km1 = y.size();
+
43  Matrix<T, Dynamic, 1> x(Km1 + 1);
+
44  T stick_len(1.0);
+
45  for (size_type k = 0; k < Km1; ++k) {
+
46  T z_k(inv_logit(y(k) - log(Km1 - k)));
+
47  x(k) = stick_len * z_k;
+
48  stick_len -= x(k);
+
49  }
+
50  x(Km1) = stick_len;
+
51  return x;
+
52  }
+
53 
+
67  template <typename T>
+
68  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
69  simplex_constrain(const Eigen::Matrix<T, Eigen::Dynamic, 1>& y,
+
70  T& lp) {
+
71  using Eigen::Dynamic;
+
72  using Eigen::Matrix;
+ + +
75  using stan::math::logit;
+
76  using stan::math::log1m;
+ +
78  using std::log;
+
79 
+
80  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
81 
+
82  int Km1 = y.size(); // K = Km1 + 1
+
83  Matrix<T, Dynamic, 1> x(Km1 + 1);
+
84  T stick_len(1.0);
+
85  for (size_type k = 0; k < Km1; ++k) {
+
86  double eq_share = -log(Km1 - k); // = logit(1.0/(Km1 + 1 - k));
+
87  T adj_y_k(y(k) + eq_share);
+
88  T z_k(inv_logit(adj_y_k));
+
89  x(k) = stick_len * z_k;
+
90  lp += log(stick_len);
+
91  lp -= log1p_exp(-adj_y_k);
+
92  lp -= log1p_exp(adj_y_k);
+
93  stick_len -= x(k); // equivalently *= (1 - z_k);
+
94  }
+
95  x(Km1) = stick_len; // no Jacobian contrib for last dim
+
96  return x;
+
97  }
+
98 
+
99  }
+
100 
+
101 }
+
102 
+
103 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
fvar< T > inv_logit(const fvar< T > &x)
Definition: inv_logit.hpp:15
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + + +
fvar< T > logit(const fvar< T > &x)
Definition: logit.hpp:17
+ +
fvar< T > log1p_exp(const fvar< T > &x)
Definition: log1p_exp.hpp:13
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > simplex_constrain(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &y)
Return the simplex corresponding to the specified free vector.
+ + +
fvar< T > log1m(const fvar< T > &x)
Definition: log1m.hpp:16
+
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diff --git a/doc/api/html/simplex__free_8hpp.html b/doc/api/html/simplex__free_8hpp.html new file mode 100644 index 00000000000..f09f5903305 --- /dev/null +++ b/doc/api/html/simplex__free_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/simplex_free.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::simplex_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 Return an unconstrained vector that when transformed produces the specified simplex. More...
 
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diff --git a/doc/api/html/simplex__free_8hpp_source.html b/doc/api/html/simplex__free_8hpp_source.html new file mode 100644 index 00000000000..5c84ada2db2 --- /dev/null +++ b/doc/api/html/simplex__free_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/simplex_free.hpp Source File + + + + + + + + + + +
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simplex_free.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SIMPLEX_FREE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SIMPLEX_FREE_HPP
+
3 
+ + + + +
8 #include <cmath>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
28  template <typename T>
+
29  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
30  simplex_free(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x) {
+
31  using Eigen::Dynamic;
+
32  using Eigen::Matrix;
+ +
34  using stan::math::logit;
+
35  using std::log;
+
36 
+
37  typedef typename index_type<Matrix<T, Dynamic, 1> >::type size_type;
+
38 
+
39  stan::math::check_simplex("stan::math::simplex_free",
+
40  "Simplex variable", x);
+
41  int Km1 = x.size() - 1;
+
42  Eigen::Matrix<T, Eigen::Dynamic, 1> y(Km1);
+
43  T stick_len(x(Km1));
+
44  for (size_type k = Km1; --k >= 0; ) {
+
45  stick_len += x(k);
+
46  T z_k(x(k) / stick_len);
+
47  y(k) = logit(z_k) + log(Km1 - k);
+
48  // note: log(Km1 - k) = logit(1.0 / (Km1 + 1 - k));
+
49  }
+
50  return y;
+
51  }
+
52 
+
53  }
+
54 
+
55 }
+
56 
+
57 #endif
+ + +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Definition: typedefs.hpp:13
+
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
fvar< T > logit(const fvar< T > &x)
Definition: logit.hpp:17
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > simplex_free(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
Return an unconstrained vector that when transformed produces the specified simplex.
+
bool check_simplex(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is simplex.
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/singular__values_8hpp.html b/doc/api/html/singular__values_8hpp.html new file mode 100644 index 00000000000..1ef549dff2e --- /dev/null +++ b/doc/api/html/singular__values_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/singular_values.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::singular_values (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Return the vector of the singular values of the specified matrix in decreasing order of magnitude. More...
 
+
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diff --git a/doc/api/html/singular__values_8hpp_source.html b/doc/api/html/singular__values_8hpp_source.html new file mode 100644 index 00000000000..6367f8f7ab3 --- /dev/null +++ b/doc/api/html/singular__values_8hpp_source.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/singular_values.hpp Source File + + + + + + + + + + +
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singular_values.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SINGULAR_VALUES_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SINGULAR_VALUES_HPP
+
3 
+
4 // NOTE: if using this with rev mode, include numeric_limits
+
5 // or else this seg-faults.
+ +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
19  template <typename T>
+
20  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
21  singular_values(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
22  return Eigen::JacobiSVD
+
23  <Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >(m).singularValues();
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+ +
Eigen::Matrix< T, Eigen::Dynamic, 1 > singular_values(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Return the vector of the singular values of the specified matrix in decreasing order of magnitude...
+ +
+
+
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diff --git a/doc/api/html/size_8hpp.html b/doc/api/html/size_8hpp.html new file mode 100644 index 00000000000..b1ccf1e5d29 --- /dev/null +++ b/doc/api/html/size_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/size.hpp File Reference + + + + + + + + + + +
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template<typename T >
int stan::math::size (const std::vector< T > &x)
 Return the size of the specified standard vector. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/size_8hpp_source.html b/doc/api/html/size_8hpp_source.html new file mode 100644 index 00000000000..73c66a87831 --- /dev/null +++ b/doc/api/html/size_8hpp_source.html @@ -0,0 +1,127 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/size.hpp Source File + + + + + + + + + + +
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size.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SIZE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SIZE_HPP
+
3 
+
4 #include <vector>
+
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
16  template <typename T>
+
17  inline int size(const std::vector<T>& x) {
+
18  return static_cast<int>(x.size());
+
19  }
+
20 
+
21  }
+
22 }
+
23 #endif
+ +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
+
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diff --git a/doc/api/html/size__of_8hpp.html b/doc/api/html/size__of_8hpp.html new file mode 100644 index 00000000000..29e7311b0c7 --- /dev/null +++ b/doc/api/html/size__of_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/size_of.hpp File Reference + + + + + + + + + + +
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size_of.hpp File Reference
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#include <stan/math/prim/scal/meta/is_vector.hpp>
+#include <cstddef>
+
+

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struct  stan::size_of_helper< T, is_vec >
 
struct  stan::size_of_helper< T, true >
 
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template<typename T >
size_t stan::size_of (const T &x)
 
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diff --git a/doc/api/html/size__of_8hpp_source.html b/doc/api/html/size__of_8hpp_source.html new file mode 100644 index 00000000000..e4c417b8a6b --- /dev/null +++ b/doc/api/html/size__of_8hpp_source.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/meta/size_of.hpp Source File + + + + + + + + + + +
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size_of.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_META_SIZE_OF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_META_SIZE_OF_HPP
+
3 
+ +
5 #include <cstddef>
+
6 
+
7 namespace stan {
+
8 
+
9  template<typename T, bool is_vec>
+
10  struct size_of_helper {
+
11  static size_t size_of(const T& /*x*/) {
+
12  return 1U;
+
13  }
+
14  };
+
15 
+
16  template<typename T>
+
17  struct size_of_helper<T, true> {
+
18  static size_t size_of(const T& x) {
+
19  return x.size();
+
20  }
+
21  };
+
22 
+
23  template <typename T>
+
24  size_t size_of(const T& x) {
+ +
26  }
+
27 
+
28 }
+
29 #endif
+
30 
+
static size_t size_of(const T &)
Definition: size_of.hpp:11
+ +
static size_t size_of(const T &x)
Definition: size_of.hpp:18
+ + +
size_t size_of(const T &x)
Definition: size_of.hpp:24
+
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diff --git a/doc/api/html/skew__normal__ccdf__log_8hpp.html b/doc/api/html/skew__normal__ccdf__log_8hpp.html new file mode 100644 index 00000000000..ab40df5a4c5 --- /dev/null +++ b/doc/api/html/skew__normal__ccdf__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::skew_normal_ccdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
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diff --git a/doc/api/html/skew__normal__ccdf__log_8hpp_source.html b/doc/api/html/skew__normal__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..b6d3509d16b --- /dev/null +++ b/doc/api/html/skew__normal__ccdf__log_8hpp_source.html @@ -0,0 +1,266 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_ccdf_log.hpp Source File + + + + + + + + + + +
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skew_normal_ccdf_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + +
17 #include <boost/random/variate_generator.hpp>
+
18 #include <boost/math/distributions.hpp>
+
19 #include <cmath>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
26  typename return_type<T_y, T_loc, T_scale, T_shape>::type
+
27  skew_normal_ccdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
28  const T_shape& alpha) {
+
29  static const char* function("stan::math::skew_normal_ccdf_log");
+
30  typedef typename stan::partials_return_type<T_y, T_loc, T_scale,
+
31  T_shape>::type
+
32  T_partials_return;
+
33 
+ + + + +
38  using stan::math::owens_t;
+ +
40 
+
41  T_partials_return ccdf_log(0.0);
+
42 
+
43  // check if any vectors are zero length
+
44  if (!(stan::length(y)
+
45  && stan::length(mu)
+
46  && stan::length(sigma)
+
47  && stan::length(alpha)))
+
48  return ccdf_log;
+
49 
+
50  check_not_nan(function, "Random variable", y);
+
51  check_finite(function, "Location parameter", mu);
+
52  check_not_nan(function, "Scale parameter", sigma);
+
53  check_positive(function, "Scale parameter", sigma);
+
54  check_finite(function, "Shape parameter", alpha);
+
55  check_not_nan(function, "Shape parameter", alpha);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Location parameter", mu,
+
59  "Scale parameter", sigma,
+
60  "Shape paramter", alpha);
+
61 
+ +
63  operands_and_partials(y, mu, sigma, alpha);
+
64 
+
65  using stan::math::SQRT_2;
+
66  using stan::math::pi;
+
67  using std::log;
+
68  using std::exp;
+
69 
+
70  VectorView<const T_y> y_vec(y);
+
71  VectorView<const T_loc> mu_vec(mu);
+
72  VectorView<const T_scale> sigma_vec(sigma);
+
73  VectorView<const T_shape> alpha_vec(alpha);
+
74  size_t N = max_size(y, mu, sigma, alpha);
+
75  const double SQRT_TWO_OVER_PI = std::sqrt(2.0 / stan::math::pi());
+
76 
+
77  for (size_t n = 0; n < N; n++) {
+
78  const T_partials_return y_dbl = value_of(y_vec[n]);
+
79  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
80  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
81  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
82  const T_partials_return alpha_dbl_sq = alpha_dbl * alpha_dbl;
+
83  const T_partials_return diff = (y_dbl - mu_dbl) / sigma_dbl;
+
84  const T_partials_return diff_sq = diff * diff;
+
85  const T_partials_return scaled_diff = diff / SQRT_2;
+
86  const T_partials_return scaled_diff_sq = diff_sq * 0.5;
+
87  const T_partials_return ccdf_log_ = 1.0 - 0.5 * erfc(-scaled_diff)
+
88  + 2 * owens_t(diff, alpha_dbl);
+
89 
+
90  // ccdf_log
+
91  ccdf_log += log(ccdf_log_);
+
92 
+
93  // gradients
+
94  const T_partials_return deriv_erfc = SQRT_TWO_OVER_PI * 0.5
+
95  * exp(-scaled_diff_sq) / sigma_dbl;
+
96  const T_partials_return deriv_owens = erf(alpha_dbl * scaled_diff)
+
97  * exp(-scaled_diff_sq) / SQRT_TWO_OVER_PI / (-2.0 * pi()) / sigma_dbl;
+
98  const T_partials_return rep_deriv = (-2.0 * deriv_owens + deriv_erfc)
+
99  / ccdf_log_;
+
100 
+ +
102  operands_and_partials.d_x1[n] -= rep_deriv;
+ +
104  operands_and_partials.d_x2[n] += rep_deriv;
+ +
106  operands_and_partials.d_x3[n] += rep_deriv * diff;
+ +
108  operands_and_partials.d_x4[n] -= -2.0 * exp(-0.5 * diff_sq
+
109  * (1.0 + alpha_dbl_sq))
+
110  / ((1 + alpha_dbl_sq) * 2.0 * pi()) / ccdf_log_;
+
111  }
+
112 
+
113  return operands_and_partials.value(ccdf_log);
+
114  }
+
115  }
+
116 }
+
117 #endif
+
118 
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ +
fvar< T > owens_t(const fvar< T > &x1, const fvar< T > &x2)
Definition: owens_t.hpp:14
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_ccdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/skew__normal__cdf_8hpp.html b/doc/api/html/skew__normal__cdf_8hpp.html new file mode 100644 index 00000000000..d7f5db3e6e7 --- /dev/null +++ b/doc/api/html/skew__normal__cdf_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
skew_normal_cdf.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::skew_normal_cdf (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/skew__normal__cdf_8hpp_source.html b/doc/api/html/skew__normal__cdf_8hpp_source.html new file mode 100644 index 00000000000..f668d0df165 --- /dev/null +++ b/doc/api/html/skew__normal__cdf_8hpp_source.html @@ -0,0 +1,282 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
skew_normal_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_CDF_HPP
+
3 
+ + + + + + + + + + + + + +
17 #include <boost/random/variate_generator.hpp>
+
18 #include <boost/math/distributions.hpp>
+
19 #include <cmath>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
26  typename return_type<T_y, T_loc, T_scale, T_shape>::type
+
27  skew_normal_cdf(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
28  const T_shape& alpha) {
+
29  static const char* function("stan::math::skew_normal_cdf");
+
30  typedef typename stan::partials_return_type<T_y, T_loc, T_scale,
+
31  T_shape>::type
+
32  T_partials_return;
+
33 
+ + + + +
38  using stan::math::owens_t;
+ +
40 
+
41  T_partials_return cdf(1.0);
+
42 
+
43  // check if any vectors are zero length
+
44  if (!(stan::length(y)
+
45  && stan::length(mu)
+
46  && stan::length(sigma)
+
47  && stan::length(alpha)))
+
48  return cdf;
+
49 
+
50  check_not_nan(function, "Random variable", y);
+
51  check_finite(function, "Location parameter", mu);
+
52  check_not_nan(function, "Scale parameter", sigma);
+
53  check_positive(function, "Scale parameter", sigma);
+
54  check_finite(function, "Shape parameter", alpha);
+
55  check_not_nan(function, "Shape parameter", alpha);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Location parameter", mu,
+
59  "Scale parameter", sigma,
+
60  "Shape paramter", alpha);
+
61 
+ +
63  operands_and_partials(y, mu, sigma, alpha);
+
64 
+
65  using stan::math::SQRT_2;
+
66  using stan::math::pi;
+
67  using std::exp;
+
68 
+
69  VectorView<const T_y> y_vec(y);
+
70  VectorView<const T_loc> mu_vec(mu);
+
71  VectorView<const T_scale> sigma_vec(sigma);
+
72  VectorView<const T_shape> alpha_vec(alpha);
+
73  size_t N = max_size(y, mu, sigma, alpha);
+
74  const double SQRT_TWO_OVER_PI = std::sqrt(2.0 / stan::math::pi());
+
75 
+
76  for (size_t n = 0; n < N; n++) {
+
77  const T_partials_return y_dbl = value_of(y_vec[n]);
+
78  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
79  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
80  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
81  const T_partials_return alpha_dbl_sq = alpha_dbl * alpha_dbl;
+
82  const T_partials_return diff = (y_dbl - mu_dbl) / sigma_dbl;
+
83  const T_partials_return diff_sq = diff * diff;
+
84  const T_partials_return scaled_diff = diff / SQRT_2;
+
85  const T_partials_return scaled_diff_sq = diff_sq * 0.5;
+
86  const T_partials_return cdf_ = 0.5 * erfc(-scaled_diff) - 2
+
87  * owens_t(diff, alpha_dbl);
+
88 
+
89  // cdf
+
90  cdf *= cdf_;
+
91 
+
92  // gradients
+
93  const T_partials_return deriv_erfc = SQRT_TWO_OVER_PI * 0.5
+
94  * exp(-scaled_diff_sq)
+
95  / sigma_dbl;
+
96  const T_partials_return deriv_owens = erf(alpha_dbl * scaled_diff)
+
97  * exp(-scaled_diff_sq) / SQRT_TWO_OVER_PI / (-2.0 * pi()) / sigma_dbl;
+
98  const T_partials_return rep_deriv = (-2.0 * deriv_owens + deriv_erfc)
+
99  / cdf_;
+
100 
+ +
102  operands_and_partials.d_x1[n] += rep_deriv;
+ +
104  operands_and_partials.d_x2[n] -= rep_deriv;
+ +
106  operands_and_partials.d_x3[n] -= rep_deriv * diff;
+ +
108  operands_and_partials.d_x4[n] += -2.0 * exp(-0.5 * diff_sq
+
109  * (1.0 + alpha_dbl_sq))
+
110  / ((1 + alpha_dbl_sq) * 2.0 * pi()) / cdf_;
+
111  }
+
112 
+ +
114  for (size_t n = 0; n < stan::length(y); ++n)
+
115  operands_and_partials.d_x1[n] *= cdf;
+
116  }
+ +
118  for (size_t n = 0; n < stan::length(mu); ++n)
+
119  operands_and_partials.d_x2[n] *= cdf;
+
120  }
+ +
122  for (size_t n = 0; n < stan::length(sigma); ++n)
+
123  operands_and_partials.d_x3[n] *= cdf;
+
124  }
+ +
126  for (size_t n = 0; n < stan::length(alpha); ++n)
+
127  operands_and_partials.d_x4[n] *= cdf;
+
128  }
+
129 
+
130  return operands_and_partials.value(cdf);
+
131  }
+
132  }
+
133 }
+
134 #endif
+
135 
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_cdf(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ +
fvar< T > owens_t(const fvar< T > &x1, const fvar< T > &x2)
Definition: owens_t.hpp:14
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/skew__normal__cdf__log_8hpp.html b/doc/api/html/skew__normal__cdf__log_8hpp.html new file mode 100644 index 00000000000..8c5e79e4918 --- /dev/null +++ b/doc/api/html/skew__normal__cdf__log_8hpp.html @@ -0,0 +1,145 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
skew_normal_cdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::skew_normal_cdf_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/skew__normal__cdf__log_8hpp_source.html b/doc/api/html/skew__normal__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..944cc50c549 --- /dev/null +++ b/doc/api/html/skew__normal__cdf__log_8hpp_source.html @@ -0,0 +1,267 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
skew_normal_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + +
17 #include <boost/random/variate_generator.hpp>
+
18 #include <boost/math/distributions.hpp>
+
19 #include <cmath>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
26  typename return_type<T_y, T_loc, T_scale, T_shape>::type
+
27  skew_normal_cdf_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
28  const T_shape& alpha) {
+
29  static const char* function("stan::math::skew_normal_cdf_log");
+
30  typedef typename stan::partials_return_type<T_y, T_loc, T_scale,
+
31  T_shape>::type
+
32  T_partials_return;
+
33 
+ + + + + +
39  using stan::math::owens_t;
+
40 
+
41  T_partials_return cdf_log(0.0);
+
42 
+
43  // check if any vectors are zero length
+
44  if (!(stan::length(y)
+
45  && stan::length(mu)
+
46  && stan::length(sigma)
+
47  && stan::length(alpha)))
+
48  return cdf_log;
+
49 
+
50  check_not_nan(function, "Random variable", y);
+
51  check_finite(function, "Location parameter", mu);
+
52  check_not_nan(function, "Scale parameter", sigma);
+
53  check_positive(function, "Scale parameter", sigma);
+
54  check_finite(function, "Shape parameter", alpha);
+
55  check_not_nan(function, "Shape parameter", alpha);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Location parameter", mu,
+
59  "Scale parameter", sigma,
+
60  "Shape paramter", alpha);
+
61 
+
62 
+ +
64  operands_and_partials(y, mu, sigma, alpha);
+
65 
+
66  using stan::math::SQRT_2;
+
67  using stan::math::pi;
+
68  using std::log;
+
69  using std::exp;
+
70 
+
71  VectorView<const T_y> y_vec(y);
+
72  VectorView<const T_loc> mu_vec(mu);
+
73  VectorView<const T_scale> sigma_vec(sigma);
+
74  VectorView<const T_shape> alpha_vec(alpha);
+
75  size_t N = max_size(y, mu, sigma, alpha);
+
76  const double SQRT_TWO_OVER_PI = std::sqrt(2.0 / stan::math::pi());
+
77 
+
78  for (size_t n = 0; n < N; n++) {
+
79  const T_partials_return y_dbl = value_of(y_vec[n]);
+
80  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
81  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
82  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
83  const T_partials_return alpha_dbl_sq = alpha_dbl * alpha_dbl;
+
84  const T_partials_return diff = (y_dbl - mu_dbl) / sigma_dbl;
+
85  const T_partials_return diff_sq = diff * diff;
+
86  const T_partials_return scaled_diff = diff / SQRT_2;
+
87  const T_partials_return scaled_diff_sq = diff_sq * 0.5;
+
88  const T_partials_return cdf_log_ = 0.5 * erfc(-scaled_diff) - 2
+
89  * owens_t(diff, alpha_dbl);
+
90 
+
91  // cdf_log
+
92  cdf_log += log(cdf_log_);
+
93 
+
94  // gradients
+
95  const T_partials_return deriv_erfc = SQRT_TWO_OVER_PI * 0.5
+
96  * exp(-scaled_diff_sq) / sigma_dbl;
+
97  const T_partials_return deriv_owens = erf(alpha_dbl * scaled_diff)
+
98  * exp(-scaled_diff_sq) / SQRT_TWO_OVER_PI / (-2.0 * pi()) / sigma_dbl;
+
99  const T_partials_return rep_deriv = (-2.0 * deriv_owens + deriv_erfc)
+
100  / cdf_log_;
+
101 
+ +
103  operands_and_partials.d_x1[n] += rep_deriv;
+ +
105  operands_and_partials.d_x2[n] -= rep_deriv;
+ +
107  operands_and_partials.d_x3[n] -= rep_deriv * diff;
+ +
109  operands_and_partials.d_x4[n] += -2.0 * exp(-0.5 * diff_sq
+
110  * (1.0 + alpha_dbl_sq))
+
111  / ((1 + alpha_dbl_sq) * 2.0 * pi()) / cdf_log_;
+
112  }
+
113 
+
114  return operands_and_partials.value(cdf_log);
+
115  }
+
116  }
+
117 }
+
118 #endif
+
119 
+ +
VectorView< T_return_type, false, true > d_x2
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ +
fvar< T > owens_t(const fvar< T > &x1, const fvar< T > &x2)
Definition: owens_t.hpp:14
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
const double SQRT_2
The value of the square root of 2, .
Definition: constants.hpp:21
+ +
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_cdf_log(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/skew__normal__log_8hpp.html b/doc/api/html/skew__normal__log_8hpp.html new file mode 100644 index 00000000000..2b7379a8126 --- /dev/null +++ b/doc/api/html/skew__normal__log_8hpp.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::skew_normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
template<typename T_y , typename T_loc , typename T_scale , typename T_shape >
return_type< T_y, T_loc, T_scale, T_shape >::type stan::math::skew_normal_log (const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
 
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diff --git a/doc/api/html/skew__normal__log_8hpp_source.html b/doc/api/html/skew__normal__log_8hpp_source.html new file mode 100644 index 00000000000..f454c59491f --- /dev/null +++ b/doc/api/html/skew__normal__log_8hpp_source.html @@ -0,0 +1,303 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_log.hpp Source File + + + + + + + + + + +
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skew_normal_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_LOG_HPP
+
3 
+ + + + + + + + + + + + + +
17 #include <boost/random/variate_generator.hpp>
+
18 #include <boost/math/distributions.hpp>
+
19 #include <cmath>
+
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  template <bool propto,
+
26  typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
27  typename return_type<T_y, T_loc, T_scale, T_shape>::type
+
28  skew_normal_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
29  const T_shape& alpha) {
+
30  static const char* function("stan::math::skew_normal_log");
+
31  typedef typename stan::partials_return_type<T_y, T_loc,
+
32  T_scale, T_shape>::type
+
33  T_partials_return;
+
34 
+
35  using std::log;
+ + + + + + + +
43  using std::exp;
+
44 
+
45  // check if any vectors are zero length
+
46  if (!(stan::length(y)
+
47  && stan::length(mu)
+
48  && stan::length(sigma)
+
49  && stan::length(alpha)))
+
50  return 0.0;
+
51 
+
52  // set up return value accumulator
+
53  T_partials_return logp(0.0);
+
54 
+
55  // validate args (here done over var, which should be OK)
+
56  check_not_nan(function, "Random variable", y);
+
57  check_finite(function, "Location parameter", mu);
+
58  check_finite(function, "Shape parameter", alpha);
+
59  check_positive(function, "Scale parameter", sigma);
+
60  check_consistent_sizes(function,
+
61  "Random variable", y,
+
62  "Location parameter", mu,
+
63  "Scale parameter", sigma,
+
64  "Shape paramter", alpha);
+
65 
+
66  // check if no variables are involved and prop-to
+ +
68  return 0.0;
+
69 
+
70  // set up template expressions wrapping scalars into vector views
+ +
72  operands_and_partials(y, mu, sigma, alpha);
+
73 
+
74  using boost::math::erfc;
+
75  using boost::math::erf;
+
76  using std::log;
+
77 
+
78  VectorView<const T_y> y_vec(y);
+
79  VectorView<const T_loc> mu_vec(mu);
+
80  VectorView<const T_scale> sigma_vec(sigma);
+
81  VectorView<const T_shape> alpha_vec(alpha);
+
82  size_t N = max_size(y, mu, sigma, alpha);
+
83 
+ + +
86  T_partials_return, T_scale> log_sigma(length(sigma));
+
87  for (size_t i = 0; i < length(sigma); i++) {
+
88  inv_sigma[i] = 1.0 / value_of(sigma_vec[i]);
+ +
90  log_sigma[i] = log(value_of(sigma_vec[i]));
+
91  }
+
92 
+
93  for (size_t n = 0; n < N; n++) {
+
94  // pull out values of arguments
+
95  const T_partials_return y_dbl = value_of(y_vec[n]);
+
96  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
97  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
98  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
99 
+
100  // reusable subexpression values
+
101  const T_partials_return y_minus_mu_over_sigma
+
102  = (y_dbl - mu_dbl) * inv_sigma[n];
+
103  const double pi_dbl = stan::math::pi();
+
104 
+
105  // log probability
+ +
107  logp -= 0.5 * log(2.0 * pi_dbl);
+ +
109  logp -= log(sigma_dbl);
+ +
111  logp -= y_minus_mu_over_sigma * y_minus_mu_over_sigma / 2.0;
+ +
113  logp += log(erfc(-alpha_dbl * y_minus_mu_over_sigma
+
114  / std::sqrt(2.0)));
+
115 
+
116  // gradients
+
117  T_partials_return deriv_logerf
+
118  = 2.0 / std::sqrt(pi_dbl)
+
119  * exp(-alpha_dbl * y_minus_mu_over_sigma / std::sqrt(2.0)
+
120  * alpha_dbl * y_minus_mu_over_sigma / std::sqrt(2.0))
+
121  / (1 + erf(alpha_dbl * y_minus_mu_over_sigma
+
122  / std::sqrt(2.0)));
+ +
124  operands_and_partials.d_x1[n]
+
125  += -y_minus_mu_over_sigma / sigma_dbl
+
126  + deriv_logerf * alpha_dbl / (sigma_dbl * std::sqrt(2.0));
+ +
128  operands_and_partials.d_x2[n]
+
129  += y_minus_mu_over_sigma / sigma_dbl
+
130  + deriv_logerf * -alpha_dbl / (sigma_dbl * std::sqrt(2.0));
+ +
132  operands_and_partials.d_x3[n]
+
133  += -1.0 / sigma_dbl
+
134  + y_minus_mu_over_sigma * y_minus_mu_over_sigma / sigma_dbl
+
135  - deriv_logerf * y_minus_mu_over_sigma * alpha_dbl
+
136  / (sigma_dbl * std::sqrt(2.0));
+ +
138  operands_and_partials.d_x4[n]
+
139  += deriv_logerf * y_minus_mu_over_sigma / std::sqrt(2.0);
+
140  }
+
141  return operands_and_partials.value(logp);
+
142  }
+
143 
+
144  template <typename T_y, typename T_loc, typename T_scale, typename T_shape>
+
145  inline
+ +
147  skew_normal_log(const T_y& y, const T_loc& mu, const T_scale& sigma,
+
148  const T_shape& alpha) {
+
149  return skew_normal_log<false>(y, mu, sigma, alpha);
+
150  }
+
151  }
+
152 }
+
153 #endif
+
154 
+ +
VectorView< T_return_type, false, true > d_x2
+
return_type< T_y, T_loc, T_scale, T_shape >::type skew_normal_log(const T_y &y, const T_loc &mu, const T_scale &sigma, const T_shape &alpha)
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
fvar< T > erf(const fvar< T > &x)
Definition: erf.hpp:14
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > erfc(const fvar< T > &x)
Definition: erfc.hpp:14
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
VectorView< T_return_type, false, true > d_x1
+
VectorView< T_return_type, false, true > d_x4
+
+
+
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diff --git a/doc/api/html/skew__normal__rng_8hpp.html b/doc/api/html/skew__normal__rng_8hpp.html new file mode 100644 index 00000000000..292168d664b --- /dev/null +++ b/doc/api/html/skew__normal__rng_8hpp.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_rng.hpp File Reference + + + + + + + + + + +
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+ + + + +

+Functions

template<class RNG >
double stan::math::skew_normal_rng (const double mu, const double sigma, const double alpha, RNG &rng)
 
+
+
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diff --git a/doc/api/html/skew__normal__rng_8hpp_source.html b/doc/api/html/skew__normal__rng_8hpp_source.html new file mode 100644 index 00000000000..64b5af86578 --- /dev/null +++ b/doc/api/html/skew__normal__rng_8hpp_source.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/skew_normal_rng.hpp Source File + + + + + + + + + + +
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skew_normal_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_SKEW_NORMAL_RNG_HPP
+
3 
+
4 #include <boost/random/variate_generator.hpp>
+
5 #include <boost/math/distributions.hpp>
+ + + + + + + + + +
15 
+
16 namespace stan {
+
17 
+
18  namespace math {
+
19 
+
20  template <class RNG>
+
21  inline double
+
22  skew_normal_rng(const double mu,
+
23  const double sigma,
+
24  const double alpha,
+
25  RNG& rng) {
+
26  boost::math::skew_normal_distribution<> dist(mu, sigma, alpha);
+
27 
+
28  static const char* function("stan::math::skew_normal_rng");
+
29 
+ + +
32 
+
33  check_finite(function, "Location parameter", mu);
+
34  check_finite(function, "Shape parameter", alpha);
+
35  check_positive(function, "Scale parameter", sigma);
+
36 
+
37  return quantile(dist, stan::math::uniform_rng(0.0, 1.0, rng));
+
38  }
+
39  }
+
40 }
+
41 #endif
+
42 
+ + + +
double skew_normal_rng(const double mu, const double sigma, const double alpha, RNG &rng)
+ + +
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+ +
double uniform_rng(const double alpha, const double beta, RNG &rng)
Definition: uniform_rng.hpp:21
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + +
double dist(const std::vector< double > &x, const std::vector< double > &y)
Definition: dist.hpp:11
+ +
+
+
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diff --git a/doc/api/html/sort_8hpp.html b/doc/api/html/sort_8hpp.html new file mode 100644 index 00000000000..180ae69aab0 --- /dev/null +++ b/doc/api/html/sort_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sort.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+#include <algorithm>
+#include <functional>
+
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template<typename T >
std::vector< T > stan::math::sort_asc (std::vector< T > xs)
 Return the specified standard vector in ascending order. More...
 
template<typename T >
std::vector< T > stan::math::sort_desc (std::vector< T > xs)
 Return the specified standard vector in descending order. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > stan::math::sort_asc (Eigen::Matrix< T, R, C > xs)
 Return the specified eigen vector in ascending order. More...
 
template<typename T , int R, int C>
Eigen::Matrix< T, R, C > stan::math::sort_desc (Eigen::Matrix< T, R, C > xs)
 Return the specified eigen vector in descending order. More...
 
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diff --git a/doc/api/html/sort_8hpp_source.html b/doc/api/html/sort_8hpp_source.html new file mode 100644 index 00000000000..59aed6c7e90 --- /dev/null +++ b/doc/api/html/sort_8hpp_source.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sort.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SORT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SORT_HPP
+
3 
+ +
5 #include <vector>
+
6 #include <algorithm> // std::sort
+
7 #include <functional> // std::greater
+
8 
+
9 namespace stan {
+
10  namespace math {
+
11 
+
19  template <typename T>
+
20  inline typename std::vector<T> sort_asc(std::vector<T> xs) {
+
21  std::sort(xs.begin(), xs.end());
+
22  return xs;
+
23  }
+
24 
+
32  template <typename T>
+
33  inline typename std::vector<T> sort_desc(std::vector<T> xs) {
+
34  std::sort(xs.begin(), xs.end(), std::greater<T>());
+
35  return xs;
+
36  }
+
37 
+
45  template <typename T, int R, int C>
+
46  inline typename Eigen::Matrix<T, R, C> sort_asc(Eigen::Matrix<T, R, C> xs) {
+
47  std::sort(xs.data(), xs.data()+xs.size());
+
48  return xs;
+
49  }
+
50 
+
58  template <typename T, int R, int C>
+
59  inline typename Eigen::Matrix<T, R, C>
+
60  sort_desc(Eigen::Matrix<T, R, C> xs) {
+
61  std::sort(xs.data(), xs.data()+xs.size(), std::greater<T>());
+
62  return xs;
+
63  }
+
64 
+
65  }
+
66 }
+
67 #endif
+
std::vector< fvar< T > > sort_desc(std::vector< fvar< T > > xs)
Definition: sort_desc.hpp:17
+ + +
std::vector< fvar< T > > sort_asc(std::vector< fvar< T > > xs)
Definition: sort_asc.hpp:17
+
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+
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diff --git a/doc/api/html/sort__indices_8hpp.html b/doc/api/html/sort__indices_8hpp.html new file mode 100644 index 00000000000..962c449c47f --- /dev/null +++ b/doc/api/html/sort__indices_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sort_indices.hpp File Reference + + + + + + + + + + +
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sort_indices.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stan/math/prim/arr/meta/index_type.hpp>
+#include <algorithm>
+#include <iostream>
+#include <vector>
+
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Variable Documentation

+ +
+
+ + + + +
const C& xs_
+
+ +

Definition at line 25 of file sort_indices.hpp.

+ +
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diff --git a/doc/api/html/sort__indices_8hpp_source.html b/doc/api/html/sort__indices_8hpp_source.html new file mode 100644 index 00000000000..3fe9f8eb537 --- /dev/null +++ b/doc/api/html/sort__indices_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sort_indices.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+
+
+
sort_indices.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_SORT_INDICES_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SORT_INDICES_HPP
+
3 
+ + + +
7 #include <algorithm> // std::sort
+
8 #include <iostream>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
22  namespace {
+
23  template <bool ascending, typename C>
+
24  class index_comparator {
+
25  const C& xs_;
+
26 
+
27  public:
+
34  explicit index_comparator(const C& xs) : xs_(xs) { }
+
35 
+
44  bool operator()(int i, int j) const {
+
45  if (ascending)
+
46  return xs_[i-1] < xs_[j-1];
+
47  else
+
48  return xs_[i-1] > xs_[j-1];
+
49  }
+
50  };
+
51 
+
52 
+
63  template <bool ascending, typename C>
+
64  std::vector<int> sort_indices(const C& xs) {
+
65  typedef typename index_type<C>::type idx_t;
+
66  idx_t size = xs.size();
+
67  std::vector<int> idxs;
+
68  idxs.resize(size);
+
69  for (idx_t i = 0; i < size; ++i)
+
70  idxs[i] = i + 1;
+
71  index_comparator<ascending, C> comparator(xs);
+
72  std::sort(idxs.begin(), idxs.end(), comparator);
+
73  return idxs;
+
74  }
+
75 
+
76  }
+
77 
+
78  }
+
79 }
+
80 #endif
+ + + + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
const C & xs_
+
+
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diff --git a/doc/api/html/sort__indices__asc_8hpp.html b/doc/api/html/sort__indices__asc_8hpp.html new file mode 100644 index 00000000000..284ca01b995 --- /dev/null +++ b/doc/api/html/sort__indices__asc_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sort_indices_asc.hpp File Reference + + + + + + + + + + +
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sort_indices_asc.hpp File Reference
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stan/math/prim/mat/fun/sort_indices.hpp>
+#include <algorithm>
+#include <iostream>
+#include <vector>
+
+

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 Matrices and templated mathematical functions.
 
+ + + + + +

+Functions

template<typename C >
std::vector< int > stan::math::sort_indices_asc (const C &xs)
 Return a sorted copy of the argument container in ascending order. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/sort__indices__asc_8hpp_source.html b/doc/api/html/sort__indices__asc_8hpp_source.html new file mode 100644 index 00000000000..21a47b1487e --- /dev/null +++ b/doc/api/html/sort__indices__asc_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sort_indices_asc.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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sort_indices_asc.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_SORT_INDICES_ASC_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SORT_INDICES_ASC_HPP
+
3 
+ + + +
7 #include <algorithm> // std::sort
+
8 #include <iostream>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
22  template <typename C>
+
23  std::vector<int> sort_indices_asc(const C& xs) {
+
24  return sort_indices<true>(xs);
+
25  }
+
26 
+
27  }
+
28 }
+
29 #endif
+ + +
std::vector< int > sort_indices_asc(const C &xs)
Return a sorted copy of the argument container in ascending order.
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/sort__indices__desc_8hpp.html b/doc/api/html/sort__indices__desc_8hpp.html new file mode 100644 index 00000000000..5bd2783ea69 --- /dev/null +++ b/doc/api/html/sort__indices__desc_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sort_indices_desc.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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sort_indices_desc.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/meta/index_type.hpp>
+#include <stan/math/prim/mat/fun/sort_indices.hpp>
+#include <algorithm>
+#include <iostream>
+#include <vector>
+
+

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 stan::math
 Matrices and templated mathematical functions.
 
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+Functions

template<typename C >
std::vector< int > stan::math::sort_indices_desc (const C &xs)
 Return a sorted copy of the argument container in ascending order. More...
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/sort__indices__desc_8hpp_source.html b/doc/api/html/sort__indices__desc_8hpp_source.html new file mode 100644 index 00000000000..5238211bbc8 --- /dev/null +++ b/doc/api/html/sort__indices__desc_8hpp_source.html @@ -0,0 +1,137 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sort_indices_desc.hpp Source File + + + + + + + + + + +
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sort_indices_desc.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_SORT_INDICES_DESC_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SORT_INDICES_DESC_HPP
+
3 
+ + + +
7 #include <algorithm> // std::sort
+
8 #include <iostream>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
22  template <typename C>
+
23  std::vector<int> sort_indices_desc(const C& xs) {
+
24  return sort_indices<false>(xs);
+
25  }
+
26 
+
27 
+
28  }
+
29 }
+
30 #endif
+ + + + +
std::vector< int > sort_indices_desc(const C &xs)
Return a sorted copy of the argument container in ascending order.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/splitbar.png b/doc/api/html/splitbar.png new file mode 100644 index 0000000000000000000000000000000000000000..fe895f2c58179b471a22d8320b39a4bd7312ec8e GIT binary patch literal 314 zcmeAS@N?(olHy`uVBq!ia0vp^Yzz!63>-{AmhX=Jf(#6djGiuzAr*{o?=JLmPLyc> z_*`QK&+BH@jWrYJ7>r6%keRM@)Qyv8R=enp0jiI>aWlGyB58O zFVR20d+y`K7vDw(hJF3;>dD*3-?v=<8M)@x|EEGLnJsniYK!2U1 Y!`|5biEc?d1`HDhPgg&ebxsLQ02F6;9RL6T literal 0 HcmV?d00001 diff --git a/doc/api/html/stack__alloc_8hpp.html b/doc/api/html/stack__alloc_8hpp.html new file mode 100644 index 00000000000..4d931ea6e4a --- /dev/null +++ b/doc/api/html/stack__alloc_8hpp.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: stan/math/memory/stack_alloc.hpp File Reference + + + + + + + + + + +
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stack_alloc.hpp File Reference
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+
+
#include <stdint.h>
+#include <stan/math/prim/scal/meta/likely.hpp>
+#include <cstdlib>
+#include <cstddef>
+#include <sstream>
+#include <stdexcept>
+#include <vector>
+
+

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+Classes

class  stan::math::stack_alloc
 An instance of this class provides a memory pool through which blocks of raw memory may be allocated and then collected simultaneously. More...
 
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+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
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template<typename T >
bool stan::math::is_aligned (T *ptr, unsigned int bytes_aligned)
 Return true if the specified pointer is aligned on the number of bytes. More...
 
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diff --git a/doc/api/html/stack__alloc_8hpp_source.html b/doc/api/html/stack__alloc_8hpp_source.html new file mode 100644 index 00000000000..c8db03de77c --- /dev/null +++ b/doc/api/html/stack__alloc_8hpp_source.html @@ -0,0 +1,290 @@ + + + + + + +Stan Math Library: stan/math/memory/stack_alloc.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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stack_alloc.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_MEMORY_STACK_ALLOC_HPP
+
2 #define STAN_MATH_MEMORY_STACK_ALLOC_HPP
+
3 
+
4 // TODO(Bob): <cstddef> replaces this ifdef in C++11, until then this
+
5 // is best we can do to get safe pointer casts to uints.
+
6 #include <stdint.h>
+ +
8 #include <cstdlib>
+
9 #include <cstddef>
+
10 #include <sstream>
+
11 #include <stdexcept>
+
12 #include <vector>
+
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
17 
+
29  template <typename T>
+
30  bool is_aligned(T* ptr, unsigned int bytes_aligned) {
+
31  return (reinterpret_cast<uintptr_t>(ptr) % bytes_aligned) == 0U;
+
32  }
+
33 
+
34 
+
35  namespace {
+
36  const size_t DEFAULT_INITIAL_NBYTES = 1 << 16; // 64KB
+
37 
+
38 
+
39  // FIXME: enforce alignment
+
40  // big fun to inline, but only called twice
+
41  inline char* eight_byte_aligned_malloc(size_t size) {
+
42  char* ptr = static_cast<char*>(malloc(size));
+
43  if (!ptr) return ptr; // malloc failed to alloc
+
44  if (!is_aligned(ptr, 8U)) {
+
45  std::stringstream s;
+
46  s << "invalid alignment to 8 bytes, ptr="
+
47  << reinterpret_cast<uintptr_t>(ptr)
+
48  << std::endl;
+
49  throw std::runtime_error(s.str());
+
50  }
+
51  return ptr;
+
52  }
+
53  }
+
54 
+
74  class stack_alloc {
+
75  private:
+
76  std::vector<char*> blocks_; // storage for blocks,
+
77  // may be bigger than cur_block_
+
78  std::vector<size_t> sizes_; // could store initial & shift for others
+
79  size_t cur_block_; // index into blocks_ for next alloc
+
80  char* cur_block_end_; // ptr to cur_block_ptr_ + sizes_[cur_block_]
+
81  char* next_loc_; // ptr to next available spot in cur
+
82  // block
+
83  // next three for keeping track of nested allocations on top of stack:
+
84  std::vector<size_t> nested_cur_blocks_;
+
85  std::vector<char*> nested_next_locs_;
+
86  std::vector<char*> nested_cur_block_ends_;
+
87 
+
88 
+
97  char* move_to_next_block(size_t len) {
+
98  char* result;
+
99  ++cur_block_;
+
100  // Find the next block (if any) containing at least len bytes.
+
101  while ((cur_block_ < blocks_.size()) && (sizes_[cur_block_] < len))
+
102  ++cur_block_;
+
103  // Allocate a new block if necessary.
+
104  if (unlikely(cur_block_ >= blocks_.size())) {
+
105  // New block should be max(2*size of last block, len) bytes.
+
106  size_t newsize = sizes_.back() * 2;
+
107  if (newsize < len)
+
108  newsize = len;
+
109  blocks_.push_back(eight_byte_aligned_malloc(newsize));
+
110  if (!blocks_.back())
+
111  throw std::bad_alloc();
+
112  sizes_.push_back(newsize);
+
113  }
+
114  result = blocks_[cur_block_];
+
115  // Get the object's state back in order.
+
116  next_loc_ = result + len;
+
117  cur_block_end_ = result + sizes_[cur_block_];
+
118  return result;
+
119  }
+
120 
+
121  public:
+
131  explicit stack_alloc(size_t initial_nbytes = DEFAULT_INITIAL_NBYTES) :
+
132  blocks_(1, eight_byte_aligned_malloc(initial_nbytes)),
+
133  sizes_(1, initial_nbytes),
+
134  cur_block_(0),
+
135  cur_block_end_(blocks_[0] + initial_nbytes),
+
136  next_loc_(blocks_[0]) {
+
137  if (!blocks_[0])
+
138  throw std::bad_alloc(); // no msg allowed in bad_alloc ctor
+
139  }
+
140 
+ +
148  // free ALL blocks
+
149  for (size_t i = 0; i < blocks_.size(); ++i)
+
150  if (blocks_[i])
+
151  free(blocks_[i]);
+
152  }
+
153 
+
166  inline void* alloc(size_t len) {
+
167  // Typically, just return and increment the next location.
+
168  char* result = next_loc_;
+
169  next_loc_ += len;
+
170  // Occasionally, we have to switch blocks.
+
171  if (unlikely(next_loc_ >= cur_block_end_))
+
172  result = move_to_next_block(len);
+
173  return reinterpret_cast<void*>(result);
+
174  }
+
175 
+
184  template <typename T>
+
185  inline
+
186  T* alloc_array(size_t n) {
+
187  return static_cast<T*>(alloc(n * sizeof(T)));
+
188  }
+
189 
+
190 
+
197  inline void recover_all() {
+
198  cur_block_ = 0;
+
199  next_loc_ = blocks_[0];
+
200  cur_block_end_ = next_loc_ + sizes_[0];
+
201  }
+
202 
+
207  inline void start_nested() {
+
208  nested_cur_blocks_.push_back(cur_block_);
+
209  nested_next_locs_.push_back(next_loc_);
+
210  nested_cur_block_ends_.push_back(cur_block_end_);
+
211  }
+
212 
+
216  inline void recover_nested() {
+
217  if (unlikely(nested_cur_blocks_.empty()))
+
218  recover_all();
+
219 
+
220  cur_block_ = nested_cur_blocks_.back();
+
221  nested_cur_blocks_.pop_back();
+
222 
+
223  next_loc_ = nested_next_locs_.back();
+
224  nested_next_locs_.pop_back();
+
225 
+
226  cur_block_end_ = nested_cur_block_ends_.back();
+
227  nested_cur_block_ends_.pop_back();
+
228  }
+
229 
+
235  inline void free_all() {
+
236  // frees all BUT the first (index 0) block
+
237  for (size_t i = 1; i < blocks_.size(); ++i)
+
238  if (blocks_[i])
+
239  free(blocks_[i]);
+
240  sizes_.resize(1);
+
241  blocks_.resize(1);
+
242  recover_all();
+
243  }
+
244 
+
255  size_t bytes_allocated() {
+
256  size_t sum = 0;
+
257  for (size_t i = 0; i <= cur_block_; ++i) {
+
258  sum += sizes_[i];
+
259  }
+
260  return sum;
+
261  }
+
262  };
+
263 
+
264  }
+
265 }
+
266 #endif
+
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition: sum.hpp:20
+ +
~stack_alloc()
Destroy this memory allocator.
+
void recover_nested()
recover memory back to the last start_nested call.
+
#define unlikely(x)
Definition: likely.hpp:9
+
void free_all()
Free all memory used by the stack allocator other than the initial block allocation back to the syste...
+
void recover_all()
Recover all the memory used by the stack allocator.
+
size_t bytes_allocated()
Return number of bytes allocated to this instance by the heap.
+ +
T * alloc_array(size_t n)
Allocate an array on the arena of the specified size to hold values of the specified template paramet...
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
void start_nested()
Store current positions before doing nested operation so can recover back to start.
+
bool is_aligned(T *ptr, unsigned int bytes_aligned)
Return true if the specified pointer is aligned on the number of bytes.
Definition: stack_alloc.hpp:30
+
stack_alloc(size_t initial_nbytes=DEFAULT_INITIAL_NBYTES)
Construct a resizable stack allocator initially holding the specified number of bytes.
+
An instance of this class provides a memory pool through which blocks of raw memory may be allocated ...
Definition: stack_alloc.hpp:74
+
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+
+
+
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diff --git a/doc/api/html/stan_8dox.html b/doc/api/html/stan_8dox.html new file mode 100644 index 00000000000..1e9446d24e7 --- /dev/null +++ b/doc/api/html/stan_8dox.html @@ -0,0 +1,114 @@ + + + + + + +Stan Math Library: doxygen/stan.dox File Reference + + + + + + + + + + +
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doxygen/stan.dox File Reference
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static void stan::math::start_nested ()
 Record the current position so that recover_memory_nested() can find it. More...
 
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diff --git a/doc/api/html/start__nested_8hpp_source.html b/doc/api/html/start__nested_8hpp_source.html new file mode 100644 index 00000000000..b1ad2958410 --- /dev/null +++ b/doc/api/html/start__nested_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/rev/core/start_nested.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_START_NESTED_HPP
+
2 #define STAN_MATH_REV_CORE_START_NESTED_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
13  static inline void start_nested() {
+ +
15  .push_back(ChainableStack::var_stack_.size());
+ + + + + +
21  }
+
22 
+
23  }
+
24 }
+
25 #endif
+ + +
static std::vector< ChainableAllocT * > var_alloc_stack_
+
static std::vector< ChainableT * > var_nochain_stack_
+
static std::vector< size_t > nested_var_nochain_stack_sizes_
+
static std::vector< size_t > nested_var_stack_sizes_
+
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
void start_nested()
Store current positions before doing nested operation so can recover back to start.
+ +
static std::vector< ChainableT * > var_stack_
+
static void start_nested()
Record the current position so that recover_memory_nested() can find it.
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int std::isinf (const stan::math::var &a)
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diff --git a/doc/api/html/std__isinf_8hpp_source.html b/doc/api/html/std__isinf_8hpp_source.html new file mode 100644 index 00000000000..342bcc9750a --- /dev/null +++ b/doc/api/html/std__isinf_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/rev/core/std_isinf.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_STD_ISINF_HPP
+
2 #define STAN_MATH_REV_CORE_STD_ISINF_HPP
+
3 
+ +
5 #include <cmath>
+
6 
+
7 namespace std {
+
8 
+
18  inline int isinf(const stan::math::var& a) {
+
19  return isinf(a.val());
+
20  }
+
21 
+
22 }
+
23 #endif
+
int isinf(const stan::math::var &a)
Checks if the given number is infinite.
Definition: std_isinf.hpp:18
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
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diff --git a/doc/api/html/std__isnan_8hpp.html b/doc/api/html/std__isnan_8hpp.html new file mode 100644 index 00000000000..7ff84347ea8 --- /dev/null +++ b/doc/api/html/std__isnan_8hpp.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/rev/core/std_isnan.hpp File Reference + + + + + + + + + + +
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int std::isnan (const stan::math::var &a)
 Checks if the given number is NaN. More...
 
