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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

0.19.1 - 2026-08-11

Added

  • let callers choose the binomial sampling algorithm

Fixed

  • Correct exact distribution boundaries
  • Beta::sf returning exactly 1.0 for tiny x
  • order the selection fast paths by total_cmp, not <=
  • replace hand-rolled quickselect with select_nth_unstable_by
  • address review on the BINV/BTPE sampler

Other

  • Alias f64 constants
  • Fix nightly f64 deprecation warnings
  • add a selection benchmark, and ordered fast paths it exposed
  • build the NaN order-statistic test under no_std
  • move binomial sampling into its own module
  • split the sampler's branch selection out of the RNG path
  • require std for the BTPE chi-square test
  • sample Binomial via BINV/BTPE instead of n Bernoulli trials
  • Bound the Newton iteration count and cover the quantile guards
  • Add safeguarded-Newton inverse_cdf for Chi and InverseGamma

0.19.0 - 2026-07-20

Added

  • Add initial no_std support
  • gate density estimation behind a "kde" feature
  • add first implementation of kernel density estimation.
  • add bandwith support for knn density estimation.
  • add a more generic implementation of knn density estimation.
  • add knn density estimation with kdtree rs tree.
  • add OnlineMoments accumulator using Welford
  • Add WebAssembly RNG support and update nalgebra
  • (distribution) narrow error type to avoid trait object
  • (distribution) add non-panicking try_inverse_cdf
  • autofix.ci for lint and fmt
  • (geometric) finer panic bounds
  • (function) add comprehensive kernel suite for KDE and smoothing (#193)
  • update to 2024 edition, apply formatting and fix new clippy lints
  • [breaking] rely on prec module for precision needs and consts for math constants
  • use crate::prec macro assertions in tests instead of approx directly
  • (prec) write macros that delegate to approx using our defaults
  • add std feature
  • rename cov_chol_decomp to clone_cov_chol_decomp and return a cloned matrix
  • add methods for covariance decomposition, mean, covariance, and precision in MultivariateNormal
  • add accessor methods to various distribution
  • (stats_tests) implement KS test
  • enhance Levy distribution with comprehensive documentation and methods
  • add Levy distribution
  • (stats_tests) implement chisquare
  • (stats_tests) implement skewtest
  • (stats_tests) implement mannwhitneyu
  • (stats_tests) implement ttest_onesample
  • (stats_tests) implement f_oneway

Fixed

  • format assertion message with precision
  • fail autofix when clippy --fix can't clear every lint
  • drop PAT from autofix-ci.yml
  • make autofix clippy match other parts of ci
  • Automate MSRV lockfile updates
  • update to rand 0.10 and use seeded rng for tests
  • fix imports and add some tests.
  • kernel density computation.
  • drop excess precision requirements
  • wrap online stats with iter_statistics for #376
  • Refresh MSRV lockfile
  • Leave getrandom backend selection to applications
  • Use valid order statistics benchmark inputs
  • correct entropy formulas for Pareto, Geometric, StudentsT, and Dirichlet
  • safeguard Gamma::inverse_cdf Newton step for shape < 1
  • compute Multinomial pmf/ln_pmf in log space to avoid NaN for large n
  • post updates to rand
  • update usage after rand dep update
  • restore missing normalization of Dirichlet samples
  • unblock PR 364 CI
  • remove unused testing imports
  • use core instead of std in KDE
  • (fmt) apply 2024 formatting to KDE
  • (clippy) use constants provided by core
  • (clippy) fix clippy failures in CI
  • (distribution_tests) pass if only one numerical relationship between pdf and cdf numerically close
  • change tests to rely on relative precision for math lib independence
  • Gate some stats_tests behind std feature
  • Use core over std where possible
  • update examples in mu and cov methods to use correct types from nalgebra
  • exact implementation of Bernoulli cdf
  • one more condition in inverse_cdf to account for small enough probabilities.
  • feature gate exact KS test one-sample method