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diff --git a/doc/api/html/std__isnan_8hpp_source.html b/doc/api/html/std__isnan_8hpp_source.html new file mode 100644 index 00000000000..aa626d42464 --- /dev/null +++ b/doc/api/html/std__isnan_8hpp_source.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan/math/rev/core/std_isnan.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_STD_ISNAN_HPP
+
2 #define STAN_MATH_REV_CORE_STD_ISNAN_HPP
+
3 
+ +
5 #include <cmath>
+
6 
+
7 namespace std {
+
8 
+
18  inline int isnan(const stan::math::var& a) {
+
19  return isnan(a.val());
+
20  }
+
21 
+
22 }
+
23 #endif
+ +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
int isnan(const stan::math::var &a)
Checks if the given number is NaN.
Definition: std_isnan.hpp:18
+ +
double val() const
Return the value of this variable.
Definition: var.hpp:233
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diff --git a/doc/api/html/stored__gradient__vari_8hpp.html b/doc/api/html/stored__gradient__vari_8hpp.html new file mode 100644 index 00000000000..84fe25d8d3d --- /dev/null +++ b/doc/api/html/stored__gradient__vari_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/rev/core/stored_gradient_vari.hpp File Reference + + + + + + + + + + +
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+Classes

class  stan::math::stored_gradient_vari
 A var implementation that stores the daughter variable implementation pointers and the partial derivative with respect to the result explicitly in arrays constructed on the auto-diff memory stack. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/stored__gradient__vari_8hpp_source.html b/doc/api/html/stored__gradient__vari_8hpp_source.html new file mode 100644 index 00000000000..ca081d4d666 --- /dev/null +++ b/doc/api/html/stored__gradient__vari_8hpp_source.html @@ -0,0 +1,156 @@ + + + + + + +Stan Math Library: stan/math/rev/core/stored_gradient_vari.hpp Source File + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+
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+
+
+
stored_gradient_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_STORED_GRADIENT_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_STORED_GRADIENT_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
18  class stored_gradient_vari : public vari {
+
19  protected:
+
20  size_t size_;
+ +
22  double* partials_;
+
23 
+
24  public:
+
35  stored_gradient_vari(double value,
+
36  size_t size,
+
37  vari** dtrs,
+
38  double* partials)
+
39  : vari(value),
+
40  size_(size),
+
41  dtrs_(dtrs),
+
42  partials_(partials) {
+
43  }
+
44 
+
49  void chain() {
+
50  for (size_t i = 0; i < size_; ++i)
+
51  dtrs_[i]->adj_ += adj_ * partials_[i];
+
52  }
+
53  };
+
54 
+
55  }
+
56 }
+
57 
+
58 #endif
+
stored_gradient_vari(double value, size_t size, vari **dtrs, double *partials)
Construct a stored gradient vari with the specified value, size, daughter varis, and partial derivati...
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+
A var implementation that stores the daughter variable implementation pointers and the partial deriva...
+ +
void chain()
Propagate derivatives through this vari with partial derivatives given for the daughter vari by the s...
+ + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html b/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..f438be78c1c --- /dev/null +++ b/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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Eigen::NumTraits< stan::math::fvar< T > > Member List
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diff --git a/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html b/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..bc299f67a03 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html @@ -0,0 +1,387 @@ + + + + + + +Stan Math Library: Eigen::NumTraits< stan::math::fvar< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::NumTraits< stan::math::fvar< T > > Struct Template Reference
+
+
+ +

Numerical traits template override for Eigen for automatic gradient variables. + More...

+ +

#include <Eigen_NumTraits.hpp>

+ + + + + + + + + + + + + + +

+Public Types

enum  {
+  IsInteger = 0, +IsSigned = 1, +IsComplex = 0, +RequireInitialization = 1, +
+  ReadCost = 1, +AddCost = 1, +MulCost = 1, +HasFloatingPoint = 1 +
+ }
 Properties for automatic differentiation variables read by Eigen matrix library. More...
 
typedef stan::math::fvar< T > Real
 Real-valued variables. More...
 
typedef stan::math::fvar< T > NonInteger
 Non-integer valued variables. More...
 
typedef stan::math::fvar< T > Nested
 Nested variables. More...
 
+ + + + + + + + + + + + + +

+Static Public Member Functions

static Real epsilon ()
 Return standard library's epsilon for double-precision floating point, std::numeric_limits<double>::epsilon(). More...
 
static Real dummy_precision ()
 Return dummy precision. More...
 
static Real highest ()
 Return standard library's highest for double-precision floating point, std::numeric_limits<double>max(). More...
 
static Real lowest ()
 Return standard library's lowest for double-precision floating point, &#45;std::numeric_limits<double>max(). More...
 
+

Detailed Description

+

template<typename T>
+struct Eigen::NumTraits< stan::math::fvar< T > >

+ +

Numerical traits template override for Eigen for automatic gradient variables.

+ +

Definition at line 15 of file Eigen_NumTraits.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef stan::math::fvar<T> Eigen::NumTraits< stan::math::fvar< T > >::Nested
+
+ +

Nested variables.

+

Required for numerical traits.

+ +

Definition at line 35 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + +
typedef stan::math::fvar<T> Eigen::NumTraits< stan::math::fvar< T > >::NonInteger
+
+ +

Non-integer valued variables.

+

Required for numerical traits.

+ +

Definition at line 28 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + +
typedef stan::math::fvar<T> Eigen::NumTraits< stan::math::fvar< T > >::Real
+
+ +

Real-valued variables.

+

Required for numerical traits.

+ +

Definition at line 21 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ +

Properties for automatic differentiation variables read by Eigen matrix library.

+ + + + + + + + + +
Enumerator
IsInteger  +
IsSigned  +
IsComplex  +
RequireInitialization  +
ReadCost  +
AddCost  +
MulCost  +
HasFloatingPoint  +
+ +

Definition at line 78 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static Real Eigen::NumTraits< stan::math::fvar< T > >::dummy_precision ()
+
+inlinestatic
+
+ +

Return dummy precision.

+ +

Definition at line 50 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static Real Eigen::NumTraits< stan::math::fvar< T > >::epsilon ()
+
+inlinestatic
+
+ +

Return standard library's epsilon for double-precision floating point, std::numeric_limits<double>::epsilon().

+
Returns
Same epsilon as a double.
+ +

Definition at line 43 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static Real Eigen::NumTraits< stan::math::fvar< T > >::highest ()
+
+inlinestatic
+
+ +

Return standard library's highest for double-precision floating point, std::numeric_limits<double>max().

+
Returns
Same highest value as a double.
+ +

Definition at line 60 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static Real Eigen::NumTraits< stan::math::fvar< T > >::lowest ()
+
+inlinestatic
+
+ +

Return standard library's lowest for double-precision floating point, &#45;std::numeric_limits<double>max().

+
Returns
Same lowest value as a double.
+ +

Definition at line 70 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1var_01_4-members.html b/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1var_01_4-members.html new file mode 100644 index 00000000000..02f6463be28 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1var_01_4-members.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
Eigen::NumTraits< stan::math::var > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1var_01_4.html b/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..c37b14ab596 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1_num_traits_3_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,371 @@ + + + + + + +Stan Math Library: Eigen::NumTraits< stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::NumTraits< stan::math::var > Struct Template Reference
+
+
+ +

Numerical traits template override for Eigen for automatic gradient variables. + More...

+ +

#include <Eigen_NumTraits.hpp>

+ + + + + + + + + + + + + + +

+Public Types

enum  {
+  IsInteger = 0, +IsSigned = 1, +IsComplex = 0, +RequireInitialization = 0, +
+  ReadCost = 1, +AddCost = 1, +MulCost = 1, +HasFloatingPoint = 1 +
+ }
 Properties for automatic differentiation variables read by Eigen matrix library. More...
 
typedef stan::math::var Real
 Real-valued variables. More...
 
typedef stan::math::var NonInteger
 Non-integer valued variables. More...
 
typedef stan::math::var Nested
 Nested variables. More...
 
+ + + + + + + + + + + + + +

+Static Public Member Functions

static Real epsilon ()
 Return standard library's epsilon for double-precision floating point, std::numeric_limits<double>::epsilon(). More...
 
static Real dummy_precision ()
 Return dummy precision. More...
 
static Real highest ()
 Return standard library's highest for double-precision floating point, std::numeric_limits<double>max(). More...
 
static Real lowest ()
 Return standard library's lowest for double-precision floating point, &#45;std::numeric_limits<double>max(). More...
 
+

Detailed Description

+

template<>
+struct Eigen::NumTraits< stan::math::var >

+ +

Numerical traits template override for Eigen for automatic gradient variables.

+ +

Definition at line 16 of file Eigen_NumTraits.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef stan::math::var Eigen::NumTraits< stan::math::var >::Nested
+
+ +

Nested variables.

+

Required for numerical traits.

+ +

Definition at line 36 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+ + + + +
typedef stan::math::var Eigen::NumTraits< stan::math::var >::NonInteger
+
+ +

Non-integer valued variables.

+

Required for numerical traits.

+ +

Definition at line 29 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+ + + + +
typedef stan::math::var Eigen::NumTraits< stan::math::var >::Real
+
+ +

Real-valued variables.

+

Required for numerical traits.

+ +

Definition at line 22 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+ + + + +
anonymous enum
+
+ +

Properties for automatic differentiation variables read by Eigen matrix library.

+ + + + + + + + + +
Enumerator
IsInteger  +
IsSigned  +
IsComplex  +
RequireInitialization  +
ReadCost  +
AddCost  +
MulCost  +
HasFloatingPoint  +
+ +

Definition at line 79 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
static Real Eigen::NumTraits< stan::math::var >::dummy_precision ()
+
+inlinestatic
+
+ +

Return dummy precision.

+ +

Definition at line 51 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static Real Eigen::NumTraits< stan::math::var >::epsilon ()
+
+inlinestatic
+
+ +

Return standard library's epsilon for double-precision floating point, std::numeric_limits<double>::epsilon().

+
Returns
Same epsilon as a double.
+ +

Definition at line 44 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static Real Eigen::NumTraits< stan::math::var >::highest ()
+
+inlinestatic
+
+ +

Return standard library's highest for double-precision floating point, std::numeric_limits<double>max().

+
Returns
Same highest value as a double.
+ +

Definition at line 61 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static Real Eigen::NumTraits< stan::math::var >::lowest ()
+
+inlinestatic
+
+ +

Return standard library's lowest for double-precision floating point, &#45;std::numeric_limits<double>max().

+
Returns
Same lowest value as a double.
+ +

Definition at line 71 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__matrix__product_3_01_index_00_01stan_1_1math_1_1var891c74b697344c5a91d6cb1ea74e2dbb.html b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__matrix__product_3_01_index_00_01stan_1_1math_1_1var891c74b697344c5a91d6cb1ea74e2dbb.html new file mode 100644 index 00000000000..e63749427b3 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__matrix__product_3_01_index_00_01stan_1_1math_1_1var891c74b697344c5a91d6cb1ea74e2dbb.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__matrix__product_3_01_index_00_01stan_1_1math_1_1vare08cb3fdb73f9bece710a9e80e67eb28.html b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__matrix__product_3_01_index_00_01stan_1_1math_1_1vare08cb3fdb73f9bece710a9e80e67eb28.html new file mode 100644 index 00000000000..85fd881d493 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__matrix__product_3_01_index_00_01stan_1_1math_1_1vare08cb3fdb73f9bece710a9e80e67eb28.html @@ -0,0 +1,289 @@ + + + + + + +Stan Math Library: Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor > Struct Template Reference
+
+
+ +

#include <Eigen_NumTraits.hpp>

+ + + + + + + + +

+Public Types

typedef stan::math::var LhsScalar
 
typedef stan::math::var RhsScalar
 
typedef scalar_product_traits< LhsScalar, RhsScalar >::ReturnType ResScalar
 
+ + + +

+Static Public Member Functions

static void run (Index rows, Index cols, Index depth, const LhsScalar *_lhs, Index lhsStride, const RhsScalar *_rhs, Index rhsStride, ResScalar *res, Index resStride, const ResScalar &alpha, level3_blocking< LhsScalar, RhsScalar > &, GemmParallelInfo< Index > *)
 
+

Detailed Description

+

template<typename Index, int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder, bool ConjugateRhs>
+struct Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor >

+ + +

Definition at line 186 of file Eigen_NumTraits.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename Index , int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder, bool ConjugateRhs>
+ + + + +
typedef stan::math::var Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor >::LhsScalar
+
+ +

Definition at line 190 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename Index , int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder, bool ConjugateRhs>
+ + + + +
typedef scalar_product_traits<LhsScalar, RhsScalar>::ReturnType Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor >::ResScalar
+
+ +

Definition at line 193 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename Index , int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder, bool ConjugateRhs>
+ + + + +
typedef stan::math::var Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor >::RhsScalar
+
+ +

Definition at line 191 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename Index , int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder, bool ConjugateRhs>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static void Eigen::internal::general_matrix_matrix_product< Index, stan::math::var, LhsStorageOrder, ConjugateLhs, stan::math::var, RhsStorageOrder, ConjugateRhs, ColMajor >::run (Index rows,
Index cols,
Index depth,
const LhsScalar_lhs,
Index lhsStride,
const RhsScalar_rhs,
Index rhsStride,
ResScalarres,
Index resStride,
const ResScalaralpha,
level3_blocking< LhsScalar, RhsScalar > & ,
GemmParallelInfo< Index > *  
)
+
+inlinestatic
+
+ +

Definition at line 194 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var1321060376072aa9eff79393bb0b3bcf.html b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var1321060376072aa9eff79393bb0b3bcf.html new file mode 100644 index 00000000000..548e30a1c10 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var1321060376072aa9eff79393bb0b3bcf.html @@ -0,0 +1,299 @@ + + + + + + +Stan Math Library: Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs > Struct Template Reference
+
+
+ +

Override matrix-vector and matrix-matrix products to use more efficient implementation. + More...

+ +

#include <Eigen_NumTraits.hpp>

+ + + + + + + + + + +

+Public Types

enum  { LhsStorageOrder = ColMajor + }
 
typedef stan::math::var LhsScalar
 
typedef stan::math::var RhsScalar
 
typedef scalar_product_traits< LhsScalar, RhsScalar >::ReturnType ResScalar
 
+ + + +

+Static Public Member Functions

static EIGEN_DONT_INLINE void run (Index rows, Index cols, const LhsScalar *lhs, Index lhsStride, const RhsScalar *rhs, Index rhsIncr, ResScalar *res, Index resIncr, const ResScalar &alpha)
 
+

Detailed Description

+

template<typename Index, bool ConjugateLhs, bool ConjugateRhs>
+struct Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs >

+ +

Override matrix-vector and matrix-matrix products to use more efficient implementation.

+ +

Definition at line 128 of file Eigen_NumTraits.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + +
typedef stan::math::var Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs >::LhsScalar
+
+ +

Definition at line 131 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + +
typedef scalar_product_traits<LhsScalar, RhsScalar>::ReturnType Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs >::ResScalar
+
+ +

Definition at line 134 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + +
typedef stan::math::var Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs >::RhsScalar
+
+ +

Definition at line 132 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + +
anonymous enum
+
+ + +
Enumerator
LhsStorageOrder  +
+ +

Definition at line 135 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static EIGEN_DONT_INLINE void Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs >::run (Index rows,
Index cols,
const LhsScalarlhs,
Index lhsStride,
const RhsScalarrhs,
Index rhsIncr,
ResScalarres,
Index resIncr,
const ResScalaralpha 
)
+
+inlinestatic
+
+ +

Definition at line 137 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var66e15893d6f734727ea794ad7f157d69.html b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var66e15893d6f734727ea794ad7f157d69.html new file mode 100644 index 00000000000..2d39e106d90 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var66e15893d6f734727ea794ad7f157d69.html @@ -0,0 +1,119 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+
+
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+
+ + +
+ +
+ + +
+
+
+
Eigen::internal::general_matrix_vector_product< Index, stan::math::var, ColMajor, ConjugateLhs, stan::math::var, ConjugateRhs > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var71b7c65516c0cd3d91b4d68782f6b239.html b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var71b7c65516c0cd3d91b4d68782f6b239.html new file mode 100644 index 00000000000..ab82fd652af --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var71b7c65516c0cd3d91b4d68782f6b239.html @@ -0,0 +1,119 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var869db506dfaf992a1f3fe10cc2ff3202.html b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var869db506dfaf992a1f3fe10cc2ff3202.html new file mode 100644 index 00000000000..e4ba464a0c4 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1general__matrix__vector__product_3_01_index_00_01stan_1_1math_1_1var869db506dfaf992a1f3fe10cc2ff3202.html @@ -0,0 +1,295 @@ + + + + + + +Stan Math Library: Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs > Struct Template Reference
+
+
+ +

#include <Eigen_NumTraits.hpp>

+ + + + + + + + + + +

+Public Types

enum  { LhsStorageOrder = RowMajor + }
 
typedef stan::math::var LhsScalar
 
typedef stan::math::var RhsScalar
 
typedef scalar_product_traits< LhsScalar, RhsScalar >::ReturnType ResScalar
 
+ + + +

+Static Public Member Functions

static EIGEN_DONT_INLINE void run (Index rows, Index cols, const LhsScalar *lhs, Index lhsStride, const RhsScalar *rhs, Index rhsIncr, ResScalar *res, Index resIncr, const RhsScalar &alpha)
 
+

Detailed Description

+

template<typename Index, bool ConjugateLhs, bool ConjugateRhs>
+struct Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs >

+ + +

Definition at line 157 of file Eigen_NumTraits.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + +
typedef stan::math::var Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs >::LhsScalar
+
+ +

Definition at line 160 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + +
typedef scalar_product_traits<LhsScalar, RhsScalar>::ReturnType Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs >::ResScalar
+
+ +

Definition at line 163 of file Eigen_NumTraits.hpp.

+ +
+
+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + +
typedef stan::math::var Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs >::RhsScalar
+
+ +

Definition at line 161 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + +
anonymous enum
+
+ + +
Enumerator
LhsStorageOrder  +
+ +

Definition at line 164 of file Eigen_NumTraits.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename Index , bool ConjugateLhs, bool ConjugateRhs>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static EIGEN_DONT_INLINE void Eigen::internal::general_matrix_vector_product< Index, stan::math::var, RowMajor, ConjugateLhs, stan::math::var, ConjugateRhs >::run (Index rows,
Index cols,
const LhsScalarlhs,
Index lhsStride,
const RhsScalarrhs,
Index rhsIncr,
ResScalarres,
Index resIncr,
const RhsScalaralpha 
)
+
+inlinestatic
+
+ +

Definition at line 167 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01double_00_01stan_1_1math_1_1var_01_4-members.html b/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01double_00_01stan_1_1math_1_1var_01_4-members.html new file mode 100644 index 00000000000..efb9c242327 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01double_00_01stan_1_1math_1_1var_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+
+
Eigen::internal::scalar_product_traits< double, stan::math::var > Member List
+
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+
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diff --git a/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01double_00_01stan_1_1math_1_1var_01_4.html b/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01double_00_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..d86802b7032 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01double_00_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: Eigen::internal::scalar_product_traits< double, stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::internal::scalar_product_traits< double, stan::math::var > Struct Template Reference
+
+
+ +

Scalar product traits override for Eigen for automatic gradient variables. + More...

+ +

#include <Eigen_NumTraits.hpp>

+ + + + +

+Public Types

typedef stan::math::var ReturnType
 
+

Detailed Description

+

template<>
+struct Eigen::internal::scalar_product_traits< double, stan::math::var >

+ +

Scalar product traits override for Eigen for automatic gradient variables.

+ +

Definition at line 120 of file Eigen_NumTraits.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef stan::math::var Eigen::internal::scalar_product_traits< double, stan::math::var >::ReturnType
+
+ +

Definition at line 121 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01stan_1_1math_1_1var_00_01double_01_4-members.html b/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01stan_1_1math_1_1var_00_01double_01_4-members.html new file mode 100644 index 00000000000..c2c9142e4ec --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01stan_1_1math_1_1var_00_01double_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+
Eigen::internal::scalar_product_traits< stan::math::var, double > Member List
+
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diff --git a/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01stan_1_1math_1_1var_00_01double_01_4.html b/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01stan_1_1math_1_1var_00_01double_01_4.html new file mode 100644 index 00000000000..f770d6f3a00 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1scalar__product__traits_3_01stan_1_1math_1_1var_00_01double_01_4.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: Eigen::internal::scalar_product_traits< stan::math::var, double > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::internal::scalar_product_traits< stan::math::var, double > Struct Template Reference
+
+
+ +

Scalar product traits override for Eigen for automatic gradient variables. + More...

+ +

#include <Eigen_NumTraits.hpp>

+ + + + +

+Public Types

typedef stan::math::var ReturnType
 
+

Detailed Description

+

template<>
+struct Eigen::internal::scalar_product_traits< stan::math::var, double >

+ +

Scalar product traits override for Eigen for automatic gradient variables.

+ +

Definition at line 111 of file Eigen_NumTraits.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef stan::math::var Eigen::internal::scalar_product_traits< stan::math::var, double >::ReturnType
+
+ +

Definition at line 112 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1fvar_3_01_t_01_4_00_01false_01_4-members.html b/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1fvar_3_01_t_01_4_00_01false_01_4-members.html new file mode 100644 index 00000000000..05ceea8a7ea --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1fvar_3_01_t_01_4_00_01false_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Eigen::internal::significant_decimals_default_impl< stan::math::fvar< T >, false > Member List
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diff --git a/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1fvar_3_01_t_01_4_00_01false_01_4.html b/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1fvar_3_01_t_01_4_00_01false_01_4.html new file mode 100644 index 00000000000..c37425989aa --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1fvar_3_01_t_01_4_00_01false_01_4.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: Eigen::internal::significant_decimals_default_impl< stan::math::fvar< T >, false > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::internal::significant_decimals_default_impl< stan::math::fvar< T >, false > Struct Template Reference
+
+
+ +

Implemented this for printing to stream. + More...

+ +

#include <Eigen_NumTraits.hpp>

+ + + + +

+Static Public Member Functions

static int run ()
 
+

Detailed Description

+

template<typename T>
+struct Eigen::internal::significant_decimals_default_impl< stan::math::fvar< T >, false >

+ +

Implemented this for printing to stream.

+ +

Definition at line 95 of file Eigen_NumTraits.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static int Eigen::internal::significant_decimals_default_impl< stan::math::fvar< T >, false >::run ()
+
+inlinestatic
+
+ +

Definition at line 96 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1var_00_01false_01_4-members.html b/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1var_00_01false_01_4-members.html new file mode 100644 index 00000000000..e23fd929ea3 --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1var_00_01false_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+ +
+ + +
+
+
+
Eigen::internal::significant_decimals_default_impl< stan::math::var, false > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1var_00_01false_01_4.html b/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1var_00_01false_01_4.html new file mode 100644 index 00000000000..48002a484ca --- /dev/null +++ b/doc/api/html/struct_eigen_1_1internal_1_1significant__decimals__default__impl_3_01stan_1_1math_1_1var_00_01false_01_4.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: Eigen::internal::significant_decimals_default_impl< stan::math::var, false > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
Eigen::internal::significant_decimals_default_impl< stan::math::var, false > Struct Template Reference
+
+
+ +

Implemented this for printing to stream. + More...

+ +

#include <Eigen_NumTraits.hpp>

+ + + + +

+Static Public Member Functions

static int run ()
 
+

Detailed Description

+

template<>
+struct Eigen::internal::significant_decimals_default_impl< stan::math::var, false >

+ +

Implemented this for printing to stream.

+ +

Definition at line 96 of file Eigen_NumTraits.hpp.

+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
static int Eigen::internal::significant_decimals_default_impl< stan::math::var, false >::run ()
+
+inlinestatic
+
+ +

Definition at line 97 of file Eigen_NumTraits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1contains__fvar-members.html b/doc/api/html/structstan_1_1contains__fvar-members.html new file mode 100644 index 00000000000..1d8af0a2c98 --- /dev/null +++ b/doc/api/html/structstan_1_1contains__fvar-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
+
stan::contains_fvar< T1, T2, T3, T4, T5, T6 > Member List
+
+
+ +

This is the complete list of members for stan::contains_fvar< T1, T2, T3, T4, T5, T6 >, including all inherited members.

+ + +
value enum valuestan::contains_fvar< T1, T2, T3, T4, T5, T6 >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1contains__fvar.html b/doc/api/html/structstan_1_1contains__fvar.html new file mode 100644 index 00000000000..69ed69510c1 --- /dev/null +++ b/doc/api/html/structstan_1_1contains__fvar.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan::contains_fvar< T1, T2, T3, T4, T5, T6 > Struct Template Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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stan::contains_fvar< T1, T2, T3, T4, T5, T6 > Struct Template Reference
+
+
+ +

Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters. + More...

+ +

#include <contains_fvar.hpp>

+ + + + +

+Public Types

enum  { value + }
 
+

Detailed Description

+

template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+struct stan::contains_fvar< T1, T2, T3, T4, T5, T6 >

+ +

Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters.

+ +

Definition at line 19 of file contains_fvar.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T1 , typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 20 of file contains_fvar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1contains__nonconstant__struct-members.html b/doc/api/html/structstan_1_1contains__nonconstant__struct-members.html new file mode 100644 index 00000000000..2f41bdf7c80 --- /dev/null +++ b/doc/api/html/structstan_1_1contains__nonconstant__struct-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
+
stan::contains_nonconstant_struct< T1, T2, T3, T4, T5, T6 > Member List
+
+
+ +

This is the complete list of members for stan::contains_nonconstant_struct< T1, T2, T3, T4, T5, T6 >, including all inherited members.

+ + +
value enum valuestan::contains_nonconstant_struct< T1, T2, T3, T4, T5, T6 >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1contains__nonconstant__struct.html b/doc/api/html/structstan_1_1contains__nonconstant__struct.html new file mode 100644 index 00000000000..6b8ca82391e --- /dev/null +++ b/doc/api/html/structstan_1_1contains__nonconstant__struct.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::contains_nonconstant_struct< T1, T2, T3, T4, T5, T6 > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::contains_nonconstant_struct< T1, T2, T3, T4, T5, T6 > Struct Template Reference
+
+
+ +

#include <contains_nonconstant_struct.hpp>

+ + + + +

+Public Types

enum  { value + }
 
+

Detailed Description

+

template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+struct stan::contains_nonconstant_struct< T1, T2, T3, T4, T5, T6 >

+ + +

Definition at line 14 of file contains_nonconstant_struct.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T1 , typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 15 of file contains_nonconstant_struct.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1contains__vector-members.html b/doc/api/html/structstan_1_1contains__vector-members.html new file mode 100644 index 00000000000..feb48644f4b --- /dev/null +++ b/doc/api/html/structstan_1_1contains__vector-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ +
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+
+
stan::contains_vector< T1, T2, T3, T4, T5, T6 > Member List
+
+
+ +

This is the complete list of members for stan::contains_vector< T1, T2, T3, T4, T5, T6 >, including all inherited members.

+ + +
value enum valuestan::contains_vector< T1, T2, T3, T4, T5, T6 >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1contains__vector.html b/doc/api/html/structstan_1_1contains__vector.html new file mode 100644 index 00000000000..4d827955451 --- /dev/null +++ b/doc/api/html/structstan_1_1contains__vector.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::contains_vector< T1, T2, T3, T4, T5, T6 > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+ + +
+ +
+ + +
+
+ +
+
stan::contains_vector< T1, T2, T3, T4, T5, T6 > Struct Template Reference
+
+
+ +

#include <contains_vector.hpp>

+ + + + +

+Public Types

enum  { value + }
 
+

Detailed Description

+

template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+struct stan::contains_vector< T1, T2, T3, T4, T5, T6 >

+ + +

Definition at line 14 of file contains_vector.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 15 of file contains_vector.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1error__index-members.html b/doc/api/html/structstan_1_1error__index-members.html new file mode 100644 index 00000000000..8f23786b452 --- /dev/null +++ b/doc/api/html/structstan_1_1error__index-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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stan::error_index Member List
+
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+ +

This is the complete list of members for stan::error_index, including all inherited members.

+ + +
value enum valuestan::error_index
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1error__index.html b/doc/api/html/structstan_1_1error__index.html new file mode 100644 index 00000000000..20e6cb9aad3 --- /dev/null +++ b/doc/api/html/structstan_1_1error__index.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::error_index Struct Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+ + +
+ +
+ + +
+
+ +
+
stan::error_index Struct Reference
+
+
+ +

#include <error_index.hpp>

+ + + + +

+Public Types

enum  { value + }
 
+

Detailed Description

+
+

Definition at line 6 of file error_index.hpp.

+

Member Enumeration Documentation

+ +
+
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 7 of file error_index.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant-members.html b/doc/api/html/structstan_1_1is__constant-members.html new file mode 100644 index 00000000000..433420299dc --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ +
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+
+
+
stan::is_constant< T > Member List
+
+
+ +

This is the complete list of members for stan::is_constant< T >, including all inherited members.

+ + +
value enum valuestan::is_constant< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant.html b/doc/api/html/structstan_1_1is__constant.html new file mode 100644 index 00000000000..b631d3feb37 --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant.html @@ -0,0 +1,168 @@ + + + + + + +Stan Math Library: stan::is_constant< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_constant< T > Struct Template Reference
+
+
+ +

Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the C++ const sense). + More...

+ +

#include <is_constant.hpp>

+ + + + + +

+Public Types

enum  { value = boost::is_convertible<T, double>::value + }
 A boolean constant with equal to true if the type parameter T is a mathematical constant. More...
 
+

Detailed Description

+

template<typename T>
+struct stan::is_constant< T >

+ +

Metaprogramming struct to detect whether a given type is constant in the mathematical sense (not the C++ const sense).

+

If the parameter type is constant, value will be equal to true.

+

The baseline implementation in this abstract base class is to classify a type T as constant if it can be converted (i.e., assigned) to a double. This baseline should be overridden for any type that should be treated as a variable.

+
Template Parameters
+ + +
TType being tested.
+
+
+ +

Definition at line 22 of file is_constant.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ +

A boolean constant with equal to true if the type parameter T is a mathematical constant.

+ + +
Enumerator
value  +
+ +

Definition at line 27 of file is_constant.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant__struct-members.html b/doc/api/html/structstan_1_1is__constant__struct-members.html new file mode 100644 index 00000000000..dd2b71d32b9 --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant__struct-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+
+
stan::is_constant_struct< T > Member List
+
+
+ +

This is the complete list of members for stan::is_constant_struct< T >, including all inherited members.

+ + +
value enum valuestan::is_constant_struct< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant__struct.html b/doc/api/html/structstan_1_1is__constant__struct.html new file mode 100644 index 00000000000..ca4f39856ed --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant__struct.html @@ -0,0 +1,157 @@ + + + + + + +Stan Math Library: stan::is_constant_struct< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_constant_struct< T > Struct Template Reference
+
+
+ +

Metaprogram to determine if a type has a base scalar type that can be assigned to type double. + More...

+ +

#include <is_constant_struct.hpp>

+ + + + +

+Public Types

enum  { value = is_constant<T>::value + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_constant_struct< T >

+ +

Metaprogram to determine if a type has a base scalar type that can be assigned to type double.

+ +

Definition at line 13 of file is_constant_struct.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T>
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 14 of file is_constant_struct.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_block_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_block_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..1fa1fc007c7 --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_block_3_01_t_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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stan::is_constant_struct< Eigen::Block< T > > Member List
+
+
+ +

This is the complete list of members for stan::is_constant_struct< Eigen::Block< T > >, including all inherited members.

+ + +
value enum valuestan::is_constant_struct< Eigen::Block< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_block_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_block_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..1b8c259ce73 --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_block_3_01_t_01_4_01_4.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::is_constant_struct< Eigen::Block< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_constant_struct< Eigen::Block< T > > Struct Template Reference
+
+
+ +

#include <is_constant_struct.hpp>

+ + + + +

+Public Types

enum  { value = is_constant_struct<T>::value + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_constant_struct< Eigen::Block< T > >

+ + +

Definition at line 17 of file is_constant_struct.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 18 of file is_constant_struct.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html new file mode 100644 index 00000000000..d80f0df15e7 --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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stan::is_constant_struct< Eigen::Matrix< T, R, C > > Member List
+
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+ +

This is the complete list of members for stan::is_constant_struct< Eigen::Matrix< T, R, C > >, including all inherited members.

+ + +
value enum valuestan::is_constant_struct< Eigen::Matrix< T, R, C > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html b/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html new file mode 100644 index 00000000000..2d871024882 --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant__struct_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::is_constant_struct< Eigen::Matrix< T, R, C > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_constant_struct< Eigen::Matrix< T, R, C > > Struct Template Reference
+
+
+ +

#include <is_constant_struct.hpp>

+ + + + +

+Public Types

enum  { value = is_constant_struct<T>::value + }
 
+

Detailed Description

+

template<typename T, int R, int C>
+struct stan::is_constant_struct< Eigen::Matrix< T, R, C > >

+ + +

Definition at line 12 of file is_constant_struct.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 13 of file is_constant_struct.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant__struct_3_01std_1_1vector_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__constant__struct_3_01std_1_1vector_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..72f02835c5a --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant__struct_3_01std_1_1vector_3_01_t_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ +
+ + +
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+
+
stan::is_constant_struct< std::vector< T > > Member List
+
+
+ +

This is the complete list of members for stan::is_constant_struct< std::vector< T > >, including all inherited members.

+ + +
value enum valuestan::is_constant_struct< std::vector< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__constant__struct_3_01std_1_1vector_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1is__constant__struct_3_01std_1_1vector_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..0e611fa2021 --- /dev/null +++ b/doc/api/html/structstan_1_1is__constant__struct_3_01std_1_1vector_3_01_t_01_4_01_4.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::is_constant_struct< std::vector< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_constant_struct< std::vector< T > > Struct Template Reference
+
+
+ +

#include <is_constant_struct.hpp>

+ + + + +

+Public Types

enum  { value = is_constant_struct<T>::value + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_constant_struct< std::vector< T > >

+ + +

Definition at line 11 of file is_constant_struct.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 12 of file is_constant_struct.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__fvar-members.html b/doc/api/html/structstan_1_1is__fvar-members.html new file mode 100644 index 00000000000..d6aac129067 --- /dev/null +++ b/doc/api/html/structstan_1_1is__fvar-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ +
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+
+
stan::is_fvar< T > Member List
+
+
+ +

This is the complete list of members for stan::is_fvar< T >, including all inherited members.

+ + +
value enum valuestan::is_fvar< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__fvar.html b/doc/api/html/structstan_1_1is__fvar.html new file mode 100644 index 00000000000..ee6db0b7549 --- /dev/null +++ b/doc/api/html/structstan_1_1is__fvar.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::is_fvar< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_fvar< T > Struct Template Reference
+
+
+ +

#include <is_fvar.hpp>

+ + + + +

+Public Types

enum  { value = false + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_fvar< T >

+ + +

Definition at line 7 of file is_fvar.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 8 of file is_fvar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__fvar_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__fvar_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..c6b5a3cd6e0 --- /dev/null +++ b/doc/api/html/structstan_1_1is__fvar_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ + +
+ +
+ + +
+
+
+
stan::is_fvar< stan::math::fvar< T > > Member List
+
+
+ +

This is the complete list of members for stan::is_fvar< stan::math::fvar< T > >, including all inherited members.

+ + +
value enum valuestan::is_fvar< stan::math::fvar< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__fvar_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1is__fvar_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..3e340dbbb62 --- /dev/null +++ b/doc/api/html/structstan_1_1is__fvar_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::is_fvar< stan::math::fvar< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_fvar< stan::math::fvar< T > > Struct Template Reference
+
+
+ +

#include <is_fvar.hpp>

+ + + + +

+Public Types

enum  { value = true + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_fvar< stan::math::fvar< T > >

+ + +

Definition at line 10 of file is_fvar.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 11 of file is_fvar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__var-members.html b/doc/api/html/structstan_1_1is__var-members.html new file mode 100644 index 00000000000..a44e1140fd7 --- /dev/null +++ b/doc/api/html/structstan_1_1is__var-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+
+
stan::is_var< T > Member List
+
+
+ +

This is the complete list of members for stan::is_var< T >, including all inherited members.

+ + +
value enum valuestan::is_var< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__var.html b/doc/api/html/structstan_1_1is__var.html new file mode 100644 index 00000000000..f6d3e145e43 --- /dev/null +++ b/doc/api/html/structstan_1_1is__var.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::is_var< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_var< T > Struct Template Reference
+
+
+ +

#include <is_var.hpp>

+ + + + +

+Public Types

enum  { value = false + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_var< T >

+ + +

Definition at line 7 of file is_var.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 8 of file is_var.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__var_3_01stan_1_1math_1_1var_01_4-members.html b/doc/api/html/structstan_1_1is__var_3_01stan_1_1math_1_1var_01_4-members.html new file mode 100644 index 00000000000..b442078f8de --- /dev/null +++ b/doc/api/html/structstan_1_1is__var_3_01stan_1_1math_1_1var_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+
+
stan::is_var< stan::math::var > Member List
+
+
+ +

This is the complete list of members for stan::is_var< stan::math::var >, including all inherited members.

+ + +
value enum valuestan::is_var< stan::math::var >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__var_3_01stan_1_1math_1_1var_01_4.html b/doc/api/html/structstan_1_1is__var_3_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..0e9d28620d1 --- /dev/null +++ b/doc/api/html/structstan_1_1is__var_3_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan::is_var< stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_var< stan::math::var > Struct Template Reference
+
+
+ +

#include <is_var.hpp>

+ + + + +

+Public Types

enum  { value = true + }
 
+

Detailed Description

+

template<>
+struct stan::is_var< stan::math::var >

+ + +

Definition at line 10 of file is_var.hpp.

+

Member Enumeration Documentation

+ +
+
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 11 of file is_var.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__var__or__arithmetic-members.html b/doc/api/html/structstan_1_1is__var__or__arithmetic-members.html new file mode 100644 index 00000000000..35967afcd3f --- /dev/null +++ b/doc/api/html/structstan_1_1is__var__or__arithmetic-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+ +
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+
+
+
stan::is_var_or_arithmetic< T1, T2, T3, T4, T5, T6 > Member List
+
+
+ +

This is the complete list of members for stan::is_var_or_arithmetic< T1, T2, T3, T4, T5, T6 >, including all inherited members.

+ + +
value enum valuestan::is_var_or_arithmetic< T1, T2, T3, T4, T5, T6 >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__var__or__arithmetic.html b/doc/api/html/structstan_1_1is__var__or__arithmetic.html new file mode 100644 index 00000000000..c13ae16a179 --- /dev/null +++ b/doc/api/html/structstan_1_1is__var__or__arithmetic.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan::is_var_or_arithmetic< T1, T2, T3, T4, T5, T6 > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_var_or_arithmetic< T1, T2, T3, T4, T5, T6 > Struct Template Reference
+
+
+ +

#include <is_var_or_arithmetic.hpp>

+ + + + +

+Public Types

enum  { value + }
 
+

Detailed Description

+

template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+struct stan::is_var_or_arithmetic< T1, T2, T3, T4, T5, T6 >

+ + +

Definition at line 16 of file is_var_or_arithmetic.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T1 , typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 17 of file is_var_or_arithmetic.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector-members.html b/doc/api/html/structstan_1_1is__vector-members.html new file mode 100644 index 00000000000..69408d00bd1 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
+
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+
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+ +
+ + +
+
+
+
stan::is_vector< T > Member List
+
+
+ +

This is the complete list of members for stan::is_vector< T >, including all inherited members.

+ + + +
type typedefstan::is_vector< T >
value enum valuestan::is_vector< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector.html b/doc/api/html/structstan_1_1is__vector.html new file mode 100644 index 00000000000..0e6c5695396 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector.html @@ -0,0 +1,172 @@ + + + + + + +Stan Math Library: stan::is_vector< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector< T > Struct Template Reference
+
+
+ +

#include <is_vector.hpp>

+ + + + + + +

+Public Types

enum  { value = 0 + }
 
typedef T type
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector< T >

+ + +

Definition at line 10 of file is_vector.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T>
+ + + + +
typedef T stan::is_vector< T >::type
+
+ +

Definition at line 12 of file is_vector.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename T>
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 11 of file is_vector.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_block_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_block_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..c3a77e407d3 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_block_3_01_t_01_4_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+
+
+
stan::is_vector< Eigen::Block< T > > Member List
+
+
+ +

This is the complete list of members for stan::is_vector< Eigen::Block< T > >, including all inherited members.

+ + + +
type typedefstan::is_vector< Eigen::Block< T > >
value enum valuestan::is_vector< Eigen::Block< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_block_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_block_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..e7551bfbd4d --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_block_3_01_t_01_4_01_4.html @@ -0,0 +1,172 @@ + + + + + + +Stan Math Library: stan::is_vector< Eigen::Block< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector< Eigen::Block< T > > Struct Template Reference
+
+
+ +

#include <is_vector.hpp>

+ + + + + + +

+Public Types

enum  { value = 1 + }
 
typedef T type
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector< Eigen::Block< T > >

+ + +

Definition at line 23 of file is_vector.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef T stan::is_vector< Eigen::Block< T > >::type
+
+ +

Definition at line 25 of file is_vector.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 24 of file is_vector.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_011_00_01_eigen_1_1_dynamic_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_011_00_01_eigen_1_1_dynamic_01_4_01_4-members.html new file mode 100644 index 00000000000..b59beb7d93a --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_011_00_01_eigen_1_1_dynamic_01_4_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+ +
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+
+
+
stan::is_vector< Eigen::Matrix< T, 1, Eigen::Dynamic > > Member List
+
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+
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diff --git a/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html new file mode 100644 index 00000000000..c02229965e0 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html @@ -0,0 +1,172 @@ + + + + + + +Stan Math Library: stan::is_vector< Eigen::Matrix< T, 1, Eigen::Dynamic > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector< Eigen::Matrix< T, 1, Eigen::Dynamic > > Struct Template Reference
+
+
+ +

#include <is_vector.hpp>

+ + + + + + +

+Public Types

enum  { value = 1 + }
 
typedef T type
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector< Eigen::Matrix< T, 1, Eigen::Dynamic > >

+ + +

Definition at line 18 of file is_vector.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef T stan::is_vector< Eigen::Matrix< T, 1, Eigen::Dynamic > >::type
+
+ +

Definition at line 20 of file is_vector.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 19 of file is_vector.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_011_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_011_01_4_01_4-members.html new file mode 100644 index 00000000000..3fd14b2ef4e --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_011_01_4_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+
+ + +
+ +
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+
+
+
stan::is_vector< Eigen::Matrix< T, Eigen::Dynamic, 1 > > Member List
+
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html new file mode 100644 index 00000000000..366b38f0a98 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html @@ -0,0 +1,172 @@ + + + + + + +Stan Math Library: stan::is_vector< Eigen::Matrix< T, Eigen::Dynamic, 1 > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector< Eigen::Matrix< T, Eigen::Dynamic, 1 > > Struct Template Reference
+
+
+ +

#include <is_vector.hpp>

+ + + + + + +

+Public Types

enum  { value = 1 + }
 
typedef T type
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector< Eigen::Matrix< T, Eigen::Dynamic, 1 > >

+ + +

Definition at line 13 of file is_vector.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef T stan::is_vector< Eigen::Matrix< T, Eigen::Dynamic, 1 > >::type
+
+ +

Definition at line 15 of file is_vector.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 14 of file is_vector.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01const_01_t_01_4-members.html b/doc/api/html/structstan_1_1is__vector_3_01const_01_t_01_4-members.html new file mode 100644 index 00000000000..365f740dddf --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01const_01_t_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+
+
stan::is_vector< const T > Member List
+
+
+ +

This is the complete list of members for stan::is_vector< const T >, including all inherited members.

+ + + +
type typedefstan::is_vector< const T >
value enum valuestan::is_vector< const T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01const_01_t_01_4.html b/doc/api/html/structstan_1_1is__vector_3_01const_01_t_01_4.html new file mode 100644 index 00000000000..a4d9f0142d8 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01const_01_t_01_4.html @@ -0,0 +1,172 @@ + + + + + + +Stan Math Library: stan::is_vector< const T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector< const T > Struct Template Reference
+
+
+ +

#include <is_vector.hpp>

+ + + + + + +

+Public Types

enum  { value = is_vector<T>::value + }
 
typedef T type
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector< const T >

+ + +

Definition at line 13 of file is_vector.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef T stan::is_vector< const T >::type
+
+ +

Definition at line 15 of file is_vector.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 14 of file is_vector.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01std_1_1vector_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__vector_3_01std_1_1vector_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..ceb78c365d7 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01std_1_1vector_3_01_t_01_4_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
+
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+
+ + +
+ +
+ + +
+
+
+
stan::is_vector< std::vector< T > > Member List
+
+
+ +

This is the complete list of members for stan::is_vector< std::vector< T > >, including all inherited members.

+ + + +
type typedefstan::is_vector< std::vector< T > >
value enum valuestan::is_vector< std::vector< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector_3_01std_1_1vector_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1is__vector_3_01std_1_1vector_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..823ed165499 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector_3_01std_1_1vector_3_01_t_01_4_01_4.html @@ -0,0 +1,172 @@ + + + + + + +Stan Math Library: stan::is_vector< std::vector< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector< std::vector< T > > Struct Template Reference
+
+
+ +

#include <is_vector.hpp>

+ + + + + + +

+Public Types

enum  { value = 1 + }
 
typedef T type
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector< std::vector< T > >

+ + +

Definition at line 18 of file is_vector.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef T stan::is_vector< std::vector< T > >::type
+
+ +

Definition at line 20 of file is_vector.hpp.

+ +
+
+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 19 of file is_vector.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector__like-members.html b/doc/api/html/structstan_1_1is__vector__like-members.html new file mode 100644 index 00000000000..8d5d9091e05 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector__like-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::is_vector_like< T > Member List
+
+
+ +

This is the complete list of members for stan::is_vector_like< T >, including all inherited members.

+ + +
value enum valuestan::is_vector_like< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector__like.html b/doc/api/html/structstan_1_1is__vector__like.html new file mode 100644 index 00000000000..02f99f82a2c --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector__like.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan::is_vector_like< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector_like< T > Struct Template Reference
+
+
+ +

Template metaprogram indicates whether a type is vector_like. + More...

+ +

#include <is_vector_like.hpp>

+ + + + +

+Public Types

enum  { value = stan::is_vector<T>::value + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector_like< T >

+ +

Template metaprogram indicates whether a type is vector_like.

+

A type is vector_like if an instance can be accessed like a vector, i.e. square brackets.

+

Access is_vector_like::value for the result.

+

Default behavior is to use the is_vector template metaprogram.

+
Template Parameters
+ + +
TType to test
+
+
+ +

Definition at line 21 of file is_vector_like.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T>
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 22 of file is_vector_like.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector__like_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4-members.html b/doc/api/html/structstan_1_1is__vector__like_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4-members.html new file mode 100644 index 00000000000..f8b9ea515b8 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector__like_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::is_vector_like< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector__like_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html b/doc/api/html/structstan_1_1is__vector__like_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html new file mode 100644 index 00000000000..d23aa1a9edf --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector__like_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan::is_vector_like< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector_like< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > > Struct Template Reference
+
+
+ +

Template metaprogram indicates whether a type is vector_like. + More...

+ +

#include <is_vector_like.hpp>

+ + + + +

+Public Types

enum  { value = true + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector_like< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >

+ +

Template metaprogram indicates whether a type is vector_like.

+

A type is vector_like if an instance can be accessed like a vector, i.e. square brackets.

+

Access is_vector_like::value for the result.

+

This metaprogram removes the const qualifier.

+
Template Parameters
+ + +
TType to test
+
+
+ +

Definition at line 22 of file is_vector_like.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 23 of file is_vector_like.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector__like_3_01_t_01_5_01_4-members.html b/doc/api/html/structstan_1_1is__vector__like_3_01_t_01_5_01_4-members.html new file mode 100644 index 00000000000..6d7e5ae6bae --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector__like_3_01_t_01_5_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::is_vector_like< T * > Member List
+
+
+ +

This is the complete list of members for stan::is_vector_like< T * >, including all inherited members.

+ + +
value enum valuestan::is_vector_like< T * >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector__like_3_01_t_01_5_01_4.html b/doc/api/html/structstan_1_1is__vector__like_3_01_t_01_5_01_4.html new file mode 100644 index 00000000000..4d51bfa30a3 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector__like_3_01_t_01_5_01_4.html @@ -0,0 +1,165 @@ + + + + + + +Stan Math Library: stan::is_vector_like< T * > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector_like< T * > Struct Template Reference
+
+
+ +

Template metaprogram indicates whether a type is vector_like. + More...

+ +

#include <is_vector_like.hpp>

+ + + + +

+Public Types

enum  { value = true + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector_like< T * >

+ +

Template metaprogram indicates whether a type is vector_like.

+

A type is vector_like if an instance can be accessed like a vector, i.e. square brackets.

+

A C++ array of T is vector_like.

+
Template Parameters
+ + +
TType to test
+
+
+ +

Definition at line 36 of file is_vector_like.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 37 of file is_vector_like.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector__like_3_01const_01_t_01_4-members.html b/doc/api/html/structstan_1_1is__vector__like_3_01const_01_t_01_4-members.html new file mode 100644 index 00000000000..1546ed071cf --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector__like_3_01const_01_t_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::is_vector_like< const T > Member List
+
+
+ +

This is the complete list of members for stan::is_vector_like< const T >, including all inherited members.

+ + +
value enum valuestan::is_vector_like< const T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1is__vector__like_3_01const_01_t_01_4.html b/doc/api/html/structstan_1_1is__vector__like_3_01const_01_t_01_4.html new file mode 100644 index 00000000000..61e9d13c381 --- /dev/null +++ b/doc/api/html/structstan_1_1is__vector__like_3_01const_01_t_01_4.html @@ -0,0 +1,166 @@ + + + + + + +Stan Math Library: stan::is_vector_like< const T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::is_vector_like< const T > Struct Template Reference
+
+
+ +

Template metaprogram indicates whether a type is vector_like. + More...

+ +

#include <is_vector_like.hpp>

+ + + + +

+Public Types

enum  { value = stan::is_vector_like<T>::value + }
 
+

Detailed Description

+

template<typename T>
+struct stan::is_vector_like< const T >

+ +

Template metaprogram indicates whether a type is vector_like.

+

A type is vector_like if an instance can be accessed like a vector, i.e. square brackets.

+

Access is_vector_like::value for the result.

+

This metaprogram removes the const qualifier.

+
Template Parameters
+ + +
TType to test
+
+
+ +

Definition at line 54 of file is_vector_like.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<typename T >
+ + + + +
anonymous enum
+
+ + +
Enumerator
value  +
+ +

Definition at line 55 of file is_vector_like.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1_autodiff_stack_storage-members.html b/doc/api/html/structstan_1_1math_1_1_autodiff_stack_storage-members.html new file mode 100644 index 00000000000..cf27a36c10f --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1_autodiff_stack_storage-members.html @@ -0,0 +1,121 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1_autodiff_stack_storage.html b/doc/api/html/structstan_1_1math_1_1_autodiff_stack_storage.html new file mode 100644 index 00000000000..c29d871c984 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1_autodiff_stack_storage.html @@ -0,0 +1,312 @@ + + + + + + +Stan Math Library: stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT > Struct Template Reference
+
+
+ +

#include <autodiffstackstorage.hpp>

+ + + + + + + + + + + + + + + + +

+Static Public Attributes

static std::vector< ChainableT * > var_stack_
 
static std::vector< ChainableT * > var_nochain_stack_
 
static std::vector< ChainableAllocT * > var_alloc_stack_
 
static stack_alloc memalloc_
 
static std::vector< size_t > nested_var_stack_sizes_
 
static std::vector< size_t > nested_var_nochain_stack_sizes_
 
static std::vector< size_t > nested_var_alloc_stack_starts_
 
+

Detailed Description

+

template<typename ChainableT, typename ChainableAllocT>
+struct stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >

+ + +

Definition at line 12 of file autodiffstackstorage.hpp.

+

Member Data Documentation

+ +
+
+
+template<typename ChainableT , typename ChainableAllocT >
+ + + + + +
+ + + + +
stack_alloc stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >::memalloc_
+
+static
+
+ +

Definition at line 16 of file autodiffstackstorage.hpp.

+ +
+
+ +
+
+
+template<typename ChainableT , typename ChainableAllocT >
+ + + + + +
+ + + + +
std::vector< size_t > stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >::nested_var_alloc_stack_starts_
+
+static
+
+ +

Definition at line 21 of file autodiffstackstorage.hpp.

+ +
+
+ +
+
+
+template<typename ChainableT , typename ChainableAllocT >
+ + + + + +
+ + + + +
std::vector< size_t > stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >::nested_var_nochain_stack_sizes_
+
+static
+
+ +

Definition at line 20 of file autodiffstackstorage.hpp.

+ +
+
+ +
+
+
+template<typename ChainableT , typename ChainableAllocT >
+ + + + + +
+ + + + +
std::vector< size_t > stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >::nested_var_stack_sizes_
+
+static
+
+ +

Definition at line 19 of file autodiffstackstorage.hpp.

+ +
+
+ +
+
+
+template<typename ChainableT , typename ChainableAllocT >
+ + + + + +
+ + + + +
std::vector< ChainableAllocT * > stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >::var_alloc_stack_
+
+static
+
+ +

Definition at line 15 of file autodiffstackstorage.hpp.

+ +
+
+ +
+
+
+template<typename ChainableT , typename ChainableAllocT >
+ + + + + +
+ + + + +
std::vector< ChainableT * > stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >::var_nochain_stack_
+
+static
+
+ +

Definition at line 14 of file autodiffstackstorage.hpp.

+ +
+
+ +
+
+
+template<typename ChainableT , typename ChainableAllocT >
+ + + + + +
+ + + + +
std::vector< ChainableT * > stan::math::AutodiffStackStorage< ChainableT, ChainableAllocT >::var_stack_
+
+static
+
+ +

Definition at line 13 of file autodiffstackstorage.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1_operands_and_partials-members.html b/doc/api/html/structstan_1_1math_1_1_operands_and_partials-members.html new file mode 100644 index 00000000000..e9f0df4a410 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1_operands_and_partials-members.html @@ -0,0 +1,122 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1_operands_and_partials.html b/doc/api/html/structstan_1_1math_1_1_operands_and_partials.html new file mode 100644 index 00000000000..4748d8a77ef --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1_operands_and_partials.html @@ -0,0 +1,380 @@ + + + + + + +Stan Math Library: stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type > Struct Template Reference
+
+
+ +

This class builds partial derivatives with respect to a set of operands. + More...

+ +

#include <OperandsAndPartials.hpp>

+ + + + + + + + +

+Public Member Functions

 OperandsAndPartials (const T1 &x1=0, const T2 &x2=0, const T3 &x3=0, const T4 &x4=0, const T5 &x5=0, const T6 &x6=0)
 Constructor. More...
 
T_return_type value (double value)
 Returns a T_return_type with the value specified with the partial derivatves. More...
 
+ + + + + + + + + + + + + +

+Public Attributes

VectorView< T_return_type, false, true > d_x1
 
VectorView< T_return_type, false, true > d_x2
 
VectorView< T_return_type, false, true > d_x3
 
VectorView< T_return_type, false, true > d_x4
 
VectorView< T_return_type, false, true > d_x5
 
VectorView< T_return_type, false, true > d_x6
 
+

Detailed Description

+

template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+struct stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >

+ +

This class builds partial derivatives with respect to a set of operands.

+

There are two reason for the generality of this class. The first is to handle vector and scalar arguments without needing to write additional code. The second is to use this class for writing probability distributions that handle primitives, reverse mode, and forward mode variables seamlessly.

+

The default template class handles the case where the arguments are primitive. There are template specializations for reverse mode and forward mode.

+
Template Parameters
+ + + + + + + + +
T1First set of operands.
T2Second set of operands.
T3Third set of operands.
T4Fourth set of operands.
T5Fifth set of operands.
T6Sixth set of operands.
T_return_typeReturn type of the expression. This defaults to a template metaprogram that calculates the scalar promotion of T1 – T6.
+
+
+ +

Definition at line 38 of file OperandsAndPartials.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >::OperandsAndPartials (const T1 & x1 = 0,
const T2 & x2 = 0,
const T3 & x3 = 0,
const T4 & x4 = 0,
const T5 & x5 = 0,
const T6 & x6 = 0 
)
+
+inline
+
+ +

Constructor.

+
Parameters
+ + + + + + + +
x1first set of operands
x2second set of operands
x3third set of operands
x4fourth set of operands
x5fifth set of operands
x6sixth set of operands
+
+
+ +

Definition at line 56 of file OperandsAndPartials.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+ + + + + +
+ + + + + + + + +
T_return_type stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >::value (double value)
+
+inline
+
+ +

Returns a T_return_type with the value specified with the partial derivatves.

+
Parameters
+ + +
[in]valueValue of the variable
+
+
+
Returns
a variable with the appropriate value
+ +

Definition at line 68 of file OperandsAndPartials.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+ + + + +
VectorView<T_return_type, false, true> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >::d_x1
+
+ +

Definition at line 39 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+ + + + +
VectorView<T_return_type, false, true> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >::d_x2
+
+ +

Definition at line 40 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+ + + + +
VectorView<T_return_type, false, true> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >::d_x3
+
+ +

Definition at line 41 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+ + + + +
VectorView<T_return_type, false, true> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >::d_x4
+
+ +

Definition at line 42 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+ + + + +
VectorView<T_return_type, false, true> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >::d_x5
+
+ +

Definition at line 43 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T_return_type = typename stan::return_type<T1, T2, T3, T4, T5, T6>::type>
+ + + + +
VectorView<T_return_type, false, true> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, T_return_type >::d_x6
+
+ +

Definition at line 44 of file OperandsAndPartials.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t26e82752e3914da782ee32e686dd30e2.html b/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t26e82752e3914da782ee32e686dd30e2.html new file mode 100644 index 00000000000..bb43cb21d11 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t26e82752e3914da782ee32e686dd30e2.html @@ -0,0 +1,552 @@ + + + + + + +Stan Math Library: stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > > Struct Template Reference
+
+
+ +

This class builds partial derivatives with respect to a set of operands. + More...

+ +

#include <OperandsAndPartials.hpp>

+ + + + +

+Public Types

typedef stan::math::fvar< T_partials_return > T_return_type
 
+ + + + + + + +

+Public Member Functions

 OperandsAndPartials (const T1 &x1=0, const T2 &x2=0, const T3 &x3=0, const T4 &x4=0, const T5 &x5=0, const T6 &x6=0)
 
T_return_type value (T_partials_return value)
 
 ~OperandsAndPartials ()
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Attributes

const T1 & x1_
 
const T2 & x2_
 
const T3 & x3_
 
const T4 & x4_
 
const T5 & x5_
 
const T6 & x6_
 
size_t n_partials
 
T_partials_return * all_partials
 
VectorView< T_partials_return, is_vector< T1 >::value, is_constant_struct< T1 >::value > d_x1
 
VectorView< T_partials_return, is_vector< T2 >::value, is_constant_struct< T2 >::value > d_x2
 
VectorView< T_partials_return, is_vector< T3 >::value, is_constant_struct< T3 >::value > d_x3
 
VectorView< T_partials_return, is_vector< T4 >::value, is_constant_struct< T4 >::value > d_x4
 
VectorView< T_partials_return, is_vector< T5 >::value, is_constant_struct< T5 >::value > d_x5
 
VectorView< T_partials_return, is_vector< T6 >::value, is_constant_struct< T6 >::value > d_x6
 
+

Detailed Description

+

template<typename T1, typename T2, typename T3, typename T4, typename T5, typename T6, typename T_partials_return>
+struct stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >

+ +

This class builds partial derivatives with respect to a set of operands.

+

There are two reason for the generality of this class. The first is to handle vector and scalar arguments without needing to write additional code. The second is to use this class for writing probability distributions that handle primitives, reverse mode, and forward mode variables seamlessly.

+

This is the partial template specialization for when the return type is stan::math::fvar<T>.

+
Template Parameters
+ + + + + + + + +
T1First set of operands.
T2Second set of operands.
T3Third set of operands.
T4Fourth set of operands.
T5Fifth set of operands.
T6Sixth set of operands.
T_return_typeReturn type of the expression. This defaults to a template metaprogram that calculates the scalar promotion of T1 – T6.
+
+
+ +

Definition at line 104 of file OperandsAndPartials.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
typedef stan::math::fvar<T_partials_return> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::T_return_type
+
+ +

Definition at line 106 of file OperandsAndPartials.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::OperandsAndPartials (const T1 & x1 = 0,
const T2 & x2 = 0,
const T3 & x3 = 0,
const T4 & x4 = 0,
const T5 & x5 = 0,
const T6 & x6 = 0 
)
+
+inline
+
+ +

Definition at line 138 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + + +
+ + + + + + + +
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::~OperandsAndPartials ()
+
+inline
+
+ +

Definition at line 180 of file OperandsAndPartials.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + + +
+ + + + + + + + +
T_return_type stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::value (T_partials_return value)
+
+inline
+
+ +

Definition at line 173 of file OperandsAndPartials.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
T_partials_return* stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::all_partials
+
+ +

Definition at line 116 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
VectorView<T_partials_return, is_vector<T1>::value, is_constant_struct<T1>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::d_x1
+
+ +

Definition at line 121 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
VectorView<T_partials_return, is_vector<T2>::value, is_constant_struct<T2>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::d_x2
+
+ +

Definition at line 124 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
VectorView<T_partials_return, is_vector<T3>::value, is_constant_struct<T3>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::d_x3
+
+ +

Definition at line 127 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
VectorView<T_partials_return, is_vector<T4>::value, is_constant_struct<T4>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::d_x4
+
+ +

Definition at line 130 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
VectorView<T_partials_return, is_vector<T5>::value, is_constant_struct<T5>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::d_x5
+
+ +

Definition at line 133 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
VectorView<T_partials_return, is_vector<T6>::value, is_constant_struct<T6>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::d_x6
+
+ +

Definition at line 136 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
size_t stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::n_partials
+
+ +

Definition at line 115 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
const T1& stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::x1_
+
+ +

Definition at line 108 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
const T2& stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::x2_
+
+ +

Definition at line 109 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
const T3& stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::x3_
+
+ +

Definition at line 110 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
const T4& stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::x4_
+
+ +

Definition at line 111 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
const T5& stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::x5_
+
+ +

Definition at line 112 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 , typename T_partials_return >
+ + + + +
const T6& stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >::x6_
+
+ +

Definition at line 113 of file OperandsAndPartials.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t6_00_01stan_1_1math_1_1var_01_4.html b/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t6_00_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..3a4cd753227 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t6_00_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,434 @@ + + + + + + +Stan Math Library: stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var > Struct Template Reference
+
+
+ +

This class builds partial derivatives with respect to a set of operands. + More...

+ +

#include <OperandsAndPartials.hpp>

+ + + + + + + + +

+Public Member Functions

 OperandsAndPartials (const T1 &x1=0, const T2 &x2=0, const T3 &x3=0, const T4 &x4=0, const T5 &x5=0, const T6 &x6=0)
 Constructor. More...
 
stan::math::var value (double value)
 Returns a T_return_type with the value specified with the partial derivatves. More...
 
+ + + + + + + + + + + + + + + + + + + +

+Public Attributes

size_t nvaris
 
vari ** all_varis
 
double * all_partials
 
VectorView< double, is_vector< T1 >::value, is_constant_struct< T1 >::valued_x1
 
VectorView< double, is_vector< T2 >::value, is_constant_struct< T2 >::valued_x2
 
VectorView< double, is_vector< T3 >::value, is_constant_struct< T3 >::valued_x3
 
VectorView< double, is_vector< T4 >::value, is_constant_struct< T4 >::valued_x4
 
VectorView< double, is_vector< T5 >::value, is_constant_struct< T5 >::valued_x5
 
VectorView< double, is_vector< T6 >::value, is_constant_struct< T6 >::valued_x6
 
+

Detailed Description

+

template<typename T1, typename T2, typename T3, typename T4, typename T5, typename T6>
+struct stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >

+ +

This class builds partial derivatives with respect to a set of operands.

+

There are two reason for the generality of this class. The first is to handle vector and scalar arguments without needing to write additional code. The second is to use this class for writing probability distributions that handle primitives, reverse mode, and forward mode variables seamlessly.

+

This is the partial template specialization for when the return type is stan::math::var.

+
Template Parameters
+ + + + + + + + +
T1First set of operands.
T2Second set of operands.
T3Third set of operands.
T4Fourth set of operands.
T5Fifth set of operands.
T6Sixth set of operands.
T_return_typeReturn type of the expression. This defaults to a template metaprogram that calculates the scalar promotion of T1 – T6.
+
+
+ +

Definition at line 91 of file OperandsAndPartials.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::OperandsAndPartials (const T1 & x1 = 0,
const T2 & x2 = 0,
const T3 & x3 = 0,
const T4 & x4 = 0,
const T5 & x5 = 0,
const T6 & x6 = 0 
)
+
+inline
+
+ +

Constructor.

+
Parameters
+ + + + + + + +
x1first set of operands
x2second set of operands
x3third set of operands
x4fourth set of operands
x5fifth set of operands
x6sixth set of operands
+
+
+ +

Definition at line 125 of file OperandsAndPartials.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + + +
+ + + + + + + + +
stan::math::var stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::value (double value)
+
+inline
+
+ +

Returns a T_return_type with the value specified with the partial derivatves.

+
Parameters
+ + +
[in]valueValue of the variable
+
+
+
Returns
a variable with the appropriate value and the adjoints set for reverse mode autodiff
+ +

Definition at line 185 of file OperandsAndPartials.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
double* stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::all_partials
+
+ +

Definition at line 94 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
vari** stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::all_varis
+
+ +

Definition at line 93 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
VectorView<double, is_vector<T1>::value, is_constant_struct<T1>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::d_x1
+
+ +

Definition at line 98 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
VectorView<double, is_vector<T2>::value, is_constant_struct<T2>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::d_x2
+
+ +

Definition at line 101 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
VectorView<double, is_vector<T3>::value, is_constant_struct<T3>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::d_x3
+
+ +

Definition at line 104 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
VectorView<double, is_vector<T4>::value, is_constant_struct<T4>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::d_x4
+
+ +

Definition at line 107 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
VectorView<double, is_vector<T5>::value, is_constant_struct<T5>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::d_x5
+
+ +

Definition at line 110 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
VectorView<double, is_vector<T6>::value, is_constant_struct<T6>::value> stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::d_x6
+
+ +

Definition at line 113 of file OperandsAndPartials.hpp.

+ +
+
+ +
+
+
+template<typename T1 , typename T2 , typename T3 , typename T4 , typename T5 , typename T6 >
+ + + + +
size_t stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var >::nvaris
+
+ +

Definition at line 92 of file OperandsAndPartials.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t841c0b0c581f52f6b8f93e4e3a87f348.html b/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t841c0b0c581f52f6b8f93e4e3a87f348.html new file mode 100644 index 00000000000..c106cfb96ed --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_t841c0b0c581f52f6b8f93e4e3a87f348.html @@ -0,0 +1,125 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, stan::math::var > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_tca784ab8aab99bfebf572ac7b8367ed7.html b/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_tca784ab8aab99bfebf572ac7b8367ed7.html new file mode 100644 index 00000000000..1fb4ed5ac9d --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1_operands_and_partials_3_01_t1_00_01_t2_00_01_t3_00_01_t4_00_01_t5_00_01_tca784ab8aab99bfebf572ac7b8367ed7.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > > Member List
+
+
+ +

This is the complete list of members for stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >, including all inherited members.

+ + + + + + + + + + + + + + + + + + + +
all_partialsstan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
d_x1stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
d_x2stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
d_x3stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
d_x4stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
d_x5stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
d_x6stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
n_partialsstan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
OperandsAndPartials(const T1 &x1=0, const T2 &x2=0, const T3 &x3=0, const T4 &x4=0, const T5 &x5=0, const T6 &x6=0)stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >inline
T_return_type typedefstan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
value(T_partials_return value)stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >inline
x1_stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
x2_stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
x3_stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
x4_stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
x5_stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
x6_stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >
~OperandsAndPartials()stan::math::OperandsAndPartials< T1, T2, T3, T4, T5, T6, typename stan::math::fvar< T_partials_return > >inline
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary-members.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary-members.html new file mode 100644 index 00000000000..487eb1a695e --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary-members.html @@ -0,0 +1,117 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::apply_scalar_unary< F, T > Member List
+
+
+ +

This is the complete list of members for stan::math::apply_scalar_unary< F, T >, including all inherited members.

+ + + + +
apply(const T &x)stan::math::apply_scalar_unary< F, T >inlinestatic
return_t typedefstan::math::apply_scalar_unary< F, T >
scalar_t typedefstan::math::apply_scalar_unary< F, T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary.html new file mode 100644 index 00000000000..004e2f2970e --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary.html @@ -0,0 +1,230 @@ + + + + + + +Stan Math Library: stan::math::apply_scalar_unary< F, T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::apply_scalar_unary< F, T > Struct Template Reference
+
+
+ +

Base template class for vectorization of unary scalar functions defined by a template class F to a scalar, standard library vector, or Eigen dense matrix expression template. + More...

+ +

#include <apply_scalar_unary.hpp>

+ + + + + + + + +

+Public Types

typedef Eigen::internal::traits< T >::Scalar scalar_t
 Type of underlying scalar for the matrix type T. More...
 
typedef Eigen::Matrix< scalar_t, T::RowsAtCompileTime, T::ColsAtCompileTime > return_t
 Return type for applying the function elementwise to a matrix expression template of type T. More...
 
+ + + + +

+Static Public Member Functions

static return_t apply (const T &x)
 Return the result of applying the function defined by the template parameter F to the specified matrix argument. More...
 
+

Detailed Description

+

template<typename F, typename T>
+struct stan::math::apply_scalar_unary< F, T >

+ +

Base template class for vectorization of unary scalar functions defined by a template class F to a scalar, standard library vector, or Eigen dense matrix expression template.

+

The base class applies to any Eigen dense matrix expression template. Specializations define applications to scalars (primitive or autodiff in the corresponding autodiff library directories) or to standard library vectors of vectorizable types (primitives, Eigen dense matrix expressions, or further standard vectors).

+

Each specialization must define the typedef return_t for the vectorized return type and the function apply which defines the vectorization or base application of the function defined statically by the class F. The function definition class F defines a static function fun(), which defines the function's behavior on scalars.

+
Template Parameters
+ + + +
FType of function to apply.
TType of argument to which function is applied.
+
+
+ +

Definition at line 36 of file apply_scalar_unary.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename F , typename T >
+ + + + +
typedef Eigen::Matrix<scalar_t, T::RowsAtCompileTime, T::ColsAtCompileTime> stan::math::apply_scalar_unary< F, T >::return_t
+
+ +

Return type for applying the function elementwise to a matrix expression template of type T.

+ +

Definition at line 48 of file apply_scalar_unary.hpp.

+ +
+
+ +
+
+
+template<typename F , typename T >
+ + + + +
typedef Eigen::internal::traits<T>::Scalar stan::math::apply_scalar_unary< F, T >::scalar_t
+
+ +

Type of underlying scalar for the matrix type T.

+ +

Definition at line 40 of file apply_scalar_unary.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F , typename T >
+ + + + + +
+ + + + + + + + +
static return_t stan::math::apply_scalar_unary< F, T >::apply (const T & x)
+
+inlinestatic
+
+ +

Return the result of applying the function defined by the template parameter F to the specified matrix argument.

+
Parameters
+ + +
xMatrix to which operation is applied.
+
+
+
Returns
Componentwise application of the function specified by F to the specified matrix.
+ +

Definition at line 58 of file apply_scalar_unary.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01double_01_4-members.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01double_01_4-members.html new file mode 100644 index 00000000000..bbacd5d746e --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01double_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::apply_scalar_unary< F, double > Member List
+
+
+ +

This is the complete list of members for stan::math::apply_scalar_unary< F, double >, including all inherited members.

+ + + +
apply(double x)stan::math::apply_scalar_unary< F, double >inlinestatic
return_t typedefstan::math::apply_scalar_unary< F, double >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01double_01_4.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01double_01_4.html new file mode 100644 index 00000000000..535fac0e8a1 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01double_01_4.html @@ -0,0 +1,207 @@ + + + + + + +Stan Math Library: stan::math::apply_scalar_unary< F, double > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::apply_scalar_unary< F, double > Struct Template Reference
+
+
+ +

Template specialization for vectorized functions applying to double arguments. + More...

+ +

#include <apply_scalar_unary.hpp>

+ + + + + +

+Public Types

typedef double return_t
 The return type, double. More...
 
+ + + + +

+Static Public Member Functions

static return_t apply (double x)
 Apply the function specified by F to the specified argument. More...
 
+

Detailed Description

+

template<typename F>
+struct stan::math::apply_scalar_unary< F, double >

+ +

Template specialization for vectorized functions applying to double arguments.

+
Template Parameters
+ + +
FType of function defining static apply function.
+
+
+ +

Definition at line 74 of file apply_scalar_unary.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename F >
+ + + + +
typedef double stan::math::apply_scalar_unary< F, double >::return_t
+
+ +

The return type, double.

+ +

Definition at line 78 of file apply_scalar_unary.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + +
static return_t stan::math::apply_scalar_unary< F, double >::apply (double x)
+
+inlinestatic
+
+ +

Apply the function specified by F to the specified argument.

+

This is defined through a direct application of F::fun(), which must be defined for double arguments.

+
Parameters
+ + +
xArgument scalar.
+
+
+
Returns
Result of applying F to the scalar.
+ +

Definition at line 89 of file apply_scalar_unary.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01int_01_4-members.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01int_01_4-members.html new file mode 100644 index 00000000000..f177b770608 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01int_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::apply_scalar_unary< F, int > Member List
+
+
+ +

This is the complete list of members for stan::math::apply_scalar_unary< F, int >, including all inherited members.

+ + + +
apply(int x)stan::math::apply_scalar_unary< F, int >inlinestatic
return_t typedefstan::math::apply_scalar_unary< F, int >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01int_01_4.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01int_01_4.html new file mode 100644 index 00000000000..f1006dbfc06 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01int_01_4.html @@ -0,0 +1,208 @@ + + + + + + +Stan Math Library: stan::math::apply_scalar_unary< F, int > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::apply_scalar_unary< F, int > Struct Template Reference
+
+
+ +

Template specialization for vectorized functions applying to integer arguments. + More...

+ +

#include <apply_scalar_unary.hpp>

+ + + + + +

+Public Types

typedef double return_t
 The return type, double. More...
 
+ + + + +

+Static Public Member Functions

static return_t apply (int x)
 Apply the function specified by F to the specified argument. More...
 
+

Detailed Description

+

template<typename F>
+struct stan::math::apply_scalar_unary< F, int >

+ +

Template specialization for vectorized functions applying to integer arguments.

+

Although the argument is integer, the return type is specified as double. This allows promotion of integers to doubles in vectorized functions, or in containers.

+
Template Parameters
+ + +
FType of function defining static apply function.
+
+
+ +

Definition at line 103 of file apply_scalar_unary.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename F >
+ + + + +
typedef double stan::math::apply_scalar_unary< F, int >::return_t
+
+ +

The return type, double.

+ +

Definition at line 107 of file apply_scalar_unary.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + +
static return_t stan::math::apply_scalar_unary< F, int >::apply (int x)
+
+inlinestatic
+
+ +

Apply the function specified by F to the specified argument.

+

This is defined through a direct application of F::fun(), which must be defined for double arguments.

+
Parameters
+ + +
xArgument scalar.
+
+
+
Returns
Result of applying F to the scalar.
+ +

Definition at line 118 of file apply_scalar_unary.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..d6e1816b017 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::apply_scalar_unary< F, stan::math::fvar< T > > Member List
+
+
+ +

This is the complete list of members for stan::math::apply_scalar_unary< F, stan::math::fvar< T > >, including all inherited members.

+ + + +
apply(const stan::math::fvar< T > &x)stan::math::apply_scalar_unary< F, stan::math::fvar< T > >inlinestatic
return_t typedefstan::math::apply_scalar_unary< F, stan::math::fvar< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..e447132782f --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html @@ -0,0 +1,208 @@ + + + + + + +Stan Math Library: stan::math::apply_scalar_unary< F, stan::math::fvar< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::apply_scalar_unary< F, stan::math::fvar< T > > Struct Template Reference
+
+
+ +

Template specialization to fvar for vectorizing a unary scalar function. + More...

+ +

#include <apply_scalar_unary.hpp>

+ + + + + +

+Public Types

typedef stan::math::fvar< T > return_t
 Function return type, which is same as the argument type for the function, fvar<T>. More...
 
+ + + + +

+Static Public Member Functions

static return_t apply (const stan::math::fvar< T > &x)
 Apply the function specified by F to the specified argument. More...
 
+

Detailed Description

+

template<typename F, typename T>
+struct stan::math::apply_scalar_unary< F, stan::math::fvar< T > >

+ +

Template specialization to fvar for vectorizing a unary scalar function.

+

This is a base scalar specialization. It applies the function specified by the template parameter to the argument.

+
Template Parameters
+ + + +
FType of function to apply.
TValue and tangent type for for forward-mode autodiff variable.
+
+
+ +

Definition at line 22 of file apply_scalar_unary.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename F , typename T >
+ + + + +
typedef stan::math::fvar<T> stan::math::apply_scalar_unary< F, stan::math::fvar< T > >::return_t
+
+ +

Function return type, which is same as the argument type for the function, fvar<T>.

+ +

Definition at line 27 of file apply_scalar_unary.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F , typename T >
+ + + + + +
+ + + + + + + + +
static return_t stan::math::apply_scalar_unary< F, stan::math::fvar< T > >::apply (const stan::math::fvar< T > & x)
+
+inlinestatic
+
+ +

Apply the function specified by F to the specified argument.

+
Parameters
+ + +
xArgument variable.
+
+
+
Returns
Function applied to the variable.
+ +

Definition at line 35 of file apply_scalar_unary.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1var_01_4-members.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1var_01_4-members.html new file mode 100644 index 00000000000..bdcca3d1c4f --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1var_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::apply_scalar_unary< F, stan::math::var > Member List
+
+
+ +

This is the complete list of members for stan::math::apply_scalar_unary< F, stan::math::var >, including all inherited members.

+ + + +
apply(const stan::math::var &x)stan::math::apply_scalar_unary< F, stan::math::var >inlinestatic
return_t typedefstan::math::apply_scalar_unary< F, stan::math::var >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1var_01_4.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..36b73a4d982 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,207 @@ + + + + + + +Stan Math Library: stan::math::apply_scalar_unary< F, stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::apply_scalar_unary< F, stan::math::var > Struct Template Reference
+
+
+ +

Template specialization to var for vectorizing a unary scalar function. + More...

+ +

#include <apply_scalar_unary.hpp>

+ + + + + +

+Public Types

typedef stan::math::var return_t
 Function return type, which is var. More...
 
+ + + + +

+Static Public Member Functions

static return_t apply (const stan::math::var &x)
 Apply the function specified by F to the specified argument. More...
 
+

Detailed Description

+

template<typename F>
+struct stan::math::apply_scalar_unary< F, stan::math::var >

+ +

Template specialization to var for vectorizing a unary scalar function.

+

This is a base scalar specialization. It applies the function specified by the template parameter to the argument.

+
Template Parameters
+ + +
FType of function to apply.
+
+
+ +

Definition at line 20 of file apply_scalar_unary.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename F >
+ + + + +
typedef stan::math::var stan::math::apply_scalar_unary< F, stan::math::var >::return_t
+
+ +

Function return type, which is var.

+ +

Definition at line 24 of file apply_scalar_unary.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + +
static return_t stan::math::apply_scalar_unary< F, stan::math::var >::apply (const stan::math::varx)
+
+inlinestatic
+
+ +

Apply the function specified by F to the specified argument.

+
Parameters
+ + +
xArgument variable.
+
+
+
Returns
Function applied to the variable.
+ +

Definition at line 32 of file apply_scalar_unary.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01std_1_1vector_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01std_1_1vector_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..3653e29219d --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01std_1_1vector_3_01_t_01_4_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::apply_scalar_unary< F, std::vector< T > > Member List
+
+
+ +

This is the complete list of members for stan::math::apply_scalar_unary< F, std::vector< T > >, including all inherited members.

+ + + +
apply(const std::vector< T > &x)stan::math::apply_scalar_unary< F, std::vector< T > >inlinestatic
return_t typedefstan::math::apply_scalar_unary< F, std::vector< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01std_1_1vector_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01std_1_1vector_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..d496b8e928a --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1apply__scalar__unary_3_01_f_00_01std_1_1vector_3_01_t_01_4_01_4.html @@ -0,0 +1,209 @@ + + + + + + +Stan Math Library: stan::math::apply_scalar_unary< F, std::vector< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::apply_scalar_unary< F, std::vector< T > > Struct Template Reference
+
+
+ +

Template specialization for vectorized functions applying to standard vector containers. + More...

+ +

#include <apply_scalar_unary.hpp>

+ + + + + +

+Public Types

typedef std::vector< typename apply_scalar_unary< F, T >::return_treturn_t
 Return type, which is calculated recursively as a standard vector of the return type of the contained type T. More...
 
+ + + + +

+Static Public Member Functions

static return_t apply (const std::vector< T > &x)
 Apply the function specified by F elementwise to the specified argument. More...
 
+

Detailed Description

+

template<typename F, typename T>
+struct stan::math::apply_scalar_unary< F, std::vector< T > >

+ +

Template specialization for vectorized functions applying to standard vector containers.

+

The lowest-level scalar type of the argument will determine the return type. Integers are promoted to double values.

+
Template Parameters
+ + + +
FClass defining a static apply function.
TType of element contained in standard vector.
+
+
+ +

Definition at line 133 of file apply_scalar_unary.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename F , typename T >
+ + + + +
typedef std::vector<typename apply_scalar_unary<F, T>::return_t> stan::math::apply_scalar_unary< F, std::vector< T > >::return_t
+
+ +

Return type, which is calculated recursively as a standard vector of the return type of the contained type T.

+ +

Definition at line 139 of file apply_scalar_unary.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F , typename T >
+ + + + + +
+ + + + + + + + +
static return_t stan::math::apply_scalar_unary< F, std::vector< T > >::apply (const std::vector< T > & x)
+
+inlinestatic
+
+ +

Apply the function specified by F elementwise to the specified argument.

+

This is defined recursively through this class applied to elements of type T.

+
Parameters
+ + +
xArgument container.
+
+
+
Returns
Elementwise application of F to the elements of the container.
+ +

Definition at line 150 of file apply_scalar_unary.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1array__builder-members.html b/doc/api/html/structstan_1_1math_1_1array__builder-members.html new file mode 100644 index 00000000000..b8bf9ffa6f0 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1array__builder-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::array_builder< T > Member List
+
+
+ +

This is the complete list of members for stan::math::array_builder< T >, including all inherited members.

+ + + + + +
add(const F &u)stan::math::array_builder< T >inline
array()stan::math::array_builder< T >inline
array_builder()stan::math::array_builder< T >inline
x_stan::math::array_builder< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1array__builder.html b/doc/api/html/structstan_1_1math_1_1array__builder.html new file mode 100644 index 00000000000..15c5ada1291 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1array__builder.html @@ -0,0 +1,249 @@ + + + + + + +Stan Math Library: stan::math::array_builder< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::array_builder< T > Struct Template Reference
+
+
+ +

Structure for building up arrays in an expression (rather than in statements) using an argumentchaining add() method and a getter method array() to return the result. + More...

+ +

#include <array_builder.hpp>

+ + + + + + + + + +

+Public Member Functions

 array_builder ()
 
template<typename F >
array_builderadd (const F &u)
 
std::vector< T > array ()
 
+ + + +

+Public Attributes

std::vector< T > x_
 
+

Detailed Description

+

template<typename T>
+struct stan::math::array_builder< T >

+ +

Structure for building up arrays in an expression (rather than in statements) using an argumentchaining add() method and a getter method array() to return the result.

+ +

Definition at line 16 of file array_builder.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
stan::math::array_builder< T >::array_builder ()
+
+inline
+
+ +

Definition at line 18 of file array_builder.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T >
+
+template<typename F >
+ + + + + +
+ + + + + + + + +
array_builder& stan::math::array_builder< T >::add (const F & u)
+
+inline
+
+ +

Definition at line 20 of file array_builder.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
std::vector<T> stan::math::array_builder< T >::array ()
+
+inline
+
+ +

Definition at line 26 of file array_builder.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename T >
+ + + + +
std::vector<T> stan::math::array_builder< T >::x_
+
+ +

Definition at line 17 of file array_builder.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1child__type-members.html b/doc/api/html/structstan_1_1math_1_1child__type-members.html new file mode 100644 index 00000000000..0f2bca4a65c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1child__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
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+
+
+
stan::math::child_type< T > Member List
+
+
+ +

This is the complete list of members for stan::math::child_type< T >, including all inherited members.

+ + +
type typedefstan::math::child_type< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1child__type.html b/doc/api/html/structstan_1_1math_1_1child__type.html new file mode 100644 index 00000000000..d83a8f0c46c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1child__type.html @@ -0,0 +1,159 @@ + + + + + + +Stan Math Library: stan::math::child_type< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::child_type< T > Struct Template Reference
+
+
+ +

Primary template class for metaprogram to compute child type of T. + More...

+ +

#include <child_type.hpp>

+ + + + +

+Public Types

typedef double type
 
+

Detailed Description

+

template<typename T>
+struct stan::math::child_type< T >

+ +

Primary template class for metaprogram to compute child type of T.

+

See test/unit/math/meta/child_type_test.cpp for intended usage.

+
Template Parameters
+ + +
Ttype of container.
+
+
+ +

Definition at line 19 of file child_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef double stan::math::child_type< T >::type
+
+ +

Definition at line 20 of file child_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1child__type_3_01_t__struct_3_01_t__child_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1child__type_3_01_t__struct_3_01_t__child_01_4_01_4-members.html new file mode 100644 index 00000000000..6a2ab7febfa --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1child__type_3_01_t__struct_3_01_t__child_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::child_type< T_struct< T_child > > Member List
+
+
+ +

This is the complete list of members for stan::math::child_type< T_struct< T_child > >, including all inherited members.

+ + +
type typedefstan::math::child_type< T_struct< T_child > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1child__type_3_01_t__struct_3_01_t__child_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1child__type_3_01_t__struct_3_01_t__child_01_4_01_4.html new file mode 100644 index 00000000000..bbae522b927 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1child__type_3_01_t__struct_3_01_t__child_01_4_01_4.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan::math::child_type< T_struct< T_child > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::child_type< T_struct< T_child > > Struct Template Reference
+
+
+ +

Specialization for template classes / structs. + More...

+ +

#include <child_type.hpp>

+ + + + +

+Public Types

typedef T_child type
 
+

Detailed Description

+

template<template< typename > class T_struct, typename T_child>
+struct stan::math::child_type< T_struct< T_child > >

+ +

Specialization for template classes / structs.

+

See test/unit/math/meta/child_type_test.cpp for intended usage.

+
Template Parameters
+ + + +
T_structtype of parent.
T_childtype of child type.
+
+
+ +

Definition at line 34 of file child_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<template< typename > class T_struct, typename T_child >
+ + + + +
typedef T_child stan::math::child_type< T_struct< T_child > >::type
+
+ +

Definition at line 35 of file child_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1common__type-members.html b/doc/api/html/structstan_1_1math_1_1common__type-members.html new file mode 100644 index 00000000000..e1539dcab26 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1common__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::common_type< T1, T2 > Member List
+
+
+ +

This is the complete list of members for stan::math::common_type< T1, T2 >, including all inherited members.

+ + +
type typedefstan::math::common_type< T1, T2 >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1common__type.html b/doc/api/html/structstan_1_1math_1_1common__type.html new file mode 100644 index 00000000000..985a63380d3 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1common__type.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::math::common_type< T1, T2 > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::common_type< T1, T2 > Struct Template Reference
+
+
+ +

#include <common_type.hpp>

+ + + + +

+Public Types

typedef boost::math::tools::promote_args< T1, T2 >::type type
 
+

Detailed Description

+

template<typename T1, typename T2>
+struct stan::math::common_type< T1, T2 >

+ + +

Definition at line 13 of file common_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1, typename T2>
+ + + + +
typedef boost::math::tools::promote_args<T1, T2>::type stan::math::common_type< T1, T2 >::type
+
+ +

Definition at line 14 of file common_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1common__type_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eige106a86f1021708b40db478c4e2fef0a7.html b/doc/api/html/structstan_1_1math_1_1common__type_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eige106a86f1021708b40db478c4e2fef0a7.html new file mode 100644 index 00000000000..317f8744a9c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1common__type_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eige106a86f1021708b40db478c4e2fef0a7.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::common_type< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1common__type_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eiged8accfa00e73f240c58ad02ac582ba93.html b/doc/api/html/structstan_1_1math_1_1common__type_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eiged8accfa00e73f240c58ad02ac582ba93.html new file mode 100644 index 00000000000..4646b221a6d --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1common__type_3_01_eigen_1_1_matrix_3_01_t1_00_01_r_00_01_c_01_4_00_01_eiged8accfa00e73f240c58ad02ac582ba93.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::math::common_type< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::common_type< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > > Struct Template Reference
+
+
+ +

#include <common_type.hpp>

+ + + + +

+Public Types

typedef Eigen::Matrix< typename common_type< T1, T2 >::type, R, C > type
 
+

Detailed Description

+

template<typename T1, typename T2, int R, int C>
+struct stan::math::common_type< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >

+ + +

Definition at line 23 of file common_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1 , typename T2 , int R, int C>
+ + + + +
typedef Eigen::Matrix<typename common_type<T1, T2>::type, R, C> stan::math::common_type< Eigen::Matrix< T1, R, C >, Eigen::Matrix< T2, R, C > >::type
+
+ +

Definition at line 24 of file common_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1common__type_3_01std_1_1vector_3_01_t1_01_4_00_01std_1_1vector_3_01_t2_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1common__type_3_01std_1_1vector_3_01_t1_01_4_00_01std_1_1vector_3_01_t2_01_4_01_4-members.html new file mode 100644 index 00000000000..dd54869abbc --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1common__type_3_01std_1_1vector_3_01_t1_01_4_00_01std_1_1vector_3_01_t2_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::common_type< std::vector< T1 >, std::vector< T2 > > Member List
+
+
+ +

This is the complete list of members for stan::math::common_type< std::vector< T1 >, std::vector< T2 > >, including all inherited members.

+ + +
type typedefstan::math::common_type< std::vector< T1 >, std::vector< T2 > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1common__type_3_01std_1_1vector_3_01_t1_01_4_00_01std_1_1vector_3_01_t2_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1common__type_3_01std_1_1vector_3_01_t1_01_4_00_01std_1_1vector_3_01_t2_01_4_01_4.html new file mode 100644 index 00000000000..92314e3e38a --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1common__type_3_01std_1_1vector_3_01_t1_01_4_00_01std_1_1vector_3_01_t2_01_4_01_4.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::math::common_type< std::vector< T1 >, std::vector< T2 > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::common_type< std::vector< T1 >, std::vector< T2 > > Struct Template Reference
+
+
+ +

#include <common_type.hpp>

+ + + + +

+Public Types

typedef std::vector< typename common_type< T1, T2 >::typetype
 
+

Detailed Description

+

template<typename T1, typename T2>
+struct stan::math::common_type< std::vector< T1 >, std::vector< T2 > >

+ + +

Definition at line 18 of file common_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1 , typename T2 >
+ + + + +
typedef std::vector<typename common_type<T1, T2>::type> stan::math::common_type< std::vector< T1 >, std::vector< T2 > >::type
+
+ +

Definition at line 19 of file common_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__observer-members.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__observer-members.html new file mode 100644 index 00000000000..796737510dc --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__observer-members.html @@ -0,0 +1,118 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::coupled_ode_observer Member List
+
+
+ +

This is the complete list of members for stan::math::coupled_ode_observer, including all inherited members.

+ + + + + +
coupled_ode_observer(std::vector< std::vector< double > > &y_coupled)stan::math::coupled_ode_observerinlineexplicit
n_stan::math::coupled_ode_observer
operator()(const std::vector< double > &coupled_state, const double t)stan::math::coupled_ode_observerinline
y_coupled_stan::math::coupled_ode_observer
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__observer.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__observer.html new file mode 100644 index 00000000000..3aa85bd3a23 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__observer.html @@ -0,0 +1,255 @@ + + + + + + +Stan Math Library: stan::math::coupled_ode_observer Struct Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::coupled_ode_observer Struct Reference
+
+
+ +

Observer for the coupled states. + More...

+ +

#include <coupled_ode_observer.hpp>

+ + + + + + + + +

+Public Member Functions

 coupled_ode_observer (std::vector< std::vector< double > > &y_coupled)
 Construct a coupled ODE observer from the specified coupled vector. More...
 
void operator() (const std::vector< double > &coupled_state, const double t)
 Callback function for Boost's ODE solver to record values. More...
 
+ + + + + +

+Public Attributes

std::vector< std::vector< double > > & y_coupled_
 
int n_
 
+

Detailed Description

+

Observer for the coupled states.

+

Holds a reference to an externally defined vector of vectors passed in at construction time.

+ +

Definition at line 15 of file coupled_ode_observer.hpp.

+

Constructor & Destructor Documentation

+ +
+
+ + + + + +
+ + + + + + + + +
stan::math::coupled_ode_observer::coupled_ode_observer (std::vector< std::vector< double > > & y_coupled)
+
+inlineexplicit
+
+ +

Construct a coupled ODE observer from the specified coupled vector.

+
Parameters
+ + +
y_coupledreference to a vector of vector of doubles.
+
+
+ +

Definition at line 25 of file coupled_ode_observer.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
void stan::math::coupled_ode_observer::operator() (const std::vector< double > & coupled_state,
const double t 
)
+
+inline
+
+ +

Callback function for Boost's ODE solver to record values.

+
Parameters
+ + + +
coupled_statesolution at the specified time.
ttime of solution.
+
+
+ +

Definition at line 36 of file coupled_ode_observer.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + +
int stan::math::coupled_ode_observer::n_
+
+ +

Definition at line 17 of file coupled_ode_observer.hpp.

+ +
+
+ +
+
+ + + + +
std::vector<std::vector<double> >& stan::math::coupled_ode_observer::y_coupled_
+
+ +

Definition at line 16 of file coupled_ode_observer.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__system.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__system.html new file mode 100644 index 00000000000..060ac7fc1fa --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__system.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan::math::coupled_ode_system< F, T1, T2 > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::coupled_ode_system< F, T1, T2 > Struct Template Reference
+
+
+ +

Base template class for a coupled ordinary differential equation system, which adds sensitivities to the base system. + More...

+ +

#include <coupled_ode_system.hpp>

+

Detailed Description

+

template<typename F, typename T1, typename T2>
+struct stan::math::coupled_ode_system< F, T1, T2 >

+ +

Base template class for a coupled ordinary differential equation system, which adds sensitivities to the base system.

+

This template class declaration should not be instantiated directly — it is just here to serve as a base for its specializations, some of which are defined in namespace stan::aggrad.

+
Template Parameters
+ + + + +
Fthe functor for the base ode system
T1type of the initial state
T2type of the parameters
+
+
+ +

Definition at line 25 of file coupled_ode_system.hpp.

+

The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01stan_1_1math_1_1var_01_4-members.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01stan_1_1math_1_1var_01_4-members.html new file mode 100644 index 00000000000..d9e544a5efd --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01stan_1_1math_1_1var_01_4-members.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::coupled_ode_system< F, double, stan::math::var > Member List
+
+
+ +

This is the complete list of members for stan::math::coupled_ode_system< F, double, stan::math::var >, including all inherited members.

+ + + + + + + + + + + + + + + + +
coupled_ode_system(const F &f, const std::vector< double > &y0, const std::vector< stan::math::var > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)stan::math::coupled_ode_system< F, double, stan::math::var >inline
decouple_states(const std::vector< std::vector< double > > &y)stan::math::coupled_ode_system< F, double, stan::math::var >inline
f_stan::math::coupled_ode_system< F, double, stan::math::var >
initial_state()stan::math::coupled_ode_system< F, double, stan::math::var >inline
M_stan::math::coupled_ode_system< F, double, stan::math::var >
msgs_stan::math::coupled_ode_system< F, double, stan::math::var >
N_stan::math::coupled_ode_system< F, double, stan::math::var >
operator()(const std::vector< double > &z, std::vector< double > &dz_dt, double t)stan::math::coupled_ode_system< F, double, stan::math::var >inline
size() const stan::math::coupled_ode_system< F, double, stan::math::var >inline
size_stan::math::coupled_ode_system< F, double, stan::math::var >
theta_stan::math::coupled_ode_system< F, double, stan::math::var >
theta_dbl_stan::math::coupled_ode_system< F, double, stan::math::var >
x_stan::math::coupled_ode_system< F, double, stan::math::var >
x_int_stan::math::coupled_ode_system< F, double, stan::math::var >
y0_dbl_stan::math::coupled_ode_system< F, double, stan::math::var >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01stan_1_1math_1_1var_01_4.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..cae05ff8712 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01double_00_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,582 @@ + + + + + + +Stan Math Library: stan::math::coupled_ode_system< F, double, stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::coupled_ode_system< F, double, stan::math::var > Struct Template Reference
+
+
+ +

The coupled ODE system for known initial values and unknown parameters. + More...

+ +

#include <coupled_ode_system.hpp>

+ + + + + + + + + + + + + + + + + +

+Public Member Functions

 coupled_ode_system (const F &f, const std::vector< double > &y0, const std::vector< stan::math::var > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
 Construct a coupled ODE system with the specified base ODE system, base initial state, parameters, data, and a message stream. More...
 
void operator() (const std::vector< double > &z, std::vector< double > &dz_dt, double t)
 Assign the derivative vector with the system derivatives at the specified state and time. More...
 
size_t size () const
 Returns the size of the coupled system. More...
 
std::vector< double > initial_state ()
 Returns the initial state of the coupled system. More...
 
std::vector< std::vector< stan::math::var > > decouple_states (const std::vector< std::vector< double > > &y)
 Returns the base ODE system state corresponding to the specified coupled system state. More...
 
+ + + + + + + + + + + + + + + + + + + + + +

+Public Attributes

const F & f_
 
const std::vector< double > & y0_dbl_
 
const std::vector< stan::math::var > & theta_
 
std::vector< double > theta_dbl_
 
const std::vector< double > & x_
 
const std::vector< int > & x_int_
 
const size_t N_
 
const size_t M_
 
const size_t size_
 
std::ostream * msgs_
 
+

Detailed Description

+

template<typename F>
+struct stan::math::coupled_ode_system< F, double, stan::math::var >

+ +

The coupled ODE system for known initial values and unknown parameters.

+

If the base ODE state is size N and there are M parameters, the coupled system has N + N * M states.

+

The first N states correspond to the base system's N states: $ \frac{d x_n}{dt} $

+

The next M states correspond to the sensitivities of the parameters with respect to the first base system equation:

+\[ \frac{d x_{N+m}}{dt} = \frac{d}{dt} \frac{\partial x_1}{\partial \theta_m} \] +

+

The final M states correspond to the sensitivities with respect to the second base system equation, etc.

+
Template Parameters
+ + +
Ftype of functor for the base ode system.
+
+
+ +

Definition at line 63 of file coupled_ode_system.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::coupled_ode_system< F, double, stan::math::var >::coupled_ode_system (const F & f,
const std::vector< double > & y0,
const std::vector< stan::math::var > & theta,
const std::vector< double > & x,
const std::vector< int > & x_int,
std::ostream * msgs 
)
+
+inline
+
+ +

Construct a coupled ODE system with the specified base ODE system, base initial state, parameters, data, and a message stream.

+
Parameters
+ + + + + + + +
[in]fthe base ODE system functor.
[in]y0the initial state of the base ode.
[in]thetaparameters of the base ode.
[in]xreal data.
[in]x_intinteger data.
[in,out]msgsstream to which messages are printed.
+
+
+ +

Definition at line 87 of file coupled_ode_system.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + +
std::vector<std::vector<stan::math::var> > stan::math::coupled_ode_system< F, double, stan::math::var >::decouple_states (const std::vector< std::vector< double > > & y)
+
+inline
+
+ +

Returns the base ODE system state corresponding to the specified coupled system state.

+
Parameters
+ + +
ycoupled states after solving the ode
+
+
+ +

Definition at line 212 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + +
std::vector<double> stan::math::coupled_ode_system< F, double, stan::math::var >::initial_state ()
+
+inline
+
+ +

Returns the initial state of the coupled system.

+

Because the initial values are known, the initial state of the coupled system is the same as the initial state of the base ODE system.

+

This initial state returned is of size size() where the first N (base ODE system size) parameters are the initial conditions of the base ode system and the rest of the initial condition elements are 0.

+
Returns
the initial condition of the coupled system.
+ +

Definition at line 198 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::coupled_ode_system< F, double, stan::math::var >::operator() (const std::vector< double > & z,
std::vector< double > & dz_dt,
double t 
)
+
+inline
+
+ +

Assign the derivative vector with the system derivatives at the specified state and time.

+

The input state must be of size size(), and the output produced will be of the same size.

+
Parameters
+ + + + +
[in]zstate of the coupled ode system.
[out]dz_dtpopulated with the derivatives of the coupled system at the specified state and time.
[in]ttime.
+
+
+
Exceptions
+ + +
exceptionif the system function does not return the same number of derivatives as the state vector size.
+
+
+

y is the base ODE system state

+ +

Definition at line 124 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + +
size_t stan::math::coupled_ode_system< F, double, stan::math::var >::size () const
+
+inline
+
+ +

Returns the size of the coupled system.

+
Returns
size of the coupled system.
+ +

Definition at line 181 of file coupled_ode_system.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename F >
+ + + + +
const F& stan::math::coupled_ode_system< F, double, stan::math::var >::f_
+
+ +

Definition at line 64 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, double, stan::math::var >::M_
+
+ +

Definition at line 71 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
std::ostream* stan::math::coupled_ode_system< F, double, stan::math::var >::msgs_
+
+ +

Definition at line 73 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, double, stan::math::var >::N_
+
+ +

Definition at line 70 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, double, stan::math::var >::size_
+
+ +

Definition at line 72 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<stan::math::var>& stan::math::coupled_ode_system< F, double, stan::math::var >::theta_
+
+ +

Definition at line 66 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
std::vector<double> stan::math::coupled_ode_system< F, double, stan::math::var >::theta_dbl_
+
+ +

Definition at line 67 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<double>& stan::math::coupled_ode_system< F, double, stan::math::var >::x_
+
+ +

Definition at line 68 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<int>& stan::math::coupled_ode_system< F, double, stan::math::var >::x_int_
+
+ +

Definition at line 69 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<double>& stan::math::coupled_ode_system< F, double, stan::math::var >::y0_dbl_
+
+ +

Definition at line 65 of file coupled_ode_system.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01double_01_4-members.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01double_01_4-members.html new file mode 100644 index 00000000000..65b057a5b98 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01double_01_4-members.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::coupled_ode_system< F, stan::math::var, double > Member List
+
+
+ +

This is the complete list of members for stan::math::coupled_ode_system< F, stan::math::var, double >, including all inherited members.

+ + + + + + + + + + + + + + + + +
coupled_ode_system(const F &f, const std::vector< stan::math::var > &y0, const std::vector< double > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)stan::math::coupled_ode_system< F, stan::math::var, double >inline
decouple_states(const std::vector< std::vector< double > > &y)stan::math::coupled_ode_system< F, stan::math::var, double >inline
f_stan::math::coupled_ode_system< F, stan::math::var, double >
initial_state()stan::math::coupled_ode_system< F, stan::math::var, double >inline
M_stan::math::coupled_ode_system< F, stan::math::var, double >
msgs_stan::math::coupled_ode_system< F, stan::math::var, double >
N_stan::math::coupled_ode_system< F, stan::math::var, double >
operator()(const std::vector< double > &z, std::vector< double > &dz_dt, double t)stan::math::coupled_ode_system< F, stan::math::var, double >inline
size() const stan::math::coupled_ode_system< F, stan::math::var, double >inline
size_stan::math::coupled_ode_system< F, stan::math::var, double >
theta_dbl_stan::math::coupled_ode_system< F, stan::math::var, double >
x_stan::math::coupled_ode_system< F, stan::math::var, double >
x_int_stan::math::coupled_ode_system< F, stan::math::var, double >
y0_stan::math::coupled_ode_system< F, stan::math::var, double >
y0_dbl_stan::math::coupled_ode_system< F, stan::math::var, double >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01double_01_4.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01double_01_4.html new file mode 100644 index 00000000000..69b7653aaa3 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01double_01_4.html @@ -0,0 +1,581 @@ + + + + + + +Stan Math Library: stan::math::coupled_ode_system< F, stan::math::var, double > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::coupled_ode_system< F, stan::math::var, double > Struct Template Reference
+
+
+ +

The coupled ODE system for unknown initial values and known parameters. + More...

+ +

#include <coupled_ode_system.hpp>

+ + + + + + + + + + + + + + + + + +

+Public Member Functions

 coupled_ode_system (const F &f, const std::vector< stan::math::var > &y0, const std::vector< double > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
 Construct a coupled ODE system for an unknown initial state and known parameters givne the specified base system functor, base initial state, parameters, data, and an output stream for messages. More...
 
void operator() (const std::vector< double > &z, std::vector< double > &dz_dt, double t)
 Calculates the derivative of the coupled ode system with respect to the state y at time t. More...
 
size_t size () const
 Returns the size of the coupled system. More...
 
std::vector< double > initial_state ()
 Returns the initial state of the coupled system. More...
 
std::vector< std::vector< stan::math::var > > decouple_states (const std::vector< std::vector< double > > &y)
 Return the solutions to the basic ODE system, including appropriate autodiff partial derivatives, given the specified coupled system solution. More...
 
+ + + + + + + + + + + + + + + + + + + + + +

+Public Attributes

const F & f_
 
const std::vector< stan::math::var > & y0_
 
std::vector< double > y0_dbl_
 
const std::vector< double > & theta_dbl_
 
const std::vector< double > & x_
 
const std::vector< int > & x_int_
 
std::ostream * msgs_
 
const size_t N_
 
const size_t M_
 
const size_t size_
 
+

Detailed Description

+

template<typename F>
+struct stan::math::coupled_ode_system< F, stan::math::var, double >

+ +

The coupled ODE system for unknown initial values and known parameters.

+

If the original ODE has states of size N, the coupled system has N + N * N states. (derivatives of each state with respect to each initial value)

+

The coupled system has N + N * N states, where N is the size of the state vector in the base system.

+

The first N states correspond to the base system's N states: $ \frac{d x_n}{dt} $

+

The next N states correspond to the sensitivities of the initial conditions with respect to the to the first base system equation:

+\[ \frac{d x_{N+n}}{dt} = \frac{d}{dt} \frac{\partial x_1}{\partial y0_n} \] +

+

The next N states correspond to the sensitivities with respect to the second base system equation, etc.

+
Template Parameters
+ + +
Ftype of base ODE system functor
+
+
+ +

Definition at line 262 of file coupled_ode_system.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::coupled_ode_system< F, stan::math::var, double >::coupled_ode_system (const F & f,
const std::vector< stan::math::var > & y0,
const std::vector< double > & theta,
const std::vector< double > & x,
const std::vector< int > & x_int,
std::ostream * msgs 
)
+
+inline
+
+ +

Construct a coupled ODE system for an unknown initial state and known parameters givne the specified base system functor, base initial state, parameters, data, and an output stream for messages.

+
Parameters
+ + + + + + + +
[in]fbase ODE system functor.
[in]y0initial state of the base ODE.
[in]thetasystem parameters.
[in]xreal data.
[in]x_intinteger data.
[in,out]msgsoutput stream for messages.
+
+
+ +

Definition at line 287 of file coupled_ode_system.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + +
std::vector<std::vector<stan::math::var> > stan::math::coupled_ode_system< F, stan::math::var, double >::decouple_states (const std::vector< std::vector< double > > & y)
+
+inline
+
+ +

Return the solutions to the basic ODE system, including appropriate autodiff partial derivatives, given the specified coupled system solution.

+
Parameters
+ + +
ythe vector of the coupled states after solving the ode
+
+
+ +

Definition at line 410 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + +
std::vector<double> stan::math::coupled_ode_system< F, stan::math::var, double >::initial_state ()
+
+inline
+
+ +

Returns the initial state of the coupled system.

+

Because the starting state is unknown, the coupled system incorporates the initial conditions as parameters. The initial conditions for the coupled part of the system are set to zero along with the rest of the initial state, because the value of the initial state has been moved into the parameters.

+
Returns
the initial condition of the coupled system. This is a vector of length size() where all elements are 0.
+ +

Definition at line 398 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::coupled_ode_system< F, stan::math::var, double >::operator() (const std::vector< double > & z,
std::vector< double > & dz_dt,
double t 
)
+
+inline
+
+ +

Calculates the derivative of the coupled ode system with respect to the state y at time t.