Other

  • add some geometric pathological tests
  • enable autofix to use same clippy as other ci
  • Verify df one density integral
  • Cover chi-squared boundary behavior
  • update lock MSRV for kde deps change
  • module docs and feature doc
  • add paper reference and simple usage docs
  • document DensityError variants and mark non_exhaustive
  • add use of one dimensional gaussian kernel function.
  • density functions borrowing evaluation pointS instead of owning them.
  • some refactoring.
  • add performance bench.
  • add performance bench.
  • [autofix.ci] apply automated fixes
  • sample Multinomial via sequential conditional Binomial instead of categorical-style draw-and-scan
  • add characterization tests for Multinomial::sample before algorithm change
  • share binary-search lookup between Categorical::sample and inverse_cdf
  • derive Categorical::sf from cdf instead of storing it
  • Categorical now stores normalized values
  • Update dependencies and GitHub Actions
  • Converge the default continuous inverse_cdf
  • Align autofix toolchain with MSRV
  • Cover geometric inverse CDF overflow guards
  • how to release
  • wire up release-plz for crates.io publishing
  • remove fast-fail semantics of test ci
  • update branch refs from master to main
  • Add test for Dirichlet sample normalization
  • Add clippy fixes
  • more clippy lints
  • update lockfile after updating rand
  • Format with cargo fmt
  • update rand 0.9 -> 0.10
  • Fixed redundant word "may"
  • use core panic instead of std
  • add comments
  • add tests for coverage
  • add specialised inverse cdf implementation for geometric distribution
  • Simplify polynomial evaluation function
  • Add a MultivariateNormal constructor from the Cholesky decomposition
  • Make documented value of DEFAULT_RELATIVE_ACC match actual value.
  • don't fail fast when testing on different OSs
  • Bumped MSRV to 1.87.0.
  • Bumped rand to 0.9.0 and mechanically modified the code to accommodate the changes in that dependency.
  • Use -x instead of -1.0 * x
  • Merge pull request #336 from FreezyLemon/optimize-chisquare-test
  • Fix merge from master
  • Merge branch 'master' into optimize-chisquare-test
  • lint
  • use functionality from prec module outside tests
  • doctests should use approx instead of statrs::prec
  • update precision docs
  • update to not use macro_use directives
  • update readme to regard precision, open to updates
  • [breaking] define precision consts within mod prec
  • add "std" feature-gate where needed
  • Remove catch_unwind from test code
  • add no_std testing
  • only implement Error with feature "std"
  • use panic! with msg instead of println!
  • some tests do not need Vec
  • prefer core imports over std
  • more tests for inverse cdf of discrete distributions.
  • more efficient calculation for KS one-sample exact
  • remove ks_twosample usage of nalgebra
  • cfg wrap for rand
  • Fix gamma parameterization for negative binomial sampling
  • (deps) bump codecov/codecov-action from 4 to 5
  • update docs and result chaining idioms
  • enhance checks for continuous distributions with panic safety
  • improve numerical stability in CDF derivative check
  • add check for derivative of CDF to ensure it matches PDF
  • (stats_test) better attribution of sources
  • more coverage for f_oneway
  • more coverage for mannwhitneyu
  • mut in function header instead of in function

[0.18.0] - 2024-12-02

✨ Added

  • Added more inverse cumulative distribution functions.
  • Introduced feature flags: rand and nalgebra.
  • Added the std_dev method to the Distribution trait explicitly.
  • Supported sampling integers from discrete distributions.
  • Added support for the Gumbel distribution.

⚠️ Breaking Changes

  • Migrated multivariate distributions to generic dimensions.
  • Replaced StatsError with module-level error types in distribution and its children.
  • Changed checked_logit, checked_multinomial, and similar methods to return Option to handle invalid inputs.
  • Changed Chi distribution to use u64 for degrees of freedom.

🛠️ Changed

  • Upgraded nalgebra to version 0.33.
    • Upgrades MSRV to 1.65+
  • Improved documentation and added examples (e.g., for Hypergeometric distribution).
  • Added MSRV (Minimum Supported Rust Version) metadata to Cargo.toml and documentation.
  • Introduced coverage reporting with llvm-cov.
  • Updated CI to check all feature combinations and ensure MSRV compliance.
  • Added an MSRV badge to crates.io.

✅ Fixed

  • Corrected formatting issues in documentation.
  • Fixed several rustdoc warnings.
  • Expanded test coverage for Dirichlet and Multinomial distributions.
  • Improved ergonomics at cli for tests and ensured compatibility with updated NIST data.

❌ Removed

  • Replaced StatsError with module-level error types.
  • Deprecated the error module and preformatted NIST data.
  • Removed rustfmt.toml as part of CI clean-up.

🎉 New Contributors

  • @SabrinaJewson and @alimf17 made their first contributions!

0.17.1 - 2024-06-08

Details

Changed

  • Release statrs version 0.17.1 by @YeungOnion

Fixed

  • Code in benches still needs criterion by @YeungOnion

0.17.0 - 2024-05-30

Added

  • specializes inverse_cdf() for Uniform (#166)
  • Add way to get standard normal distribution easily. (#228)
  • reject constructing Uniform of infinite support (#218)
  • extend StatsError for finiteness (#218)
  • default implementation of survival function with generics (#179)
  • update MultivariateNormal API
    • construct from nalgebra with MultivariateNormal::new_from_nalgebra (#177)
    • support std::vec vector input in addition to nalgebra vectors (#199)

Fixed

  • Update nalgebra to 0.32 (#187)
  • for Gamma with shape<1 there is no mode, returns None instead of some negative number (#212)
  • fix precision of ::inverse_cdf with some newton raphson steps (#227)
    • adds test case from #200
  • fix integer bisection for default implementation of <D as DiscreteCDF>::inverse_cdf (#220)
    • also add tests from (#185)