+
Parameters
+ + + + +
[in]zthe current state of the coupled, shifted ode system. This is a a vector of double of length size().
[out]dz_dta vector of length size() with the derivatives of the coupled system evaluated with state y and time t.
[in]ttime.
+
+
+
Exceptions
+ + +
exceptionif the system functor does not return a derivative vector of the same size as the state vector.
+
+
+

y is the base ODE system state

+ +

Definition at line 323 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + +
size_t stan::math::coupled_ode_system< F, stan::math::var, double >::size () const
+
+inline
+
+ +

Returns the size of the coupled system.

+
Returns
size of the coupled system.
+ +

Definition at line 380 of file coupled_ode_system.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename F >
+ + + + +
const F& stan::math::coupled_ode_system< F, stan::math::var, double >::f_
+
+ +

Definition at line 263 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, stan::math::var, double >::M_
+
+ +

Definition at line 271 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
std::ostream* stan::math::coupled_ode_system< F, stan::math::var, double >::msgs_
+
+ +

Definition at line 269 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, stan::math::var, double >::N_
+
+ +

Definition at line 270 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, stan::math::var, double >::size_
+
+ +

Definition at line 272 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<double>& stan::math::coupled_ode_system< F, stan::math::var, double >::theta_dbl_
+
+ +

Definition at line 266 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<double>& stan::math::coupled_ode_system< F, stan::math::var, double >::x_
+
+ +

Definition at line 267 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<int>& stan::math::coupled_ode_system< F, stan::math::var, double >::x_int_
+
+ +

Definition at line 268 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<stan::math::var>& stan::math::coupled_ode_system< F, stan::math::var, double >::y0_
+
+ +

Definition at line 264 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
std::vector<double> stan::math::coupled_ode_system< F, stan::math::var, double >::y0_dbl_
+
+ +

Definition at line 265 of file coupled_ode_system.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01stan_1_1math_1_1var_01_4-members.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01stan_1_1math_1_1var_01_4-members.html new file mode 100644 index 00000000000..788010fc7b2 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01stan_1_1math_1_1var_01_4-members.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::coupled_ode_system< F, stan::math::var, stan::math::var > Member List
+
+
+ +

This is the complete list of members for stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >, including all inherited members.

+ + + + + + + + + + + + + + + + + +
coupled_ode_system(const F &f, const std::vector< stan::math::var > &y0, const std::vector< stan::math::var > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >inline
decouple_states(const std::vector< std::vector< double > > &y)stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >inline
f_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
initial_state()stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >inline
M_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
msgs_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
N_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
operator()(const std::vector< double > &z, std::vector< double > &dz_dt, double t)stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >inline
size() const stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >inline
size_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
theta_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
theta_dbl_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
x_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
x_int_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
y0_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
y0_dbl_stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01stan_1_1math_1_1var_01_4.html b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..2822a9ec072 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1coupled__ode__system_3_01_f_00_01stan_1_1math_1_1var_00_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,605 @@ + + + + + + +Stan Math Library: stan::math::coupled_ode_system< F, stan::math::var, stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::coupled_ode_system< F, stan::math::var, stan::math::var > Struct Template Reference
+
+
+ +

The coupled ode system for unknown intial values and unknown parameters. + More...

+ +

#include <coupled_ode_system.hpp>

+ + + + + + + + + + + + + + + + + +

+Public Member Functions

 coupled_ode_system (const F &f, const std::vector< stan::math::var > &y0, const std::vector< stan::math::var > &theta, const std::vector< double > &x, const std::vector< int > &x_int, std::ostream *msgs)
 Construct a coupled ODE system with unknown initial value and known parameters, given the base ODE system functor, the initial state of the base ODE, the parameters, data, and an output stream to which to write messages. More...
 
void operator() (const std::vector< double > &z, std::vector< double > &dz_dt, double t)
 Populates the derivative vector with derivatives of the coupled ODE system state with respect to time evaluated at the specified state and specified time. More...
 
size_t size () const
 Returns the size of the coupled system. More...
 
std::vector< double > initial_state ()
 Returns the initial state of the coupled system. More...
 
std::vector< std::vector< stan::math::var > > decouple_states (const std::vector< std::vector< double > > &y)
 Return the basic ODE solutions given the specified coupled system solutions, including the partials versus the parameters encoded in the autodiff results. More...
 
+ + + + + + + + + + + + + + + + + + + + + + + +

+Public Attributes

const F & f_
 
const std::vector< stan::math::var > & y0_
 
std::vector< double > y0_dbl_
 
const std::vector< stan::math::var > & theta_
 
std::vector< double > theta_dbl_
 
const std::vector< double > & x_
 
const std::vector< int > & x_int_
 
const size_t N_
 
const size_t M_
 
const size_t size_
 
std::ostream * msgs_
 
+

Detailed Description

+

template<typename F>
+struct stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >

+ +

The coupled ode system for unknown intial values and unknown parameters.

+

The coupled system has N + N * (N + M) states, where N is size of the base ODE state vector and M is the number of parameters.

+

The first N states correspond to the base system's N states: $ \frac{d x_n}{dt} $

+

The next N+M states correspond to the sensitivities of the initial conditions, then to the parameters with respect to the to the first base system equation:

+

+\[ \frac{d x_{N + n}}{dt} = \frac{d}{dt} \frac{\partial x_1}{\partial y0_n} \] +

+

+\[ \frac{d x_{N+N+m}}{dt} = \frac{d}{dt} \frac{\partial x_1}{\partial \theta_m} \] +

+

The next N+M states correspond to the sensitivities with respect to the second base system equation, etc.

+

If the original ode has a state vector of size N states and a parameter vector of size M, the coupled system has N + N * (N

    +
  • M) states. (derivatives of each state with respect to each initial value and each theta)
  • +
+
Template Parameters
+ + +
Fthe functor for the base ode system
+
+
+ +

Definition at line 474 of file coupled_ode_system.hpp.

+

Constructor & Destructor Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::coupled_ode_system (const F & f,
const std::vector< stan::math::var > & y0,
const std::vector< stan::math::var > & theta,
const std::vector< double > & x,
const std::vector< int > & x_int,
std::ostream * msgs 
)
+
+inline
+
+ +

Construct a coupled ODE system with unknown initial value and known parameters, given the base ODE system functor, the initial state of the base ODE, the parameters, data, and an output stream to which to write messages.

+
Parameters
+ + + + + + + +
[in]fthe base ode system functor.
[in]y0the initial state of the base ode.
[in]thetaparameters of the base ode.
[in]xreal data.
[in]x_intinteger data.
[in,out]msgsoutput stream to which to print messages.
+
+
+ +

Definition at line 500 of file coupled_ode_system.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + +
std::vector<std::vector<stan::math::var> > stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::decouple_states (const std::vector< std::vector< double > > & y)
+
+inline
+
+ +

Return the basic ODE solutions given the specified coupled system solutions, including the partials versus the parameters encoded in the autodiff results.

+
Parameters
+ + +
ythe vector of the coupled states after solving the ode
+
+
+ +

Definition at line 627 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + +
std::vector<double> stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::initial_state ()
+
+inline
+
+ +

Returns the initial state of the coupled system.

+

Because the initial state is unknown, the coupled system incorporates the initial condition offset from zero as a parameter, and hence the return of this function is a vector of zeros.

+
Returns
the initial condition of the coupled system. This is a vector of length size() where all elements are 0.
+ +

Definition at line 615 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + +
void stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::operator() (const std::vector< double > & z,
std::vector< double > & dz_dt,
double t 
)
+
+inline
+
+ +

Populates the derivative vector with derivatives of the coupled ODE system state with respect to time evaluated at the specified state and specified time.

+
Parameters
+ + + + +
[in]zthe current state of the coupled, shifted ode system, of size size().
[in,out]dz_dtpopulate with the derivatives of the coupled system evaluated at the specified state and time.
[in]ttime.
+
+
+
Exceptions
+ + +
exceptionif the base system does not return a derivative vector of the same size as the state vector.
+
+
+

y is the base ODE system state

+ +

Definition at line 540 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + + +
+ + + + + + + +
size_t stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::size () const
+
+inline
+
+ +

Returns the size of the coupled system.

+
Returns
size of the coupled system.
+ +

Definition at line 600 of file coupled_ode_system.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename F >
+ + + + +
const F& stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::f_
+
+ +

Definition at line 475 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::M_
+
+ +

Definition at line 483 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
std::ostream* stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::msgs_
+
+ +

Definition at line 485 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::N_
+
+ +

Definition at line 482 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const size_t stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::size_
+
+ +

Definition at line 484 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<stan::math::var>& stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::theta_
+
+ +

Definition at line 478 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
std::vector<double> stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::theta_dbl_
+
+ +

Definition at line 479 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<double>& stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::x_
+
+ +

Definition at line 480 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<int>& stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::x_int_
+
+ +

Definition at line 481 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
const std::vector<stan::math::var>& stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::y0_
+
+ +

Definition at line 476 of file coupled_ode_system.hpp.

+ +
+
+ +
+
+
+template<typename F >
+ + + + +
std::vector<double> stan::math::coupled_ode_system< F, stan::math::var, stan::math::var >::y0_dbl_
+
+ +

Definition at line 477 of file coupled_ode_system.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1detail_1_1bounded-members.html b/doc/api/html/structstan_1_1math_1_1detail_1_1bounded-members.html new file mode 100644 index 00000000000..2608c278c7c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1detail_1_1bounded-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::detail::bounded< T_y, T_low, T_high, y_is_vec > Member List
+
+
+ +

This is the complete list of members for stan::math::detail::bounded< T_y, T_low, T_high, y_is_vec >, including all inherited members.

+ + +
check(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)stan::math::detail::bounded< T_y, T_low, T_high, y_is_vec >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1detail_1_1bounded.html b/doc/api/html/structstan_1_1math_1_1detail_1_1bounded.html new file mode 100644 index 00000000000..d2e028ddc2b --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1detail_1_1bounded.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan::math::detail::bounded< T_y, T_low, T_high, y_is_vec > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::detail::bounded< T_y, T_low, T_high, y_is_vec > Struct Template Reference
+
+
+ +

#include <check_bounded.hpp>

+ + + + +

+Static Public Member Functions

static bool check (const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
 
+

Detailed Description

+

template<typename T_y, typename T_low, typename T_high, bool y_is_vec>
+struct stan::math::detail::bounded< T_y, T_low, T_high, y_is_vec >

+ + +

Definition at line 24 of file check_bounded.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T_y , typename T_low , typename T_high , bool y_is_vec>
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static bool stan::math::detail::bounded< T_y, T_low, T_high, y_is_vec >::check (const char * function,
const char * name,
const T_y & y,
const T_low & low,
const T_high & high 
)
+
+inlinestatic
+
+ +

Definition at line 25 of file check_bounded.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1detail_1_1bounded_3_01_t__y_00_01_t__low_00_01_t__high_00_01true_01_4-members.html b/doc/api/html/structstan_1_1math_1_1detail_1_1bounded_3_01_t__y_00_01_t__low_00_01_t__high_00_01true_01_4-members.html new file mode 100644 index 00000000000..d9c1937ecfa --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1detail_1_1bounded_3_01_t__y_00_01_t__low_00_01_t__high_00_01true_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::detail::bounded< T_y, T_low, T_high, true > Member List
+
+
+ +

This is the complete list of members for stan::math::detail::bounded< T_y, T_low, T_high, true >, including all inherited members.

+ + +
check(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)stan::math::detail::bounded< T_y, T_low, T_high, true >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1detail_1_1bounded_3_01_t__y_00_01_t__low_00_01_t__high_00_01true_01_4.html b/doc/api/html/structstan_1_1math_1_1detail_1_1bounded_3_01_t__y_00_01_t__low_00_01_t__high_00_01true_01_4.html new file mode 100644 index 00000000000..7b7a6243add --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1detail_1_1bounded_3_01_t__y_00_01_t__low_00_01_t__high_00_01true_01_4.html @@ -0,0 +1,188 @@ + + + + + + +Stan Math Library: stan::math::detail::bounded< T_y, T_low, T_high, true > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::detail::bounded< T_y, T_low, T_high, true > Struct Template Reference
+
+
+ +

#include <check_bounded.hpp>

+ + + + +

+Static Public Member Functions

static bool check (const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
 
+

Detailed Description

+

template<typename T_y, typename T_low, typename T_high>
+struct stan::math::detail::bounded< T_y, T_low, T_high, true >

+ + +

Definition at line 49 of file check_bounded.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T_y , typename T_low , typename T_high >
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
static bool stan::math::detail::bounded< T_y, T_low, T_high, true >::check (const char * function,
const char * name,
const T_y & y,
const T_low & low,
const T_high & high 
)
+
+inlinestatic
+
+ +

Definition at line 50 of file check_bounded.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1dummy.html b/doc/api/html/structstan_1_1math_1_1dummy.html new file mode 100644 index 00000000000..026d3c79561 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1dummy.html @@ -0,0 +1,123 @@ + + + + + + +Stan Math Library: stan::math::dummy Struct Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::dummy Struct Reference
+
+
+ +

Empty struct for use in boost::condtional<is_constant_struct<T1>::value, T1, dummy>::type as false condtion for safe indexing. + More...

+ +

#include <container_view.hpp>

+

Detailed Description

+

Empty struct for use in boost::condtional<is_constant_struct<T1>::value, T1, dummy>::type as false condtion for safe indexing.

+ +

Definition at line 53 of file container_view.hpp.

+

The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1fvar-members.html b/doc/api/html/structstan_1_1math_1_1fvar-members.html new file mode 100644 index 00000000000..effbe8bb3ea --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1fvar-members.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::fvar< T > Member List
+
+
+ +

This is the complete list of members for stan::math::fvar< T >, including all inherited members.

+ + + + + + + + + + + + + + + + + + + + + + + +
d_stan::math::fvar< T >
fvar()stan::math::fvar< T >inline
fvar(const fvar< T > &x)stan::math::fvar< T >inline
fvar(const TV &val, const TD &deriv)stan::math::fvar< T >inline
fvar(const TV &val)stan::math::fvar< T >inline
operator*=(const fvar< T > &x2)stan::math::fvar< T >inline
operator*=(double x2)stan::math::fvar< T >inline
operator++()stan::math::fvar< T >inline
operator++(int)stan::math::fvar< T >inline
operator+=(const fvar< T > &x2)stan::math::fvar< T >inline
operator+=(double x2)stan::math::fvar< T >inline
operator--()stan::math::fvar< T >inline
operator--(int)stan::math::fvar< T >inline
operator-=(const fvar< T > &x2)stan::math::fvar< T >inline
operator-=(double x2)stan::math::fvar< T >inline
operator/=(const fvar< T > &x2)stan::math::fvar< T >inline
operator/=(double x2)stan::math::fvar< T >inline
operator<<(std::ostream &os, const fvar< T > &v)stan::math::fvar< T >friend
tangent() const stan::math::fvar< T >inline
val() const stan::math::fvar< T >inline
val_stan::math::fvar< T >
value_type typedefstan::math::fvar< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1fvar.html b/doc/api/html/structstan_1_1math_1_1fvar.html new file mode 100644 index 00000000000..3551ff6e12a --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1fvar.html @@ -0,0 +1,791 @@ + + + + + + +Stan Math Library: stan::math::fvar< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::fvar< T > Struct Template Reference
+
+
+ +

#include <fvar.hpp>

+ + + + +

+Public Types

typedef fvar value_type
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

val () const
 
tangent () const
 
 fvar ()
 
 fvar (const fvar< T > &x)
 
template<typename TV , typename TD >
 fvar (const TV &val, const TD &deriv)
 
template<typename TV >
 fvar (const TV &val)
 
fvar< T > & operator+= (const fvar< T > &x2)
 
fvar< T > & operator+= (double x2)
 
fvar< T > & operator-= (const fvar< T > &x2)
 
fvar< T > & operator-= (double x2)
 
fvar< T > & operator*= (const fvar< T > &x2)
 
fvar< T > & operator*= (double x2)
 
fvar< T > & operator/= (const fvar< T > &x2)
 
fvar< T > & operator/= (double x2)
 
fvar< T > & operator++ ()
 
fvar< T > operator++ (int)
 
fvar< T > & operator-- ()
 
fvar< T > operator-- (int)
 
+ + + + + +

+Public Attributes

val_
 
d_
 
+ + + +

+Friends

std::ostream & operator<< (std::ostream &os, const fvar< T > &v)
 
+

Detailed Description

+

template<typename T>
+struct stan::math::fvar< T >

+ + +

Definition at line 13 of file fvar.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T>
+ + + + +
typedef fvar stan::math::fvar< T >::value_type
+
+ +

Definition at line 20 of file fvar.hpp.

+ +
+
+

Constructor & Destructor Documentation

+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + +
stan::math::fvar< T >::fvar ()
+
+inline
+
+ +

Definition at line 22 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
stan::math::fvar< T >::fvar (const fvar< T > & x)
+
+inline
+
+ +

Definition at line 24 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+
+template<typename TV , typename TD >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
stan::math::fvar< T >::fvar (const TV & val,
const TD & deriv 
)
+
+inline
+
+ +

Definition at line 30 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+
+template<typename TV >
+ + + + + +
+ + + + + + + + +
stan::math::fvar< T >::fvar (const TV & val)
+
+inline
+
+ +

Definition at line 37 of file fvar.hpp.

+ +
+
+

Member Function Documentation

+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T>& stan::math::fvar< T >::operator*= (const fvar< T > & x2)
+
+inline
+
+ +

Definition at line 76 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T>& stan::math::fvar< T >::operator*= (double x2)
+
+inline
+
+ +

Definition at line 84 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + +
fvar<T>& stan::math::fvar< T >::operator++ ()
+
+inline
+
+ +

Definition at line 110 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::fvar< T >::operator++ (int )
+
+inline
+
+ +

Definition at line 117 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T>& stan::math::fvar< T >::operator+= (const fvar< T > & x2)
+
+inline
+
+ +

Definition at line 46 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T>& stan::math::fvar< T >::operator+= (double x2)
+
+inline
+
+ +

Definition at line 54 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + +
fvar<T>& stan::math::fvar< T >::operator-- ()
+
+inline
+
+ +

Definition at line 125 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T> stan::math::fvar< T >::operator-- (int )
+
+inline
+
+ +

Definition at line 131 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T>& stan::math::fvar< T >::operator-= (const fvar< T > & x2)
+
+inline
+
+ +

Definition at line 61 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T>& stan::math::fvar< T >::operator-= (double x2)
+
+inline
+
+ +

Definition at line 69 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T>& stan::math::fvar< T >::operator/= (const fvar< T > & x2)
+
+inline
+
+ +

Definition at line 94 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + +
fvar<T>& stan::math::fvar< T >::operator/= (double x2)
+
+inline
+
+ +

Definition at line 102 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + +
T stan::math::fvar< T >::tangent () const
+
+inline
+
+ +

Definition at line 18 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + +
T stan::math::fvar< T >::val () const
+
+inline
+
+ +

Definition at line 17 of file fvar.hpp.

+ +
+
+

Friends And Related Function Documentation

+ +
+
+
+template<typename T>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
std::ostream& operator<< (std::ostream & os,
const fvar< T > & v 
)
+
+friend
+
+ +

Definition at line 139 of file fvar.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename T>
+ + + + +
T stan::math::fvar< T >::d_
+
+ +

Definition at line 15 of file fvar.hpp.

+ +
+
+ +
+
+
+template<typename T>
+ + + + +
T stan::math::fvar< T >::val_
+
+ +

Definition at line 14 of file fvar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1include__summand-members.html b/doc/api/html/structstan_1_1math_1_1include__summand-members.html new file mode 100644 index 00000000000..36150a6dd40 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1include__summand-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::include_summand< propto, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10 > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1include__summand.html b/doc/api/html/structstan_1_1math_1_1include__summand.html new file mode 100644 index 00000000000..7a926c61952 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1include__summand.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan::math::include_summand< propto, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10 > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::include_summand< propto, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10 > Struct Template Reference
+
+
+ +

Template metaprogram to calculate whether a summand needs to be included in a proportional (log) probability calculation. + More...

+ +

#include <include_summand.hpp>

+ + + + + +

+Public Types

enum  { value + }
 true if a term with the specified propto value and subterm types should be included in a proportionality calculation. More...
 
+

Detailed Description

+

template<bool propto, typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T7 = double, typename T8 = double, typename T9 = double, typename T10 = double>
+struct stan::math::include_summand< propto, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10 >

+ +

Template metaprogram to calculate whether a summand needs to be included in a proportional (log) probability calculation.

+

For usage, the first boolean parameter should be set to true if calculating a term up to proportionality. Other type parameters should be included for all of the types of variables in a term.

+

The value enum will be true if the propto parameter is false or if any of the other template arguments are not constants as defined by stan::is_constant<T>.

+
Template Parameters
+ + + +
proptotrue if calculating up to a proportionality constant.
T1First
+
+
+ +

Definition at line 36 of file include_summand.hpp.

+

Member Enumeration Documentation

+ +
+
+
+template<bool propto, typename T1 = double, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double, typename T7 = double, typename T8 = double, typename T9 = double, typename T10 = double>
+ + + + +
anonymous enum
+
+ +

true if a term with the specified propto value and subterm types should be included in a proportionality calculation.

+ + +
Enumerator
value  +
+ +

Definition at line 42 of file include_summand.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1index__type.html b/doc/api/html/structstan_1_1math_1_1index__type.html new file mode 100644 index 00000000000..8f295111aeb --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1index__type.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan::math::index_type< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::index_type< T > Struct Template Reference
+
+
+ +

Primary template class for the metaprogram to compute the index type of a container. + More...

+ +

#include <index_type.hpp>

+

Detailed Description

+

template<typename T>
+struct stan::math::index_type< T >

+ +

Primary template class for the metaprogram to compute the index type of a container.

+

Only the specializations have behavior that can be used, and all implement a typedef type for the type of the index given container T.

+

tparam T type of container.

+ +

Definition at line 19 of file index_type.hpp.

+

The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1index__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1index__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html new file mode 100644 index 00000000000..c1cefc0342c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1index__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::index_type< Eigen::Matrix< T, R, C > > Member List
+
+
+ +

This is the complete list of members for stan::math::index_type< Eigen::Matrix< T, R, C > >, including all inherited members.

+ + +
type typedefstan::math::index_type< Eigen::Matrix< T, R, C > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1index__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1index__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html new file mode 100644 index 00000000000..df2f3e3b7eb --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1index__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan::math::index_type< Eigen::Matrix< T, R, C > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::index_type< Eigen::Matrix< T, R, C > > Struct Template Reference
+
+
+ +

Template metaprogram defining typedef for the type of index for an Eigen matrix, vector, or row vector. + More...

+ +

#include <index_type.hpp>

+ + + + +

+Public Types

typedef Eigen::Matrix< T, R, C >::Index type
 
+

Detailed Description

+

template<typename T, int R, int C>
+struct stan::math::index_type< Eigen::Matrix< T, R, C > >

+ +

Template metaprogram defining typedef for the type of index for an Eigen matrix, vector, or row vector.

+
Template Parameters
+ + + + +
Ttype of matrix.
Rnumber of rows for matrix.
Cnumber of columns for matrix.
+
+
+ +

Definition at line 20 of file index_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + +
typedef Eigen::Matrix<T, R, C>::Index stan::math::index_type< Eigen::Matrix< T, R, C > >::type
+
+ +

Definition at line 21 of file index_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1index__type_3_01const_01_t_01_4-members.html b/doc/api/html/structstan_1_1math_1_1index__type_3_01const_01_t_01_4-members.html new file mode 100644 index 00000000000..195b28bac29 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1index__type_3_01const_01_t_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::index_type< const T > Member List
+
+
+ +

This is the complete list of members for stan::math::index_type< const T >, including all inherited members.

+ + +
type typedefstan::math::index_type< const T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1index__type_3_01const_01_t_01_4.html b/doc/api/html/structstan_1_1math_1_1index__type_3_01const_01_t_01_4.html new file mode 100644 index 00000000000..9504d505f64 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1index__type_3_01const_01_t_01_4.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan::math::index_type< const T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::index_type< const T > Struct Template Reference
+
+
+ +

Template class for metaprogram to compute the type of indexes used in a constant container type. + More...

+ +

#include <index_type.hpp>

+ + + + +

+Public Types

typedef index_type< T >::type type
 
+

Detailed Description

+

template<typename T>
+struct stan::math::index_type< const T >

+ +

Template class for metaprogram to compute the type of indexes used in a constant container type.

+
Template Parameters
+ + +
Ttype of container without const modifier.
+
+
+ +

Definition at line 30 of file index_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef index_type<T>::type stan::math::index_type< const T >::type
+
+ +

Definition at line 31 of file index_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1index__type_3_01std_1_1vector_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1index__type_3_01std_1_1vector_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..1bafe4fd3d3 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1index__type_3_01std_1_1vector_3_01_t_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::index_type< std::vector< T > > Member List
+
+
+ +

This is the complete list of members for stan::math::index_type< std::vector< T > >, including all inherited members.

+ + +
type typedefstan::math::index_type< std::vector< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1index__type_3_01std_1_1vector_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1index__type_3_01std_1_1vector_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..cc02b08f496 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1index__type_3_01std_1_1vector_3_01_t_01_4_01_4.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan::math::index_type< std::vector< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::index_type< std::vector< T > > Struct Template Reference
+
+
+ +

Template metaprogram class to compute the type of index for a standard vector. + More...

+ +

#include <index_type.hpp>

+ + + + + +

+Public Types

typedef std::vector< T >::size_type type
 Typedef for index of standard vectors. More...
 
+

Detailed Description

+

template<typename T>
+struct stan::math::index_type< std::vector< T > >

+ +

Template metaprogram class to compute the type of index for a standard vector.

+
Template Parameters
+ + +
Ttype of elements in standard vector.
+
+
+ +

Definition at line 18 of file index_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef std::vector<T>::size_type stan::math::index_type< std::vector< T > >::type
+
+ +

Typedef for index of standard vectors.

+ +

Definition at line 22 of file index_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1pass__type-members.html b/doc/api/html/structstan_1_1math_1_1pass__type-members.html new file mode 100644 index 00000000000..e0715eba2d3 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1pass__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::pass_type< T > Member List
+
+
+ +

This is the complete list of members for stan::math::pass_type< T >, including all inherited members.

+ + +
type typedefstan::math::pass_type< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1pass__type.html b/doc/api/html/structstan_1_1math_1_1pass__type.html new file mode 100644 index 00000000000..9f4707d9270 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1pass__type.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::math::pass_type< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::pass_type< T > Struct Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + +

+Public Types

typedef const T & type
 
+

Detailed Description

+

template<typename T>
+struct stan::math::pass_type< T >

+ + +

Definition at line 27 of file seq_view.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T>
+ + + + +
typedef const T& stan::math::pass_type< T >::type
+
+ +

Definition at line 28 of file seq_view.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1pass__type_3_01double_01_4-members.html b/doc/api/html/structstan_1_1math_1_1pass__type_3_01double_01_4-members.html new file mode 100644 index 00000000000..44c61fef7f6 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1pass__type_3_01double_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::pass_type< double > Member List
+
+
+ +

This is the complete list of members for stan::math::pass_type< double >, including all inherited members.

+ + +
type typedefstan::math::pass_type< double >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1pass__type_3_01double_01_4.html b/doc/api/html/structstan_1_1math_1_1pass__type_3_01double_01_4.html new file mode 100644 index 00000000000..765b454b95c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1pass__type_3_01double_01_4.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan::math::pass_type< double > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::pass_type< double > Struct Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + +

+Public Types

typedef double type
 
+

Detailed Description

+

template<>
+struct stan::math::pass_type< double >

+ + +

Definition at line 31 of file seq_view.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef double stan::math::pass_type< double >::type
+
+ +

Definition at line 32 of file seq_view.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1pass__type_3_01int_01_4-members.html b/doc/api/html/structstan_1_1math_1_1pass__type_3_01int_01_4-members.html new file mode 100644 index 00000000000..f677ded9940 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1pass__type_3_01int_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
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+ +
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+
+
+
stan::math::pass_type< int > Member List
+
+
+ +

This is the complete list of members for stan::math::pass_type< int >, including all inherited members.

+ + +
type typedefstan::math::pass_type< int >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1pass__type_3_01int_01_4.html b/doc/api/html/structstan_1_1math_1_1pass__type_3_01int_01_4.html new file mode 100644 index 00000000000..7582a783d6c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1pass__type_3_01int_01_4.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan::math::pass_type< int > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::pass_type< int > Struct Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + +

+Public Types

typedef int type
 
+

Detailed Description

+

template<>
+struct stan::math::pass_type< int >

+ + +

Definition at line 35 of file seq_view.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef int stan::math::pass_type< int >::type
+
+ +

Definition at line 36 of file seq_view.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct-members.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct-members.html new file mode 100644 index 00000000000..ec04bb37da7 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_struct< T, S > Member List
+
+
+ +

This is the complete list of members for stan::math::promote_scalar_struct< T, S >, including all inherited members.

+ + +
apply(S x)stan::math::promote_scalar_struct< T, S >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct.html new file mode 100644 index 00000000000..622c877e572 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_struct< T, S > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_struct< T, S > Struct Template Reference
+
+
+ +

General struct to hold static function for promoting underlying scalar types. + More...

+ +

#include <promote_scalar.hpp>

+ + + + + +

+Static Public Member Functions

static T apply (S x)
 Return the value of the input argument promoted to the type specified by the template parameter. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_struct< T, S >

+ +

General struct to hold static function for promoting underlying scalar types.

+
Template Parameters
+ + + +
Treturn type of nested static function.
Sinput type for nested static function, whose underlying scalar type must be assignable to T.
+
+
+ +

Definition at line 19 of file promote_scalar.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
static T stan::math::promote_scalar_struct< T, S >::apply (x)
+
+inlinestatic
+
+ +

Return the value of the input argument promoted to the type specified by the template parameter.

+

This is the base case for mismatching template parameter types in which the underlying scalar type of template parameter S is assignable to type T.

+
Parameters
+ + +
xinput of type S.
+
+
+
Returns
input promoted to have scalars of type T.
+ +

Definition at line 31 of file promote_scalar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00-1_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00-1_01_4_01_4-members.html new file mode 100644 index 00000000000..88d4d2622b8 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00-1_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
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+ +
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+
+
+
stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > > Member List
+
+
+ +

This is the complete list of members for stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > >, including all inherited members.

+ + +
apply(const Eigen::Matrix< S,-1,-1 > &x)stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00-1_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00-1_01_4_01_4.html new file mode 100644 index 00000000000..37c3c76c2c7 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00-1_01_4_01_4.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > > Struct Template Reference
+
+
+ +

Struct to hold static function for promoting underlying scalar types. + More...

+ +

#include <promote_scalar.hpp>

+ + + + + +

+Static Public Member Functions

static Eigen::Matrix< typename promote_scalar_type< T, S >::type,-1,-1 > apply (const Eigen::Matrix< S,-1,-1 > &x)
 Return the matrix consisting of the recursive promotion of the elements of the input matrix to the scalar type specified by the return template parameter. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > >

+ +

Struct to hold static function for promoting underlying scalar types.

+

This specialization is for Eigen matrix inputs.

+
Template Parameters
+ + + +
Treturn scalar type
Sinput matrix scalar type for static nested function, which must have a scalar type assignable to T
+
+
+ +

Definition at line 21 of file promote_scalar.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
static Eigen::Matrix<typename promote_scalar_type<T, S>::type, -1, -1> stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1,-1 > >::apply (const Eigen::Matrix< S,-1,-1 > & x)
+
+inlinestatic
+
+ +

Return the matrix consisting of the recursive promotion of the elements of the input matrix to the scalar type specified by the return template parameter.

+
Parameters
+ + +
xinput matrix.
+
+
+
Returns
matrix with values promoted from input vector.
+ +

Definition at line 31 of file promote_scalar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00_011_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00_011_01_4_01_4-members.html new file mode 100644 index 00000000000..e6495e9ebc4 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00_011_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > > Member List
+
+
+ +

This is the complete list of members for stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > >, including all inherited members.

+ + +
apply(const Eigen::Matrix< S,-1, 1 > &x)stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00_011_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00_011_01_4_01_4.html new file mode 100644 index 00000000000..22bd9619b89 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00-1_00_011_01_4_01_4.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > > Struct Template Reference
+
+
+ +

Struct to hold static function for promoting underlying scalar types. + More...

+ +

#include <promote_scalar.hpp>

+ + + + + +

+Static Public Member Functions

static Eigen::Matrix< typename promote_scalar_type< T, S >::type,-1, 1 > apply (const Eigen::Matrix< S,-1, 1 > &x)
 Return the row vector consisting of the recursive promotion of the elements of the input row vector to the scalar type specified by the return template parameter. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > >

+ +

Struct to hold static function for promoting underlying scalar types.

+

This specialization is for Eigen row vector inputs.

+
Template Parameters
+ + + +
Treturn scalar type
Sinput matrix scalar type for static nested function, which must have a scalar type assignable to T
+
+
+ +

Definition at line 79 of file promote_scalar.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
static Eigen::Matrix<typename promote_scalar_type<T, S>::type, -1, 1> stan::math::promote_scalar_struct< T, Eigen::Matrix< S,-1, 1 > >::apply (const Eigen::Matrix< S,-1, 1 > & x)
+
+inlinestatic
+
+ +

Return the row vector consisting of the recursive promotion of the elements of the input row vector to the scalar type specified by the return template parameter.

+
Parameters
+ + +
xinput row vector.
+
+
+
Returns
row vector with values promoted from input vector.
+ +

Definition at line 89 of file promote_scalar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00-1_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00-1_01_4_01_4-members.html new file mode 100644 index 00000000000..52db3f13221 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00-1_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > > Member List
+
+
+ +

This is the complete list of members for stan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > >, including all inherited members.

+ + +
apply(const Eigen::Matrix< S, 1,-1 > &x)stan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00-1_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00-1_01_4_01_4.html new file mode 100644 index 00000000000..48ef3d64e68 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00-1_01_4_01_4.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > > Struct Template Reference
+
+
+ +

Struct to hold static function for promoting underlying scalar types. + More...

+ +

#include <promote_scalar.hpp>

+ + + + + +

+Static Public Member Functions

static Eigen::Matrix< typename promote_scalar_type< T, S >::type, 1,-1 > apply (const Eigen::Matrix< S, 1,-1 > &x)
 Return the column vector consisting of the recursive promotion of the elements of the input column vector to the scalar type specified by the return template parameter. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > >

+ +

Struct to hold static function for promoting underlying scalar types.

+

This specialization is for Eigen column vector inputs.

+
Template Parameters
+ + + +
Treturn scalar type
Sinput matrix scalar type for static nested function, which must have a scalar type assignable to T
+
+
+ +

Definition at line 50 of file promote_scalar.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
static Eigen::Matrix<typename promote_scalar_type<T, S>::type, 1, -1> stan::math::promote_scalar_struct< T, Eigen::Matrix< S, 1,-1 > >::apply (const Eigen::Matrix< S, 1,-1 > & x)
+
+inlinestatic
+
+ +

Return the column vector consisting of the recursive promotion of the elements of the input column vector to the scalar type specified by the return template parameter.

+
Parameters
+ + +
xinput column vector.
+
+
+
Returns
column vector with values promoted from input vector.
+ +

Definition at line 60 of file promote_scalar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_t_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_t_01_4-members.html new file mode 100644 index 00000000000..44e60aa26a2 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_t_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_struct< T, T > Member List
+
+
+ +

This is the complete list of members for stan::math::promote_scalar_struct< T, T >, including all inherited members.

+ + +
apply(const T &x)stan::math::promote_scalar_struct< T, T >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_t_01_4.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_t_01_4.html new file mode 100644 index 00000000000..c2dbd616a40 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01_t_01_4.html @@ -0,0 +1,181 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_struct< T, T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_struct< T, T > Struct Template Reference
+
+
+ +

Struct to hold static function for promoting underlying scalar types. + More...

+ +

#include <promote_scalar.hpp>

+ + + + + +

+Static Public Member Functions

static T apply (const T &x)
 Return the unmodified input. More...
 
+

Detailed Description

+

template<typename T>
+struct stan::math::promote_scalar_struct< T, T >

+ +

Struct to hold static function for promoting underlying scalar types.

+

This specialization is for equal input and output types of function types.

+
Template Parameters
+ + +
Tinput and return type of nested static function.
+
+
+ +

Definition at line 44 of file promote_scalar.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
static T stan::math::promote_scalar_struct< T, T >::apply (const T & x)
+
+inlinestatic
+
+ +

Return the unmodified input.

+
Parameters
+ + +
xinput of type T.
+
+
+
Returns
input unmodified.
+ +

Definition at line 51 of file promote_scalar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html new file mode 100644 index 00000000000..4d60ef5b57e --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_struct< T, std::vector< S > > Member List
+
+
+ +

This is the complete list of members for stan::math::promote_scalar_struct< T, std::vector< S > >, including all inherited members.

+ + +
apply(const std::vector< S > &x)stan::math::promote_scalar_struct< T, std::vector< S > >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html new file mode 100644 index 00000000000..62f5d02f1d9 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__struct_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html @@ -0,0 +1,182 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_struct< T, std::vector< S > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_struct< T, std::vector< S > > Struct Template Reference
+
+
+ +

Struct to hold static function for promoting underlying scalar types. + More...

+ +

#include <promote_scalar.hpp>

+ + + + + +

+Static Public Member Functions

static std::vector< typename promote_scalar_type< T, S >::type > apply (const std::vector< S > &x)
 Return the standard vector consisting of the recursive promotion of the elements of the input standard vector to the scalar type specified by the return template parameter. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_struct< T, std::vector< S > >

+ +

Struct to hold static function for promoting underlying scalar types.

+

This specialization is for standard vector inputs.

+
Template Parameters
+ + + +
Treturn scalar type
Sinput type for standard vector elements in static nested function, which must have an underlying scalar type assignable to T.
+
+
+ +

Definition at line 22 of file promote_scalar.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + + +
+ + + + + + + + +
static std::vector<typename promote_scalar_type<T, S>::type> stan::math::promote_scalar_struct< T, std::vector< S > >::apply (const std::vector< S > & x)
+
+inlinestatic
+
+ +

Return the standard vector consisting of the recursive promotion of the elements of the input standard vector to the scalar type specified by the return template parameter.

+
Parameters
+ + +
xinput standard vector.
+
+
+
Returns
standard vector with values promoted from input vector.
+ +

Definition at line 32 of file promote_scalar.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type-members.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type-members.html new file mode 100644 index 00000000000..0afe41ea6c3 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_type< T, S > Member List
+
+
+ +

This is the complete list of members for stan::math::promote_scalar_type< T, S >, including all inherited members.

+ + +
type typedefstan::math::promote_scalar_type< T, S >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type.html new file mode 100644 index 00000000000..72a995f89d9 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_type< T, S > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_type< T, S > Struct Template Reference
+
+
+ +

Template metaprogram to calculate a type for converting a convertible type. + More...

+ +

#include <promote_scalar_type.hpp>

+ + + + + +

+Public Types

typedef T type
 The promoted type. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_type< T, S >

+ +

Template metaprogram to calculate a type for converting a convertible type.

+

This is the base case.

+
Template Parameters
+ + + +
Tresult scalar type.
Sinput type
+
+
+ +

Definition at line 15 of file promote_scalar_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T, typename S>
+ + + + +
typedef T stan::math::promote_scalar_type< T, S >::type
+
+ +

The promoted type.

+ +

Definition at line 19 of file promote_scalar_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eia6a45e8e9b504fc35f96b001b609d995.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eia6a45e8e9b504fc35f96b001b609d995.html new file mode 100644 index 00000000000..b57d81998d6 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eia6a45e8e9b504fc35f96b001b609d995.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_type< T, Eigen::Matrix< S, 1, Eigen::Dynamic > > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html new file mode 100644 index 00000000000..501865fcd73 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_011_00_01_eigen_1_1_dynamic_01_4_01_4.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_type< T, Eigen::Matrix< S, 1, Eigen::Dynamic > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_type< T, Eigen::Matrix< S, 1, Eigen::Dynamic > > Struct Template Reference
+
+
+ +

Template metaprogram to calculate a type for a row vector whose underlying scalar is converted from the second template parameter type to the first. + More...

+ +

#include <promote_scalar_type.hpp>

+ + + + + +

+Public Types

typedef Eigen::Matrix< typename promote_scalar_type< T, S >::type, 1, Eigen::Dynamic > type
 The promoted type. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_type< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >

+ +

Template metaprogram to calculate a type for a row vector whose underlying scalar is converted from the second template parameter type to the first.

+
Template Parameters
+ + + +
Tresult scalar type.
Sinput row vector scalar type
+
+
+ +

Definition at line 62 of file promote_scalar_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + +
typedef Eigen::Matrix<typename promote_scalar_type<T, S>::type, 1, Eigen::Dynamic> stan::math::promote_scalar_type< T, Eigen::Matrix< S, 1, Eigen::Dynamic > >::type
+
+ +

The promoted type.

+ +

Definition at line 68 of file promote_scalar_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_113ef15935bb161dd1b5f33fbfe2aaa09.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_113ef15935bb161dd1b5f33fbfe2aaa09.html new file mode 100644 index 00000000000..d195fb9af61 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_113ef15935bb161dd1b5f33fbfe2aaa09.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_18da53f05c7a1ffa21962d8ed9d876a8b.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_18da53f05c7a1ffa21962d8ed9d876a8b.html new file mode 100644 index 00000000000..bcb16fca2de --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_18da53f05c7a1ffa21962d8ed9d876a8b.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html new file mode 100644 index 00000000000..730aac8c5a6 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1_dynamic_00_011_01_4_01_4.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > > Struct Template Reference
+
+
+ +

Template metaprogram to calculate a type for a vector whose underlying scalar is converted from the second template parameter type to the first. + More...

+ +

#include <promote_scalar_type.hpp>

+ + + + + +

+Public Types

typedef Eigen::Matrix< typename promote_scalar_type< T, S >::type, Eigen::Dynamic, 1 > type
 The promoted type. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >

+ +

Template metaprogram to calculate a type for a vector whose underlying scalar is converted from the second template parameter type to the first.

+
Template Parameters
+ + + +
Tresult scalar type.
Sinput vector scalar type
+
+
+ +

Definition at line 43 of file promote_scalar_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + +
typedef Eigen::Matrix<typename promote_scalar_type<T, S>::type, Eigen::Dynamic, 1> stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, 1 > >::type
+
+ +

The promoted type.

+ +

Definition at line 49 of file promote_scalar_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1cc87c7d31d6c5454918a83df72a8f3b0.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1cc87c7d31d6c5454918a83df72a8f3b0.html new file mode 100644 index 00000000000..4728e2fcb37 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01_eigen_1_1_matrix_3_01_s_00_01_eigen_1_1cc87c7d31d6c5454918a83df72a8f3b0.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > > Struct Template Reference
+
+
+ +

Template metaprogram to calculate a type for a matrix whose underlying scalar is converted from the second template parameter type to the first. + More...

+ +

#include <promote_scalar_type.hpp>

+ + + + + +

+Public Types

typedef Eigen::Matrix< typename promote_scalar_type< T, S >::type, Eigen::Dynamic, Eigen::Dynamic > type
 The promoted type. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >

+ +

Template metaprogram to calculate a type for a matrix whose underlying scalar is converted from the second template parameter type to the first.

+

This is the case for a vector container type.

+
Template Parameters
+ + + +
Tresult scalar type.
Sinput matrix scalar type
+
+
+ +

Definition at line 23 of file promote_scalar_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + +
typedef Eigen::Matrix<typename promote_scalar_type<T, S>::type, Eigen::Dynamic, Eigen::Dynamic> stan::math::promote_scalar_type< T, Eigen::Matrix< S, Eigen::Dynamic, Eigen::Dynamic > >::type
+
+ +

The promoted type.

+ +

Definition at line 30 of file promote_scalar_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html new file mode 100644 index 00000000000..cfef4e240d6 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promote_scalar_type< T, std::vector< S > > Member List
+
+
+ +

This is the complete list of members for stan::math::promote_scalar_type< T, std::vector< S > >, including all inherited members.

+ + +
type typedefstan::math::promote_scalar_type< T, std::vector< S > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html new file mode 100644 index 00000000000..469bedc8a37 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promote__scalar__type_3_01_t_00_01std_1_1vector_3_01_s_01_4_01_4.html @@ -0,0 +1,162 @@ + + + + + + +Stan Math Library: stan::math::promote_scalar_type< T, std::vector< S > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promote_scalar_type< T, std::vector< S > > Struct Template Reference
+
+
+ +

Template metaprogram to calculate a type for a container whose underlying scalar is converted from the second template parameter type to the first. + More...

+ +

#include <promote_scalar_type.hpp>

+ + + + + +

+Public Types

typedef std::vector< typename promote_scalar_type< T, S >::typetype
 The promoted type. More...
 
+

Detailed Description

+

template<typename T, typename S>
+struct stan::math::promote_scalar_type< T, std::vector< S > >

+ +

Template metaprogram to calculate a type for a container whose underlying scalar is converted from the second template parameter type to the first.

+
Template Parameters
+ + + +
Tresult scalar type.
Sinput type
+
+
+ +

Definition at line 19 of file promote_scalar_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , typename S >
+ + + + +
typedef std::vector<typename promote_scalar_type<T, S>::type> stan::math::promote_scalar_type< T, std::vector< S > >::type
+
+ +

The promoted type.

+ +

Definition at line 23 of file promote_scalar_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter-members.html b/doc/api/html/structstan_1_1math_1_1promoter-members.html new file mode 100644 index 00000000000..2eb8fe90e19 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promoter< F, T > Member List
+
+
+ +

This is the complete list of members for stan::math::promoter< F, T >, including all inherited members.

+ + + +
promote(const F &u, T &t)stan::math::promoter< F, T >inlinestatic
promote_to(const F &u)stan::math::promoter< F, T >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter.html b/doc/api/html/structstan_1_1math_1_1promoter.html new file mode 100644 index 00000000000..74a53ce6938 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter.html @@ -0,0 +1,200 @@ + + + + + + +Stan Math Library: stan::math::promoter< F, T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promoter< F, T > Struct Template Reference
+
+
+ +

#include <promoter.hpp>

+ + + + + + +

+Static Public Member Functions

static void promote (const F &u, T &t)
 
static T promote_to (const F &u)
 
+

Detailed Description

+

template<typename F, typename T>
+struct stan::math::promoter< F, T >

+ + +

Definition at line 14 of file promoter.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename F, typename T>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
static void stan::math::promoter< F, T >::promote (const F & u,
T & t 
)
+
+inlinestatic
+
+ +

Definition at line 15 of file promoter.hpp.

+ +
+
+ +
+
+
+template<typename F, typename T>
+ + + + + +
+ + + + + + + + +
static T stan::math::promoter< F, T >::promote_to (const F & u)
+
+inlinestatic
+
+ +

Definition at line 18 of file promoter.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_f_00_01_r_00_01_c_01_4_00_01_eigen_1_142b48fda94601374e41a81325f3f7b84.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_f_00_01_r_00_01_c_01_4_00_01_eigen_1_142b48fda94601374e41a81325f3f7b84.html new file mode 100644 index 00000000000..d15e4aefa25 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_f_00_01_r_00_01_c_01_4_00_01_eigen_1_142b48fda94601374e41a81325f3f7b84.html @@ -0,0 +1,200 @@ + + + + + + +Stan Math Library: stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > > Struct Template Reference
+
+
+ +

#include <promoter.hpp>

+ + + + + + +

+Static Public Member Functions

static void promote (const Eigen::Matrix< F, R, C > &u, Eigen::Matrix< T, R, C > &t)
 
static Eigen::Matrix< T, R, C > promote_to (const Eigen::Matrix< F, R, C > &u)
 
+

Detailed Description

+

template<typename F, typename T, int R, int C>
+struct stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > >

+ + +

Definition at line 63 of file promoter.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename F , typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
static void stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > >::promote (const Eigen::Matrix< F, R, C > & u,
Eigen::Matrix< T, R, C > & t 
)
+
+inlinestatic
+
+ +

Definition at line 64 of file promoter.hpp.

+ +
+
+ +
+
+
+template<typename F , typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
static Eigen::Matrix<T, R, C> stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > >::promote_to (const Eigen::Matrix< F, R, C > & u)
+
+inlinestatic
+
+ +

Definition at line 71 of file promoter.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_f_00_01_r_00_01_c_01_4_00_01_eigen_1_19fcbf4e7bc8e106173bfa338a15054ff.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_f_00_01_r_00_01_c_01_4_00_01_eigen_1_19fcbf4e7bc8e106173bfa338a15054ff.html new file mode 100644 index 00000000000..601a24245e6 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_f_00_01_r_00_01_c_01_4_00_01_eigen_1_19fcbf4e7bc8e106173bfa338a15054ff.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > > Member List
+
+
+ +

This is the complete list of members for stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > >, including all inherited members.

+ + + +
promote(const Eigen::Matrix< F, R, C > &u, Eigen::Matrix< T, R, C > &t)stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > >inlinestatic
promote_to(const Eigen::Matrix< F, R, C > &u)stan::math::promoter< Eigen::Matrix< F, R, C >, Eigen::Matrix< T, R, C > >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01_eigen_1_12d7fadf0560f1f2f3abc5388b7666f9c.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01_eigen_1_12d7fadf0560f1f2f3abc5388b7666f9c.html new file mode 100644 index 00000000000..6323b0ac98c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01_eigen_1_12d7fadf0560f1f2f3abc5388b7666f9c.html @@ -0,0 +1,200 @@ + + + + + + +Stan Math Library: stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > > Struct Template Reference
+
+
+ +

#include <promoter.hpp>

+ + + + + + +

+Static Public Member Functions

static void promote (const Eigen::Matrix< T, R, C > &u, Eigen::Matrix< T, R, C > &t)
 
static Eigen::Matrix< T, R, C > promote_to (const Eigen::Matrix< T, R, C > &u)
 
+

Detailed Description

+

template<typename T, int R, int C>
+struct stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > >

+ + +

Definition at line 80 of file promoter.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
static void stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > >::promote (const Eigen::Matrix< T, R, C > & u,
Eigen::Matrix< T, R, C > & t 
)
+
+inlinestatic
+
+ +

Definition at line 81 of file promoter.hpp.

+ +
+
+ +
+
+
+template<typename T , int R, int C>
+ + + + + +
+ + + + + + + + +
static Eigen::Matrix<T, R, C> stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > >::promote_to (const Eigen::Matrix< T, R, C > & u)
+
+inlinestatic
+
+ +

Definition at line 86 of file promoter.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01_eigen_1_1ab38afe2feaa91a91579e3639d1f03b0.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01_eigen_1_1ab38afe2feaa91a91579e3639d1f03b0.html new file mode 100644 index 00000000000..862ef10e15a --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_00_01_eigen_1_1ab38afe2feaa91a91579e3639d1f03b0.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > > Member List
+
+
+ +

This is the complete list of members for stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > >, including all inherited members.

+ + + +
promote(const Eigen::Matrix< T, R, C > &u, Eigen::Matrix< T, R, C > &t)stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > >inlinestatic
promote_to(const Eigen::Matrix< T, R, C > &u)stan::math::promoter< Eigen::Matrix< T, R, C >, Eigen::Matrix< T, R, C > >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01_t_00_01_t_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01_t_00_01_t_01_4-members.html new file mode 100644 index 00000000000..e7d1f2fcd5f --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01_t_00_01_t_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promoter< T, T > Member List
+
+
+ +

This is the complete list of members for stan::math::promoter< T, T >, including all inherited members.

+ + + +
promote(const T &u, T &t)stan::math::promoter< T, T >inlinestatic
promote_to(const T &u)stan::math::promoter< T, T >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01_t_00_01_t_01_4.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01_t_00_01_t_01_4.html new file mode 100644 index 00000000000..a0150de579a --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01_t_00_01_t_01_4.html @@ -0,0 +1,200 @@ + + + + + + +Stan Math Library: stan::math::promoter< T, T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promoter< T, T > Struct Template Reference
+
+
+ +

#include <promoter.hpp>

+ + + + + + +

+Static Public Member Functions

static void promote (const T &u, T &t)
 
static T promote_to (const T &u)
 
+

Detailed Description

+

template<typename T>
+struct stan::math::promoter< T, T >

+ + +

Definition at line 24 of file promoter.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
static void stan::math::promoter< T, T >::promote (const T & u,
T & t 
)
+
+inlinestatic
+
+ +

Definition at line 25 of file promoter.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
static T stan::math::promoter< T, T >::promote_to (const T & u)
+
+inlinestatic
+
+ +

Definition at line 28 of file promoter.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_f_01_4_00_01std_1_1vector_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_f_01_4_00_01std_1_1vector_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..15ab362ee64 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_f_01_4_00_01std_1_1vector_3_01_t_01_4_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promoter< std::vector< F >, std::vector< T > > Member List
+
+
+ +

This is the complete list of members for stan::math::promoter< std::vector< F >, std::vector< T > >, including all inherited members.

+ + + +
promote(const std::vector< F > &u, std::vector< T > &t)stan::math::promoter< std::vector< F >, std::vector< T > >inlinestatic
promote_to(const std::vector< F > &u)stan::math::promoter< std::vector< F >, std::vector< T > >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_f_01_4_00_01std_1_1vector_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_f_01_4_00_01std_1_1vector_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..33128d62c64 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_f_01_4_00_01std_1_1vector_3_01_t_01_4_01_4.html @@ -0,0 +1,200 @@ + + + + + + +Stan Math Library: stan::math::promoter< std::vector< F >, std::vector< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promoter< std::vector< F >, std::vector< T > > Struct Template Reference
+
+
+ +

#include <promoter.hpp>

+ + + + + + +

+Static Public Member Functions

static void promote (const std::vector< F > &u, std::vector< T > &t)
 
static std::vector< T > promote_to (const std::vector< F > &u)
 
+

Detailed Description

+

template<typename F, typename T>
+struct stan::math::promoter< std::vector< F >, std::vector< T > >

+ + +

Definition at line 35 of file promoter.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename F , typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
static void stan::math::promoter< std::vector< F >, std::vector< T > >::promote (const std::vector< F > & u,
std::vector< T > & t 
)
+
+inlinestatic
+
+ +

Definition at line 36 of file promoter.hpp.

+ +
+
+ +
+
+
+template<typename F , typename T >
+ + + + + +
+ + + + + + + + +
static std::vector<T> stan::math::promoter< std::vector< F >, std::vector< T > >::promote_to (const std::vector< F > & u)
+
+inlinestatic
+
+ +

Definition at line 43 of file promoter.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_t_01_4_00_01std_1_1vector_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_t_01_4_00_01std_1_1vector_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..e19254fd39f --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_t_01_4_00_01std_1_1vector_3_01_t_01_4_01_4-members.html @@ -0,0 +1,116 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::promoter< std::vector< T >, std::vector< T > > Member List
+
+
+ +

This is the complete list of members for stan::math::promoter< std::vector< T >, std::vector< T > >, including all inherited members.

+ + + +
promote(const std::vector< T > &u, std::vector< T > &t)stan::math::promoter< std::vector< T >, std::vector< T > >inlinestatic
promote_to(const std::vector< T > &u)stan::math::promoter< std::vector< T >, std::vector< T > >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_t_01_4_00_01std_1_1vector_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_t_01_4_00_01std_1_1vector_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..70ed9a6a50c --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1promoter_3_01std_1_1vector_3_01_t_01_4_00_01std_1_1vector_3_01_t_01_4_01_4.html @@ -0,0 +1,200 @@ + + + + + + +Stan Math Library: stan::math::promoter< std::vector< T >, std::vector< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::promoter< std::vector< T >, std::vector< T > > Struct Template Reference
+
+
+ +

#include <promoter.hpp>

+ + + + + + +

+Static Public Member Functions

static void promote (const std::vector< T > &u, std::vector< T > &t)
 
static std::vector< T > promote_to (const std::vector< T > &u)
 
+

Detailed Description

+

template<typename T>
+struct stan::math::promoter< std::vector< T >, std::vector< T > >

+ + +

Definition at line 51 of file promoter.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
static void stan::math::promoter< std::vector< T >, std::vector< T > >::promote (const std::vector< T > & u,
std::vector< T > & t 
)
+
+inlinestatic
+
+ +

Definition at line 52 of file promoter.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
static std::vector<T> stan::math::promoter< std::vector< T >, std::vector< T > >::promote_to (const std::vector< T > & u)
+
+inlinestatic
+
+ +

Definition at line 56 of file promoter.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1store__type-members.html b/doc/api/html/structstan_1_1math_1_1store__type-members.html new file mode 100644 index 00000000000..96dbbf6e033 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1store__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::store_type< T > Member List
+
+
+ +

This is the complete list of members for stan::math::store_type< T >, including all inherited members.

+ + +
type typedefstan::math::store_type< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1store__type.html b/doc/api/html/structstan_1_1math_1_1store__type.html new file mode 100644 index 00000000000..6af4d58d58e --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1store__type.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::math::store_type< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::store_type< T > Struct Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + +

+Public Types

typedef const T & type
 
+

Detailed Description

+

template<typename T>
+struct stan::math::store_type< T >

+ + +

Definition at line 13 of file seq_view.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T>
+ + + + +
typedef const T& stan::math::store_type< T >::type
+
+ +

Definition at line 14 of file seq_view.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1store__type_3_01double_01_4-members.html b/doc/api/html/structstan_1_1math_1_1store__type_3_01double_01_4-members.html new file mode 100644 index 00000000000..2526c2e07d9 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1store__type_3_01double_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::store_type< double > Member List
+
+
+ +

This is the complete list of members for stan::math::store_type< double >, including all inherited members.

+ + +
type typedefstan::math::store_type< double >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1store__type_3_01double_01_4.html b/doc/api/html/structstan_1_1math_1_1store__type_3_01double_01_4.html new file mode 100644 index 00000000000..44893837289 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1store__type_3_01double_01_4.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan::math::store_type< double > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::store_type< double > Struct Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + +

+Public Types

typedef const double type
 
+

Detailed Description

+

template<>
+struct stan::math::store_type< double >

+ + +

Definition at line 17 of file seq_view.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef const double stan::math::store_type< double >::type
+
+ +

Definition at line 18 of file seq_view.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1store__type_3_01int_01_4-members.html b/doc/api/html/structstan_1_1math_1_1store__type_3_01int_01_4-members.html new file mode 100644 index 00000000000..09a6e4aa1fe --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1store__type_3_01int_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ + +
+ +
+ + +
+
+
+
stan::math::store_type< int > Member List
+
+
+ +

This is the complete list of members for stan::math::store_type< int >, including all inherited members.

+ + +
type typedefstan::math::store_type< int >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1store__type_3_01int_01_4.html b/doc/api/html/structstan_1_1math_1_1store__type_3_01int_01_4.html new file mode 100644 index 00000000000..1ff26024085 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1store__type_3_01int_01_4.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan::math::store_type< int > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::store_type< int > Struct Template Reference
+
+
+ +

#include <seq_view.hpp>

+ + + + +

+Public Types

typedef const int type
 
+

Detailed Description

+

template<>
+struct stan::math::store_type< int >

+ + +

Definition at line 21 of file seq_view.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef const int stan::math::store_type< int >::type
+
+ +

Definition at line 22 of file seq_view.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1value__type.html b/doc/api/html/structstan_1_1math_1_1value__type.html new file mode 100644 index 00000000000..ec87e0a5969 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1value__type.html @@ -0,0 +1,128 @@ + + + + + + +Stan Math Library: stan::math::value_type< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::value_type< T > Struct Template Reference
+
+
+ +

Primary template class for metaprogram to compute the type of values stored in a container. + More...

+ +

#include <value_type.hpp>

+

Detailed Description

+

template<typename T>
+struct stan::math::value_type< T >

+ +

Primary template class for metaprogram to compute the type of values stored in a container.

+

Only the specializations have behavior that can be used, and all implement a typedef type for the type of the values in the container.

+

tparam T type of container.

+ +

Definition at line 18 of file value_type.hpp.

+

The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1value__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1value__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html new file mode 100644 index 00000000000..598649ab970 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1value__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::value_type< Eigen::Matrix< T, R, C > > Member List
+
+
+ +

This is the complete list of members for stan::math::value_type< Eigen::Matrix< T, R, C > >, including all inherited members.

+ + +
type typedefstan::math::value_type< Eigen::Matrix< T, R, C > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1value__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1value__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html new file mode 100644 index 00000000000..b82d8230468 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1value__type_3_01_eigen_1_1_matrix_3_01_t_00_01_r_00_01_c_01_4_01_4.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan::math::value_type< Eigen::Matrix< T, R, C > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::value_type< Eigen::Matrix< T, R, C > > Struct Template Reference
+
+
+ +

Template metaprogram defining the type of values stored in an Eigen matrix, vector, or row vector. + More...

+ +

#include <value_type.hpp>

+ + + + +

+Public Types

typedef Eigen::Matrix< T, R, C >::Scalar type
 
+

Detailed Description

+

template<typename T, int R, int C>
+struct stan::math::value_type< Eigen::Matrix< T, R, C > >

+ +

Template metaprogram defining the type of values stored in an Eigen matrix, vector, or row vector.

+
Template Parameters
+ + + + +
Ttype of matrix.
Rnumber of rows for matrix.
Cnumber of columns for matrix.
+
+
+ +

Definition at line 20 of file value_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T , int R, int C>
+ + + + +
typedef Eigen::Matrix<T, R, C>::Scalar stan::math::value_type< Eigen::Matrix< T, R, C > >::type
+
+ +

Definition at line 21 of file value_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1value__type_3_01const_01_t_01_4-members.html b/doc/api/html/structstan_1_1math_1_1value__type_3_01const_01_t_01_4-members.html new file mode 100644 index 00000000000..44eaa61316a --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1value__type_3_01const_01_t_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::value_type< const T > Member List
+
+
+ +

This is the complete list of members for stan::math::value_type< const T >, including all inherited members.

+ + +
type typedefstan::math::value_type< const T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1value__type_3_01const_01_t_01_4.html b/doc/api/html/structstan_1_1math_1_1value__type_3_01const_01_t_01_4.html new file mode 100644 index 00000000000..25d0d2bb4da --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1value__type_3_01const_01_t_01_4.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan::math::value_type< const T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::value_type< const T > Struct Template Reference
+
+
+ +

Template class for metaprogram to compute the type of values stored in a constant container. + More...

+ +

#include <value_type.hpp>

+ + + + +

+Public Types

typedef value_type< T >::type type
 
+

Detailed Description

+

template<typename T>
+struct stan::math::value_type< const T >

+ +

Template class for metaprogram to compute the type of values stored in a constant container.

+
Template Parameters
+ + +
Ttype of container without const modifier.
+
+
+ +

Definition at line 28 of file value_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef value_type<T>::type stan::math::value_type< const T >::type
+
+ +

Definition at line 29 of file value_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1value__type_3_01std_1_1vector_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1math_1_1value__type_3_01std_1_1vector_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..4931a9c1196 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1value__type_3_01std_1_1vector_3_01_t_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::math::value_type< std::vector< T > > Member List
+
+
+ +

This is the complete list of members for stan::math::value_type< std::vector< T > >, including all inherited members.

+ + +
type typedefstan::math::value_type< std::vector< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1math_1_1value__type_3_01std_1_1vector_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1math_1_1value__type_3_01std_1_1vector_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..6d4c0951c51 --- /dev/null +++ b/doc/api/html/structstan_1_1math_1_1value__type_3_01std_1_1vector_3_01_t_01_4_01_4.html @@ -0,0 +1,161 @@ + + + + + + +Stan Math Library: stan::math::value_type< std::vector< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::math::value_type< std::vector< T > > Struct Template Reference
+
+
+ +

Template metaprogram class to compute the type of values stored in a standard vector. + More...

+ +

#include <value_type.hpp>

+ + + + + +

+Public Types

typedef std::vector< T >::value_type type
 Type of value stored in a standard vector with type T entries. More...
 
+

Detailed Description

+

template<typename T>
+struct stan::math::value_type< std::vector< T > >

+ +

Template metaprogram class to compute the type of values stored in a standard vector.

+
Template Parameters
+ + +
Ttype of elements in standard vector.
+
+
+ +

Definition at line 17 of file value_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef std::vector<T>::value_type stan::math::value_type< std::vector< T > >::type
+
+ +

Type of value stored in a standard vector with type T entries.

+ +

Definition at line 22 of file value_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1partials__return__type-members.html b/doc/api/html/structstan_1_1partials__return__type-members.html new file mode 100644 index 00000000000..2ada0c6f311 --- /dev/null +++ b/doc/api/html/structstan_1_1partials__return__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::partials_return_type< T1, T2, T3, T4, T5, T6 > Member List
+
+
+ +

This is the complete list of members for stan::partials_return_type< T1, T2, T3, T4, T5, T6 >, including all inherited members.

+ + +
type typedefstan::partials_return_type< T1, T2, T3, T4, T5, T6 >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1partials__return__type.html b/doc/api/html/structstan_1_1partials__return__type.html new file mode 100644 index 00000000000..c4a986a797f --- /dev/null +++ b/doc/api/html/structstan_1_1partials__return__type.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::partials_return_type< T1, T2, T3, T4, T5, T6 > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::partials_return_type< T1, T2, T3, T4, T5, T6 > Struct Template Reference
+
+
+ +

#include <partials_return_type.hpp>

+ + + + +

+Public Types

typedef boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
 
+

Detailed Description

+

template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+struct stan::partials_return_type< T1, T2, T3, T4, T5, T6 >

+ + +

Definition at line 16 of file partials_return_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+ + + + +
typedef boost::math::tools::promote_args<typename partials_type<typename scalar_type<T1>::type>::type, typename partials_type<typename scalar_type<T2>::type>::type, typename partials_type<typename scalar_type<T3>::type>::type, typename partials_type<typename scalar_type<T4>::type>::type, typename partials_type<typename scalar_type<T5>::type>::type, typename partials_type<typename scalar_type<T6>::type>::type>::type stan::partials_return_type< T1, T2, T3, T4, T5, T6 >::type
+
+ +

Definition at line 26 of file partials_return_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1partials__type-members.html b/doc/api/html/structstan_1_1partials__type-members.html new file mode 100644 index 00000000000..61b15f73b06 --- /dev/null +++ b/doc/api/html/structstan_1_1partials__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::partials_type< T > Member List
+
+
+ +

This is the complete list of members for stan::partials_type< T >, including all inherited members.

+ + +
type typedefstan::partials_type< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1partials__type.html b/doc/api/html/structstan_1_1partials__type.html new file mode 100644 index 00000000000..c930be6df14 --- /dev/null +++ b/doc/api/html/structstan_1_1partials__type.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::partials_type< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::partials_type< T > Struct Template Reference
+
+
+ +

#include <partials_type.hpp>

+ + + + +

+Public Types

typedef T type
 
+

Detailed Description

+

template<typename T>
+struct stan::partials_type< T >

+ + +

Definition at line 7 of file partials_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef T stan::partials_type< T >::type
+
+ +

Definition at line 8 of file partials_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html b/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..ba88399dc61 --- /dev/null +++ b/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
stan::partials_type< stan::math::fvar< T > > Member List
+
+
+ +

This is the complete list of members for stan::partials_type< stan::math::fvar< T > >, including all inherited members.

+ + +
type typedefstan::partials_type< stan::math::fvar< T > >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html b/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..df63d1af2ad --- /dev/null +++ b/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::partials_type< stan::math::fvar< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::partials_type< stan::math::fvar< T > > Struct Template Reference
+
+
+ +

#include <partials_type.hpp>

+ + + + +

+Public Types

typedef T type
 
+

Detailed Description

+

template<typename T>
+struct stan::partials_type< stan::math::fvar< T > >

+ + +

Definition at line 10 of file partials_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef T stan::partials_type< stan::math::fvar< T > >::type
+
+ +

Definition at line 11 of file partials_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1var_01_4-members.html b/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1var_01_4-members.html new file mode 100644 index 00000000000..6af00dacfcf --- /dev/null +++ b/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1var_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
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+ + +
+
+
+
stan::partials_type< stan::math::var > Member List
+
+
+ +

This is the complete list of members for stan::partials_type< stan::math::var >, including all inherited members.

+ + +
type typedefstan::partials_type< stan::math::var >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1var_01_4.html b/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..e1a6f8604ad --- /dev/null +++ b/doc/api/html/structstan_1_1partials__type_3_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan::partials_type< stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::partials_type< stan::math::var > Struct Template Reference
+
+
+ +

#include <partials_type.hpp>

+ + + + +

+Public Types

typedef double type
 
+

Detailed Description

+

template<>
+struct stan::partials_type< stan::math::var >

+ + +

Definition at line 10 of file partials_type.hpp.

+

Member Typedef Documentation

+ +
+
+ + + + +
typedef double stan::partials_type< stan::math::var >::type
+
+ +

Definition at line 11 of file partials_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1return__type-members.html b/doc/api/html/structstan_1_1return__type-members.html new file mode 100644 index 00000000000..dc16d0ebba0 --- /dev/null +++ b/doc/api/html/structstan_1_1return__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
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+
+
stan::return_type< T1, T2, T3, T4, T5, T6 > Member List
+
+
+ +

This is the complete list of members for stan::return_type< T1, T2, T3, T4, T5, T6 >, including all inherited members.

+ + +
type typedefstan::return_type< T1, T2, T3, T4, T5, T6 >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1return__type.html b/doc/api/html/structstan_1_1return__type.html new file mode 100644 index 00000000000..d3a8cc74896 --- /dev/null +++ b/doc/api/html/structstan_1_1return__type.html @@ -0,0 +1,152 @@ + + + + + + +Stan Math Library: stan::return_type< T1, T2, T3, T4, T5, T6 > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::return_type< T1, T2, T3, T4, T5, T6 > Struct Template Reference
+
+
+ +

Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters. + More...

+ +

#include <return_type.hpp>

+ + + + +

+Public Types

typedef boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
 
+

Detailed Description

+

template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+struct stan::return_type< T1, T2, T3, T4, T5, T6 >

+ +

Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of the template parameters.

+ +

Definition at line 19 of file return_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T1, typename T2 = double, typename T3 = double, typename T4 = double, typename T5 = double, typename T6 = double>
+ + + + +
typedef boost::math::tools::promote_args<typename scalar_type<T1>::type, typename scalar_type<T2>::type, typename scalar_type<T3>::type, typename scalar_type<T4>::type, typename scalar_type<T5>::type, typename scalar_type<T6>::type>::type stan::return_type< T1, T2, T3, T4, T5, T6 >::type
+
+ +

Definition at line 27 of file return_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1scalar__type-members.html b/doc/api/html/structstan_1_1scalar__type-members.html new file mode 100644 index 00000000000..365fbb12e86 --- /dev/null +++ b/doc/api/html/structstan_1_1scalar__type-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+ +
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+
stan::scalar_type< T > Member List
+
+
+ +

This is the complete list of members for stan::scalar_type< T >, including all inherited members.

+ + +
type typedefstan::scalar_type< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1scalar__type.html b/doc/api/html/structstan_1_1scalar__type.html new file mode 100644 index 00000000000..d7eafd3a4d9 --- /dev/null +++ b/doc/api/html/structstan_1_1scalar__type.html @@ -0,0 +1,159 @@ + + + + + + +Stan Math Library: stan::scalar_type< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::scalar_type< T > Struct Template Reference
+
+
+ +

Metaprogram structure to determine the base scalar type of a template argument. + More...

+ +

#include <scalar_type.hpp>

+ + + + +

+Public Types

typedef scalar_type_helper< is_vector< T >::value, T >::type type
 
+

Detailed Description

+

template<typename T>
+struct stan::scalar_type< T >

+ +

Metaprogram structure to determine the base scalar type of a template argument.

+

This base class should be specialized for structured types.

+
Template Parameters
+ + +
TType of object.
+
+
+ +

Definition at line 34 of file scalar_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T>
+ + + + +
typedef scalar_type_helper<is_vector<T>::value, T>::type stan::scalar_type< T >::type
+
+ +

Definition at line 35 of file scalar_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1scalar__type_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4-members.html b/doc/api/html/structstan_1_1scalar__type_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4-members.html new file mode 100644 index 00000000000..559459cb86a --- /dev/null +++ b/doc/api/html/structstan_1_1scalar__type_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
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+ +
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+
stan::scalar_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > > Member List
+
+ +
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1scalar__type_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html b/doc/api/html/structstan_1_1scalar__type_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html new file mode 100644 index 00000000000..194ac0fbc12 --- /dev/null +++ b/doc/api/html/structstan_1_1scalar__type_3_01_eigen_1_1_matrix_3_01_t_00_01_eigen_1_1_dynamic_00_01_eigen_1_1_dynamic_01_4_01_4.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::scalar_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::scalar_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > > Struct Template Reference
+
+
+ +

#include <scalar_type.hpp>

+ + + + +

+Public Types

typedef scalar_type< T >::type type
 
+

Detailed Description

+

template<typename T>
+struct stan::scalar_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >

+ + +

Definition at line 12 of file scalar_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef scalar_type<T>::type stan::scalar_type< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > >::type
+
+ +

Definition at line 13 of file scalar_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1scalar__type_3_01_t_01_5_01_4-members.html b/doc/api/html/structstan_1_1scalar__type_3_01_t_01_5_01_4-members.html new file mode 100644 index 00000000000..1a5cd6d76da --- /dev/null +++ b/doc/api/html/structstan_1_1scalar__type_3_01_t_01_5_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
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+ +
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+
+
+
stan::scalar_type< T * > Member List
+
+
+ +

This is the complete list of members for stan::scalar_type< T * >, including all inherited members.

+ + +
type typedefstan::scalar_type< T * >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1scalar__type_3_01_t_01_5_01_4.html b/doc/api/html/structstan_1_1scalar__type_3_01_t_01_5_01_4.html new file mode 100644 index 00000000000..5e28079d51d --- /dev/null +++ b/doc/api/html/structstan_1_1scalar__type_3_01_t_01_5_01_4.html @@ -0,0 +1,148 @@ + + + + + + +Stan Math Library: stan::scalar_type< T * > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::scalar_type< T * > Struct Template Reference
+
+
+ +

#include <scalar_type.hpp>

+ + + + +

+Public Types

typedef scalar_type< T >::type type
 
+

Detailed Description

+

template<typename T>
+struct stan::scalar_type< T * >

+ + +

Definition at line 39 of file scalar_type.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T >
+ + + + +
typedef scalar_type<T>::type stan::scalar_type< T * >::type
+
+ +

Definition at line 40 of file scalar_type.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1scalar__type__pre-members.html b/doc/api/html/structstan_1_1scalar__type__pre-members.html new file mode 100644 index 00000000000..edd490fec05 --- /dev/null +++ b/doc/api/html/structstan_1_1scalar__type__pre-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
+
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+ +
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+
+
stan::scalar_type_pre< T > Member List
+
+
+ +

This is the complete list of members for stan::scalar_type_pre< T >, including all inherited members.

+ + +
type typedefstan::scalar_type_pre< T >
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1scalar__type__pre.html b/doc/api/html/structstan_1_1scalar__type__pre.html new file mode 100644 index 00000000000..3e53d450535 --- /dev/null +++ b/doc/api/html/structstan_1_1scalar__type__pre.html @@ -0,0 +1,158 @@ + + + + + + +Stan Math Library: stan::scalar_type_pre< T > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::scalar_type_pre< T > Struct Template Reference
+
+
+ +

Metaprogram structure to determine the type of first container of the base scalar type of a template argument. + More...

+ +

#include <scalar_type_pre.hpp>

+ + + + +

+Public Types

typedef scalar_type_helper_pre< is_vector< typename stan::math::value_type< T >::type >::value, typename stan::math::value_type< T >::type, T >::type type
 
+

Detailed Description

+

template<typename T>
+struct stan::scalar_type_pre< T >

+ +

Metaprogram structure to determine the type of first container of the base scalar type of a template argument.

+
Template Parameters
+ + +
TType of object.
+
+
+ +

Definition at line 34 of file scalar_type_pre.hpp.

+

Member Typedef Documentation

+ +
+
+
+template<typename T>
+ + + + +
typedef scalar_type_helper_pre<is_vector <typename stan::math::value_type<T>::type>::value, typename stan::math::value_type<T>::type, T>::type stan::scalar_type_pre< T >::type
+
+ +

Definition at line 39 of file scalar_type_pre.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1size__of__helper-members.html b/doc/api/html/structstan_1_1size__of__helper-members.html new file mode 100644 index 00000000000..5688859ac09 --- /dev/null +++ b/doc/api/html/structstan_1_1size__of__helper-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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+
+
+ + + + + + +
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+ + +
+ +
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+
+
+
stan::size_of_helper< T, is_vec > Member List
+
+
+ +

This is the complete list of members for stan::size_of_helper< T, is_vec >, including all inherited members.

+ + +
size_of(const T &)stan::size_of_helper< T, is_vec >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1size__of__helper.html b/doc/api/html/structstan_1_1size__of__helper.html new file mode 100644 index 00000000000..5a4d9147531 --- /dev/null +++ b/doc/api/html/structstan_1_1size__of__helper.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan::size_of_helper< T, is_vec > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
stan::size_of_helper< T, is_vec > Struct Template Reference
+
+
+ +

#include <size_of.hpp>

+ + + + +

+Static Public Member Functions

static size_t size_of (const T &)
 
+

Detailed Description

+

template<typename T, bool is_vec>
+struct stan::size_of_helper< T, is_vec >

+ + +

Definition at line 10 of file size_of.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T, bool is_vec>
+ + + + + +
+ + + + + + + + +
static size_t stan::size_of_helper< T, is_vec >::size_of (const T & )
+
+inlinestatic
+
+ +

Definition at line 11 of file size_of.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1size__of__helper_3_01_t_00_01true_01_4-members.html b/doc/api/html/structstan_1_1size__of__helper_3_01_t_00_01true_01_4-members.html new file mode 100644 index 00000000000..d191a7a2ad7 --- /dev/null +++ b/doc/api/html/structstan_1_1size__of__helper_3_01_t_00_01true_01_4-members.html @@ -0,0 +1,115 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+ +
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+
+
stan::size_of_helper< T, true > Member List
+
+
+ +

This is the complete list of members for stan::size_of_helper< T, true >, including all inherited members.

+ + +
size_of(const T &x)stan::size_of_helper< T, true >inlinestatic
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstan_1_1size__of__helper_3_01_t_00_01true_01_4.html b/doc/api/html/structstan_1_1size__of__helper_3_01_t_00_01true_01_4.html new file mode 100644 index 00000000000..58955fb4a21 --- /dev/null +++ b/doc/api/html/structstan_1_1size__of__helper_3_01_t_00_01true_01_4.html @@ -0,0 +1,160 @@ + + + + + + +Stan Math Library: stan::size_of_helper< T, true > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
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+
+ +
+
stan::size_of_helper< T, true > Struct Template Reference
+
+
+ +

#include <size_of.hpp>

+ + + + +

+Static Public Member Functions

static size_t size_of (const T &x)
 
+

Detailed Description

+

template<typename T>
+struct stan::size_of_helper< T, true >

+ + +

Definition at line 17 of file size_of.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + + +
static size_t stan::size_of_helper< T, true >::size_of (const T & x)
+
+inlinestatic
+
+ +

Definition at line 18 of file size_of.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html b/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html new file mode 100644 index 00000000000..ae310ce4771 --- /dev/null +++ b/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4-members.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
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+
+
std::numeric_limits< stan::math::fvar< T > > Member List
+
+
+ +

This is the complete list of members for std::numeric_limits< stan::math::fvar< T > >, including all inherited members.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
denorm_min()std::numeric_limits< stan::math::fvar< T > >inlinestatic
digitsstd::numeric_limits< stan::math::fvar< T > >static
digits10std::numeric_limits< stan::math::fvar< T > >static
epsilon()std::numeric_limits< stan::math::fvar< T > >inlinestatic
has_denormstd::numeric_limits< stan::math::fvar< T > >static
has_denorm_lossstd::numeric_limits< stan::math::fvar< T > >static
has_infinitystd::numeric_limits< stan::math::fvar< T > >static
has_quiet_NaNstd::numeric_limits< stan::math::fvar< T > >static
has_signaling_NaNstd::numeric_limits< stan::math::fvar< T > >static
infinity()std::numeric_limits< stan::math::fvar< T > >inlinestatic
is_boundedstd::numeric_limits< stan::math::fvar< T > >static
is_exactstd::numeric_limits< stan::math::fvar< T > >static
is_iec559std::numeric_limits< stan::math::fvar< T > >static
is_integerstd::numeric_limits< stan::math::fvar< T > >static
is_modulostd::numeric_limits< stan::math::fvar< T > >static
is_signedstd::numeric_limits< stan::math::fvar< T > >static
is_specializedstd::numeric_limits< stan::math::fvar< T > >static
max()std::numeric_limits< stan::math::fvar< T > >inlinestatic
max_exponentstd::numeric_limits< stan::math::fvar< T > >static
max_exponent10std::numeric_limits< stan::math::fvar< T > >static
min()std::numeric_limits< stan::math::fvar< T > >inlinestatic
min_exponentstd::numeric_limits< stan::math::fvar< T > >static
min_exponent10std::numeric_limits< stan::math::fvar< T > >static
quiet_NaN()std::numeric_limits< stan::math::fvar< T > >inlinestatic
radixstd::numeric_limits< stan::math::fvar< T > >static
round_error()std::numeric_limits< stan::math::fvar< T > >inlinestatic
round_stylestd::numeric_limits< stan::math::fvar< T > >static
signaling_NaN()std::numeric_limits< stan::math::fvar< T > >inlinestatic
tinyness_beforestd::numeric_limits< stan::math::fvar< T > >static
trapsstd::numeric_limits< stan::math::fvar< T > >static
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html b/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html new file mode 100644 index 00000000000..51bdb0004f9 --- /dev/null +++ b/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1fvar_3_01_t_01_4_01_4.html @@ -0,0 +1,945 @@ + + + + + + +Stan Math Library: std::numeric_limits< stan::math::fvar< T > > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
std::numeric_limits< stan::math::fvar< T > > Struct Template Reference
+
+
+ +

#include <std_numeric_limits.hpp>

+ + + + + + + + + + + + + + + + + + +

+Static Public Member Functions

static stan::math::fvar< T > min ()
 
static stan::math::fvar< T > max ()
 
static stan::math::fvar< T > epsilon ()
 
static stan::math::fvar< T > round_error ()
 
static stan::math::fvar< T > infinity ()
 
static stan::math::fvar< T > quiet_NaN ()
 
static stan::math::fvar< T > signaling_NaN ()
 
static stan::math::fvar< T > denorm_min ()
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Static Public Attributes

static const bool is_specialized = true
 
static const int digits = numeric_limits<double>::digits
 
static const int digits10 = numeric_limits<double>::digits10
 
static const bool is_signed = numeric_limits<double>::is_signed
 
static const bool is_integer = numeric_limits<double>::is_integer
 
static const bool is_exact = numeric_limits<double>::is_exact
 
static const int radix = numeric_limits<double>::radix
 
static const int min_exponent = numeric_limits<double>::min_exponent
 
static const int min_exponent10 = numeric_limits<double>::min_exponent10
 
static const int max_exponent = numeric_limits<double>::max_exponent
 
static const int max_exponent10 = numeric_limits<double>::max_exponent10
 
static const bool has_infinity = numeric_limits<double>::has_infinity
 
static const bool has_quiet_NaN = numeric_limits<double>::has_quiet_NaN
 
static const bool has_signaling_NaN
 
static const float_denorm_style has_denorm
 
static const bool has_denorm_loss = numeric_limits<double>::has_denorm_loss
 
static const bool is_iec559 = numeric_limits<double>::is_iec559
 
static const bool is_bounded = numeric_limits<double>::is_bounded
 
static const bool is_modulo = numeric_limits<double>::is_modulo
 
static const bool traps = numeric_limits<double>::traps
 
static const bool tinyness_before = numeric_limits<double>::tinyness_before
 
static const float_round_style round_style
 
+

Detailed Description

+

template<typename T>
+struct std::numeric_limits< stan::math::fvar< T > >

+ + +

Definition at line 11 of file std_numeric_limits.hpp.

+

Member Function Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static stan::math::fvar<T> std::numeric_limits< stan::math::fvar< T > >::denorm_min ()
+
+inlinestatic
+
+ +

Definition at line 44 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static stan::math::fvar<T> std::numeric_limits< stan::math::fvar< T > >::epsilon ()
+
+inlinestatic
+
+ +

Definition at line 21 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static stan::math::fvar<T> std::numeric_limits< stan::math::fvar< T > >::infinity ()
+
+inlinestatic
+
+ +

Definition at line 38 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static stan::math::fvar<T> std::numeric_limits< stan::math::fvar< T > >::max ()
+
+inlinestatic
+
+ +

Definition at line 14 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static stan::math::fvar<T> std::numeric_limits< stan::math::fvar< T > >::min ()
+
+inlinestatic
+
+ +

Definition at line 13 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static stan::math::fvar<T> std::numeric_limits< stan::math::fvar< T > >::quiet_NaN ()
+
+inlinestatic
+
+ +

Definition at line 40 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static stan::math::fvar<T> std::numeric_limits< stan::math::fvar< T > >::round_error ()
+
+inlinestatic
+
+ +

Definition at line 23 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + + + + +
static stan::math::fvar<T> std::numeric_limits< stan::math::fvar< T > >::signaling_NaN ()
+
+inlinestatic
+
+ +

Definition at line 42 of file std_numeric_limits.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::fvar< T > >::digits = numeric_limits<double>::digits
+
+static
+
+ +

Definition at line 15 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::fvar< T > >::digits10 = numeric_limits<double>::digits10
+
+static
+
+ +

Definition at line 16 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const float_denorm_style std::numeric_limits< stan::math::fvar< T > >::has_denorm
+
+static
+
+Initial value:
=
+
numeric_limits<double>::has_denorm
+
+

Definition at line 35 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::has_denorm_loss = numeric_limits<double>::has_denorm_loss
+
+static
+
+ +

Definition at line 37 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::has_infinity = numeric_limits<double>::has_infinity
+
+static
+
+ +

Definition at line 31 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::has_quiet_NaN = numeric_limits<double>::has_quiet_NaN
+
+static
+
+ +

Definition at line 32 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::has_signaling_NaN
+
+static
+
+Initial value:
=
+
numeric_limits<double>::has_signaling_NaN
+
+

Definition at line 33 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::is_bounded = numeric_limits<double>::is_bounded
+
+static
+
+ +

Definition at line 48 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::is_exact = numeric_limits<double>::is_exact
+
+static
+
+ +

Definition at line 19 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::is_iec559 = numeric_limits<double>::is_iec559
+
+static
+
+ +

Definition at line 47 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::is_integer = numeric_limits<double>::is_integer
+
+static
+
+ +

Definition at line 18 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::is_modulo = numeric_limits<double>::is_modulo
+
+static
+
+ +

Definition at line 49 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::is_signed = numeric_limits<double>::is_signed
+
+static
+
+ +

Definition at line 17 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::is_specialized = true
+
+static
+
+ +

Definition at line 12 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::fvar< T > >::max_exponent = numeric_limits<double>::max_exponent
+
+static
+
+ +

Definition at line 28 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::fvar< T > >::max_exponent10 = numeric_limits<double>::max_exponent10
+
+static
+
+ +

Definition at line 29 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::fvar< T > >::min_exponent = numeric_limits<double>::min_exponent
+
+static
+
+ +

Definition at line 26 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::fvar< T > >::min_exponent10 = numeric_limits<double>::min_exponent10
+
+static
+
+ +

Definition at line 27 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::fvar< T > >::radix = numeric_limits<double>::radix
+
+static
+
+ +

Definition at line 20 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const float_round_style std::numeric_limits< stan::math::fvar< T > >::round_style
+
+static
+
+Initial value:
=
+
numeric_limits<double>::round_style
+
+

Definition at line 53 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::tinyness_before = numeric_limits<double>::tinyness_before
+
+static
+
+ +

Definition at line 52 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+
+template<typename T >
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::fvar< T > >::traps = numeric_limits<double>::traps
+
+static
+
+ +

Definition at line 51 of file std_numeric_limits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1var_01_4-members.html b/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1var_01_4-members.html new file mode 100644 index 00000000000..309dfdbc886 --- /dev/null +++ b/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1var_01_4-members.html @@ -0,0 +1,144 @@ + + + + + + +Stan Math Library: Member List + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
std::numeric_limits< stan::math::var > Member List
+
+
+ +

This is the complete list of members for std::numeric_limits< stan::math::var >, including all inherited members.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
denorm_min()std::numeric_limits< stan::math::var >inlinestatic
digitsstd::numeric_limits< stan::math::var >static
digits10std::numeric_limits< stan::math::var >static
epsilon()std::numeric_limits< stan::math::var >inlinestatic
has_denormstd::numeric_limits< stan::math::var >static
has_denorm_lossstd::numeric_limits< stan::math::var >static
has_infinitystd::numeric_limits< stan::math::var >static
has_quiet_NaNstd::numeric_limits< stan::math::var >static
has_signaling_NaNstd::numeric_limits< stan::math::var >static
infinity()std::numeric_limits< stan::math::var >inlinestatic
is_boundedstd::numeric_limits< stan::math::var >static
is_exactstd::numeric_limits< stan::math::var >static
is_iec559std::numeric_limits< stan::math::var >static
is_integerstd::numeric_limits< stan::math::var >static
is_modulostd::numeric_limits< stan::math::var >static
is_signedstd::numeric_limits< stan::math::var >static
is_specializedstd::numeric_limits< stan::math::var >static
max()std::numeric_limits< stan::math::var >inlinestatic
max_exponentstd::numeric_limits< stan::math::var >static
max_exponent10std::numeric_limits< stan::math::var >static
min()std::numeric_limits< stan::math::var >inlinestatic
min_exponentstd::numeric_limits< stan::math::var >static
min_exponent10std::numeric_limits< stan::math::var >static
quiet_NaN()std::numeric_limits< stan::math::var >inlinestatic
radixstd::numeric_limits< stan::math::var >static
round_error()std::numeric_limits< stan::math::var >inlinestatic
round_stylestd::numeric_limits< stan::math::var >static
signaling_NaN()std::numeric_limits< stan::math::var >inlinestatic
tinyness_beforestd::numeric_limits< stan::math::var >static
trapsstd::numeric_limits< stan::math::var >static
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1var_01_4.html b/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1var_01_4.html new file mode 100644 index 00000000000..ec762120f1e --- /dev/null +++ b/doc/api/html/structstd_1_1numeric__limits_3_01stan_1_1math_1_1var_01_4.html @@ -0,0 +1,884 @@ + + + + + + +Stan Math Library: std::numeric_limits< stan::math::var > Struct Template Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
std::numeric_limits< stan::math::var > Struct Template Reference
+
+
+ +

Specialization of numeric limits for var objects. + More...

+ +

#include <std_numeric_limits.hpp>

+ + + + + + + + + + + + + + + + + + +

+Static Public Member Functions

static stan::math::var min ()
 
static stan::math::var max ()
 
static stan::math::var epsilon ()
 
static stan::math::var round_error ()
 
static stan::math::var infinity ()
 
static stan::math::var quiet_NaN ()
 
static stan::math::var signaling_NaN ()
 
static stan::math::var denorm_min ()
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Static Public Attributes

static const bool is_specialized = true
 
static const int digits = numeric_limits<double>::digits
 
static const int digits10 = numeric_limits<double>::digits10
 
static const bool is_signed = numeric_limits<double>::is_signed
 
static const bool is_integer = numeric_limits<double>::is_integer
 
static const bool is_exact = numeric_limits<double>::is_exact
 
static const int radix = numeric_limits<double>::radix
 
static const int min_exponent = numeric_limits<double>::min_exponent
 
static const int min_exponent10 = numeric_limits<double>::min_exponent10
 
static const int max_exponent = numeric_limits<double>::max_exponent
 
static const int max_exponent10 = numeric_limits<double>::max_exponent10
 
static const bool has_infinity = numeric_limits<double>::has_infinity
 
static const bool has_quiet_NaN = numeric_limits<double>::has_quiet_NaN
 
static const bool has_signaling_NaN = numeric_limits<double>::has_signaling_NaN
 
static const float_denorm_style has_denorm = numeric_limits<double>::has_denorm
 
static const bool has_denorm_loss = numeric_limits<double>::has_denorm_loss
 
static const bool is_iec559 = numeric_limits<double>::is_iec559
 
static const bool is_bounded = numeric_limits<double>::is_bounded
 
static const bool is_modulo = numeric_limits<double>::is_modulo
 
static const bool traps = numeric_limits<double>::traps
 
static const bool tinyness_before = numeric_limits<double>::tinyness_before
 
static const float_round_style round_style = numeric_limits<double>::round_style
 
+

Detailed Description

+

template<>
+struct std::numeric_limits< stan::math::var >

+ +

Specialization of numeric limits for var objects.

+

This implementation of std::numeric_limits<stan::math::var> is used to treat var objects like doubles.

+ +

Definition at line 16 of file std_numeric_limits.hpp.

+

Member Function Documentation

+ +
+
+ + + + + +
+ + + + + + + +
static stan::math::var std::numeric_limits< stan::math::var >::denorm_min ()
+
+inlinestatic
+
+ +

Definition at line 54 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static stan::math::var std::numeric_limits< stan::math::var >::epsilon ()
+
+inlinestatic
+
+ +

Definition at line 26 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static stan::math::var std::numeric_limits< stan::math::var >::infinity ()
+
+inlinestatic
+
+ +

Definition at line 45 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static stan::math::var std::numeric_limits< stan::math::var >::max ()
+
+inlinestatic
+
+ +

Definition at line 19 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static stan::math::var std::numeric_limits< stan::math::var >::min ()
+
+inlinestatic
+
+ +

Definition at line 18 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static stan::math::var std::numeric_limits< stan::math::var >::quiet_NaN ()
+
+inlinestatic
+
+ +

Definition at line 48 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static stan::math::var std::numeric_limits< stan::math::var >::round_error ()
+
+inlinestatic
+
+ +

Definition at line 29 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + + + + +
static stan::math::var std::numeric_limits< stan::math::var >::signaling_NaN ()
+
+inlinestatic
+
+ +

Definition at line 51 of file std_numeric_limits.hpp.

+ +
+
+

Member Data Documentation

+ +
+
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::var >::digits = numeric_limits<double>::digits
+
+static
+
+ +

Definition at line 20 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::var >::digits10 = numeric_limits<double>::digits10
+
+static
+
+ +

Definition at line 21 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const float_denorm_style std::numeric_limits< stan::math::var >::has_denorm = numeric_limits<double>::has_denorm
+
+static
+
+ +

Definition at line 43 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::has_denorm_loss = numeric_limits<double>::has_denorm_loss
+
+static
+
+ +

Definition at line 44 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::has_infinity = numeric_limits<double>::has_infinity
+
+static
+
+ +

Definition at line 38 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::has_quiet_NaN = numeric_limits<double>::has_quiet_NaN
+
+static
+
+ +

Definition at line 39 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::has_signaling_NaN = numeric_limits<double>::has_signaling_NaN
+
+static
+
+ +

Definition at line 41 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::is_bounded = numeric_limits<double>::is_bounded
+
+static
+
+ +

Definition at line 59 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::is_exact = numeric_limits<double>::is_exact
+
+static
+
+ +

Definition at line 24 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::is_iec559 = numeric_limits<double>::is_iec559
+
+static
+
+ +

Definition at line 58 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::is_integer = numeric_limits<double>::is_integer
+
+static
+
+ +

Definition at line 23 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::is_modulo = numeric_limits<double>::is_modulo
+
+static
+
+ +

Definition at line 60 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::is_signed = numeric_limits<double>::is_signed
+
+static
+
+ +

Definition at line 22 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::is_specialized = true
+
+static
+
+ +

Definition at line 17 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::var >::max_exponent = numeric_limits<double>::max_exponent
+
+static
+
+ +

Definition at line 35 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::var >::max_exponent10 = numeric_limits<double>::max_exponent10
+
+static
+
+ +

Definition at line 36 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::var >::min_exponent = numeric_limits<double>::min_exponent
+
+static
+
+ +

Definition at line 33 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::var >::min_exponent10 = numeric_limits<double>::min_exponent10
+
+static
+
+ +

Definition at line 34 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const int std::numeric_limits< stan::math::var >::radix = numeric_limits<double>::radix
+
+static
+
+ +

Definition at line 25 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const float_round_style std::numeric_limits< stan::math::var >::round_style = numeric_limits<double>::round_style
+
+static
+
+ +

Definition at line 65 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::tinyness_before = numeric_limits<double>::tinyness_before
+
+static
+
+ +

Definition at line 63 of file std_numeric_limits.hpp.

+ +
+
+ +
+
+ + + + + +
+ + + + +
const bool std::numeric_limits< stan::math::var >::traps = numeric_limits<double>::traps
+
+static
+
+ +

Definition at line 62 of file std_numeric_limits.hpp.

+ +
+
+
The documentation for this struct was generated from the following file: +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/student__t__ccdf__log_8hpp.html b/doc/api/html/student__t__ccdf__log_8hpp.html new file mode 100644 index 00000000000..df90d41645f --- /dev/null +++ b/doc/api/html/student__t__ccdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_ccdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
student_t_ccdf_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type stan::math::student_t_ccdf_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/student__t__ccdf__log_8hpp_source.html b/doc/api/html/student__t__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..126631c6051 --- /dev/null +++ b/doc/api/html/student__t__ccdf__log_8hpp_source.html @@ -0,0 +1,357 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_ccdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
student_t_ccdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/student_t_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <limits>
+
25 #include <cmath>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_y, typename T_dof, typename T_loc, typename T_scale>
+
32  typename return_type<T_y, T_dof, T_loc, T_scale>::type
+
33  student_t_ccdf_log(const T_y& y, const T_dof& nu, const T_loc& mu,
+
34  const T_scale& sigma) {
+
35  typedef
+ +
37  T_partials_return;
+
38 
+
39  // Size checks
+
40  if (!(stan::length(y) && stan::length(nu) && stan::length(mu)
+
41  && stan::length(sigma)))
+
42  return 0.0;
+
43 
+
44  static const char* function("stan::math::student_t_ccdf_log");
+
45 
+ + + + + +
51  using std::exp;
+
52 
+
53  T_partials_return P(0.0);
+
54 
+
55  check_not_nan(function, "Random variable", y);
+
56  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
57  check_finite(function, "Location parameter", mu);
+
58  check_positive_finite(function, "Scale parameter", sigma);
+
59 
+
60  // Wrap arguments in vectors
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_dof> nu_vec(nu);
+
63  VectorView<const T_loc> mu_vec(mu);
+
64  VectorView<const T_scale> sigma_vec(sigma);
+
65  size_t N = max_size(y, nu, mu, sigma);
+
66 
+ +
68  operands_and_partials(y, nu, mu, sigma);
+
69 
+
70  // Explicit return for extreme values
+
71  // The gradients are technically ill-defined, but treated as zero
+
72  for (size_t i = 0; i < stan::length(y); i++) {
+
73  if (value_of(y_vec[i]) == -std::numeric_limits<double>::infinity())
+
74  return operands_and_partials.value(0.0);
+
75  }
+
76 
+
77  using stan::math::digamma;
+
78  using stan::math::lbeta;
+ +
80  using std::pow;
+
81  using std::exp;
+
82  using std::log;
+
83 
+
84  // Cache a few expensive function calls if nu is a parameter
+
85  T_partials_return digammaHalf = 0;
+
86 
+ +
88  T_partials_return, T_dof>
+
89  digamma_vec(stan::length(nu));
+ +
91  T_partials_return, T_dof>
+
92  digammaNu_vec(stan::length(nu));
+ +
94  T_partials_return, T_dof>
+
95  digammaNuPlusHalf_vec(stan::length(nu));
+
96 
+ +
98  digammaHalf = digamma(0.5);
+
99 
+
100  for (size_t i = 0; i < stan::length(nu); i++) {
+
101  const T_partials_return nu_dbl = value_of(nu_vec[i]);
+
102 
+
103  digammaNu_vec[i] = digamma(0.5 * nu_dbl);
+
104  digammaNuPlusHalf_vec[i] = digamma(0.5 + 0.5 * nu_dbl);
+
105  }
+
106  }
+
107 
+
108  // Compute vectorized cdf_log and gradient
+
109  for (size_t n = 0; n < N; n++) {
+
110  // Explicit results for extreme values
+
111  // The gradients are technically ill-defined, but treated as zero
+
112  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
113  return operands_and_partials.value(stan::math::negative_infinity());
+
114  }
+
115 
+
116  const T_partials_return sigma_inv = 1.0 / value_of(sigma_vec[n]);
+
117  const T_partials_return t = (value_of(y_vec[n]) - value_of(mu_vec[n]))
+
118  * sigma_inv;
+
119  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+
120  const T_partials_return q = nu_dbl / (t * t);
+
121  const T_partials_return r = 1.0 / (1.0 + q);
+
122  const T_partials_return J = 2 * r * r * q / t;
+
123  const T_partials_return betaNuHalf = exp(lbeta(0.5, 0.5 * nu_dbl));
+
124  T_partials_return zJacobian = t > 0 ? - 0.5 : 0.5;
+
125 
+
126  if (q < 2) {
+
127  T_partials_return z = inc_beta(0.5 * nu_dbl, (T_partials_return)0.5,
+
128  1.0 - r);
+
129  const T_partials_return Pn = t > 0 ? 0.5 * z : 1.0 - 0.5 * z;
+
130  const T_partials_return d_ibeta = pow(r, -0.5)
+
131  * pow(1.0 - r, 0.5*nu_dbl - 1) / betaNuHalf;
+
132 
+
133  P += log(Pn);
+
134 
+ +
136  operands_and_partials.d_x1[n]
+
137  += zJacobian * d_ibeta * J * sigma_inv / Pn;
+
138 
+ +
140  T_partials_return g1 = 0;
+
141  T_partials_return g2 = 0;
+
142 
+
143  stan::math::grad_reg_inc_beta(g1, g2, 0.5 * nu_dbl,
+
144  (T_partials_return)0.5, 1.0 - r,
+
145  digammaNu_vec[n], digammaHalf,
+
146  digammaNuPlusHalf_vec[n],
+
147  betaNuHalf);
+
148 
+
149  operands_and_partials.d_x2[n]
+
150  -= zJacobian * (d_ibeta * (r / t) * (r / t) + 0.5 * g1) / Pn;
+
151  }
+
152 
+ +
154  operands_and_partials.d_x3[n]
+
155  -= zJacobian * d_ibeta * J * sigma_inv / Pn;
+ +
157  operands_and_partials.d_x4[n]
+
158  -= zJacobian * d_ibeta * J * sigma_inv * t / Pn;
+
159 
+
160  } else {
+
161  T_partials_return z = 1.0 - inc_beta((T_partials_return)0.5,
+
162  0.5*nu_dbl, r);
+
163  zJacobian *= -1;
+
164 
+
165  const T_partials_return Pn = t > 0 ? 0.5 * z : 1.0 - 0.5 * z;
+
166 
+
167  T_partials_return d_ibeta = pow(1.0-r, 0.5*nu_dbl-1) * pow(r, -0.5)
+
168  / betaNuHalf;
+
169 
+
170  P += log(Pn);
+
171 
+ +
173  operands_and_partials.d_x1[n]
+
174  -= zJacobian * d_ibeta * J * sigma_inv / Pn;
+
175 
+ +
177  T_partials_return g1 = 0;
+
178  T_partials_return g2 = 0;
+
179 
+
180  stan::math::grad_reg_inc_beta(g1, g2, (T_partials_return)0.5,
+
181  0.5 * nu_dbl, r,
+
182  digammaHalf, digammaNu_vec[n],
+
183  digammaNuPlusHalf_vec[n],
+
184  betaNuHalf);
+
185 
+
186  operands_and_partials.d_x2[n]
+
187  -= zJacobian * (- d_ibeta * (r / t) * (r / t) + 0.5 * g2) / Pn;
+
188  }
+
189 
+ +
191  operands_and_partials.d_x3[n]
+
192  += zJacobian * d_ibeta * J * sigma_inv / Pn;
+ +
194  operands_and_partials.d_x4[n]
+
195  += zJacobian * d_ibeta * J * sigma_inv * t / Pn;
+
196  }
+
197  }
+
198 
+
199  return operands_and_partials.value(P);
+
200  }
+
201  }
+
202 }
+
203 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_ccdf_log(const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
+
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/student__t__cdf_8hpp.html b/doc/api/html/student__t__cdf_8hpp.html new file mode 100644 index 00000000000..72e373b2069 --- /dev/null +++ b/doc/api/html/student__t__cdf_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
student_t_cdf.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type stan::math::student_t_cdf (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/student__t__cdf_8hpp_source.html b/doc/api/html/student__t__cdf_8hpp_source.html new file mode 100644 index 00000000000..0a94e4b9d9b --- /dev/null +++ b/doc/api/html/student__t__cdf_8hpp_source.html @@ -0,0 +1,369 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
student_t_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/student_t_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <limits>
+
25 #include <cmath>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_y, typename T_dof, typename T_loc, typename T_scale>
+
32  typename return_type<T_y, T_dof, T_loc, T_scale>::type
+
33  student_t_cdf(const T_y& y, const T_dof& nu, const T_loc& mu,
+
34  const T_scale& sigma) {
+
35  typedef typename stan::partials_return_type<T_y, T_dof, T_loc,
+
36  T_scale>::type
+
37  T_partials_return;
+
38 
+
39  // Size checks
+
40  if (!(stan::length(y) && stan::length(nu) && stan::length(mu)
+
41  && stan::length(sigma)))
+
42  return 1.0;
+
43 
+
44  static const char* function("stan::math::student_t_cdf");
+
45 
+ + + + + +
51  using std::exp;
+
52 
+
53  T_partials_return P(1.0);
+
54 
+
55  check_not_nan(function, "Random variable", y);
+
56  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
57  check_finite(function, "Location parameter", mu);
+
58  check_positive_finite(function, "Scale parameter", sigma);
+
59 
+
60  // Wrap arguments in vectors
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_dof> nu_vec(nu);
+
63  VectorView<const T_loc> mu_vec(mu);
+
64  VectorView<const T_scale> sigma_vec(sigma);
+
65  size_t N = max_size(y, nu, mu, sigma);
+
66 
+ +
68  operands_and_partials(y, nu, mu, sigma);
+
69 
+
70  // Explicit return for extreme values
+
71  // The gradients are technically ill-defined, but treated as zero
+
72  for (size_t i = 0; i < stan::length(y); i++) {
+
73  if (value_of(y_vec[i]) == -std::numeric_limits<double>::infinity())
+
74  return operands_and_partials.value(0.0);
+
75  }
+
76 
+
77  using stan::math::digamma;
+
78  using stan::math::lbeta;
+ +
80  using std::pow;
+
81  using std::exp;
+
82 
+
83  // Cache a few expensive function calls if nu is a parameter
+
84  T_partials_return digammaHalf = 0;
+
85 
+ +
87  T_partials_return, T_dof>
+
88  digamma_vec(stan::length(nu));
+ +
90  T_partials_return, T_dof>
+
91  digammaNu_vec(stan::length(nu));
+ +
93  T_partials_return, T_dof>
+
94  digammaNuPlusHalf_vec(stan::length(nu));
+
95 
+ +
97  digammaHalf = digamma(0.5);
+
98 
+
99  for (size_t i = 0; i < stan::length(nu); i++) {
+
100  const T_partials_return nu_dbl = value_of(nu_vec[i]);
+
101 
+
102  digammaNu_vec[i] = digamma(0.5 * nu_dbl);
+
103  digammaNuPlusHalf_vec[i] = digamma(0.5 + 0.5 * nu_dbl);
+
104  }
+
105  }
+
106 
+
107  // Compute vectorized CDF and gradient
+
108  for (size_t n = 0; n < N; n++) {
+
109  // Explicit results for extreme values
+
110  // The gradients are technically ill-defined, but treated as zero
+
111  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
112  continue;
+
113  }
+
114 
+
115  const T_partials_return sigma_inv = 1.0 / value_of(sigma_vec[n]);
+
116  const T_partials_return t = (value_of(y_vec[n]) - value_of(mu_vec[n]))
+
117  * sigma_inv;
+
118  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+
119  const T_partials_return q = nu_dbl / (t * t);
+
120  const T_partials_return r = 1.0 / (1.0 + q);
+
121  const T_partials_return J = 2 * r * r * q / t;
+
122  const T_partials_return betaNuHalf = exp(lbeta(0.5, 0.5*nu_dbl));
+
123  double zJacobian = t > 0 ? - 0.5 : 0.5;
+
124 
+
125  if (q < 2) {
+
126  T_partials_return z = inc_beta(0.5 * nu_dbl, (T_partials_return)0.5,
+
127  1.0 - r);
+
128  const T_partials_return Pn = t > 0 ? 1.0 - 0.5 * z : 0.5 * z;
+
129  const T_partials_return d_ibeta = pow(r, -0.5)
+
130  * pow(1.0 - r, 0.5*nu_dbl - 1) / betaNuHalf;
+
131 
+
132  P *= Pn;
+
133 
+ +
135  operands_and_partials.d_x1[n]
+
136  += - zJacobian * d_ibeta * J * sigma_inv / Pn;
+ +
138  T_partials_return g1 = 0;
+
139  T_partials_return g2 = 0;
+
140 
+
141  stan::math::grad_reg_inc_beta(g1, g2, 0.5 * nu_dbl,
+
142  (T_partials_return)0.5, 1.0 - r,
+
143  digammaNu_vec[n], digammaHalf,
+
144  digammaNuPlusHalf_vec[n],
+
145  betaNuHalf);
+
146 
+
147  operands_and_partials.d_x2[n]
+
148  += zJacobian * (d_ibeta * (r / t) * (r / t) + 0.5 * g1) / Pn;
+
149  }
+
150 
+ +
152  operands_and_partials.d_x3[n]
+
153  += zJacobian * d_ibeta * J * sigma_inv / Pn;
+ +
155  operands_and_partials.d_x4[n]
+
156  += zJacobian * d_ibeta * J * sigma_inv * t / Pn;
+
157 
+
158  } else {
+
159  T_partials_return z = 1.0 - inc_beta((T_partials_return)0.5,
+
160  0.5*nu_dbl, r);
+
161 
+
162  zJacobian *= -1;
+
163 
+
164  const T_partials_return Pn = t > 0 ? 1.0 - 0.5 * z : 0.5 * z;
+
165 
+
166  T_partials_return d_ibeta = pow(1.0-r, 0.5*nu_dbl-1) * pow(r, -0.5)
+
167  / betaNuHalf;
+
168 
+
169  P *= Pn;
+
170 
+ +
172  operands_and_partials.d_x1[n]
+
173  += zJacobian * d_ibeta * J * sigma_inv / Pn;
+ +
175  T_partials_return g1 = 0;
+
176  T_partials_return g2 = 0;
+
177 
+
178  stan::math::grad_reg_inc_beta(g1, g2, (T_partials_return)0.5,
+
179  0.5 * nu_dbl, r,
+
180  digammaHalf, digammaNu_vec[n],
+
181  digammaNuPlusHalf_vec[n],
+
182  betaNuHalf);
+
183 
+
184  operands_and_partials.d_x2[n]
+
185  += zJacobian * (- d_ibeta * (r / t) * (r / t) + 0.5 * g2) / Pn;
+
186  }
+ +
188  operands_and_partials.d_x3[n]
+
189  += - zJacobian * d_ibeta * J * sigma_inv / Pn;
+ +
191  operands_and_partials.d_x4[n]
+
192  += - zJacobian * d_ibeta * J * sigma_inv * t / Pn;
+
193  }
+
194  }
+
195 
+ +
197  for (size_t n = 0; n < stan::length(y); ++n)
+
198  operands_and_partials.d_x1[n] *= P;
+
199  }
+ +
201  for (size_t n = 0; n < stan::length(nu); ++n)
+
202  operands_and_partials.d_x2[n] *= P;
+
203  }
+ +
205  for (size_t n = 0; n < stan::length(mu); ++n)
+
206  operands_and_partials.d_x3[n] *= P;
+
207  }
+ +
209  for (size_t n = 0; n < stan::length(sigma); ++n)
+
210  operands_and_partials.d_x4[n] *= P;
+
211  }
+
212 
+
213  return operands_and_partials.value(P);
+
214  }
+
215  }
+
216 }
+
217 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_cdf(const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
VectorView< T_return_type, false, true > d_x4
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/student__t__cdf__log_8hpp.html b/doc/api/html/student__t__cdf__log_8hpp.html new file mode 100644 index 00000000000..1b5209340da --- /dev/null +++ b/doc/api/html/student__t__cdf__log_8hpp.html @@ -0,0 +1,151 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_cdf_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
student_t_cdf_log.hpp File Reference
+
+
+ +

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+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type stan::math::student_t_cdf_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 
+
+
+
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diff --git a/doc/api/html/student__t__cdf__log_8hpp_source.html b/doc/api/html/student__t__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..6460cdb93ab --- /dev/null +++ b/doc/api/html/student__t__cdf__log_8hpp_source.html @@ -0,0 +1,357 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+ + +
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+
+
+
student_t_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/student_t_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <limits>
+
25 #include <cmath>
+
26 
+
27 namespace stan {
+
28 
+
29  namespace math {
+
30 
+
31  template <typename T_y, typename T_dof, typename T_loc, typename T_scale>
+
32  typename return_type<T_y, T_dof, T_loc, T_scale>::type
+
33  student_t_cdf_log(const T_y& y, const T_dof& nu, const T_loc& mu,
+
34  const T_scale& sigma) {
+
35  typedef typename
+ +
37  T_partials_return;
+
38 
+
39  // Size checks
+
40  if (!(stan::length(y) && stan::length(nu) && stan::length(mu)
+
41  && stan::length(sigma)))
+
42  return 0.0;
+
43 
+
44  static const char* function("stan::math::student_t_cdf_log");
+
45 
+ + + + + +
51  using std::exp;
+
52 
+
53  T_partials_return P(0.0);
+
54 
+
55  check_not_nan(function, "Random variable", y);
+
56  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
57  check_finite(function, "Location parameter", mu);
+
58  check_positive_finite(function, "Scale parameter", sigma);
+
59 
+
60  // Wrap arguments in vectors
+
61  VectorView<const T_y> y_vec(y);
+
62  VectorView<const T_dof> nu_vec(nu);
+
63  VectorView<const T_loc> mu_vec(mu);
+
64  VectorView<const T_scale> sigma_vec(sigma);
+
65  size_t N = max_size(y, nu, mu, sigma);
+
66 
+ +
68  operands_and_partials(y, nu, mu, sigma);
+
69 
+
70  // Explicit return for extreme values
+
71  // The gradients are technically ill-defined, but treated as zero
+
72  for (size_t i = 0; i < stan::length(y); i++) {
+
73  if (value_of(y_vec[i]) == -std::numeric_limits<double>::infinity())
+
74  return operands_and_partials.value(stan::math::negative_infinity());
+
75  }
+
76 
+
77  using stan::math::digamma;
+
78  using stan::math::lbeta;
+ +
80  using std::pow;
+
81  using std::exp;
+
82  using std::log;
+
83 
+
84  // Cache a few expensive function calls if nu is a parameter
+
85  T_partials_return digammaHalf = 0;
+
86 
+ +
88  T_partials_return, T_dof>
+
89  digamma_vec(stan::length(nu));
+ +
91  T_partials_return, T_dof>
+
92  digammaNu_vec(stan::length(nu));
+ +
94  T_partials_return, T_dof>
+
95  digammaNuPlusHalf_vec(stan::length(nu));
+
96 
+ +
98  digammaHalf = digamma(0.5);
+
99 
+
100  for (size_t i = 0; i < stan::length(nu); i++) {
+
101  const T_partials_return nu_dbl = value_of(nu_vec[i]);
+
102 
+
103  digammaNu_vec[i] = digamma(0.5 * nu_dbl);
+
104  digammaNuPlusHalf_vec[i] = digamma(0.5 + 0.5 * nu_dbl);
+
105  }
+
106  }
+
107 
+
108  // Compute vectorized cdf_log and gradient
+
109  for (size_t n = 0; n < N; n++) {
+
110  // Explicit results for extreme values
+
111  // The gradients are technically ill-defined, but treated as zero
+
112  if (value_of(y_vec[n]) == std::numeric_limits<double>::infinity()) {
+
113  continue;
+
114  }
+
115 
+
116  const T_partials_return sigma_inv = 1.0 / value_of(sigma_vec[n]);
+
117  const T_partials_return t = (value_of(y_vec[n]) - value_of(mu_vec[n]))
+
118  * sigma_inv;
+
119  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+
120  const T_partials_return q = nu_dbl / (t * t);
+
121  const T_partials_return r = 1.0 / (1.0 + q);
+
122  const T_partials_return J = 2 * r * r * q / t;
+
123  const T_partials_return betaNuHalf = exp(lbeta(0.5, 0.5 * nu_dbl));
+
124  T_partials_return zJacobian = t > 0 ? - 0.5 : 0.5;
+
125 
+
126  if (q < 2) {
+
127  T_partials_return z
+
128  = inc_beta(0.5 * nu_dbl, (T_partials_return)0.5, 1.0 - r);
+
129  const T_partials_return Pn = t > 0 ? 1.0 - 0.5 * z : 0.5 * z;
+
130  const T_partials_return d_ibeta = pow(r, -0.5)
+
131  * pow(1.0 - r, 0.5*nu_dbl - 1) / betaNuHalf;
+
132 
+
133  P += log(Pn);
+
134 
+ +
136  operands_and_partials.d_x1[n]
+
137  += - zJacobian * d_ibeta * J * sigma_inv / Pn;
+
138 
+ +
140  T_partials_return g1 = 0;
+
141  T_partials_return g2 = 0;
+
142 
+
143  stan::math::grad_reg_inc_beta(g1, g2, 0.5 * nu_dbl,
+
144  (T_partials_return)0.5, 1.0 - r,
+
145  digammaNu_vec[n], digammaHalf,
+
146  digammaNuPlusHalf_vec[n],
+
147  betaNuHalf);
+
148 
+
149  operands_and_partials.d_x2[n]
+
150  += zJacobian * (d_ibeta * (r / t) * (r / t) + 0.5 * g1) / Pn;
+
151  }
+
152 
+ +
154  operands_and_partials.d_x3[n]
+
155  += zJacobian * d_ibeta * J * sigma_inv / Pn;
+ +
157  operands_and_partials.d_x4[n]
+
158  += zJacobian * d_ibeta * J * sigma_inv * t / Pn;
+
159 
+
160  } else {
+
161  T_partials_return z = 1.0 - inc_beta((T_partials_return)0.5,
+
162  0.5*nu_dbl, r);
+
163  zJacobian *= -1;
+
164 
+
165  const T_partials_return Pn = t > 0 ? 1.0 - 0.5 * z : 0.5 * z;
+
166 
+
167  T_partials_return d_ibeta = pow(1.0-r, 0.5*nu_dbl-1) * pow(r, -0.5)
+
168  / betaNuHalf;
+
169 
+
170  P += log(Pn);
+
171 
+ +
173  operands_and_partials.d_x1[n]
+
174  += zJacobian * d_ibeta * J * sigma_inv / Pn;
+
175 
+ +
177  T_partials_return g1 = 0;
+
178  T_partials_return g2 = 0;
+
179 
+
180  stan::math::grad_reg_inc_beta(g1, g2, (T_partials_return)0.5,
+
181  0.5 * nu_dbl, r,
+
182  digammaHalf, digammaNu_vec[n],
+
183  digammaNuPlusHalf_vec[n],
+
184  betaNuHalf);
+
185 
+
186  operands_and_partials.d_x2[n]
+
187  += zJacobian * (- d_ibeta * (r / t) * (r / t) + 0.5 * g2) / Pn;
+
188  }
+
189 
+ +
191  operands_and_partials.d_x3[n]
+
192  += - zJacobian * d_ibeta * J * sigma_inv / Pn;
+ +
194  operands_and_partials.d_x4[n]
+
195  += - zJacobian * d_ibeta * J * sigma_inv * t / Pn;
+
196  }
+
197  }
+
198 
+
199  return operands_and_partials.value(P);
+
200  }
+
201  }
+
202 }
+
203 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_cdf_log(const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
VectorView< T_return_type, false, true > d_x4
+
+
+
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diff --git a/doc/api/html/student__t__log_8hpp.html b/doc/api/html/student__t__log_8hpp.html new file mode 100644 index 00000000000..a27473929c9 --- /dev/null +++ b/doc/api/html/student__t__log_8hpp.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
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+
+ +
+
student_t_log.hpp File Reference
+
+
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Go to the source code of this file.

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+Functions

template<bool propto, typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type stan::math::student_t_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 The log of the Student-t density for the given y, nu, mean, and scale parameter. More...
 
template<typename T_y , typename T_dof , typename T_loc , typename T_scale >
return_type< T_y, T_dof, T_loc, T_scale >::type stan::math::student_t_log (const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
 
+
+
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diff --git a/doc/api/html/student__t__log_8hpp_source.html b/doc/api/html/student__t__log_8hpp_source.html new file mode 100644 index 00000000000..7afeffd9f97 --- /dev/null +++ b/doc/api/html/student__t__log_8hpp_source.html @@ -0,0 +1,358 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_log.hpp Source File + + + + + + + + + + +
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student_t_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 #include <boost/random/student_t_distribution.hpp>
+
23 #include <boost/random/variate_generator.hpp>
+
24 #include <cmath>
+
25 
+
26 namespace stan {
+
27 
+
28  namespace math {
+
29 
+
55  template <bool propto, typename T_y, typename T_dof,
+
56  typename T_loc, typename T_scale>
+
57  typename return_type<T_y, T_dof, T_loc, T_scale>::type
+
58  student_t_log(const T_y& y, const T_dof& nu, const T_loc& mu,
+
59  const T_scale& sigma) {
+
60  static const char* function("stan::math::student_t_log");
+
61  typedef typename stan::partials_return_type<T_y, T_dof, T_loc,
+
62  T_scale>::type
+
63  T_partials_return;
+
64 
+ + + + +
69 
+
70  // check if any vectors are zero length
+
71  if (!(stan::length(y)
+
72  && stan::length(nu)
+
73  && stan::length(mu)
+
74  && stan::length(sigma)))
+
75  return 0.0;
+
76 
+
77  T_partials_return logp(0.0);
+
78 
+
79  // validate args (here done over var, which should be OK)
+
80  check_not_nan(function, "Random variable", y);
+
81  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
82  check_finite(function, "Location parameter", mu);
+
83  check_positive_finite(function, "Scale parameter", sigma);
+
84  check_consistent_sizes(function,
+
85  "Random variable", y,
+
86  "Degrees of freedom parameter", nu,
+
87  "Location parameter", mu,
+
88  "Scale parameter", sigma);
+
89 
+
90  // check if no variables are involved and prop-to
+ +
92  return 0.0;
+
93 
+
94  VectorView<const T_y> y_vec(y);
+
95  VectorView<const T_dof> nu_vec(nu);
+
96  VectorView<const T_loc> mu_vec(mu);
+
97  VectorView<const T_scale> sigma_vec(sigma);
+
98  size_t N = max_size(y, nu, mu, sigma);
+
99 
+
100  using std::log;
+
101  using stan::math::digamma;
+
102  using stan::math::lgamma;
+
103  using stan::math::square;
+
104  using stan::math::value_of;
+
105  using std::log;
+
106 
+ +
108  T_partials_return, T_dof> half_nu(length(nu));
+
109  for (size_t i = 0; i < length(nu); i++)
+ +
111  half_nu[i] = 0.5 * value_of(nu_vec[i]);
+
112 
+ +
114  T_partials_return, T_dof> lgamma_half_nu(length(nu));
+ +
116  T_partials_return, T_dof>
+
117  lgamma_half_nu_plus_half(length(nu));
+ +
119  for (size_t i = 0; i < length(nu); i++) {
+
120  lgamma_half_nu[i] = lgamma(half_nu[i]);
+
121  lgamma_half_nu_plus_half[i] = lgamma(half_nu[i] + 0.5);
+
122  }
+
123  }
+
124 
+ +
126  T_partials_return, T_dof> digamma_half_nu(length(nu));
+ +
128  T_partials_return, T_dof>
+
129  digamma_half_nu_plus_half(length(nu));
+ +
131  for (size_t i = 0; i < length(nu); i++) {
+
132  digamma_half_nu[i] = digamma(half_nu[i]);
+
133  digamma_half_nu_plus_half[i] = digamma(half_nu[i] + 0.5);
+
134  }
+
135  }
+
136 
+ +
138  T_partials_return, T_dof> log_nu(length(nu));
+
139  for (size_t i = 0; i < length(nu); i++)
+ +
141  log_nu[i] = log(value_of(nu_vec[i]));
+
142 
+ +
144  T_partials_return, T_scale> log_sigma(length(sigma));
+
145  for (size_t i = 0; i < length(sigma); i++)
+ +
147  log_sigma[i] = log(value_of(sigma_vec[i]));
+
148 
+ +
150  T_partials_return, T_y, T_dof, T_loc, T_scale>
+
151  square_y_minus_mu_over_sigma__over_nu(N);
+
152 
+ +
154  T_partials_return, T_y, T_dof, T_loc, T_scale>
+
155  log1p_exp(N);
+
156 
+
157  for (size_t i = 0; i < N; i++)
+ +
159  const T_partials_return y_dbl = value_of(y_vec[i]);
+
160  const T_partials_return mu_dbl = value_of(mu_vec[i]);
+
161  const T_partials_return sigma_dbl = value_of(sigma_vec[i]);
+
162  const T_partials_return nu_dbl = value_of(nu_vec[i]);
+
163  square_y_minus_mu_over_sigma__over_nu[i]
+
164  = square((y_dbl - mu_dbl) / sigma_dbl) / nu_dbl;
+
165  log1p_exp[i] = log1p(square_y_minus_mu_over_sigma__over_nu[i]);
+
166  }
+
167 
+ +
169  operands_and_partials(y, nu, mu, sigma);
+
170  for (size_t n = 0; n < N; n++) {
+
171  const T_partials_return y_dbl = value_of(y_vec[n]);
+
172  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
173  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
174  const T_partials_return nu_dbl = value_of(nu_vec[n]);
+ +
176  logp += NEG_LOG_SQRT_PI;
+ +
178  logp += lgamma_half_nu_plus_half[n] - lgamma_half_nu[n]
+
179  - 0.5 * log_nu[n];
+ +
181  logp -= log_sigma[n];
+ +
183  logp -= (half_nu[n] + 0.5)
+
184  * log1p_exp[n];
+
185 
+ +
187  operands_and_partials.d_x1[n]
+
188  += -(half_nu[n]+0.5)
+
189  * 1.0 / (1.0 + square_y_minus_mu_over_sigma__over_nu[n])
+
190  * (2.0 * (y_dbl - mu_dbl) / square(sigma_dbl) / nu_dbl);
+
191  }
+ +
193  const T_partials_return inv_nu = 1.0 / nu_dbl;
+
194  operands_and_partials.d_x2[n]
+
195  += 0.5*digamma_half_nu_plus_half[n] - 0.5*digamma_half_nu[n]
+
196  - 0.5 * inv_nu
+
197  - 0.5*log1p_exp[n]
+
198  + (half_nu[n] + 0.5)
+
199  * (1.0/(1.0 + square_y_minus_mu_over_sigma__over_nu[n])
+
200  * square_y_minus_mu_over_sigma__over_nu[n] * inv_nu);
+
201  }
+ +
203  operands_and_partials.d_x3[n]
+
204  -= (half_nu[n] + 0.5)
+
205  / (1.0 + square_y_minus_mu_over_sigma__over_nu[n])
+
206  * (2.0 * (mu_dbl - y_dbl) / (sigma_dbl*sigma_dbl*nu_dbl));
+
207  }
+ +
209  const T_partials_return inv_sigma = 1.0 / sigma_dbl;
+
210  operands_and_partials.d_x4[n]
+
211  += -inv_sigma
+
212  + (nu_dbl + 1.0) / (1.0 + square_y_minus_mu_over_sigma__over_nu[n])
+
213  * (square_y_minus_mu_over_sigma__over_nu[n] * inv_sigma);
+
214  }
+
215  }
+
216  return operands_and_partials.value(logp);
+
217  }
+
218 
+
219  template <typename T_y, typename T_dof, typename T_loc, typename T_scale>
+
220  inline
+ +
222  student_t_log(const T_y& y, const T_dof& nu, const T_loc& mu,
+
223  const T_scale& sigma) {
+
224  return student_t_log<false>(y, nu, mu, sigma);
+
225  }
+
226  }
+
227 }
+
228 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ +
fvar< T > lgamma(const fvar< T > &x)
Definition: lgamma.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
const double NEG_LOG_SQRT_PI
Definition: constants.hpp:189
+ +
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+ +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+ +
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
fvar< T > log1p_exp(const fvar< T > &x)
Definition: log1p_exp.hpp:13
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
fvar< T > log1p(const fvar< T > &x)
Definition: log1p.hpp:16
+
return_type< T_y, T_dof, T_loc, T_scale >::type student_t_log(const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
The log of the Student-t density for the given y, nu, mean, and scale parameter.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
fvar< T > digamma(const fvar< T > &x)
Definition: digamma.hpp:16
+
VectorView< T_return_type, false, true > d_x4
+
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diff --git a/doc/api/html/student__t__rng_8hpp.html b/doc/api/html/student__t__rng_8hpp.html new file mode 100644 index 00000000000..6abe67f0bb3 --- /dev/null +++ b/doc/api/html/student__t__rng_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::student_t_rng (const double nu, const double mu, const double sigma, RNG &rng)
 
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diff --git a/doc/api/html/student__t__rng_8hpp_source.html b/doc/api/html/student__t__rng_8hpp_source.html new file mode 100644 index 00000000000..9ecb58acab3 --- /dev/null +++ b/doc/api/html/student__t__rng_8hpp_source.html @@ -0,0 +1,178 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/student_t_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_STUDENT_T_RNG_HPP
+
3 
+
4 #include <boost/random/student_t_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + + + + + + +
21 
+
22 namespace stan {
+
23 
+
24  namespace math {
+
25 
+
26  template <class RNG>
+
27  inline double
+
28  student_t_rng(const double nu,
+
29  const double mu,
+
30  const double sigma,
+
31  RNG& rng) {
+
32  using boost::variate_generator;
+
33  using boost::random::student_t_distribution;
+
34 
+
35  static const char* function("stan::math::student_t_rng");
+
36 
+ + +
39 
+
40  check_positive_finite(function, "Degrees of freedom parameter", nu);
+
41  check_finite(function, "Location parameter", mu);
+
42  check_positive_finite(function, "Scale parameter", sigma);
+
43 
+
44  variate_generator<RNG&, student_t_distribution<> >
+
45  rng_unit_student_t(rng, student_t_distribution<>(nu));
+
46  return mu + sigma * rng_unit_student_t();
+
47  }
+
48  }
+
49 }
+
50 #endif
+ + + + + + + +
double student_t_rng(const double nu, const double mu, const double sigma, RNG &rng)
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
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diff --git a/doc/api/html/sub_8hpp.html b/doc/api/html/sub_8hpp.html new file mode 100644 index 00000000000..50b1d66c291 --- /dev/null +++ b/doc/api/html/sub_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/sub.hpp File Reference + + + + + + + + + + +
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void stan::math::sub (std::vector< double > &x, std::vector< double > &y, std::vector< double > &result)
 
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diff --git a/doc/api/html/sub_8hpp_source.html b/doc/api/html/sub_8hpp_source.html new file mode 100644 index 00000000000..f19b4995cc8 --- /dev/null +++ b/doc/api/html/sub_8hpp_source.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/arr/fun/sub.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_ARR_FUN_SUB_HPP
+
2 #define STAN_MATH_PRIM_ARR_FUN_SUB_HPP
+
3 
+
4 #include <vector>
+
5 #include <cstddef>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  inline void sub(std::vector<double>& x, std::vector<double>& y,
+
11  std::vector<double>& result) {
+
12  result.resize(x.size());
+
13  for (size_t i = 0; i < x.size(); ++i)
+
14  result[i] = x[i] - y[i];
+
15  }
+
16 
+
17  }
+
18 }
+
19 
+
20 #endif
+
void sub(std::vector< double > &x, std::vector< double > &y, std::vector< double > &result)
Definition: sub.hpp:10
+ +
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diff --git a/doc/api/html/sub__col_8hpp.html b/doc/api/html/sub__col_8hpp.html new file mode 100644 index 00000000000..2435b2f9542 --- /dev/null +++ b/doc/api/html/sub__col_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sub_col.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::sub_col (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t nrows)
 Return a nrows x 1 subcolumn starting at (i-1, j-1). More...
 
+
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diff --git a/doc/api/html/sub__col_8hpp_source.html b/doc/api/html/sub__col_8hpp_source.html new file mode 100644 index 00000000000..ad6695f3ae0 --- /dev/null +++ b/doc/api/html/sub__col_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sub_col.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SUB_COL_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SUB_COL_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
19  template <typename T>
+
20  inline
+
21  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
22  sub_col(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m,
+
23  size_t i, size_t j, size_t nrows) {
+
24  stan::math::check_row_index("sub_col", "i", m, i);
+
25  if (nrows > 0)
+
26  stan::math::check_row_index("sub_col", "i+nrows-1", m, i+nrows-1);
+
27  stan::math::check_column_index("sub_col", "j", m, j);
+
28  return m.block(i - 1, j - 1, nrows, 1);
+
29  }
+
30 
+
31 
+
32  }
+
33 }
+
34 
+
35 #endif
+
Eigen::Matrix< T, Eigen::Dynamic, 1 > sub_col(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t nrows)
Return a nrows x 1 subcolumn starting at (i-1, j-1).
Definition: sub_col.hpp:22
+ + +
bool check_row_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
Return true if the specified index is a valid row of the matrix.
+ + +
bool check_column_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
Return true if the specified index is a valid column of the matrix.
+
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+
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diff --git a/doc/api/html/sub__row_8hpp.html b/doc/api/html/sub__row_8hpp.html new file mode 100644 index 00000000000..58432086d94 --- /dev/null +++ b/doc/api/html/sub__row_8hpp.html @@ -0,0 +1,133 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sub_row.hpp File Reference + + + + + + + + + + +
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template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::sub_row (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t ncols)
 Return a 1 x nrows subrow starting at (i-1, j-1). More...
 
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diff --git a/doc/api/html/sub__row_8hpp_source.html b/doc/api/html/sub__row_8hpp_source.html new file mode 100644 index 00000000000..940e67871c6 --- /dev/null +++ b/doc/api/html/sub__row_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/sub_row.hpp Source File + + + + + + + + + + +
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sub_row.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SUB_ROW_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SUB_ROW_HPP
+
3 
+ + + +
7 
+
8 namespace stan {
+
9 
+
10  namespace math {
+
11 
+
20  template <typename T>
+
21  inline
+
22  Eigen::Matrix<T, 1, Eigen::Dynamic>
+
23  sub_row(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m,
+
24  size_t i, size_t j, size_t ncols) {
+
25  stan::math::check_row_index("sub_row", "i", m, i);
+
26  stan::math::check_column_index("sub_row", "j", m, j);
+
27  if (ncols > 0)
+
28  stan::math::check_column_index("sub_col", "j+ncols-1", m, j+ncols-1);
+
29  return m.block(i - 1, j - 1, 1, ncols);
+
30  }
+
31 
+
32  }
+
33 }
+
34 
+
35 #endif
+ +
Eigen::Matrix< T, 1, Eigen::Dynamic > sub_row(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m, size_t i, size_t j, size_t ncols)
Return a 1 x nrows subrow starting at (i-1, j-1).
Definition: sub_row.hpp:23
+ +
bool check_row_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
Return true if the specified index is a valid row of the matrix.
+ + +
bool check_column_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
Return true if the specified index is a valid column of the matrix.
+
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diff --git a/doc/api/html/subtract_8hpp.html b/doc/api/html/subtract_8hpp.html new file mode 100644 index 00000000000..d89b57635b7 --- /dev/null +++ b/doc/api/html/subtract_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/subtract.hpp File Reference + + + + + + + + + + +
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#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <stan/math/prim/mat/err/check_matching_dims.hpp>
+
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template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::subtract (const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
 Return the result of subtracting the second specified matrix from the first specified matrix. More...
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::subtract (const T1 &c, const Eigen::Matrix< T2, R, C > &m)
 
template<typename T1 , typename T2 , int R, int C>
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > stan::math::subtract (const Eigen::Matrix< T1, R, C > &m, const T2 &c)
 
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diff --git a/doc/api/html/subtract_8hpp_source.html b/doc/api/html/subtract_8hpp_source.html new file mode 100644 index 00000000000..e238fc447f1 --- /dev/null +++ b/doc/api/html/subtract_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/subtract.hpp Source File + + + + + + + + + + +
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subtract.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_SUBTRACT_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_SUBTRACT_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ + +
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
24  template <typename T1, typename T2, int R, int C>
+
25  inline
+
26  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
27  subtract(const Eigen::Matrix<T1, R, C>& m1,
+
28  const Eigen::Matrix<T2, R, C>& m2) {
+ +
30  "m1", m1,
+
31  "m2", m2);
+
32  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
33  R, C>
+
34  result(m1.rows(), m1.cols());
+
35  for (int i = 0; i < result.size(); ++i)
+
36  result(i) = m1(i) - m2(i);
+
37  return result;
+
38  }
+
39 
+
40  template <typename T1, typename T2, int R, int C>
+
41  inline
+
42  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
43  subtract(const T1& c,
+
44  const Eigen::Matrix<T2, R, C>& m) {
+
45  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
46  R, C>
+
47  result(m.rows(), m.cols());
+
48  for (int i = 0; i < m.size(); ++i)
+
49  result(i) = c - m(i);
+
50  return result;
+
51  }
+
52 
+
53  template <typename T1, typename T2, int R, int C>
+
54  inline
+
55  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type, R, C>
+
56  subtract(const Eigen::Matrix<T1, R, C>& m,
+
57  const T2& c) {
+
58  Eigen::Matrix<typename boost::math::tools::promote_args<T1, T2>::type,
+
59  R, C>
+
60  result(m.rows(), m.cols());
+
61  for (int i = 0; i < m.size(); ++i)
+
62  result(i) = m(i) - c;
+
63  return result;
+
64  }
+
65 
+
66  }
+
67 }
+
68 #endif
+ + +
Eigen::Matrix< typename boost::math::tools::promote_args< T1, T2 >::type, R, C > subtract(const Eigen::Matrix< T1, R, C > &m1, const Eigen::Matrix< T2, R, C > &m2)
Return the result of subtracting the second specified matrix from the first specified matrix...
Definition: subtract.hpp:27
+
bool check_matching_dims(const char *function, const char *name1, const Eigen::Matrix< T1, R1, C1 > &y1, const char *name2, const Eigen::Matrix< T2, R2, C2 > &y2)
Return true if the two matrices are of the same size.
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::tail (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t n)
 Return the specified number of elements as a vector from the back of the specified vector. More...
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::tail (const Eigen::Matrix< T, 1, Eigen::Dynamic > &rv, size_t n)
 Return the specified number of elements as a row vector from the back of the specified row vector. More...
 
template<typename T >
std::vector< T > stan::math::tail (const std::vector< T > &sv, size_t n)
 
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diff --git a/doc/api/html/tail_8hpp_source.html b/doc/api/html/tail_8hpp_source.html new file mode 100644 index 00000000000..d1364e85e4d --- /dev/null +++ b/doc/api/html/tail_8hpp_source.html @@ -0,0 +1,174 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/tail.hpp Source File + + + + + + + + + + +
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tail.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TAIL_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TAIL_HPP
+
3 
+ + + + + + +
10 #include <vector>
+
11 
+
12 namespace stan {
+
13 
+
14  namespace math {
+
15 
+
20  template <typename T>
+
21  inline
+
22  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
23  tail(const Eigen::Matrix<T, Eigen::Dynamic, 1>& v,
+
24  size_t n) {
+
25  if (n != 0)
+
26  stan::math::check_row_index("tail", "n", v, n);
+
27  return v.tail(n);
+
28  }
+
29 
+
30 
+
35  template <typename T>
+
36  inline
+
37  Eigen::Matrix<T, 1, Eigen::Dynamic>
+
38  tail(const Eigen::Matrix<T, 1, Eigen::Dynamic>& rv,
+
39  size_t n) {
+
40  if (n != 0)
+
41  stan::math::check_column_index("tail", "n", rv, n);
+
42  return rv.tail(n);
+
43  }
+
44 
+
45  template <typename T>
+
46  std::vector<T> tail(const std::vector<T>& sv,
+
47  size_t n) {
+
48  typedef typename index_type<std::vector<T> >::type idx_t;
+
49  if (n != 0)
+
50  stan::math::check_std_vector_index("tail", "n", sv, n);
+
51  std::vector<T> s;
+
52  for (idx_t i = sv.size() - n; i < sv.size(); ++i)
+
53  s.push_back(sv[i]);
+
54  return s;
+
55  }
+
56 
+
57 
+
58  }
+
59 }
+
60 
+
61 #endif
+ + + +
Eigen::Matrix< T, Eigen::Dynamic, 1 > tail(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &v, size_t n)
Return the specified number of elements as a vector from the back of the specified vector...
Definition: tail.hpp:23
+ +
bool check_row_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, size_t i)
Return true if the specified index is a valid row of the matrix.
+ +
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
bool check_std_vector_index(const char *function, const char *name, const std::vector< T > &y, int i)
Return true if the specified index is valid in std vector.
+ + +
bool check_column_index(const char *function, const char *name, const Eigen::Matrix< T_y, R, C > &y, const size_t i)
Return true if the specified index is a valid column of the matrix.
+
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template<typename T , int R, int C>
std::vector< T > stan::math::to_array_1d (const Eigen::Matrix< T, R, C > &matrix)
 
template<typename T >
std::vector< T > stan::math::to_array_1d (const std::vector< T > &x)
 
template<typename T >
std::vector< typename scalar_type< T >::type > stan::math::to_array_1d (const std::vector< std::vector< T > > &x)
 
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diff --git a/doc/api/html/to__array__1d_8hpp_source.html b/doc/api/html/to__array__1d_8hpp_source.html new file mode 100644 index 00000000000..c450e25848c --- /dev/null +++ b/doc/api/html/to__array__1d_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_array_1d.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TO_ARRAY_1D_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TO_ARRAY_1D_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  // real[] to_array_1d(matrix)
+
12  // real[] to_array_1d(row_vector)
+
13  // real[] to_array_1d(vector)
+
14  template <typename T, int R, int C>
+
15  inline std::vector<T> to_array_1d(
+
16  const Eigen::Matrix<T, R, C> & matrix
+
17  ) {
+
18  const T* datap = matrix.data();
+
19  int size = matrix.size();
+
20  std::vector<T> result(size);
+
21  for (int i=0; i < size; i++)
+
22  result[i] = datap[i];
+
23  return result;
+
24  }
+
25 
+
26  // real[] to_array_1d(...)
+
27  template <typename T>
+
28  inline std::vector<T>
+
29  to_array_1d(const std::vector<T> & x) {
+
30  return x;
+
31  }
+
32 
+
33  // real[] to_array_1d(...)
+
34  template <typename T>
+
35  inline std::vector<typename scalar_type<T>::type>
+
36  to_array_1d(const std::vector< std::vector<T> > & x) {
+
37  size_t size1 = x.size();
+
38  size_t size2 = 0;
+
39  if (size1 != 0)
+
40  size2 = x[0].size();
+
41  std::vector<T> y(size1*size2);
+
42  for (size_t i = 0, ij = 0; i < size1; i++)
+
43  for (size_t j = 0; j < size2; j++, ij++)
+
44  y[ij] = x[i][j];
+
45  return to_array_1d(y);
+
46  }
+
47 
+
48  }
+
49 }
+
50 #endif
+ + + +
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
+
std::vector< T > to_array_1d(const Eigen::Matrix< T, R, C > &matrix)
Definition: to_array_1d.hpp:15
+
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diff --git a/doc/api/html/to__array__2d_8hpp.html b/doc/api/html/to__array__2d_8hpp.html new file mode 100644 index 00000000000..30d60f8a76c --- /dev/null +++ b/doc/api/html/to__array__2d_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_array_2d.hpp File Reference + + + + + + + + + + +
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+#include <vector>
+
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template<typename T >
std::vector< std::vector< T > > stan::math::to_array_2d (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &matrix)
 
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diff --git a/doc/api/html/to__array__2d_8hpp_source.html b/doc/api/html/to__array__2d_8hpp_source.html new file mode 100644 index 00000000000..e9f1c24d415 --- /dev/null +++ b/doc/api/html/to__array__2d_8hpp_source.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_array_2d.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TO_ARRAY_2D_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TO_ARRAY_2D_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
10  // real[, ] to_array_2d(matrix)
+
11  template <typename T>
+
12  inline std::vector< std::vector<T> >
+ +
14  const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> & matrix
+
15  ) {
+
16  using std::vector;
+
17  const T* datap = matrix.data();
+
18  int C = matrix.cols();
+
19  int R = matrix.rows();
+
20  vector< vector<T> > result(R, vector<T>(C));
+
21  for (int i=0, ij=0; i < C; i++)
+
22  for (int j=0; j < R; j++, ij++)
+
23  result[j][i] = datap[ij];
+
24  return result;
+
25  }
+
26 
+
27  }
+
28 }
+
29 #endif
+ +
std::vector< std::vector< T > > to_array_2d(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &matrix)
Definition: to_array_2d.hpp:13
+ +
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diff --git a/doc/api/html/to__matrix_8hpp.html b/doc/api/html/to__matrix_8hpp.html new file mode 100644 index 00000000000..de5fb4b04a6 --- /dev/null +++ b/doc/api/html/to__matrix_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_matrix.hpp File Reference + + + + + + + + + + +
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+#include <vector>
+
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template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > stan::math::to_matrix (const std::vector< std::vector< T > > &vec)
 
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > stan::math::to_matrix (const std::vector< std::vector< int > > &vec)
 
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diff --git a/doc/api/html/to__matrix_8hpp_source.html b/doc/api/html/to__matrix_8hpp_source.html new file mode 100644 index 00000000000..eaeb7af5b0a --- /dev/null +++ b/doc/api/html/to__matrix_8hpp_source.html @@ -0,0 +1,169 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_matrix.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TO_MATRIX_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TO_MATRIX_HPP
+
3 
+ +
5  // stan::scalar_type
+
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  // matrix to_matrix(matrix)
+
12  // matrix to_matrix(vector)
+
13  // matrix to_matrix(row_vector)
+
14  template <typename T, int R, int C>
+
15  inline Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
16  to_matrix(Eigen::Matrix<T, R, C> matrix) {
+
17  return matrix;
+
18  }
+
19 
+
20  // matrix to_matrix(real[, ])
+
21  template <typename T>
+
22  inline Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
+
23  to_matrix(const std::vector< std::vector<T> > & vec) {
+
24  size_t R = vec.size();
+
25  if (R != 0) {
+
26  size_t C = vec[0].size();
+
27  Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> result(R, C);
+
28  T* datap = result.data();
+
29  for (size_t i=0, ij=0; i < C; i++)
+
30  for (size_t j=0; j < R; j++, ij++)
+
31  datap[ij] = vec[j][i];
+
32  return result;
+
33  } else {
+
34  return Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> (0, 0);
+
35  }
+
36  }
+
37 
+
38  // matrix to_matrix(int[, ])
+
39  inline Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>
+
40  to_matrix(const std::vector< std::vector<int> > & vec) {
+
41  size_t R = vec.size();
+
42  if (R != 0) {
+
43  size_t C = vec[0].size();
+
44  Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> result(R, C);
+
45  double* datap = result.data();
+
46  for (size_t i=0, ij=0; i < C; i++)
+
47  for (size_t j=0; j < R; j++, ij++)
+
48  datap[ij] = vec[j][i];
+
49  return result;
+
50  } else {
+
51  return Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> (0, 0);
+
52  }
+
53  }
+
54 
+
55  }
+
56 }
+
57 #endif
+
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > to_matrix(Eigen::Matrix< T, R, C > matrix)
Definition: to_matrix.hpp:16
+ + +
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diff --git a/doc/api/html/to__row__vector_8hpp.html b/doc/api/html/to__row__vector_8hpp.html new file mode 100644 index 00000000000..9928a6169ff --- /dev/null +++ b/doc/api/html/to__row__vector_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_row_vector.hpp File Reference + + + + + + + + + + +
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+#include <vector>
+
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template<typename T , int R, int C>
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::to_row_vector (const Eigen::Matrix< T, R, C > &matrix)
 
template<typename T >
Eigen::Matrix< T, 1, Eigen::Dynamic > stan::math::to_row_vector (const std::vector< T > &vec)
 
Eigen::Matrix< double, 1, Eigen::Dynamic > stan::math::to_row_vector (const std::vector< int > &vec)
 
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diff --git a/doc/api/html/to__row__vector_8hpp_source.html b/doc/api/html/to__row__vector_8hpp_source.html new file mode 100644 index 00000000000..ec26a83ce82 --- /dev/null +++ b/doc/api/html/to__row__vector_8hpp_source.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_row_vector.hpp Source File + + + + + + + + + + +
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_TO_ROW_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TO_ROW_VECTOR_HPP
+
3 
+ +
5 // stan::scalar_type
+
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  // row_vector to_row_vector(matrix)
+
12  // row_vector to_row_vector(vector)
+
13  // row_vector to_row_vector(row_vector)
+
14  template <typename T, int R, int C>
+
15  inline Eigen::Matrix<T, 1, Eigen::Dynamic>
+
16  to_row_vector(const Eigen::Matrix<T, R, C>& matrix) {
+
17  return Eigen::Matrix<T, 1, Eigen::Dynamic>::Map(matrix.data(),
+
18  matrix.rows()*matrix.cols());
+
19  }
+
20 
+
21  // row_vector to_row_vector(real[])
+
22  template <typename T>
+
23  inline Eigen::Matrix<T, 1, Eigen::Dynamic>
+
24  to_row_vector(const std::vector<T> & vec) {
+
25  return Eigen::Matrix<T, 1, Eigen::Dynamic>::Map(vec.data(), vec.size());
+
26  }
+
27 
+
28  // row_vector to_row_vector(int[])
+
29  inline Eigen::Matrix<double, 1, Eigen::Dynamic>
+
30  to_row_vector(const std::vector<int> & vec) {
+
31  int C = vec.size();
+
32  Eigen::Matrix<double, 1, Eigen::Dynamic> result(C);
+
33  double* datap = result.data();
+
34  for (int i=0; i < C; i++)
+
35  datap[i] = vec[i];
+
36  return result;
+
37  }
+
38 
+
39  }
+
40 }
+
41 #endif
+ +
Eigen::Matrix< T, 1, Eigen::Dynamic > to_row_vector(const Eigen::Matrix< T, R, C > &matrix)
+ +
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diff --git a/doc/api/html/to__vector_8hpp.html b/doc/api/html/to__vector_8hpp.html new file mode 100644 index 00000000000..62586140edc --- /dev/null +++ b/doc/api/html/to__vector_8hpp.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_vector.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
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template<typename T , int R, int C>
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::to_vector (const Eigen::Matrix< T, R, C > &matrix)
 
template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::to_vector (const std::vector< T > &vec)
 
Eigen::Matrix< double, Eigen::Dynamic, 1 > stan::math::to_vector (const std::vector< int > &vec)
 
+
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diff --git a/doc/api/html/to__vector_8hpp_source.html b/doc/api/html/to__vector_8hpp_source.html new file mode 100644 index 00000000000..83b14c4e876 --- /dev/null +++ b/doc/api/html/to__vector_8hpp_source.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/to_vector.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TO_VECTOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TO_VECTOR_HPP
+
3 
+ +
5  // stan::scalar_type
+
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  // vector to_vector(matrix)
+
12  // vector to_vector(row_vector)
+
13  // vector to_vector(vector)
+
14  template <typename T, int R, int C>
+
15  inline Eigen::Matrix<T, Eigen::Dynamic, 1>
+
16  to_vector(const Eigen::Matrix<T, R, C>& matrix) {
+
17  return Eigen::Matrix<T, Eigen::Dynamic, 1>::Map(matrix.data(),
+
18  matrix.rows()*matrix.cols());
+
19  }
+
20 
+
21  // vector to_vector(real[])
+
22  template <typename T>
+
23  inline Eigen::Matrix<T, Eigen::Dynamic, 1>
+
24  to_vector(const std::vector<T> & vec) {
+
25  return Eigen::Matrix<T, Eigen::Dynamic, 1>::Map(vec.data(), vec.size());
+
26  }
+
27 
+
28  // vector to_vector(int[])
+
29  inline Eigen::Matrix<double, Eigen::Dynamic, 1>
+
30  to_vector(const std::vector<int> & vec) {
+
31  int R = vec.size();
+
32  Eigen::Matrix<double, Eigen::Dynamic, 1> result(R);
+
33  double* datap = result.data();
+
34  for (int i=0; i < R; i++)
+
35  datap[i] = vec[i];
+
36  return result;
+
37  }
+
38 
+
39 
+
40  }
+
41 }
+
42 #endif
+ + +
Eigen::Matrix< T, Eigen::Dynamic, 1 > to_vector(const Eigen::Matrix< T, R, C > &matrix)
Definition: to_vector.hpp:16
+
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diff --git a/doc/api/html/trace_8hpp.html b/doc/api/html/trace_8hpp.html new file mode 100644 index 00000000000..a85f9713d1f --- /dev/null +++ b/doc/api/html/trace_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace.hpp File Reference + + + + + + + + + + +
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template<typename T >
stan::math::trace (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
 Returns the trace of the specified matrix. More...
 
template<typename T >
stan::math::trace (const T &m)
 
+
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diff --git a/doc/api/html/trace_8hpp_source.html b/doc/api/html/trace_8hpp_source.html new file mode 100644 index 00000000000..222eaefa3b5 --- /dev/null +++ b/doc/api/html/trace_8hpp_source.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/trace.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TRACE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TRACE_HPP
+
3 
+ +
5 
+
6 
+
7 namespace stan {
+
8  namespace math {
+
9 
+
19  template <typename T>
+
20  inline T trace(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& m) {
+
21  return m.trace();
+
22  }
+
23 
+
24  template <typename T>
+
25  inline T
+
26  trace(const T& m) {
+
27  return m;
+
28  }
+
29  }
+
30 }
+
31 #endif
+ + +
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+
+
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diff --git a/doc/api/html/transpose_8hpp.html b/doc/api/html/transpose_8hpp.html new file mode 100644 index 00000000000..b18515d9242 --- /dev/null +++ b/doc/api/html/transpose_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/transpose.hpp File Reference + + + + + + + + + + +
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template<typename T , int R, int C>
Eigen::Matrix< T, C, R > stan::math::transpose (const Eigen::Matrix< T, R, C > &m)
 
+
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diff --git a/doc/api/html/transpose_8hpp_source.html b/doc/api/html/transpose_8hpp_source.html new file mode 100644 index 00000000000..b4669901548 --- /dev/null +++ b/doc/api/html/transpose_8hpp_source.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/transpose.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_TRANSPOSE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_TRANSPOSE_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  template <typename T, int R, int C>
+
10  Eigen::Matrix<T, C, R>
+
11  inline
+
12  transpose(const Eigen::Matrix<T, R, C>& m) {
+
13  return m.transpose();
+
14  }
+
15 
+
16  }
+
17 }
+
18 #endif
+ + +
Eigen::Matrix< T, C, R > transpose(const Eigen::Matrix< T, R, C > &m)
Definition: transpose.hpp:12
+
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diff --git a/doc/api/html/trigamma_8hpp.html b/doc/api/html/trigamma_8hpp.html new file mode 100644 index 00000000000..5d0c2bd3cc7 --- /dev/null +++ b/doc/api/html/trigamma_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/trigamma.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/fun/constants.hpp>
+#include <cmath>
+
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template<typename T >
stan::math::trigamma (T x)
 

+\[ \mbox{trigamma}(x) = \begin{cases} \textrm{error} & \mbox{if } x\in \{\dots, -3, -2, -1, 0\}\\ \Psi_1(x) & \mbox{if } x\not\in \{\dots, -3, -2, -1, 0\}\\[6pt] \textrm{NaN} & \mbox{if } x = \textrm{NaN} \end{cases} \] +

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diff --git a/doc/api/html/trigamma_8hpp_source.html b/doc/api/html/trigamma_8hpp_source.html new file mode 100644 index 00000000000..12904c11384 --- /dev/null +++ b/doc/api/html/trigamma_8hpp_source.html @@ -0,0 +1,191 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/trigamma.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_TRIGAMMA_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_TRIGAMMA_HPP
+
3 
+
4  // Reference:
+
5  // BE Schneider,
+
6  // Algorithm AS 121:
+
7  // Trigamma Function,
+
8  // Applied Statistics,
+
9  // Volume 27, Number 1, pages 97-99, 1978.
+
10 
+ +
12 #include <cmath>
+
13 
+
14 namespace stan {
+
15 
+
16  namespace math {
+
17 
+
47  template <typename T>
+
48  inline
+
49  T
+
50  trigamma(T x) {
+
51  using std::floor;
+
52  using std::sin;
+
53 
+
54  double small = 0.0001;
+
55  double large = 5.0;
+
56  T value;
+
57  T y;
+
58  T z;
+
59 
+
60  // bernoulli numbers
+
61  double b2 = 1.0 / 6.0;
+
62  double b4 = -1.0 / 30.0;
+
63  double b6 = 1.0 / 42.0;
+
64  double b8 = -1.0 / 30.0;
+
65 
+
66  // negative integers and zero return postiive infinity
+
67  // see http:// mathworld.wolfram.com/PolygammaFunction.html
+
68  if ((x <= 0.0) && (floor(x) == x)) {
+
69  value = positive_infinity();
+
70  return value;
+
71  }
+
72 
+
73  // negative non-integers: use the reflection formula
+
74  // see http:// mathworld.wolfram.com/PolygammaFunction.html
+
75  if ((x <= 0) && (floor(x) != x)) {
+
76  value = -trigamma(-x + 1.0) + (pi() / sin(-pi() * x))
+
77  * (pi() / sin(-pi() * x));
+
78  return value;
+
79  }
+
80 
+
81  // small value approximation if x <= small.
+
82  if (x <= small)
+
83  return 1.0 / (x * x);
+
84 
+
85  // use recurrence relation until x >= large
+
86  // see http:// mathworld.wolfram.com/PolygammaFunction.html
+
87  z = x;
+
88  value = 0.0;
+
89  while (z < large) {
+
90  value += 1.0 / (z * z);
+
91  z += 1.0;
+
92  }
+
93 
+
94  // asymptotic expansion as a Laurent series if x >= large
+
95  // see http:// en.wikipedia.org/wiki/Trigamma_function
+
96  y = 1.0 / (z * z);
+
97  value += 0.5 * y + (1.0 + y * (b2 + y * (b4 + y * (b6 + y * b8)))) / z;
+
98 
+
99  return value;
+
100  }
+
101  }
+
102 }
+
103 
+
104 #endif
+
T trigamma(T x)
Definition: trigamma.hpp:50
+ +
fvar< T > sin(const fvar< T > &x)
Definition: sin.hpp:14
+
double positive_infinity()
Return positive infinity.
Definition: constants.hpp:123
+ +
fvar< T > floor(const fvar< T > &x)
Definition: floor.hpp:11
+
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
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diff --git a/doc/api/html/ub__constrain_8hpp.html b/doc/api/html/ub__constrain_8hpp.html new file mode 100644 index 00000000000..29822a06d33 --- /dev/null +++ b/doc/api/html/ub__constrain_8hpp.html @@ -0,0 +1,138 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/ub_constrain.hpp File Reference + + + + + + + + + + +
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+
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#include <boost/math/tools/promotion.hpp>
+#include <stan/math/prim/scal/fun/identity_constrain.hpp>
+#include <cmath>
+#include <limits>
+
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template<typename T , typename TU >
boost::math::tools::promote_args< T, TU >::type stan::math::ub_constrain (const T x, const TU ub)
 Return the upper-bounded value for the specified unconstrained scalar and upper bound. More...
 
template<typename T , typename TU >
boost::math::tools::promote_args< T, TU >::type stan::math::ub_constrain (const T x, const TU ub, T &lp)
 Return the upper-bounded value for the specified unconstrained scalar and upper bound and increment the specified log probability reference with the log absolute Jacobian determinant of the transform. More...
 
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diff --git a/doc/api/html/ub__constrain_8hpp_source.html b/doc/api/html/ub__constrain_8hpp_source.html new file mode 100644 index 00000000000..a04470cbd7f --- /dev/null +++ b/doc/api/html/ub__constrain_8hpp_source.html @@ -0,0 +1,154 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/ub_constrain.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_UB_CONSTRAIN_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_UB_CONSTRAIN_HPP
+
3 
+
4 #include <boost/math/tools/promotion.hpp>
+ +
6 #include <cmath>
+
7 #include <limits>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
13  // UPPER BOUND
+
14 
+
34  template <typename T, typename TU>
+
35  inline
+
36  typename boost::math::tools::promote_args<T, TU>::type
+
37  ub_constrain(const T x, const TU ub) {
+
38  using std::exp;
+
39  if (ub == std::numeric_limits<double>::infinity())
+
40  return identity_constrain(x);
+
41  return ub - exp(x);
+
42  }
+
43 
+
67  template <typename T, typename TU>
+
68  inline
+
69  typename boost::math::tools::promote_args<T, TU>::type
+
70  ub_constrain(const T x, const TU ub, T& lp) {
+
71  using std::exp;
+
72  if (ub == std::numeric_limits<double>::infinity())
+
73  return identity_constrain(x, lp);
+
74  lp += x;
+
75  return ub - exp(x);
+
76  }
+
77 
+
78  }
+
79 
+
80 }
+
81 
+
82 #endif
+ +
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+ +
boost::math::tools::promote_args< T, TU >::type ub_constrain(const T x, const TU ub)
Return the upper-bounded value for the specified unconstrained scalar and upper bound.
+
T identity_constrain(T x)
Returns the result of applying the identity constraint transform to the input.
+
+
+
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diff --git a/doc/api/html/ub__free_8hpp.html b/doc/api/html/ub__free_8hpp.html new file mode 100644 index 00000000000..c2ebdc378fc --- /dev/null +++ b/doc/api/html/ub__free_8hpp.html @@ -0,0 +1,135 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/ub_free.hpp File Reference + + + + + + + + + + +
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#include <stan/math/prim/scal/fun/identity_free.hpp>
+#include <stan/math/prim/scal/err/check_less_or_equal.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <cmath>
+#include <limits>
+
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template<typename T , typename TU >
boost::math::tools::promote_args< T, TU >::type stan::math::ub_free (const T y, const TU ub)
 Return the free scalar that corresponds to the specified upper-bounded value with respect to the specified upper bound. More...
 
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diff --git a/doc/api/html/ub__free_8hpp_source.html b/doc/api/html/ub__free_8hpp_source.html new file mode 100644 index 00000000000..f9160abca82 --- /dev/null +++ b/doc/api/html/ub__free_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/fun/ub_free.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_UB_FREE_HPP
+
2 #define STAN_MATH_PRIM_SCAL_FUN_UB_FREE_HPP
+
3 
+ + +
6 #include <boost/math/tools/promotion.hpp>
+
7 #include <cmath>
+
8 #include <limits>
+
9 
+
10 namespace stan {
+
11 
+
12  namespace math {
+
13 
+
36  template <typename T, typename TU>
+
37  inline
+
38  typename boost::math::tools::promote_args<T, TU>::type
+
39  ub_free(const T y, const TU ub) {
+
40  using std::log;
+
41  if (ub == std::numeric_limits<double>::infinity())
+
42  return identity_free(y);
+
43  stan::math::check_less_or_equal("stan::math::ub_free",
+
44  "Upper bounded variable", y, ub);
+
45  return log(ub - y);
+
46  }
+
47 
+
48 
+
49  }
+
50 
+
51 }
+
52 
+
53 #endif
+ +
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
boost::math::tools::promote_args< T, TU >::type ub_free(const T y, const TU ub)
Return the free scalar that corresponds to the specified upper-bounded value with respect to the spec...
Definition: ub_free.hpp:39
+ +
T identity_free(const T y)
Returns the result of applying the inverse of the identity constraint transform to the input...
+
bool check_less_or_equal(const char *function, const char *name, const T_y &y, const T_high &high)
Return true if y is less or equal to high.
+
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diff --git a/doc/api/html/uniform__ccdf__log_8hpp.html b/doc/api/html/uniform__ccdf__log_8hpp.html new file mode 100644 index 00000000000..5fb74c7ec0e --- /dev/null +++ b/doc/api/html/uniform__ccdf__log_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type stan::math::uniform_ccdf_log (const T_y &y, const T_low &alpha, const T_high &beta)
 
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diff --git a/doc/api/html/uniform__ccdf__log_8hpp_source.html b/doc/api/html/uniform__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..88bb7a6c703 --- /dev/null +++ b/doc/api/html/uniform__ccdf__log_8hpp_source.html @@ -0,0 +1,234 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_ccdf_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_UNIFORM_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_UNIFORM_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/uniform_real_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_low, typename T_high>
+
24  typename return_type<T_y, T_low, T_high>::type
+
25  uniform_ccdf_log(const T_y& y, const T_low& alpha, const T_high& beta) {
+
26  static const char* function("stan::math::uniform_ccdf_log");
+ +
28  T_partials_return;
+
29 
+ + + + + +
35  using std::log;
+
36 
+
37  // check if any vectors are zero length
+
38  if (!(stan::length(y)
+
39  && stan::length(alpha)
+
40  && stan::length(beta)))
+
41  return 0.0;
+
42 
+
43  // set up return value accumulator
+
44  T_partials_return ccdf_log(0.0);
+
45  check_not_nan(function, "Random variable", y);
+
46  check_finite(function, "Lower bound parameter", alpha);
+
47  check_finite(function, "Upper bound parameter", beta);
+
48  check_greater(function, "Upper bound parameter", beta, alpha);
+
49  check_consistent_sizes(function,
+
50  "Random variable", y,
+
51  "Lower bound parameter", alpha,
+
52  "Upper bound parameter", beta);
+
53 
+
54  VectorView<const T_y> y_vec(y);
+
55  VectorView<const T_low> alpha_vec(alpha);
+
56  VectorView<const T_high> beta_vec(beta);
+
57  size_t N = max_size(y, alpha, beta);
+
58 
+
59  for (size_t n = 0; n < N; n++) {
+
60  const T_partials_return y_dbl = value_of(y_vec[n]);
+
61  if (y_dbl < value_of(alpha_vec[n])
+
62  || y_dbl > value_of(beta_vec[n]))
+
63  return 0.0;
+
64  if (y_dbl == value_of(beta_vec[n]))
+
65  return LOG_ZERO;
+
66  }
+
67 
+ +
69  operands_and_partials(y, alpha, beta);
+
70  for (size_t n = 0; n < N; n++) {
+
71  const T_partials_return y_dbl = value_of(y_vec[n]);
+
72  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
73  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
74  const T_partials_return b_min_a = beta_dbl - alpha_dbl;
+
75  const T_partials_return ccdf_log_ = 1.0 - (y_dbl - alpha_dbl) / b_min_a;
+
76 
+
77  // ccdf_log
+
78  ccdf_log += log(ccdf_log_);
+
79 
+
80  // gradients
+ +
82  operands_and_partials.d_x1[n] -= 1.0 / b_min_a / ccdf_log_;
+ +
84  operands_and_partials.d_x2[n] -= (y_dbl - beta_dbl) / b_min_a
+
85  / b_min_a / ccdf_log_;
+ +
87  operands_and_partials.d_x3[n] += (y_dbl - alpha_dbl) / b_min_a
+
88  / b_min_a / ccdf_log_;
+
89  }
+
90 
+
91  return operands_and_partials.value(ccdf_log);
+
92  }
+
93  }
+
94 }
+
95 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + +
return_type< T_y, T_low, T_high >::type uniform_ccdf_log(const T_y &y, const T_low &alpha, const T_high &beta)
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/uniform__cdf_8hpp.html b/doc/api/html/uniform__cdf_8hpp.html new file mode 100644 index 00000000000..f798e17cce1 --- /dev/null +++ b/doc/api/html/uniform__cdf_8hpp.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_cdf.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type stan::math::uniform_cdf (const T_y &y, const T_low &alpha, const T_high &beta)
 
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diff --git a/doc/api/html/uniform__cdf_8hpp_source.html b/doc/api/html/uniform__cdf_8hpp_source.html new file mode 100644 index 00000000000..3193f853b1a --- /dev/null +++ b/doc/api/html/uniform__cdf_8hpp_source.html @@ -0,0 +1,240 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_cdf.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_UNIFORM_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_UNIFORM_CDF_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/uniform_real_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 
+
18 namespace stan {
+
19 
+
20  namespace math {
+
21 
+
22  template <typename T_y, typename T_low, typename T_high>
+
23  typename return_type<T_y, T_low, T_high>::type
+
24  uniform_cdf(const T_y& y, const T_low& alpha, const T_high& beta) {
+
25  static const char* function("stan::math::uniform_cdf");
+ +
27  T_partials_return;
+
28 
+ + + + + +
34 
+
35  // check if any vectors are zero length
+
36  if (!(stan::length(y)
+
37  && stan::length(alpha)
+
38  && stan::length(beta)))
+
39  return 1.0;
+
40 
+
41  // set up return value accumulator
+
42  T_partials_return cdf(1.0);
+
43  check_not_nan(function, "Random variable", y);
+
44  check_finite(function, "Lower bound parameter", alpha);
+
45  check_finite(function, "Upper bound parameter", beta);
+
46  check_greater(function, "Upper bound parameter", beta, alpha);
+
47  check_consistent_sizes(function,
+
48  "Random variable", y,
+
49  "Lower bound parameter", alpha,
+
50  "Upper bound parameter", beta);
+
51 
+
52  VectorView<const T_y> y_vec(y);
+
53  VectorView<const T_low> alpha_vec(alpha);
+
54  VectorView<const T_high> beta_vec(beta);
+
55  size_t N = max_size(y, alpha, beta);
+
56 
+
57  for (size_t n = 0; n < N; n++) {
+
58  const T_partials_return y_dbl = value_of(y_vec[n]);
+
59  if (y_dbl < value_of(alpha_vec[n])
+
60  || y_dbl > value_of(beta_vec[n]))
+
61  return 0.0;
+
62  }
+
63 
+ +
65  operands_and_partials(y, alpha, beta);
+
66  for (size_t n = 0; n < N; n++) {
+
67  const T_partials_return y_dbl = value_of(y_vec[n]);
+
68  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
69  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
70  const T_partials_return b_min_a = beta_dbl - alpha_dbl;
+
71  const T_partials_return cdf_ = (y_dbl - alpha_dbl) / b_min_a;
+
72 
+
73  // cdf
+
74  cdf *= cdf_;
+
75 
+
76  // gradients
+ +
78  operands_and_partials.d_x1[n] += 1.0 / b_min_a / cdf_;
+ +
80  operands_and_partials.d_x2[n] += (y_dbl - beta_dbl) / b_min_a
+
81  / b_min_a / cdf_;
+ +
83  operands_and_partials.d_x3[n] -= 1.0 / b_min_a;
+
84  }
+
85 
+ +
87  for (size_t n = 0; n < stan::length(y); ++n)
+
88  operands_and_partials.d_x1[n] *= cdf;
+
89  }
+ +
91  for (size_t n = 0; n < stan::length(alpha); ++n)
+
92  operands_and_partials.d_x2[n] *= cdf;
+
93  }
+ +
95  for (size_t n = 0; n < stan::length(beta); ++n)
+
96  operands_and_partials.d_x3[n] *= cdf;
+
97  }
+
98 
+
99  return operands_and_partials.value(cdf);
+
100  }
+
101  }
+
102 }
+
103 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
return_type< T_y, T_low, T_high >::type uniform_cdf(const T_y &y, const T_low &alpha, const T_high &beta)
Definition: uniform_cdf.hpp:24
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/uniform__cdf__log_8hpp.html b/doc/api/html/uniform__cdf__log_8hpp.html new file mode 100644 index 00000000000..c9003a3d2e6 --- /dev/null +++ b/doc/api/html/uniform__cdf__log_8hpp.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_cdf_log.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
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+
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uniform_cdf_log.hpp File Reference
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template<typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type stan::math::uniform_cdf_log (const T_y &y, const T_low &alpha, const T_high &beta)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/uniform__cdf__log_8hpp_source.html b/doc/api/html/uniform__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..bab215cfed4 --- /dev/null +++ b/doc/api/html/uniform__cdf__log_8hpp_source.html @@ -0,0 +1,234 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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uniform_cdf_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_UNIFORM_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_UNIFORM_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/uniform_real_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  template <typename T_y, typename T_low, typename T_high>
+
24  typename return_type<T_y, T_low, T_high>::type
+
25  uniform_cdf_log(const T_y& y, const T_low& alpha, const T_high& beta) {
+
26  static const char* function("stan::math::uniform_cdf_log");
+ +
28  T_partials_return;
+
29 
+ + + + + +
35  using std::log;
+
36 
+
37  // check if any vectors are zero length
+
38  if (!(stan::length(y)
+
39  && stan::length(alpha)
+
40  && stan::length(beta)))
+
41  return 0.0;
+
42 
+
43  // set up return value accumulator
+
44  T_partials_return cdf_log(0.0);
+
45  check_not_nan(function, "Random variable", y);
+
46  check_finite(function, "Lower bound parameter", alpha);
+
47  check_finite(function, "Upper bound parameter", beta);
+
48  check_greater(function, "Upper bound parameter", beta, alpha);
+
49  check_consistent_sizes(function,
+
50  "Random variable", y,
+
51  "Lower bound parameter", alpha,
+
52  "Upper bound parameter", beta);
+
53 
+
54  VectorView<const T_y> y_vec(y);
+
55  VectorView<const T_low> alpha_vec(alpha);
+
56  VectorView<const T_high> beta_vec(beta);
+
57  size_t N = max_size(y, alpha, beta);
+
58 
+ +
60  operands_and_partials(y, alpha, beta);
+
61 
+
62  for (size_t n = 0; n < N; n++) {
+
63  const T_partials_return y_dbl = value_of(y_vec[n]);
+
64  if (y_dbl < value_of(alpha_vec[n])
+
65  || y_dbl > value_of(beta_vec[n]))
+ +
67  if (y_dbl == value_of(beta_vec[n]))
+
68  return operands_and_partials.value(0.0);
+
69  }
+
70 
+
71  for (size_t n = 0; n < N; n++) {
+
72  const T_partials_return y_dbl = value_of(y_vec[n]);
+
73  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
74  const T_partials_return beta_dbl = value_of(beta_vec[n]);
+
75  const T_partials_return b_min_a = beta_dbl - alpha_dbl;
+
76  const T_partials_return cdf_log_ = (y_dbl - alpha_dbl) / b_min_a;
+
77 
+
78  // cdf_log
+
79  cdf_log += log(cdf_log_);
+
80 
+
81  // gradients
+ +
83  operands_and_partials.d_x1[n] += 1.0 / b_min_a / cdf_log_;
+ +
85  operands_and_partials.d_x2[n] += (y_dbl - beta_dbl) / b_min_a
+
86  / b_min_a / cdf_log_;
+ +
88  operands_and_partials.d_x3[n] -= 1.0 / b_min_a;
+
89  }
+
90 
+
91  return operands_and_partials.value(cdf_log);
+
92  }
+
93  }
+
94 }
+
95 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ +
return_type< T_y, T_low, T_high >::type uniform_cdf_log(const T_y &y, const T_low &alpha, const T_high &beta)
+ + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ + +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
VectorView< T_return_type, false, true > d_x1
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/uniform__log_8hpp.html b/doc/api/html/uniform__log_8hpp.html new file mode 100644 index 00000000000..478762be76c --- /dev/null +++ b/doc/api/html/uniform__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ +
+
uniform_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

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 Matrices and templated mathematical functions.
 
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+Functions

template<bool propto, typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type stan::math::uniform_log (const T_y &y, const T_low &alpha, const T_high &beta)
 The log of a uniform density for the given y, lower, and upper bound. More...
 
template<typename T_y , typename T_low , typename T_high >
return_type< T_y, T_low, T_high >::type stan::math::uniform_log (const T_y &y, const T_low &alpha, const T_high &beta)
 
+
+
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diff --git a/doc/api/html/uniform__log_8hpp_source.html b/doc/api/html/uniform__log_8hpp_source.html new file mode 100644 index 00000000000..3c72d5a9cbd --- /dev/null +++ b/doc/api/html/uniform__log_8hpp_source.html @@ -0,0 +1,251 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_log.hpp Source File + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
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uniform_log.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_UNIFORM_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_UNIFORM_LOG_HPP
+
3 
+ + + + + + + + + + + +
15 #include <boost/random/uniform_real_distribution.hpp>
+
16 #include <boost/random/variate_generator.hpp>
+
17 #include <cmath>
+
18 
+
19 namespace stan {
+
20 
+
21  namespace math {
+
22 
+
23  // CONTINUOUS, UNIVARIATE DENSITIES
+
45  template <bool propto,
+
46  typename T_y, typename T_low, typename T_high>
+
47  typename return_type<T_y, T_low, T_high>::type
+
48  uniform_log(const T_y& y, const T_low& alpha, const T_high& beta) {
+
49  static const char* function("stan::math::uniform_log");
+ +
51  T_partials_return;
+
52 
+ + + + + +
58  using std::log;
+
59 
+
60  // check if any vectors are zero length
+
61  if (!(stan::length(y)
+
62  && stan::length(alpha)
+
63  && stan::length(beta)))
+
64  return 0.0;
+
65 
+
66  // set up return value accumulator
+
67  T_partials_return logp(0.0);
+
68  check_not_nan(function, "Random variable", y);
+
69  check_finite(function, "Lower bound parameter", alpha);
+
70  check_finite(function, "Upper bound parameter", beta);
+
71  check_greater(function, "Upper bound parameter", beta, alpha);
+
72  check_consistent_sizes(function,
+
73  "Random variable", y,
+
74  "Lower bound parameter", alpha,
+
75  "Upper bound parameter", beta);
+
76 
+
77  // check if no variables are involved and prop-to
+ +
79  return 0.0;
+
80 
+
81  VectorView<const T_y> y_vec(y);
+
82  VectorView<const T_low> alpha_vec(alpha);
+
83  VectorView<const T_high> beta_vec(beta);
+
84  size_t N = max_size(y, alpha, beta);
+
85 
+
86  for (size_t n = 0; n < N; n++) {
+
87  const T_partials_return y_dbl = value_of(y_vec[n]);
+
88  if (y_dbl < value_of(alpha_vec[n])
+
89  || y_dbl > value_of(beta_vec[n]))
+
90  return LOG_ZERO;
+
91  }
+
92 
+ +
94  T_partials_return, T_low, T_high>
+
95  inv_beta_minus_alpha(max_size(alpha, beta));
+
96  for (size_t i = 0; i < max_size(alpha, beta); i++)
+ +
98  inv_beta_minus_alpha[i]
+
99  = 1.0 / (value_of(beta_vec[i]) - value_of(alpha_vec[i]));
+
100 
+ +
102  T_partials_return, T_low, T_high>
+
103  log_beta_minus_alpha(max_size(alpha, beta));
+
104  for (size_t i = 0; i < max_size(alpha, beta); i++)
+ +
106  log_beta_minus_alpha[i]
+
107  = log(value_of(beta_vec[i]) - value_of(alpha_vec[i]));
+
108 
+ +
110  operands_and_partials(y, alpha, beta);
+
111  for (size_t n = 0; n < N; n++) {
+ +
113  logp -= log_beta_minus_alpha[n];
+
114 
+ +
116  operands_and_partials.d_x2[n] += inv_beta_minus_alpha[n];
+ +
118  operands_and_partials.d_x3[n] -= inv_beta_minus_alpha[n];
+
119  }
+
120  return operands_and_partials.value(logp);
+
121  }
+
122 
+
123  template <typename T_y, typename T_low, typename T_high>
+
124  inline
+ +
126  uniform_log(const T_y& y, const T_low& alpha, const T_high& beta) {
+
127  return uniform_log<false>(y, alpha, beta);
+
128  }
+
129  }
+
130 }
+
131 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
return_type< T_y, T_low, T_high >::type uniform_log(const T_y &y, const T_low &alpha, const T_high &beta)
The log of a uniform density for the given y, lower, and upper bound.
Definition: uniform_log.hpp:48
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
+
+
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diff --git a/doc/api/html/uniform__rng_8hpp.html b/doc/api/html/uniform__rng_8hpp.html new file mode 100644 index 00000000000..4e3bae31b9f --- /dev/null +++ b/doc/api/html/uniform__rng_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_rng.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
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uniform_rng.hpp File Reference
+
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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<class RNG >
double stan::math::uniform_rng (const double alpha, const double beta, RNG &rng)
 
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diff --git a/doc/api/html/uniform__rng_8hpp_source.html b/doc/api/html/uniform__rng_8hpp_source.html new file mode 100644 index 00000000000..bf524f4fa30 --- /dev/null +++ b/doc/api/html/uniform__rng_8hpp_source.html @@ -0,0 +1,163 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/uniform_rng.hpp Source File + + + + + + + + + + +
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uniform_rng.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_UNIFORM_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_UNIFORM_RNG_HPP
+
3 
+
4 #include <boost/random/uniform_real_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + +
14 
+
15 namespace stan {
+
16 
+
17  namespace math {
+
18 
+
19  template <class RNG>
+
20  inline double
+
21  uniform_rng(const double alpha,
+
22  const double beta,
+
23  RNG& rng) {
+
24  using boost::variate_generator;
+
25  using boost::random::uniform_real_distribution;
+
26 
+
27  static const char* function("stan::math::uniform_rng");
+
28 
+ + +
31 
+
32  check_finite(function, "Lower bound parameter", alpha);
+
33  check_finite(function, "Upper bound parameter", beta);
+
34  check_greater(function, "Upper bound parameter", beta, alpha);
+
35 
+
36  variate_generator<RNG&, uniform_real_distribution<> >
+
37  uniform_rng(rng, uniform_real_distribution<>(alpha, beta));
+
38  return uniform_rng();
+
39  }
+
40  }
+
41 }
+
42 #endif
+ + + + +
double uniform_rng(const double alpha, const double beta, RNG &rng)
Definition: uniform_rng.hpp:21
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + + + +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
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diff --git a/doc/api/html/unit__vector__free_8hpp.html b/doc/api/html/unit__vector__free_8hpp.html new file mode 100644 index 00000000000..2c84e05e323 --- /dev/null +++ b/doc/api/html/unit__vector__free_8hpp.html @@ -0,0 +1,134 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/unit_vector_free.hpp File Reference + + + + + + + + + + +
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 Matrices and templated mathematical functions.
 
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+Functions

template<typename T >
Eigen::Matrix< T, Eigen::Dynamic, 1 > stan::math::unit_vector_free (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
 Transformation of a unit length vector to a "free" vector However, we are just fixing the unidentified radius to 1. More...
 
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diff --git a/doc/api/html/unit__vector__free_8hpp_source.html b/doc/api/html/unit__vector__free_8hpp_source.html new file mode 100644 index 00000000000..0c653ebfa72 --- /dev/null +++ b/doc/api/html/unit__vector__free_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/unit_vector_free.hpp Source File + + + + + + + + + + +
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unit_vector_free.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_UNIT_VECTOR_FREE_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_UNIT_VECTOR_FREE_HPP
+
3 
+ + + +
7 #include <cmath>
+
8 
+
9 namespace stan {
+
10 
+
11  namespace math {
+
12 
+
22  template <typename T>
+
23  Eigen::Matrix<T, Eigen::Dynamic, 1>
+
24  unit_vector_free(const Eigen::Matrix<T, Eigen::Dynamic, 1>& x) {
+
25  stan::math::check_unit_vector("stan::math::unit_vector_free",
+
26  "Unit vector variable", x);
+
27  return x;
+
28  }
+
29 
+
30  }
+
31 
+
32 }
+
33 
+
34 #endif
+ + + +
Eigen::Matrix< T, Eigen::Dynamic, 1 > unit_vector_free(const Eigen::Matrix< T, Eigen::Dynamic, 1 > &x)
Transformation of a unit length vector to a "free" vector However, we are just fixing the unidentifie...
+ +
bool check_unit_vector(const char *function, const char *name, const Eigen::Matrix< T_prob, Eigen::Dynamic, 1 > &theta)
Return true if the specified vector is unit vector.
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diff --git a/doc/api/html/v__vari_8hpp.html b/doc/api/html/v__vari_8hpp.html new file mode 100644 index 00000000000..1a0903999dd --- /dev/null +++ b/doc/api/html/v__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/v_vari.hpp File Reference + + + + + + + + + + +
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v_vari.hpp File Reference
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+Classes

class  stan::math::op_v_vari
 
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+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
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+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/v__vari_8hpp_source.html b/doc/api/html/v__vari_8hpp_source.html new file mode 100644 index 00000000000..334fc2102bf --- /dev/null +++ b/doc/api/html/v__vari_8hpp_source.html @@ -0,0 +1,136 @@ + + + + + + +Stan Math Library: stan/math/rev/core/v_vari.hpp Source File + + + + + + + + + + +
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v_vari.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_V_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_V_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_v_vari : public vari {
+
10  protected:
+ +
12  public:
+
13  op_v_vari(double f, vari* avi) :
+
14  vari(f),
+
15  avi_(avi) {
+
16  }
+
17  };
+
18 
+
19  }
+
20 }
+
21 #endif
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+ + +
op_v_vari(double f, vari *avi)
Definition: v_vari.hpp:13
+
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diff --git a/doc/api/html/validate__non__negative__index_8hpp.html b/doc/api/html/validate__non__negative__index_8hpp.html new file mode 100644 index 00000000000..253f23cdee9 --- /dev/null +++ b/doc/api/html/validate__non__negative__index_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/validate_non_negative_index.hpp File Reference + + + + + + + + + + +
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#include <sstream>
+#include <stdexcept>
+#include <string>
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 Matrices and templated mathematical functions.
 
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void stan::math::validate_non_negative_index (const char *var_name, const char *expr, int val)
 
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diff --git a/doc/api/html/validate__non__negative__index_8hpp_source.html b/doc/api/html/validate__non__negative__index_8hpp_source.html new file mode 100644 index 00000000000..d693d753af0 --- /dev/null +++ b/doc/api/html/validate__non__negative__index_8hpp_source.html @@ -0,0 +1,140 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/err/validate_non_negative_index.hpp Source File + + + + + + + + + + +
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validate_non_negative_index.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_ERR_VALIDATE_NON_NEGATIVE_INDEX_HPP
+
2 #define STAN_MATH_PRIM_MAT_ERR_VALIDATE_NON_NEGATIVE_INDEX_HPP
+
3 
+
4 #include <sstream>
+
5 #include <stdexcept>
+
6 #include <string>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  inline void
+
12  validate_non_negative_index(const char* var_name,
+
13  const char* expr,
+
14  int val) {
+
15  if (val < 0) {
+
16  std::stringstream msg;
+
17  msg << "Found negative dimension size in variable declaration"
+
18  << "; variable=" << var_name
+
19  << "; dimension size expression=" << expr
+
20  << "; expression value=" << val;
+
21  std::string msg_str(msg.str());
+
22  throw std::invalid_argument(msg_str.c_str());
+
23  }
+
24  }
+
25 
+
26  }
+
27 }
+
28 #endif
+ +
void validate_non_negative_index(const char *var_name, const char *expr, int val)
+
void invalid_argument(const char *function, const char *name, const T &y, const char *msg1, const char *msg2)
Throw an invalid_argument exception with a consistently formatted message.
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diff --git a/doc/api/html/var_8hpp.html b/doc/api/html/var_8hpp.html new file mode 100644 index 00000000000..f5e66c73230 --- /dev/null +++ b/doc/api/html/var_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/rev/core/var.hpp File Reference + + + + + + + + + + +
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var.hpp File Reference
+
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+
#include <stan/math/rev/core/vari.hpp>
+#include <stan/math/rev/core/grad.hpp>
+#include <stan/math/rev/core/chainable_alloc.hpp>
+#include <boost/math/tools/config.hpp>
+#include <ostream>
+#include <vector>
+
+

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+Classes

class  stan::math::var
 Independent (input) and dependent (output) variables for gradients. More...
 
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+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + +

+Functions

static void stan::math::grad (vari *vi)
 
+
+
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diff --git a/doc/api/html/var_8hpp_source.html b/doc/api/html/var_8hpp_source.html new file mode 100644 index 00000000000..4d35ccd1024 --- /dev/null +++ b/doc/api/html/var_8hpp_source.html @@ -0,0 +1,285 @@ + + + + + + +Stan Math Library: stan/math/rev/core/var.hpp Source File + + + + + + + + + + +
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var.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_VAR_HPP
+
2 #define STAN_MATH_REV_CORE_VAR_HPP
+
3 
+ + + +
7 #include <boost/math/tools/config.hpp>
+
8 #include <ostream>
+
9 #include <vector>
+
10 
+
11 namespace stan {
+
12 
+
13  namespace math {
+
14 
+
15  // forward declare
+
16  static void grad(vari* vi);
+
17 
+
31  class var {
+
32  public:
+
33  // FIXME: doc what this is for
+
34  typedef double Scalar;
+
35 
+
43  vari * vi_;
+
44 
+ +
55  return (vi_ == static_cast<vari*>(0U));
+
56  }
+
57 
+
65  var() : vi_(static_cast<vari*>(0U)) { }
+
66 
+
67 
+
73  var(vari* vi) : vi_(vi) { } // NOLINT
+
74 
+
82  var(float x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
83 
+
91  var(double x) : vi_(new vari(x)) { } // NOLINT
+
92 
+
100  var(long double x) : vi_(new vari(x)) { } // NOLINT
+
101 
+
109  var(bool x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
110 
+
118  var(char x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
119 
+
127  var(short x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
128 
+
136  var(int x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
137 
+
145  var(long x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
146 
+
154  var(unsigned char x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
155 
+
163  // NOLINTNEXTLINE
+
164  var(unsigned short x) : vi_(new vari(static_cast<double>(x))) { }
+
165 
+
173  var(unsigned int x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
174 
+
182  // NOLINTNEXTLINE
+
183  var(unsigned long x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
184 
+
185 #ifdef _WIN64
+
186 
+
187  // these two ctors are for Win64 to enable 64-bit signed
+
188  // and unsigned integers, because long and unsigned long
+
189  // are still 32-bit
+
190 
+
198  var(size_t x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
199 
+
200 
+
208  var(ptrdiff_t x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
209 #endif
+
210 
+
211 
+
212 #ifdef BOOST_MATH_USE_FLOAT128
+
213 
+
214  // this ctor is for later GCCs that have the __float128
+
215  // type enabled, because it gets enabled by boost
+
216 
+
224  var(__float128 x) : vi_(new vari(static_cast<double>(x))) { } // NOLINT
+
225 
+
226 #endif
+
227 
+
233  inline double val() const {
+
234  return vi_->val_;
+
235  }
+
236 
+
245  inline double adj() const {
+
246  return vi_->adj_;
+
247  }
+
248 
+
261  void grad(std::vector<var>& x,
+
262  std::vector<double>& g) {
+
263  stan::math::grad(vi_);
+
264  g.resize(x.size());
+
265  for (size_t i = 0; i < x.size(); ++i)
+
266  g[i] = x[i].vi_->adj_;
+
267  }
+
268 
+
275  void grad() {
+
276  stan::math::grad(vi_);
+
277  }
+
278 
+
279  // POINTER OVERRIDES
+
280 
+
293  inline vari& operator*() {
+
294  return *vi_;
+
295  }
+
296 
+
307  inline vari* operator->() {
+
308  return vi_;
+
309  }
+
310 
+
311  // COMPOUND ASSIGNMENT OPERATORS
+
312 
+
323  inline var& operator+=(const var& b);
+
324 
+
335  inline var& operator+=(const double b);
+
336 
+
348  inline var& operator-=(const var& b);
+
349 
+
361  inline var& operator-=(const double b);
+
362 
+
374  inline var& operator*=(const var& b);
+
375 
+
387  inline var& operator*=(const double b);
+
388 
+
399  inline var& operator/=(const var& b);
+
400 
+
412  inline var& operator/=(const double b);
+
413 
+
422  friend std::ostream& operator<<(std::ostream& os, const var& v) {
+
423  if (v.vi_ == 0)
+
424  return os << "uninitialized";
+
425  return os << v.val();
+
426  }
+
427  };
+
428 
+
429  }
+
430 }
+
431 #endif
+
var & operator+=(const var &b)
The compound add/assignment operator for variables (C++).
+
var & operator*=(const var &b)
The compound multiply/assignment operator for variables (C++).
+
var(unsigned char x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:154
+ +
var(long x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:145
+ +
var & operator/=(const var &b)
The compound divide/assignment operator for variables (C++).
+
var(unsigned long x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:183
+
The variable implementation base class.
Definition: vari.hpp:30
+ +
var(vari *vi)
Construct a variable from a pointer to a variable implementation.
Definition: var.hpp:73
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
vari & operator*()
Return a reference to underlying implementation of this variable.
Definition: var.hpp:293
+
static void grad(vari *vi)
Compute the gradient for all variables starting from the specified root variable implementation.
Definition: grad.hpp:30
+
var & operator-=(const var &b)
The compound subtract/assignment operator for variables (C++).
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
var(double x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:91
+
var(bool x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:109
+
var(char x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:118
+
bool is_uninitialized()
Return true if this variable has been declared, but not been defined.
Definition: var.hpp:54
+
var(unsigned int x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:173
+
var()
Construct a variable for later assignment.
Definition: var.hpp:65
+
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:43
+ +
var(float x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:82
+
void grad(std::vector< var > &x, std::vector< double > &g)
Compute the gradient of this (dependent) variable with respect to the specified vector of (independen...
Definition: var.hpp:261
+
vari * operator->()
Return a pointer to the underlying implementation of this variable.
Definition: var.hpp:307
+
void grad()
Compute the gradient of this (dependent) variable with respect to all (independent) variables...
Definition: var.hpp:275
+
var(long double x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:100
+
var(int x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:136
+
double Scalar
Definition: var.hpp:34
+
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+
double val() const
Return the value of this variable.
Definition: var.hpp:233
+
friend std::ostream & operator<<(std::ostream &os, const var &v)
Write the value of this auto-dif variable and its adjoint to the specified output stream...
Definition: var.hpp:422
+
double adj() const
Return the derivative of the root expression with respect to this expression.
Definition: var.hpp:245
+
var(unsigned short x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:164
+
var(short x)
Construct a variable from the specified arithmetic argument by constructing a new vari with the argum...
Definition: var.hpp:127
+
+
+
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diff --git a/doc/api/html/vari_8hpp.html b/doc/api/html/vari_8hpp.html new file mode 100644 index 00000000000..e9ae149a1ae --- /dev/null +++ b/doc/api/html/vari_8hpp.html @@ -0,0 +1,132 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vari.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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reverse mode automatic differentiation
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+
vari.hpp File Reference
+
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Go to the source code of this file.

+ + + + + +

+Classes

class  stan::math::vari
 The variable implementation base class. More...
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vari_8hpp_source.html b/doc/api/html/vari_8hpp_source.html new file mode 100644 index 00000000000..c7e36bee3ab --- /dev/null +++ b/doc/api/html/vari_8hpp_source.html @@ -0,0 +1,195 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
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+ +
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+
+
+
vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_VARI_HPP
+
3 
+ + +
6 #include <ostream>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  // forward declaration of var
+
12  class var;
+
13 
+
30  class vari {
+
31  private:
+
32  friend class var;
+
33 
+
34  public:
+
38  const double val_;
+
39 
+
44  double adj_;
+
45 
+
58  explicit vari(const double x):
+
59  val_(x),
+
60  adj_(0.0) {
+
61  ChainableStack::var_stack_.push_back(this);
+
62  }
+
63 
+
64  vari(const double x, bool stacked):
+
65  val_(x),
+
66  adj_(0.0) {
+
67  if (stacked)
+
68  ChainableStack::var_stack_.push_back(this);
+
69  else
+
70  ChainableStack::var_nochain_stack_.push_back(this);
+
71  }
+
72 
+
80  virtual ~vari() {
+
81  // this will never get called
+
82  }
+
83 
+
89  virtual void chain() {
+
90  }
+
91 
+
98  void init_dependent() {
+
99  adj_ = 1.0;
+
100  }
+
101 
+ +
108  adj_ = 0.0;
+
109  }
+
110 
+
120  friend std::ostream& operator<<(std::ostream& os, const vari* v) {
+
121  return os << v->val_ << ":" << v->adj_;
+
122  }
+
123 
+
134  static inline void* operator new(size_t nbytes) {
+
135  return ChainableStack::memalloc_.alloc(nbytes);
+
136  }
+
137 
+
149  static inline void operator delete(void* /* ignore arg */) {
+
150  /* no op */
+
151  }
+
152  };
+
153 
+
154  }
+
155 }
+
156 #endif
+
vari(const double x)
Construct a variable implementation from a value.
Definition: vari.hpp:58
+
virtual void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
Definition: vari.hpp:89
+
friend std::ostream & operator<<(std::ostream &os, const vari *v)
Insertion operator for vari.
Definition: vari.hpp:120
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
virtual ~vari()
Throw an illegal argument exception.
Definition: vari.hpp:80
+
const double val_
The value of this variable.
Definition: vari.hpp:38
+
void set_zero_adjoint()
Set the adjoint value of this variable to 0.
Definition: vari.hpp:107
+
vari(const double x, bool stacked)
Definition: vari.hpp:64
+
static std::vector< ChainableT * > var_nochain_stack_
+ +
void init_dependent()
Initialize the adjoint for this (dependent) variable to 1.
Definition: vari.hpp:98
+
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
+ +
static std::vector< ChainableT * > var_stack_
+
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vd__vari_8hpp.html b/doc/api/html/vd__vari_8hpp.html new file mode 100644 index 00000000000..21a2ad476c0 --- /dev/null +++ b/doc/api/html/vd__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vd_vari.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
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+
+
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+
+ +
+
vd_vari.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::op_vd_vari
 
+ + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vd__vari_8hpp_source.html b/doc/api/html/vd__vari_8hpp_source.html new file mode 100644 index 00000000000..bfd7cf7b2ae --- /dev/null +++ b/doc/api/html/vd__vari_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vd_vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ +
+ + +
+
+
+
vd_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_VD_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_VD_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_vd_vari : public vari {
+
10  protected:
+ +
12  double bd_;
+
13  public:
+
14  op_vd_vari(double f, vari* avi, double b) :
+
15  vari(f),
+
16  avi_(avi),
+
17  bd_(b) {
+
18  }
+
19  };
+
20 
+
21  }
+
22 }
+
23 #endif
+
op_vd_vari(double f, vari *avi, double b)
Definition: vd_vari.hpp:14
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vdd__vari_8hpp.html b/doc/api/html/vdd__vari_8hpp.html new file mode 100644 index 00000000000..beaf4aa60ac --- /dev/null +++ b/doc/api/html/vdd__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vdd_vari.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
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+
+ +
+
vdd_vari.hpp File Reference
+
+
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Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::op_vdd_vari
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vdd__vari_8hpp_source.html b/doc/api/html/vdd__vari_8hpp_source.html new file mode 100644 index 00000000000..358364044a0 --- /dev/null +++ b/doc/api/html/vdd__vari_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vdd_vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + + + + + +
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+
+
+
vdd_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_VDD_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_VDD_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_vdd_vari : public vari {
+
10  protected:
+ +
12  double bd_;
+
13  double cd_;
+
14  public:
+
15  op_vdd_vari(double f, vari* avi, double b, double c) :
+
16  vari(f),
+
17  avi_(avi),
+
18  bd_(b),
+
19  cd_(c) {
+
20  }
+
21  };
+
22 
+
23  }
+
24 }
+
25 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+ + + +
op_vdd_vari(double f, vari *avi, double b, double c)
Definition: vdd_vari.hpp:15
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vdv__vari_8hpp.html b/doc/api/html/vdv__vari_8hpp.html new file mode 100644 index 00000000000..4dc45fdaed4 --- /dev/null +++ b/doc/api/html/vdv__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vdv_vari.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
vdv_vari.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::op_vdv_vari
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vdv__vari_8hpp_source.html b/doc/api/html/vdv__vari_8hpp_source.html new file mode 100644 index 00000000000..406b482961d --- /dev/null +++ b/doc/api/html/vdv__vari_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vdv_vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
vdv_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_VDV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_VDV_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_vdv_vari : public vari {
+
10  protected:
+ +
12  double bd_;
+ +
14  public:
+
15  op_vdv_vari(double f, vari* avi, double b, vari* cvi) :
+
16  vari(f),
+
17  avi_(avi),
+
18  bd_(b),
+
19  cvi_(cvi) {
+
20  }
+
21  };
+
22 
+
23  }
+
24 }
+
25 #endif
+ + +
The variable implementation base class.
Definition: vari.hpp:30
+ + +
op_vdv_vari(double f, vari *avi, double b, vari *cvi)
Definition: vdv_vari.hpp:15
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vector__vari_8hpp.html b/doc/api/html/vector__vari_8hpp.html new file mode 100644 index 00000000000..f5951e47c37 --- /dev/null +++ b/doc/api/html/vector__vari_8hpp.html @@ -0,0 +1,131 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vector_vari.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
vector_vari.hpp File Reference
+
+
+
#include <stan/math/rev/core/var.hpp>
+#include <stan/math/rev/core/vari.hpp>
+#include <vector>
+
+

Go to the source code of this file.

+ + + + +

+Classes

class  stan::math::op_vector_vari
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/vector__vari_8hpp_source.html b/doc/api/html/vector__vari_8hpp_source.html new file mode 100644 index 00000000000..ea8a8fac5f5 --- /dev/null +++ b/doc/api/html/vector__vari_8hpp_source.html @@ -0,0 +1,153 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vector_vari.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
vector_vari.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_REV_CORE_VECTOR_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_VECTOR_VARI_HPP
+
3 
+ + +
6 #include <vector>
+
7 
+
8 namespace stan {
+
9  namespace math {
+
10 
+
11  class op_vector_vari : public vari {
+
12  protected:
+
13  const size_t size_;
+ +
15  public:
+
16  op_vector_vari(double f, const std::vector<stan::math::var>& vs) :
+
17  vari(f),
+
18  size_(vs.size()) {
+
19  vis_ = reinterpret_cast<vari**>
+
20  (operator new(sizeof(vari*) * vs.size()));
+
21  for (size_t i = 0; i < vs.size(); ++i)
+
22  vis_[i] = vs[i].vi_;
+
23  }
+
24  vari* operator[](size_t n) const {
+
25  return vis_[n];
+
26  }
+
27  size_t size() {
+
28  return size_;
+
29  }
+
30  };
+
31 
+
32  }
+
33 }
+
34 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+
vari * operator[](size_t n) const
Definition: vector_vari.hpp:24
+ + + +
op_vector_vari(double f, const std::vector< stan::math::var > &vs)
Definition: vector_vari.hpp:16
+ +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/version_8hpp.html b/doc/api/html/version_8hpp.html new file mode 100644 index 00000000000..0e2872d1db5 --- /dev/null +++ b/doc/api/html/version_8hpp.html @@ -0,0 +1,229 @@ + + + + + + +Stan Math Library: stan/math/version.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
version.hpp File Reference
+
+
+
#include <string>
+
+

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + + + + + +

+Macros

#define STAN_STRING_EXPAND(s)   #s
 
#define STAN_STRING(s)   STAN_STRING_EXPAND(s)
 
#define STAN_MATH_MAJOR   2
 
#define STAN_MATH_MINOR   10
 
#define STAN_MATH_PATCH   0
 
+ + + + + + + + + + +

+Variables

const std::string stan::math::MAJOR_VERSION = STAN_STRING(STAN_MATH_MAJOR)
 Major version number for Stan math library. More...
 
const std::string stan::math::MINOR_VERSION = STAN_STRING(STAN_MATH_MINOR)
 Minor version number for Stan math library. More...
 
const std::string stan::math::PATCH_VERSION = STAN_STRING(STAN_MATH_PATCH)
 Patch version for Stan math library. More...
 
+

Macro Definition Documentation

+ +
+
+ + + + +
#define STAN_MATH_MAJOR   2
+
+ +

Definition at line 14 of file version.hpp.

+ +
+
+ +
+
+ + + + +
#define STAN_MATH_MINOR   10
+
+ +

Definition at line 15 of file version.hpp.

+ +
+
+ +
+
+ + + + +
#define STAN_MATH_PATCH   0
+
+ +

Definition at line 16 of file version.hpp.

+ +
+
+ +
+
+ + + + + + + + +
#define STAN_STRING( s)   STAN_STRING_EXPAND(s)
+
+ +

Definition at line 11 of file version.hpp.

+ +
+
+ +
+
+ + + + + + + + +
#define STAN_STRING_EXPAND( s)   #s
+
+ +

Definition at line 7 of file version.hpp.

+ +
+
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/version_8hpp_source.html b/doc/api/html/version_8hpp_source.html new file mode 100644 index 00000000000..3368538c6a7 --- /dev/null +++ b/doc/api/html/version_8hpp_source.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/version.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
version.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_VERSION_HPP
+
2 #define STAN_MATH_VERSION_HPP
+
3 
+
4 #include <string>
+
5 
+
6 #ifndef STAN_STRING_EXPAND
+
7 #define STAN_STRING_EXPAND(s) #s
+
8 #endif
+
9 
+
10 #ifndef STAN_STRING
+
11 #define STAN_STRING(s) STAN_STRING_EXPAND(s)
+
12 #endif
+
13 
+
14 #define STAN_MATH_MAJOR 2
+
15 #define STAN_MATH_MINOR 10
+
16 #define STAN_MATH_PATCH 0
+
17 
+
18 namespace stan {
+
19  namespace math {
+
20 
+ +
23 
+ +
26 
+ +
29 
+
30  }
+
31 }
+
32 
+
33 #endif
+
#define STAN_MATH_PATCH
Definition: version.hpp:16
+
#define STAN_MATH_MAJOR
Definition: version.hpp:14
+ +
#define STAN_MATH_MINOR
Definition: version.hpp:15
+
const std::string MINOR_VERSION
Minor version number for Stan math library.
Definition: version.hpp:25
+
const std::string PATCH_VERSION
Patch version for Stan math library.
Definition: version.hpp:28
+
const std::string MAJOR_VERSION
Major version number for Stan math library.
Definition: version.hpp:22
+
#define STAN_STRING(s)
Definition: version.hpp:11
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/von__mises__log_8hpp.html b/doc/api/html/von__mises__log_8hpp.html new file mode 100644 index 00000000000..af3ddf9b9a9 --- /dev/null +++ b/doc/api/html/von__mises__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/von_mises_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
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+
+ +
+
von_mises_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::von_mises_log (T_y const &y, T_loc const &mu, T_scale const &kappa)
 
template<typename T_y , typename T_loc , typename T_scale >
return_type< T_y, T_loc, T_scale >::type stan::math::von_mises_log (T_y const &y, T_loc const &mu, T_scale const &kappa)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/von__mises__log_8hpp_source.html b/doc/api/html/von__mises__log_8hpp_source.html new file mode 100644 index 00000000000..f6195f37595 --- /dev/null +++ b/doc/api/html/von__mises__log_8hpp_source.html @@ -0,0 +1,292 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/von_mises_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
von_mises_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_VON_MISES_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_VON_MISES_LOG_HPP
+
3 
+ + + + + + + + + + + + + + +
18 #include <cmath>
+
19 
+
20 namespace stan {
+
21 
+
22  namespace math {
+
23 
+
24  template<bool propto,
+
25  typename T_y, typename T_loc, typename T_scale>
+
26  typename return_type<T_y, T_loc, T_scale>::type
+
27  von_mises_log(T_y const& y, T_loc const& mu, T_scale const& kappa) {
+
28  static char const* const function = "stan::math::von_mises_log";
+ +
30  T_partials_return;
+
31 
+
32  // check if any vectors are zero length
+
33  if (!(stan::length(y)
+
34  && stan::length(mu)
+
35  && stan::length(kappa)))
+
36  return 0.0;
+
37 
+ + + + + + + +
45 
+ +
47  using std::log;
+
48 
+
49  // Result accumulator.
+
50  T_partials_return logp = 0.0;
+
51 
+
52  // Validate arguments.
+
53  check_finite(function, "Random variable", y);
+
54  check_finite(function, "Location paramter", mu);
+
55  check_positive_finite(function, "Scale parameter", kappa);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Location parameter", mu,
+
59  "Scale parameter", kappa);
+
60 
+
61 
+
62  // check if no variables are involved and prop-to
+ +
64  return logp;
+
65 
+
66  // Determine constants.
+
67  const bool y_const = is_constant_struct<T_y>::value;
+
68  const bool mu_const = is_constant_struct<T_loc>::value;
+
69  const bool kappa_const = is_constant_struct<T_scale>::value;
+
70 
+
71  // Determine which expensive computations to perform.
+
72  const bool compute_bessel0 = include_summand<propto, T_scale>::value;
+
73  const bool compute_bessel1 = !kappa_const;
+
74  const double TWO_PI = 2.0 * stan::math::pi();
+
75 
+
76  // Wrap scalars into vector views.
+
77  VectorView<const T_y> y_vec(y);
+
78  VectorView<const T_loc> mu_vec(mu);
+
79  VectorView<const T_scale> kappa_vec(kappa);
+
80 
+ + +
83  T_partials_return, T_scale> log_bessel0(length(kappa));
+
84  for (size_t i = 0; i < length(kappa); i++) {
+
85  kappa_dbl[i] = value_of(kappa_vec[i]);
+ +
87  log_bessel0[i]
+
88  = log(modified_bessel_first_kind(0, value_of(kappa_vec[i])));
+
89  }
+
90 
+ +
92  operands_and_partials(y, mu, kappa);
+
93 
+
94  size_t N = max_size(y, mu, kappa);
+
95 
+
96  for (size_t n = 0; n < N; n++) {
+
97  // Extract argument values.
+
98  const T_partials_return y_ = value_of(y_vec[n]);
+
99  const T_partials_return y_dbl = y_ - floor(y_ / TWO_PI) * TWO_PI;
+
100  const T_partials_return mu_dbl = value_of(mu_vec[n]);
+
101 
+
102  // Reusable values.
+
103  T_partials_return bessel0 = 0;
+
104  if (compute_bessel0)
+
105  bessel0 = modified_bessel_first_kind(0, kappa_dbl[n]);
+
106  T_partials_return bessel1 = 0;
+
107  if (compute_bessel1)
+
108  bessel1 = modified_bessel_first_kind(-1, kappa_dbl[n]);
+
109  const T_partials_return kappa_sin = kappa_dbl[n] * sin(mu_dbl - y_dbl);
+
110  const T_partials_return kappa_cos = kappa_dbl[n] * cos(mu_dbl - y_dbl);
+
111 
+
112  // Log probability.
+ +
114  logp -= LOG_TWO_PI;
+ +
116  logp -= log_bessel0[n];
+ +
118  logp += kappa_cos;
+
119 
+
120  // Gradient.
+
121  if (!y_const)
+
122  operands_and_partials.d_x1[n] += kappa_sin;
+
123  if (!mu_const)
+
124  operands_and_partials.d_x2[n] -= kappa_sin;
+
125  if (!kappa_const)
+
126  operands_and_partials.d_x3[n] += kappa_cos / kappa_dbl[n]
+
127  - bessel1 / bessel0;
+
128  }
+
129 
+
130  return operands_and_partials.value(logp);
+
131  }
+
132 
+
133  template<typename T_y, typename T_loc, typename T_scale>
+ +
135  von_mises_log(T_y const& y, T_loc const& mu, T_scale const& kappa) {
+
136  return von_mises_log<false>(y, mu, kappa);
+
137  }
+
138  }
+
139 }
+
140 #endif
+
fvar< T > cos(const fvar< T > &x)
Definition: cos.hpp:13
+
VectorView< T_return_type, false, true > d_x2
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
vari ** y_
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ +
const double LOG_TWO_PI
Definition: constants.hpp:193
+ + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > modified_bessel_first_kind(int v, const fvar< T > &z)
+
fvar< T > sin(const fvar< T > &x)
Definition: sin.hpp:14
+
return_type< T_y, T_loc, T_scale >::type von_mises_log(T_y const &y, T_loc const &mu, T_scale const &kappa)
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
fvar< T > floor(const fvar< T > &x)
Definition: floor.hpp:11
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
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diff --git a/doc/api/html/von__mises__rng_8hpp.html b/doc/api/html/von__mises__rng_8hpp.html new file mode 100644 index 00000000000..40f9ffb4500 --- /dev/null +++ b/doc/api/html/von__mises__rng_8hpp.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/von_mises_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::von_mises_rng (const double mu, const double kappa, RNG &rng)
 
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diff --git a/doc/api/html/von__mises__rng_8hpp_source.html b/doc/api/html/von__mises__rng_8hpp_source.html new file mode 100644 index 00000000000..6ea423b7ebc --- /dev/null +++ b/doc/api/html/von__mises__rng_8hpp_source.html @@ -0,0 +1,203 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/von_mises_rng.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_VON_MISES_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_VON_MISES_RNG_HPP
+
3 
+ + + + + + + + + +
13 #include <cmath>
+
14 
+
15 namespace stan {
+
16 
+
17  namespace math {
+
18 
+
19  // The algorithm used in von_mises_rng is a modified version of the
+
20  // algorithm in:
+
21  //
+
22  // Efficient Simulation of the von Mises Distribution
+
23  // D. J. Best and N. I. Fisher
+
24  // Journal of the Royal Statistical Society. Series C (Applied Statistics),
+
25  // Vol. 28, No. 2 (1979), pp. 152-157
+
26  //
+
27  // See licenses/stan-license.txt for Stan license.
+
28 
+
29  template <class RNG>
+
30  inline double
+
31  von_mises_rng(const double mu,
+
32  const double kappa,
+
33  RNG& rng) {
+
34  using boost::variate_generator;
+ +
36  using std::fmod;
+
37  using std::log;
+
38  using std::pow;
+
39 
+
40  static const char* function("stan::math::von_mises_rng");
+
41 
+
42  stan::math::check_finite(function, "mean", mu);
+
43  stan::math::check_positive_finite(function, "inverse of variance", kappa);
+
44 
+
45  double r = 1 + pow((1 + 4 * kappa * kappa), 0.5);
+
46  double rho = 0.5 * (r - pow(2 * r, 0.5)) / kappa;
+
47  double s = 0.5 * (1 + rho * rho) / rho;
+
48 
+
49  bool done = 0;
+
50  double W;
+
51  while (!done) {
+
52  double Z = std::cos(stan::math::pi() * uniform_rng(0.0, 1.0, rng));
+
53  W = (1 + s * Z) / (s + Z);
+
54  double Y = kappa * (s - W);
+
55  double U2 = uniform_rng(0.0, 1.0, rng);
+
56  done = Y * (2 - Y) - U2 > 0;
+
57 
+
58  if (!done)
+
59  done = log(Y / U2) + 1 - Y >= 0;
+
60  }
+
61 
+
62  double U3 = uniform_rng(0.0, 1.0, rng) - 0.5;
+
63  double sign = ((U3 >= 0) - (U3 <= 0));
+
64 
+
65  // it's really an fmod() with a positivity constraint
+
66  return sign * std::acos(W)
+
67  + fmod(fmod(mu, 2*stan::math::pi())+2*stan::math::pi(),
+
68  2*stan::math::pi());
+
69  }
+
70 
+
71  }
+
72 }
+
73 #endif
+
fvar< T > cos(const fvar< T > &x)
Definition: cos.hpp:13
+ + +
int sign(const T &z)
Definition: sign.hpp:9
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
fvar< T > fmod(const fvar< T > &x1, const fvar< T > &x2)
Definition: fmod.hpp:16
+ + + + +
double von_mises_rng(const double mu, const double kappa, RNG &rng)
+
double uniform_rng(const double alpha, const double beta, RNG &rng)
Definition: uniform_rng.hpp:21
+
fvar< T > acos(const fvar< T > &x)
Definition: acos.hpp:14
+
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ + +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
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diff --git a/doc/api/html/vv__vari_8hpp.html b/doc/api/html/vv__vari_8hpp.html new file mode 100644 index 00000000000..05ffd6f6f70 --- /dev/null +++ b/doc/api/html/vv__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vv_vari.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/vv__vari_8hpp_source.html b/doc/api/html/vv__vari_8hpp_source.html new file mode 100644 index 00000000000..f0e086a2610 --- /dev/null +++ b/doc/api/html/vv__vari_8hpp_source.html @@ -0,0 +1,139 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vv_vari.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_VV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_VV_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_vv_vari : public vari {
+
10  protected:
+ + +
13  public:
+
14  op_vv_vari(double f, vari* avi, vari* bvi):
+
15  vari(f),
+
16  avi_(avi),
+
17  bvi_(bvi) {
+
18  }
+
19  };
+
20 
+
21  }
+
22 }
+
23 #endif
+ + +
op_vv_vari(double f, vari *avi, vari *bvi)
Definition: vv_vari.hpp:14
+
The variable implementation base class.
Definition: vari.hpp:30
+ + + +
+
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diff --git a/doc/api/html/vvd__vari_8hpp.html b/doc/api/html/vvd__vari_8hpp.html new file mode 100644 index 00000000000..2aed5bc44f5 --- /dev/null +++ b/doc/api/html/vvd__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vvd_vari.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/vvd__vari_8hpp_source.html b/doc/api/html/vvd__vari_8hpp_source.html new file mode 100644 index 00000000000..f3b96c902cd --- /dev/null +++ b/doc/api/html/vvd__vari_8hpp_source.html @@ -0,0 +1,142 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vvd_vari.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_VVD_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_VVD_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7  namespace math {
+
8 
+
9  class op_vvd_vari : public vari {
+
10  protected:
+ + +
13  double cd_;
+
14  public:
+
15  op_vvd_vari(double f, vari* avi, vari* bvi, double c) :
+
16  vari(f),
+
17  avi_(avi),
+
18  bvi_(bvi),
+
19  cd_(c) {
+
20  }
+
21  };
+
22 
+
23  }
+
24 }
+
25 #endif
+ + + +
The variable implementation base class.
Definition: vari.hpp:30
+ +
op_vvd_vari(double f, vari *avi, vari *bvi, double c)
Definition: vvd_vari.hpp:15
+ + +
+
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diff --git a/doc/api/html/vvv__vari_8hpp.html b/doc/api/html/vvv__vari_8hpp.html new file mode 100644 index 00000000000..0d456797021 --- /dev/null +++ b/doc/api/html/vvv__vari_8hpp.html @@ -0,0 +1,129 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vvv_vari.hpp File Reference + + + + + + + + + + +
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diff --git a/doc/api/html/vvv__vari_8hpp_source.html b/doc/api/html/vvv__vari_8hpp_source.html new file mode 100644 index 00000000000..93eab699891 --- /dev/null +++ b/doc/api/html/vvv__vari_8hpp_source.html @@ -0,0 +1,143 @@ + + + + + + +Stan Math Library: stan/math/rev/core/vvv_vari.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_REV_CORE_VVV_VARI_HPP
+
2 #define STAN_MATH_REV_CORE_VVV_VARI_HPP
+
3 
+ +
5 
+
6 namespace stan {
+
7 
+
8  namespace math {
+
9 
+
10  class op_vvv_vari : public vari {
+
11  protected:
+ + + +
15  public:
+
16  op_vvv_vari(double f, vari* avi, vari* bvi, vari* cvi) :
+
17  vari(f),
+
18  avi_(avi),
+
19  bvi_(bvi),
+
20  cvi_(cvi) {
+
21  }
+
22  };
+
23 
+
24  }
+
25 }
+
26 #endif
+ + + + + +
The variable implementation base class.
Definition: vari.hpp:30
+
op_vvv_vari(double f, vari *avi, vari *bvi, vari *cvi)
Definition: vvv_vari.hpp:16
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diff --git a/doc/api/html/weibull__ccdf__log_8hpp.html b/doc/api/html/weibull__ccdf__log_8hpp.html new file mode 100644 index 00000000000..0a4f3ca5946 --- /dev/null +++ b/doc/api/html/weibull__ccdf__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_ccdf_log.hpp File Reference + + + + + + + + + + +
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template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::weibull_ccdf_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
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diff --git a/doc/api/html/weibull__ccdf__log_8hpp_source.html b/doc/api/html/weibull__ccdf__log_8hpp_source.html new file mode 100644 index 00000000000..430f631606a --- /dev/null +++ b/doc/api/html/weibull__ccdf__log_8hpp_source.html @@ -0,0 +1,222 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_ccdf_log.hpp Source File + + + + + + + + + + +
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_WEIBULL_CCDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_WEIBULL_CCDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/weibull_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <typename T_y, typename T_shape, typename T_scale>
+
28  typename return_type<T_y, T_shape, T_scale>::type
+
29  weibull_ccdf_log(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+ +
31  T_partials_return;
+
32 
+
33  static const char* function("stan::math::weibull_ccdf_log");
+
34 
+ + +
37  using boost::math::tools::promote_args;
+ +
39  using std::log;
+
40 
+
41  // check if any vectors are zero length
+
42  if (!(stan::length(y)
+
43  && stan::length(alpha)
+
44  && stan::length(sigma)))
+
45  return 0.0;
+
46 
+
47  T_partials_return ccdf_log(0.0);
+
48  check_nonnegative(function, "Random variable", y);
+
49  check_positive_finite(function, "Shape parameter", alpha);
+
50  check_positive_finite(function, "Scale parameter", sigma);
+
51 
+ +
53  operands_and_partials(y, alpha, sigma);
+
54 
+
55  VectorView<const T_y> y_vec(y);
+
56  VectorView<const T_scale> sigma_vec(sigma);
+
57  VectorView<const T_shape> alpha_vec(alpha);
+
58  size_t N = max_size(y, sigma, alpha);
+
59  for (size_t n = 0; n < N; n++) {
+
60  const T_partials_return y_dbl = value_of(y_vec[n]);
+
61  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
62  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
63  const T_partials_return pow_ = pow(y_dbl / sigma_dbl, alpha_dbl);
+
64 
+
65  // ccdf_log
+
66  ccdf_log -= pow_;
+
67 
+
68  // gradients
+ +
70  operands_and_partials.d_x1[n] -= alpha_dbl / y_dbl * pow_;
+ +
72  operands_and_partials.d_x2[n] -= log(y_dbl / sigma_dbl) * pow_;
+ +
74  operands_and_partials.d_x3[n] += alpha_dbl / sigma_dbl * pow_;
+
75  }
+
76 
+
77  return operands_and_partials.value(ccdf_log);
+
78  }
+
79  }
+
80 }
+
81 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + + +
return_type< T_y, T_shape, T_scale >::type weibull_ccdf_log(const T_y &y, const T_shape &alpha, const T_scale &sigma)
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/weibull__cdf_8hpp.html b/doc/api/html/weibull__cdf_8hpp.html new file mode 100644 index 00000000000..334106b97ca --- /dev/null +++ b/doc/api/html/weibull__cdf_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_cdf.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
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weibull_cdf.hpp File Reference
+
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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::weibull_cdf (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/weibull__cdf_8hpp_source.html b/doc/api/html/weibull__cdf_8hpp_source.html new file mode 100644 index 00000000000..0154f938c30 --- /dev/null +++ b/doc/api/html/weibull__cdf_8hpp_source.html @@ -0,0 +1,240 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_cdf.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
weibull_cdf.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_WEIBULL_CDF_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_WEIBULL_CDF_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/weibull_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <typename T_y, typename T_shape, typename T_scale>
+
28  typename return_type<T_y, T_shape, T_scale>::type
+
29  weibull_cdf(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+ +
31  T_partials_return;
+
32 
+
33  static const char* function("stan::math::weibull_cdf");
+
34 
+ + +
37  using boost::math::tools::promote_args;
+ +
39  using std::log;
+
40  using std::exp;
+
41 
+
42  // check if any vectors are zero length
+
43  if (!(stan::length(y)
+
44  && stan::length(alpha)
+
45  && stan::length(sigma)))
+
46  return 1.0;
+
47 
+
48  T_partials_return cdf(1.0);
+
49  check_nonnegative(function, "Random variable", y);
+
50  check_positive_finite(function, "Shape parameter", alpha);
+
51  check_positive_finite(function, "Scale parameter", sigma);
+
52 
+ +
54  operands_and_partials(y, alpha, sigma);
+
55 
+
56  VectorView<const T_y> y_vec(y);
+
57  VectorView<const T_scale> sigma_vec(sigma);
+
58  VectorView<const T_shape> alpha_vec(alpha);
+
59  size_t N = max_size(y, sigma, alpha);
+
60  for (size_t n = 0; n < N; n++) {
+
61  const T_partials_return y_dbl = value_of(y_vec[n]);
+
62  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
63  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
64  const T_partials_return pow_ = pow(y_dbl / sigma_dbl, alpha_dbl);
+
65  const T_partials_return exp_ = exp(-pow_);
+
66  const T_partials_return cdf_ = 1.0 - exp_;
+
67 
+
68  // cdf
+
69  cdf *= cdf_;
+
70 
+
71  // gradients
+
72  const T_partials_return rep_deriv = exp_ * pow_ / cdf_;
+ +
74  operands_and_partials.d_x1[n] += rep_deriv * alpha_dbl / y_dbl;
+ +
76  operands_and_partials.d_x2[n] += rep_deriv * log(y_dbl / sigma_dbl);
+ +
78  operands_and_partials.d_x3[n] -= rep_deriv * alpha_dbl / sigma_dbl;
+
79  }
+
80 
+ +
82  for (size_t n = 0; n < stan::length(y); ++n)
+
83  operands_and_partials.d_x1[n] *= cdf;
+
84  }
+ +
86  for (size_t n = 0; n < stan::length(alpha); ++n)
+
87  operands_and_partials.d_x2[n] *= cdf;
+
88  }
+ +
90  for (size_t n = 0; n < stan::length(sigma); ++n)
+
91  operands_and_partials.d_x3[n] *= cdf;
+
92  }
+
93 
+
94  return operands_and_partials.value(cdf);
+
95  }
+
96  }
+
97 }
+
98 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
return_type< T_y, T_shape, T_scale >::type weibull_cdf(const T_y &y, const T_shape &alpha, const T_scale &sigma)
Definition: weibull_cdf.hpp:29
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/weibull__cdf__log_8hpp.html b/doc/api/html/weibull__cdf__log_8hpp.html new file mode 100644 index 00000000000..4af487d37e1 --- /dev/null +++ b/doc/api/html/weibull__cdf__log_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_cdf_log.hpp File Reference + + + + + + + + + + +
+
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+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
weibull_cdf_log.hpp File Reference
+
+
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Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + +

+Functions

template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::weibull_cdf_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/weibull__cdf__log_8hpp_source.html b/doc/api/html/weibull__cdf__log_8hpp_source.html new file mode 100644 index 00000000000..0a6dba50e36 --- /dev/null +++ b/doc/api/html/weibull__cdf__log_8hpp_source.html @@ -0,0 +1,227 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_cdf_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
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+ + +
+
+
+
weibull_cdf_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_WEIBULL_CDF_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_WEIBULL_CDF_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/weibull_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <typename T_y, typename T_shape, typename T_scale>
+
28  typename return_type<T_y, T_shape, T_scale>::type
+
29  weibull_cdf_log(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+ +
31  T_partials_return;
+
32 
+
33  static const char* function("stan::math::weibull_cdf_log");
+
34 
+ + +
37  using boost::math::tools::promote_args;
+ +
39  using std::log;
+
40  using std::exp;
+
41 
+
42  // check if any vectors are zero length
+
43  if (!(stan::length(y)
+
44  && stan::length(alpha)
+
45  && stan::length(sigma)))
+
46  return 0.0;
+
47 
+
48  T_partials_return cdf_log(0.0);
+
49  check_nonnegative(function, "Random variable", y);
+
50  check_positive_finite(function, "Shape parameter", alpha);
+
51  check_positive_finite(function, "Scale parameter", sigma);
+
52 
+ +
54  operands_and_partials(y, alpha, sigma);
+
55 
+
56  VectorView<const T_y> y_vec(y);
+
57  VectorView<const T_scale> sigma_vec(sigma);
+
58  VectorView<const T_shape> alpha_vec(alpha);
+
59  size_t N = max_size(y, sigma, alpha);
+
60  for (size_t n = 0; n < N; n++) {
+
61  const T_partials_return y_dbl = value_of(y_vec[n]);
+
62  const T_partials_return sigma_dbl = value_of(sigma_vec[n]);
+
63  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+
64  const T_partials_return pow_ = pow(y_dbl / sigma_dbl, alpha_dbl);
+
65  const T_partials_return exp_ = exp(-pow_);
+
66  const T_partials_return cdf_ = 1.0 - exp_;
+
67 
+
68  // cdf_log
+
69  cdf_log += log(cdf_);
+
70 
+
71  // gradients
+
72  const T_partials_return rep_deriv = pow_ / (1.0 / exp_ - 1.0);
+ +
74  operands_and_partials.d_x1[n] += rep_deriv * alpha_dbl / y_dbl;
+ +
76  operands_and_partials.d_x2[n] += rep_deriv * log(y_dbl / sigma_dbl);
+ +
78  operands_and_partials.d_x3[n] -= rep_deriv * alpha_dbl / sigma_dbl;
+
79  }
+
80 
+
81  return operands_and_partials.value(cdf_log);
+
82  }
+
83  }
+
84 }
+
85 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ + + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
return_type< T_y, T_shape, T_scale >::type weibull_cdf_log(const T_y &y, const T_shape &alpha, const T_scale &sigma)
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + + + +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+
bool check_nonnegative(const char *function, const char *name, const T_y &y)
Return true if y is non-negative.
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/weibull__log_8hpp.html b/doc/api/html/weibull__log_8hpp.html new file mode 100644 index 00000000000..d86af9e1ef6 --- /dev/null +++ b/doc/api/html/weibull__log_8hpp.html @@ -0,0 +1,150 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_log.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+ +
+
weibull_log.hpp File Reference
+
+
+ +

Go to the source code of this file.

+ + + + + + + +

+Namespaces

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 stan::math
 Matrices and templated mathematical functions.
 
+ + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::weibull_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
template<typename T_y , typename T_shape , typename T_scale >
return_type< T_y, T_shape, T_scale >::type stan::math::weibull_log (const T_y &y, const T_shape &alpha, const T_scale &sigma)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/weibull__log_8hpp_source.html b/doc/api/html/weibull__log_8hpp_source.html new file mode 100644 index 00000000000..576a8295273 --- /dev/null +++ b/doc/api/html/weibull__log_8hpp_source.html @@ -0,0 +1,296 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
+
+ + + + + + +
+
+ + +
+ +
+ + +
+
+
+
weibull_log.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_SCAL_PROB_WEIBULL_LOG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_WEIBULL_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + +
19 #include <boost/random/weibull_distribution.hpp>
+
20 #include <boost/random/variate_generator.hpp>
+
21 #include <cmath>
+
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  // Weibull(y|alpha, sigma) [y >= 0; alpha > 0; sigma > 0]
+
28  // FIXME: document
+
29  template <bool propto,
+
30  typename T_y, typename T_shape, typename T_scale>
+
31  typename return_type<T_y, T_shape, T_scale>::type
+
32  weibull_log(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+
33  static const char* function("stan::math::weibull_log");
+ +
35  T_partials_return;
+
36 
+ + + + + + +
43  using std::log;
+
44 
+
45  // check if any vectors are zero length
+
46  if (!(stan::length(y)
+
47  && stan::length(alpha)
+
48  && stan::length(sigma)))
+
49  return 0.0;
+
50 
+
51  // set up return value accumulator
+
52  T_partials_return logp(0.0);
+
53  check_finite(function, "Random variable", y);
+
54  check_positive_finite(function, "Shape parameter", alpha);
+
55  check_positive_finite(function, "Scale parameter", sigma);
+
56  check_consistent_sizes(function,
+
57  "Random variable", y,
+
58  "Shape parameter", alpha,
+
59  "Scale parameter", sigma);
+
60 
+
61  // check if no variables are involved and prop-to
+ +
63  return 0.0;
+
64 
+
65  VectorView<const T_y> y_vec(y);
+
66  VectorView<const T_shape> alpha_vec(alpha);
+
67  VectorView<const T_scale> sigma_vec(sigma);
+
68  size_t N = max_size(y, alpha, sigma);
+
69 
+
70  for (size_t n = 0; n < N; n++) {
+
71  const T_partials_return y_dbl = value_of(y_vec[n]);
+
72  if (y_dbl < 0)
+
73  return LOG_ZERO;
+
74  }
+
75 
+ +
77  T_partials_return, T_shape> log_alpha(length(alpha));
+
78  for (size_t i = 0; i < length(alpha); i++)
+ +
80  log_alpha[i] = log(value_of(alpha_vec[i]));
+
81 
+ +
83  T_partials_return, T_y> log_y(length(y));
+
84  for (size_t i = 0; i < length(y); i++)
+ +
86  log_y[i] = log(value_of(y_vec[i]));
+
87 
+ +
89  T_partials_return, T_scale> log_sigma(length(sigma));
+
90  for (size_t i = 0; i < length(sigma); i++)
+ +
92  log_sigma[i] = log(value_of(sigma_vec[i]));
+
93 
+ +
95  T_partials_return, T_scale> inv_sigma(length(sigma));
+
96  for (size_t i = 0; i < length(sigma); i++)
+ +
98  inv_sigma[i] = 1.0 / value_of(sigma_vec[i]);
+
99 
+ +
101  T_partials_return, T_y, T_shape, T_scale>
+
102  y_div_sigma_pow_alpha(N);
+
103  for (size_t i = 0; i < N; i++)
+ +
105  const T_partials_return y_dbl = value_of(y_vec[i]);
+
106  const T_partials_return alpha_dbl = value_of(alpha_vec[i]);
+
107  y_div_sigma_pow_alpha[i] = pow(y_dbl * inv_sigma[i], alpha_dbl);
+
108  }
+
109 
+ +
111  operands_and_partials(y, alpha, sigma);
+
112  for (size_t n = 0; n < N; n++) {
+
113  const T_partials_return alpha_dbl = value_of(alpha_vec[n]);
+ +
115  logp += log_alpha[n];
+ +
117  logp += (alpha_dbl-1.0)*log_y[n];
+ +
119  logp -= alpha_dbl*log_sigma[n];
+ +
121  logp -= y_div_sigma_pow_alpha[n];
+
122 
+ +
124  const T_partials_return inv_y = 1.0 / value_of(y_vec[n]);
+
125  operands_and_partials.d_x1[n]
+
126  += (alpha_dbl-1.0) * inv_y
+
127  - alpha_dbl * y_div_sigma_pow_alpha[n] * inv_y;
+
128  }
+ +
130  operands_and_partials.d_x2[n]
+
131  += 1.0/alpha_dbl
+
132  + (1.0 - y_div_sigma_pow_alpha[n]) * (log_y[n] - log_sigma[n]);
+ +
134  operands_and_partials.d_x3[n]
+
135  += alpha_dbl * inv_sigma[n] * (y_div_sigma_pow_alpha[n] - 1.0);
+
136  }
+
137  return operands_and_partials.value(logp);
+
138  }
+
139 
+
140  template <typename T_y, typename T_shape, typename T_scale>
+
141  inline
+ +
143  weibull_log(const T_y& y, const T_shape& alpha, const T_scale& sigma) {
+
144  return weibull_log<false>(y, alpha, sigma);
+
145  }
+
146  }
+
147 }
+
148 #endif
+ +
VectorView< T_return_type, false, true > d_x2
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+
T_return_type value(double value)
Returns a T_return_type with the value specified with the partial derivatves.
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+ +
const double LOG_ZERO
Definition: constants.hpp:175
+
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+ + + +
Metaprogram to determine if a type has a base scalar type that can be assigned to type double...
+
This class builds partial derivatives with respect to a set of operands.
+ +
VectorView< T_return_type, false, true > d_x3
+
return_type< T_y, T_shape, T_scale >::type weibull_log(const T_y &y, const T_shape &alpha, const T_scale &sigma)
Definition: weibull_log.hpp:32
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+ + + + +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
+
VectorBuilder allocates type T1 values to be used as intermediate values.
+ +
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+
boost::math::tools::promote_args< typename partials_type< typename scalar_type< T1 >::type >::type, typename partials_type< typename scalar_type< T2 >::type >::type, typename partials_type< typename scalar_type< T3 >::type >::type, typename partials_type< typename scalar_type< T4 >::type >::type, typename partials_type< typename scalar_type< T5 >::type >::type, typename partials_type< typename scalar_type< T6 >::type >::type >::type type
+ +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
VectorView< T_return_type, false, true > d_x1
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/weibull__rng_8hpp.html b/doc/api/html/weibull__rng_8hpp.html new file mode 100644 index 00000000000..a564ab64b4c --- /dev/null +++ b/doc/api/html/weibull__rng_8hpp.html @@ -0,0 +1,141 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_rng.hpp File Reference + + + + + + + + + + +
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template<class RNG >
double stan::math::weibull_rng (const double alpha, const double sigma, RNG &rng)
 
+
+
+
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diff --git a/doc/api/html/weibull__rng_8hpp_source.html b/doc/api/html/weibull__rng_8hpp_source.html new file mode 100644 index 00000000000..90c9978a365 --- /dev/null +++ b/doc/api/html/weibull__rng_8hpp_source.html @@ -0,0 +1,164 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/weibull_rng.hpp Source File + + + + + + + + + + +
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weibull_rng.hpp
+
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_WEIBULL_RNG_HPP
+
2 #define STAN_MATH_PRIM_SCAL_PROB_WEIBULL_RNG_HPP
+
3 
+
4 #include <boost/random/weibull_distribution.hpp>
+
5 #include <boost/random/variate_generator.hpp>
+ + + + + + + + + + +
16 
+
17 namespace stan {
+
18 
+
19  namespace math {
+
20 
+
21  template <class RNG>
+
22  inline double
+
23  weibull_rng(const double alpha,
+
24  const double sigma,
+
25  RNG& rng) {
+
26  using boost::variate_generator;
+
27  using boost::random::weibull_distribution;
+
28 
+
29  static const char* function("stan::math::weibull_rng");
+
30 
+ +
32 
+
33  check_positive_finite(function, "Shape parameter", alpha);
+
34  check_positive_finite(function, "Scale parameter", sigma);
+
35 
+
36  variate_generator<RNG&, weibull_distribution<> >
+
37  weibull_rng(rng, weibull_distribution<>(alpha, sigma));
+
38  return weibull_rng();
+
39  }
+
40  }
+
41 }
+
42 #endif
+ + + + + + +
double weibull_rng(const double alpha, const double sigma, RNG &rng)
Definition: weibull_rng.hpp:23
+ + + + + +
bool check_positive_finite(const char *function, const char *name, const T_y &y)
Return true if y is positive and finite.
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/welford__covar__estimator_8hpp.html b/doc/api/html/welford__covar__estimator_8hpp.html new file mode 100644 index 00000000000..66814a2dcc3 --- /dev/null +++ b/doc/api/html/welford__covar__estimator_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/welford_covar_estimator.hpp File Reference + + + + + + + + + + +
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welford_covar_estimator.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
+

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+Classes

class  stan::math::welford_covar_estimator
 
+ + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+
+
+
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diff --git a/doc/api/html/welford__covar__estimator_8hpp_source.html b/doc/api/html/welford__covar__estimator_8hpp_source.html new file mode 100644 index 00000000000..6bd747a1916 --- /dev/null +++ b/doc/api/html/welford__covar__estimator_8hpp_source.html @@ -0,0 +1,177 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/welford_covar_estimator.hpp Source File + + + + + + + + + + +
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welford_covar_estimator.hpp
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_FUN_WELFORD_COVAR_ESTIMATOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_WELFORD_COVAR_ESTIMATOR_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+ +
12  public:
+
13  explicit welford_covar_estimator(int n)
+
14  : _m(Eigen::VectorXd::Zero(n)),
+
15  _m2(Eigen::MatrixXd::Zero(n, n)) {
+
16  restart();
+
17  }
+
18 
+
19  void restart() {
+
20  _num_samples = 0;
+
21  _m.setZero();
+
22  _m2.setZero();
+
23  }
+
24 
+
25  void add_sample(const Eigen::VectorXd& q) {
+
26  ++_num_samples;
+
27 
+
28  Eigen::VectorXd delta(q - _m);
+
29  _m += delta / _num_samples;
+
30  _m2 += (q - _m) * delta.transpose();
+
31  }
+
32 
+
33  int num_samples() { return _num_samples; }
+
34 
+
35  void sample_mean(Eigen::VectorXd& mean) { mean = _m; }
+
36 
+
37  void sample_covariance(Eigen::MatrixXd& covar) {
+
38  if (_num_samples > 1)
+
39  covar = _m2 / (_num_samples - 1.0);
+
40  }
+
41 
+
42  protected:
+
43  double _num_samples;
+
44 
+
45  Eigen::VectorXd _m;
+
46  Eigen::MatrixXd _m2;
+
47  };
+
48 
+
49  } // prob
+
50 
+
51 } // stan
+
52 
+
53 
+
54 #endif
+ + + + +
(Expert) Numerical traits for algorithmic differentiation variables.
+
void add_sample(const Eigen::VectorXd &q)
+ + +
void sample_covariance(Eigen::MatrixXd &covar)
+
boost::math::tools::promote_args< T >::type mean(const std::vector< T > &v)
Returns the sample mean (i.e., average) of the coefficients in the specified standard vector...
Definition: mean.hpp:23
+ + + + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/welford__var__estimator_8hpp.html b/doc/api/html/welford__var__estimator_8hpp.html new file mode 100644 index 00000000000..150bbea65da --- /dev/null +++ b/doc/api/html/welford__var__estimator_8hpp.html @@ -0,0 +1,130 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/welford_var_estimator.hpp File Reference + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
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+
welford_var_estimator.hpp File Reference
+
+
+
#include <stan/math/prim/mat/fun/Eigen.hpp>
+#include <vector>
+
+

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+ + + + +

+Classes

class  stan::math::welford_var_estimator
 
+ + + + + + +

+Namespaces

 stan
 
 stan::math
 Matrices and templated mathematical functions.
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/welford__var__estimator_8hpp_source.html b/doc/api/html/welford__var__estimator_8hpp_source.html new file mode 100644 index 00000000000..8f5c6d9482b --- /dev/null +++ b/doc/api/html/welford__var__estimator_8hpp_source.html @@ -0,0 +1,178 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/fun/welford_var_estimator.hpp Source File + + + + + + + + + + +
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welford_var_estimator.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_FUN_WELFORD_VAR_ESTIMATOR_HPP
+
2 #define STAN_MATH_PRIM_MAT_FUN_WELFORD_VAR_ESTIMATOR_HPP
+
3 
+ +
5 #include <vector>
+
6 
+
7 namespace stan {
+
8 
+
9  namespace math {
+
10 
+ +
12  public:
+
13  explicit welford_var_estimator(int n)
+
14  : _m(Eigen::VectorXd::Zero(n)),
+
15  _m2(Eigen::VectorXd::Zero(n)) {
+
16  restart();
+
17  }
+
18 
+
19  void restart() {
+
20  _num_samples = 0;
+
21  _m.setZero();
+
22  _m2.setZero();
+
23  }
+
24 
+
25  void add_sample(const Eigen::VectorXd& q) {
+
26  ++_num_samples;
+
27 
+
28  Eigen::VectorXd delta(q - _m);
+
29  _m += delta / _num_samples;
+
30  _m2 += delta.cwiseProduct(q - _m);
+
31  }
+
32 
+
33  int num_samples() { return _num_samples; }
+
34 
+
35  void sample_mean(Eigen::VectorXd& mean) { mean = _m; }
+
36 
+
37  void sample_variance(Eigen::VectorXd& var) {
+
38  if (_num_samples > 1)
+
39  var = _m2 / (_num_samples - 1.0);
+
40  }
+
41 
+
42  protected:
+
43  double _num_samples;
+
44 
+
45  Eigen::VectorXd _m;
+
46  Eigen::VectorXd _m2;
+
47  };
+
48 
+
49  } // prob
+
50 
+
51 } // stan
+
52 
+
53 
+
54 #endif
+ + + + + +
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
+
(Expert) Numerical traits for algorithmic differentiation variables.
+
void sample_mean(Eigen::VectorXd &mean)
+
boost::math::tools::promote_args< T >::type mean(const std::vector< T > &v)
Returns the sample mean (i.e., average) of the coefficients in the specified standard vector...
Definition: mean.hpp:23
+ +
void add_sample(const Eigen::VectorXd &q)
+ + +
void sample_variance(Eigen::VectorXd &var)
+ +
+
+
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diff --git a/doc/api/html/wiener__log_8hpp.html b/doc/api/html/wiener__log_8hpp.html new file mode 100644 index 00000000000..26b888d8bb0 --- /dev/null +++ b/doc/api/html/wiener__log_8hpp.html @@ -0,0 +1,146 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/wiener_log.hpp File Reference + + + + + + + + + + +
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template<bool propto, typename T_y , typename T_alpha , typename T_tau , typename T_beta , typename T_delta >
return_type< T_y, T_alpha, T_tau, T_beta, T_delta >::type stan::math::wiener_log (const T_y &y, const T_alpha &alpha, const T_tau &tau, const T_beta &beta, const T_delta &delta)
 The log of the first passage time density function for a (Wiener) drift diffusion model for the given $y$, boundary separation $\alpha$, nondecision time $\tau$, relative bias $\beta$, and drift rate $\delta$. More...
 
template<typename T_y , typename T_alpha , typename T_tau , typename T_beta , typename T_delta >
return_type< T_y, T_alpha, T_tau, T_beta, T_delta >::type stan::math::wiener_log (const T_y &y, const T_alpha &alpha, const T_tau &tau, const T_beta &beta, const T_delta &delta)
 
+
+
+
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diff --git a/doc/api/html/wiener__log_8hpp_source.html b/doc/api/html/wiener__log_8hpp_source.html new file mode 100644 index 00000000000..f4bc0809e1e --- /dev/null +++ b/doc/api/html/wiener__log_8hpp_source.html @@ -0,0 +1,364 @@ + + + + + + +Stan Math Library: stan/math/prim/scal/prob/wiener_log.hpp Source File + + + + + + + + + + +
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wiener_log.hpp
+
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+Go to the documentation of this file.
1 // Copyright (c) 2013, Joachim Vandekerckhove.
+
2 // All rights reserved.
+
3 //
+
4 // Redistribution and use in source and binary forms, with or without
+
5 // modification, are permitted
+
6 // provided that the following conditions are met:
+
7 //
+
8 // * Redistributions of source code must retain the above copyright notice,
+
9 // * this list of conditions and the following disclaimer.
+
10 // * Redistributions in binary form must reproduce the above copyright notice,
+
11 // * this list of conditions and the following disclaimer in the
+
12 // * documentation and/or other materials provided with the distribution.
+
13 // * Neither the name of the University of California, Irvine nor the names
+
14 // * of its contributors may be used to endorse or promote products derived
+
15 // * from this software without specific prior written permission.
+
16 //
+
17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+
18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+
19 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+
20 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+
21 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+
22 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+
23 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+
24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+
25 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+
26 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+
27 // THE POSSIBILITY OF SUCH DAMAGE.
+
28 
+
29 #ifndef STAN_MATH_PRIM_MAT_PROB_WIENER_LOG_HPP
+
30 #define STAN_MATH_PRIM_MAT_PROB_WIENER_LOG_HPP
+
31 
+ + + + + + + + + + +
42 #include <boost/math/distributions.hpp>
+
43 #include <cmath>
+
44 #include <algorithm> // for max
+
45 
+
46 namespace stan {
+
47 
+
48  namespace math {
+
49 
+
68  template <bool propto,
+
69  typename T_y, typename T_alpha, typename T_tau,
+
70  typename T_beta, typename T_delta>
+
71  typename return_type<T_y, T_alpha, T_tau, T_beta, T_delta>::type
+
72  wiener_log(const T_y& y, const T_alpha& alpha, const T_tau& tau,
+
73  const T_beta& beta, const T_delta& delta) {
+
74  static const char* function("stan::math::wiener_log(%1%)");
+
75 
+
76  using boost::math::tools::promote_args;
+
77  using boost::math::isinf;
+ +
79  using std::log;
+
80  using std::exp;
+
81  using std::pow;
+
82 
+
83  static const double WIENER_ERR = 0.000001;
+
84  static const double PI_TIMES_WIENER_ERR = pi() * WIENER_ERR;
+
85  static const double LOG_PI_LOG_WIENER_ERR =
+
86  LOG_PI + log(WIENER_ERR);
+
87  static const double
+
88  TWO_TIMES_SQRT_2_TIMES_SQRT_PI_TIMES_WIENER_ERR =
+
89  2.0 * SQRT_2_TIMES_SQRT_PI * WIENER_ERR;
+
90  static const double LOG_TWO_OVER_TWO_PLUS_LOG_SQRT_PI =
+
91  LOG_TWO / 2 + LOG_SQRT_PI;
+
92  static const double SQUARE_PI_OVER_TWO = square(pi()) * 0.5;
+
93  static const double TWO_TIMES_LOG_SQRT_PI = 2.0 * LOG_SQRT_PI;
+
94 
+
95  if (!(stan::length(y)
+
96  && stan::length(alpha)
+
97  && stan::length(beta)
+
98  && stan::length(tau)
+
99  && stan::length(delta)))
+
100  return 0.0;
+
101 
+
102  typedef typename return_type<T_y, T_alpha, T_tau,
+
103  T_beta, T_delta>::type T_return_type;
+
104  T_return_type lp(0.0);
+
105 
+
106  check_not_nan(function, "Random variable", y);
+
107  check_not_nan(function, "Boundary separation", alpha);
+
108  check_not_nan(function, "A-priori bias", beta);
+
109  check_not_nan(function, "Nondecision time", tau);
+
110  check_not_nan(function, "Drift rate", delta);
+
111  check_finite(function, "Boundary separation", alpha);
+
112  check_finite(function, "A-priori bias", beta);
+
113  check_finite(function, "Nondecision time", tau);
+
114  check_finite(function, "Drift rate", delta);
+
115  check_positive(function, "Random variable", y);
+
116  check_positive(function, "Boundary separation", alpha);
+
117  check_positive(function, "Nondecision time", tau);
+
118  check_bounded(function, "A-priori bias", beta , 0, 1);
+
119  check_consistent_sizes(function,
+
120  "Random variable", y,
+
121  "Boundary separation", alpha,
+
122  "A-priori bias", beta,
+
123  "Nondecision time", tau,
+
124  "Drift rate", delta);
+
125 
+
126  size_t N =
+
127  std::max(max_size(y, alpha, beta), max_size(tau, delta));
+
128  if (!N)
+
129  return 0.0;
+
130  VectorView<const T_y> y_vec(y);
+
131  VectorView<const T_alpha> alpha_vec(alpha);
+
132  VectorView<const T_beta> beta_vec(beta);
+
133  VectorView<const T_tau> tau_vec(tau);
+
134  VectorView<const T_delta> delta_vec(delta);
+
135 
+
136  if (!include_summand<propto, T_y, T_alpha, T_tau,
+
137  T_beta, T_delta>::value) {
+
138  return 0;
+
139  }
+
140 
+
141  for (size_t i = 0; i < N; i++)
+
142  if (y_vec[i] < tau_vec[i]) {
+ +
144  return lp;
+
145  }
+
146 
+
147  for (size_t i = 0; i < N; i++) {
+
148  typename scalar_type<T_beta>::type one_minus_beta
+
149  = 1.0 - beta_vec[i];
+
150  typename scalar_type<T_alpha>::type alpha2
+
151  = square(alpha_vec[i]);
+
152  T_return_type x = y_vec[i];
+
153  T_return_type kl, ks, tmp = 0;
+
154  T_return_type k, K;
+
155 
+
156 
+
157  x = x - tau_vec[i]; // remove non-decision time from x
+
158  x = x / alpha2; // convert t to normalized time tt
+
159  T_return_type sqrt_x = sqrt(x);
+
160  T_return_type log_x = log(x);
+
161  T_return_type one_over_pi_times_sqrt_x = 1.0 / pi() * sqrt_x;
+
162 
+
163  // calculate number of terms needed for large t:
+
164  // if error threshold is set low enough
+
165  if (PI_TIMES_WIENER_ERR * x < 1) {
+
166  // compute bound
+
167  kl = sqrt(-2.0 * SQRT_PI *
+
168  (LOG_PI_LOG_WIENER_ERR + log_x)) /
+
169  sqrt_x;
+
170  // ensure boundary conditions met
+
171  kl = (kl > one_over_pi_times_sqrt_x) ?
+
172  kl : one_over_pi_times_sqrt_x;
+
173  } else { // if error threshold set too high
+
174  kl = one_over_pi_times_sqrt_x; // set to boundary condition
+
175  }
+
176  // calculate number of terms needed for small t:
+
177  // if error threshold is set low enough
+
178  T_return_type tmp_expr0
+
179  = TWO_TIMES_SQRT_2_TIMES_SQRT_PI_TIMES_WIENER_ERR * sqrt_x;
+
180  if (tmp_expr0 < 1) {
+
181  // compute bound
+
182  ks = 2.0 + sqrt_x * sqrt(-2 * log(tmp_expr0));
+
183  // ensure boundary conditions are met
+
184  T_return_type sqrt_x_plus_one = sqrt_x + 1.0;
+
185  ks = (ks > sqrt_x_plus_one) ? ks : sqrt_x_plus_one;
+
186  } else { // if error threshold was set too high
+
187  ks = 2.0; // minimal kappa for that case
+
188  }
+
189  // compute density: f(tt|0,1,w)
+
190  if (ks < kl) { // if small t is better (i.e., lambda<0)
+
191  K = ceil(ks); // round to smallest integer meeting error
+
192  T_return_type tmp_expr1 = (K - 1.0) / 2.0;
+
193  T_return_type tmp_expr2 = ceil(tmp_expr1);
+
194  for (k = -floor(tmp_expr1); k <= tmp_expr2; k++)
+
195  // increment sum
+
196  tmp += (one_minus_beta + 2.0 * k) *
+
197  exp(-(square(one_minus_beta + 2.0 * k)) * 0.5 / x);
+
198  // add constant term
+
199  tmp = log(tmp) -
+
200  LOG_TWO_OVER_TWO_PLUS_LOG_SQRT_PI - 1.5 * log_x;
+
201  } else { // if large t is better...
+
202  K = ceil(kl); // round to smallest integer meeting error
+
203  for (k = 1; k <= K; k++)
+
204  // increment sum
+
205  tmp += k * exp(-(square(k)) *
+
206  (SQUARE_PI_OVER_TWO * x)) *
+
207  sin(k * pi() * one_minus_beta);
+
208  tmp = log(tmp) +
+
209  TWO_TIMES_LOG_SQRT_PI; // add constant term
+
210  }
+
211 
+
212  // convert to f(t|v,a,w) and return result
+
213  lp += delta_vec[i] * alpha_vec[i] * one_minus_beta -
+
214  square(delta_vec[i]) * x * alpha2 / 2.0 -
+
215  log(alpha2) + tmp;
+
216  }
+
217 
+
218  return lp;
+
219  }
+
220 
+
221  template <typename T_y, typename T_alpha, typename T_tau,
+
222  typename T_beta, typename T_delta>
+
223  inline
+ +
225  wiener_log(const T_y& y, const T_alpha& alpha, const T_tau& tau,
+
226  const T_beta& beta, const T_delta& delta) {
+
227  return wiener_log<false>(y, alpha, tau, beta, delta);
+
228  }
+
229  }
+
230 }
+
231 #endif
+ +
return_type< T_y, T_alpha, T_tau, T_beta, T_delta >::type wiener_log(const T_y &y, const T_alpha &alpha, const T_tau &tau, const T_beta &beta, const T_delta &delta)
The log of the first passage time density function for a (Wiener) drift diffusion model for the given...
Definition: wiener_log.hpp:72
+
bool isfinite(const stan::math::var &v)
Checks if the given number has finite value.
+
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+
bool check_not_nan(const char *function, const char *name, const T_y &y)
Return true if y is not NaN.
+ + +
const double LOG_PI
Definition: constants.hpp:170
+
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:15
+ +
const double LOG_SQRT_PI
Definition: constants.hpp:173
+
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
+
bool check_bounded(const char *function, const char *name, const T_y &y, const T_low &low, const T_high &high)
Return true if the value is between the low and high values, inclusively.
+
Metaprogram to calculate the base scalar return type resulting from promoting all the scalar types of...
Definition: return_type.hpp:19
+
scalar_type_helper< is_vector< T >::value, T >::type type
Definition: scalar_type.hpp:35
+ +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< typename scalar_type< T1 >::type, typename scalar_type< T2 >::type, typename scalar_type< T3 >::type, typename scalar_type< T4 >::type, typename scalar_type< T5 >::type, typename scalar_type< T6 >::type >::type type
Definition: return_type.hpp:27
+
fvar< T > square(const fvar< T > &x)
Definition: square.hpp:15
+
const double LOG_TWO
Definition: constants.hpp:177
+ +
const double SQRT_2_TIMES_SQRT_PI
Definition: constants.hpp:158
+
bool isinf(const stan::math::var &v)
Checks if the given number is infinite.
Definition: boost_isinf.hpp:22
+
fvar< T > sin(const fvar< T > &x)
Definition: sin.hpp:14
+
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
size_t max_size(const T1 &x1, const T2 &x2)
Definition: max_size.hpp:9
+
int max(const std::vector< int > &x)
Returns the maximum coefficient in the specified column vector.
Definition: max.hpp:21
+ +
bool check_finite(const char *function, const char *name, const T_y &y)
Return true if y is finite.
+ +
fvar< T > floor(const fvar< T > &x)
Definition: floor.hpp:11
+
bool check_consistent_sizes(const char *function, const char *name1, const T1 &x1, const char *name2, const T2 &x2)
Return true if the dimension of x1 is consistent with x2.
+ +
double pi()
Return the value of pi.
Definition: constants.hpp:86
+
fvar< T > pow(const fvar< T > &x1, const fvar< T > &x2)
Definition: pow.hpp:18
+ +
VectorView is a template expression that is constructed with a container or scalar, which it then allows to be used as an array using operator[].
Definition: VectorView.hpp:48
+ +
const double SQRT_PI
Definition: constants.hpp:156
+
fvar< T > ceil(const fvar< T > &x)
Definition: ceil.hpp:11
+
double negative_infinity()
Return negative infinity.
Definition: constants.hpp:132
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/wishart__log_8hpp.html b/doc/api/html/wishart__log_8hpp.html new file mode 100644 index 00000000000..ecc03946f35 --- /dev/null +++ b/doc/api/html/wishart__log_8hpp.html @@ -0,0 +1,149 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/wishart_log.hpp File Reference + + + + + + + + + + +
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Stan Math Library +  2.10.0 +
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+
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+ + + + + + + +

+Namespaces

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 Matrices and templated mathematical functions.
 
+ + + + + + + + +

+Functions

template<bool propto, typename T_y , typename T_dof , typename T_scale >
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type stan::math::wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
 The log of the Wishart density for the given W, degrees of freedom, and scale matrix. More...
 
template<typename T_y , typename T_dof , typename T_scale >
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type stan::math::wishart_log (const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
 
+
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
diff --git a/doc/api/html/wishart__log_8hpp_source.html b/doc/api/html/wishart__log_8hpp_source.html new file mode 100644 index 00000000000..1a043912967 --- /dev/null +++ b/doc/api/html/wishart__log_8hpp_source.html @@ -0,0 +1,249 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/wishart_log.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
+
Stan Math Library +  2.10.0 +
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wishart_log.hpp
+
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+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_WISHART_LOG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_WISHART_LOG_HPP
+
3 
+ + + + + + + + + + + + + + + + +
20 
+
21 namespace stan {
+
22 
+
23  namespace math {
+
24 
+
25  // Wishart(Sigma|n, Omega) [Sigma, Omega symmetric, non-neg, definite;
+
26  // Sigma.dims() = Omega.dims();
+
27  // n > Sigma.rows() - 1]
+
55  template <bool propto,
+
56  typename T_y, typename T_dof, typename T_scale>
+
57  typename boost::math::tools::promote_args<T_y, T_dof, T_scale>::type
+
58  wishart_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& W,
+
59  const T_dof& nu,
+
60  const Eigen::Matrix<T_scale, Eigen::Dynamic, Eigen::Dynamic>&
+
61  S) {
+
62  static const char* function("stan::math::wishart_log");
+
63 
+
64  using boost::math::tools::promote_args;
+
65  using Eigen::Dynamic;
+
66  using Eigen::Lower;
+
67  using Eigen::Matrix;
+ + + + + + + + +
76 
+
77 
+ +
79  = W.rows();
+
80  typename promote_args<T_y, T_dof, T_scale>::type lp(0.0);
+
81  check_greater(function, "Degrees of freedom parameter", nu, k-1);
+
82  check_square(function, "random variable", W);
+
83  check_square(function, "scale parameter", S);
+
84  check_size_match(function,
+
85  "Rows of random variable", W.rows(),
+
86  "columns of scale parameter", S.rows());
+
87  // FIXME: domain checks
+
88 
+ +
90  if (!check_ldlt_factor(function, "LDLT_Factor of random variable",
+
91  ldlt_W))
+
92  return lp;
+
93 
+ +
95  if (!check_ldlt_factor(function, "LDLT_Factor of scale parameter",
+
96  ldlt_S))
+
97  return lp;
+
98 
+
99  using stan::math::trace;
+
100  using stan::math::lmgamma;
+ +
102  lp += nu * k * NEG_LOG_TWO_OVER_TWO;
+
103 
+ +
105  lp -= lmgamma(k, 0.5 * nu);
+
106 
+ +
108  lp -= 0.5 * nu * log_determinant_ldlt(ldlt_S);
+
109 
+ +
111  Matrix<typename promote_args<T_y, T_scale>::type, Dynamic, Dynamic>
+
112  Sinv_W(mdivide_left_ldlt
+
113  (ldlt_S,
+
114  static_cast<Matrix<T_y, Dynamic, Dynamic> >
+
115  (W.template selfadjointView<Lower>())));
+
116  lp -= 0.5 * trace(Sinv_W);
+
117  }
+
118 
+
119  if (include_summand<propto, T_y, T_dof>::value && nu != (k + 1))
+
120  lp += 0.5 * (nu - k - 1.0) * log_determinant_ldlt(ldlt_W);
+
121  return lp;
+
122  }
+
123 
+
124  template <typename T_y, typename T_dof, typename T_scale>
+
125  inline
+
126  typename boost::math::tools::promote_args<T_y, T_dof, T_scale>::type
+
127  wishart_log(const Eigen::Matrix<T_y, Eigen::Dynamic, Eigen::Dynamic>& W,
+
128  const T_dof& nu,
+
129  const Eigen::Matrix
+
130  <T_scale, Eigen::Dynamic, Eigen::Dynamic>& S) {
+
131  return wishart_log<false>(W, nu, S);
+
132  }
+
133 
+
134  }
+
135 
+
136 }
+
137 #endif
+ + + + +
Template metaprogram to calculate whether a summand needs to be included in a proportional (log) prob...
+
boost::math::tools::promote_args< T_y, T_dof, T_scale >::type wishart_log(const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &W, const T_dof &nu, const Eigen::Matrix< T_scale, Eigen::Dynamic, Eigen::Dynamic > &S)
The log of the Wishart density for the given W, degrees of freedom, and scale matrix.
Definition: wishart_log.hpp:58
+ + + + + +
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+ + +
Eigen::Matrix< fvar< T2 >, R1, C2 > mdivide_left_ldlt(const stan::math::LDLT_factor< double, R1, C1 > &A, const Eigen::Matrix< fvar< T2 >, R2, C2 > &b)
Returns the solution of the system Ax=b given an LDLT_factor of A.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ + + +
T trace(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &m)
Returns the trace of the specified matrix.
Definition: trace.hpp:20
+
const double NEG_LOG_TWO_OVER_TWO
Definition: constants.hpp:191
+ +
T log_determinant_ldlt(stan::math::LDLT_factor< T, R, C > &A)
+
fvar< typename stan::return_type< T, int >::type > lmgamma(int x1, const fvar< T > &x2)
Definition: lmgamma.hpp:16
+
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
bool check_greater(const char *function, const char *name, const T_y &y, const T_low &low)
Return true if y is strictly greater than low.
+
bool check_ldlt_factor(const char *function, const char *name, stan::math::LDLT_factor< T, R, C > &A)
Return true if the argument is a valid stan::math::LDLT_factor.
+ + +
+
+
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diff --git a/doc/api/html/wishart__rng_8hpp.html b/doc/api/html/wishart__rng_8hpp.html new file mode 100644 index 00000000000..60f14323830 --- /dev/null +++ b/doc/api/html/wishart__rng_8hpp.html @@ -0,0 +1,147 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/wishart_rng.hpp File Reference + + + + + + + + + + +
+
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Stan Math Library +  2.10.0 +
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wishart_rng.hpp File Reference
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diff --git a/doc/api/html/wishart__rng_8hpp_source.html b/doc/api/html/wishart__rng_8hpp_source.html new file mode 100644 index 00000000000..2589c90aafb --- /dev/null +++ b/doc/api/html/wishart__rng_8hpp_source.html @@ -0,0 +1,197 @@ + + + + + + +Stan Math Library: stan/math/prim/mat/prob/wishart_rng.hpp Source File + + + + + + + + + + +
+
+ + + + + + + +
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Stan Math Library +  2.10.0 +
+
reverse mode automatic differentiation
+
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+ + +
+ +
+ + +
+
+
+
wishart_rng.hpp
+
+
+Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_WISHART_RNG_HPP
+
2 #define STAN_MATH_PRIM_MAT_PROB_WISHART_RNG_HPP
+
3 
+ + + + + + + + + + + + + + + + + + +
22 
+
23 namespace stan {
+
24 
+
25  namespace math {
+
26 
+
27  template <class RNG>
+
28  inline Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>
+
29  wishart_rng(const double nu,
+
30  const Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& S,
+
31  RNG& rng) {
+
32  using Eigen::MatrixXd;
+ + + + +
37 
+
38  static const char* function("stan::math::wishart_rng");
+
39 
+
40  typename index_type<MatrixXd>::type k = S.rows();
+
41 
+
42  check_positive(function, "degrees of freedom", nu);
+
43  check_square(function, "scale parameter", S);
+
44 
+
45  MatrixXd B = MatrixXd::Zero(k, k);
+
46 
+
47  for (int j = 0; j < k; ++j) {
+
48  for (int i = 0; i < j; ++i)
+
49  B(i, j) = normal_rng(0, 1, rng);
+
50  B(j, j) = std::sqrt(chi_square_rng(nu - j, rng));
+
51  }
+
52 
+
53  return stan::math::crossprod(B * S.llt().matrixU());
+
54  }
+
55 
+
56 
+
57  }
+
58 
+
59 }
+
60 #endif
+
double chi_square_rng(const double nu, RNG &rng)
+ +
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:15
+ + + + + + + + + +
Primary template class for the metaprogram to compute the index type of a container.
Definition: index_type.hpp:19
+
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > wishart_rng(const double nu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &S, RNG &rng)
Definition: wishart_rng.hpp:29
+ +
Eigen::Matrix< fvar< T >, C, C > crossprod(const Eigen::Matrix< fvar< T >, R, C > &m)
Definition: crossprod.hpp:17
+
bool check_positive(const char *function, const char *name, const T_y &y)
Return true if y is positive.
+
bool check_size_match(const char *function, const char *name_i, T_size1 i, const char *name_j, T_size2 j)
Return true if the provided sizes match.
+ + + + + +
bool check_square(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Return true if the specified matrix is square.
+ +
double normal_rng(const double mu, const double sigma, RNG &rng)
Definition: normal_rng.hpp:19
+ + +
+
+
+ +      + [ Stan Home Page ] + + + © 2011–2016, + Stan Development Team. +      + + +
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