Other

  • Remove "nightly" feature and drop testing requirement for nightly (#234)
  • Allow some imprecision in specific test case (#215)
  • Update CI (#215)
    • Check formatting in CI via rustfmt
    • Expand CI test job
    • Add clippy job to CI
  • update README with formatting and adding to "Contributing" (#213)
  • Add test asserting that StatsError is Sync & Send (#226)
  • Rename private struct NonNAN to NonNan (#222)
  • Remove lazy-static dependency and make FCACHE a proper const (#211)
  • crate examples shall be in docstrings instead of README (#213)
  • alias inverse_cdf as "quantile function" in docs (#213)
  • docstrings with math shall be text instead of ignore (#213)

[0.16.0]

  • Adds an sf method to the ContinuousCDF and DiscreteCDF traits
    • Calculates the survival function (CDF complement) for the distribution.
  • Survival function implemented for all distributions implementing ContinuousCDF and DiscreteCDF
  • update nalgebra to 0.29

v0.15.0

  • upgrade nalgebra to 0.27.1 to avoid RUSTSEC-2021-0070

v0.14.0

  • upgrade rand dependency to 0.8
  • fix inaccurate sampling of Gamma
  • Implemented Empirical distribution
  • Implemented Laplace distribution
  • Removed Checked* traits
  • Almost clippy-clean
  • Almost fully enabled rustfmt
  • Begin applying consistent numeric relative-accuracy targets with the approx crate
  • Introduce macro to generate testing boilerplate, yet not all tests use this yet
  • Moved to dynamic vectors in the MultivariateNormal distribution
  • Reduced a number of distribution-specific traits into the Distribution and DiscreteDistribution traits

v0.13.0

  • Implemented MultivariateNormal distribution (depends on nalgebra 0.19)
  • Implemented Dirac distribution
  • Implemented Negative Binomial distribution

v0.12.0

  • upgrade rand dependency to 0.7

v0.11.0

  • upgrade rand dependency to 0.6
  • Implement CheckedInverseCDF and InverseCDF for Normal distribution

v0.10.0

  • upgrade rand dependency to 0.5
  • Removes the Distribution trait in favor of the rand::distributions::Distribution trait
  • Removed functions deprecated in 0.8.0 (periodic, periodic_custom, sinusoidal, sinusoidal_custom)

v0.9.0

  • implemented infinite sequence generator for periodic sequence
  • implemented infinite sequence generator for sinusoidal sequence
  • implemented infinite sequence generator for square sequence
  • implemented infinite sequence generator for triangle sequence
  • implemented infinite sequence generator for sawtooth sequence
  • deprecate old non-infinite iterators in favor of new infinite iterators with take
  • Implemented Pareto distribution
  • Implemented Entropy trait for the Categorical distribution
  • Add a checked_ interface to all distribution methods and functions that may panic

v0.8.0

  • cdf(x), pdf(x) and pmf(x) now return the correct value instead of panicking when x is outside the range of values that the distribution can attain.
  • Fixed a bug in the Uniform distribution implementation where samples were drawn from range [min, max + 1) instead of [min, max]. The samples are now drawn correctly from the range [min, max].
  • Implement generate::log_spaced function
  • Implement generate::Periodic iterator
  • Implement generate::Sinusoidal iterator
  • Implement generate::Square iterator
  • Implement generate::Triangle iterator
  • Implement generate::Sawtooth iterator
  • Deprecate generate::periodic and generate::periodic_custom
  • Deprecate generate::sinusoidal and generate::sinusoidal_custom

Note: A recent commit to the Rust nightly build causes compile errors when using empty slices with the Statistics trait, specifically the Statistics::min and Statistics::max methods. This only affects the case where the compiler must infer the type of the empty slice:

use statrs::statistics::Statistics;

// compile error! Assumes the use of Ord::min rather than
// Statistcs::min
let x = [];
assert!(x.min().is_nan());

The fix is to pin the type of the empty slice:

// no compile error
let x: [f64; 0] = [];
assert!(x.min().is_nan());

Since the regression affects a very slim edge-case and the fix is very simple, no breaking changes to the Statistics API was deemed necessary

v0.7.0

  • Implemented Categorical distribution
  • Implemented Erlang distribution
  • Implemented Multinomial distribution
  • New InverseCDF trait for distributions that implement the inverse cdf function

v0.6.0

  • gamma::gamma_ur, gamma::gamma_ui, gamma::gamma_lr, and gamma::gamma_li now follow strict gamma function domain, panicking if a or x are not in (0, +inf)
  • beta::beta_reg no longer allows 0.0 for a or b arguments
  • InverseGamma distribution no longer accepts f64::INFINITY as valid arguments for shape or rate as the value is nonsense
  • Binomial::cdf no longer accepts arguments outside the domain of [0, n]
  • Bernoulli::cdf no longer accepts arguments outside the domain of [0, 1]
  • DiscreteUniform::cdf no longer accepts arguments outside the domain of [min, max]
  • Uniform::cdf no longer accepts arguments outside the domain of [min, max]
  • Triangular::cdf no longer accepts arguments outside the domain of [min, max]
  • FisherSnedecor no longer accepts f64::INFINITY as a valid argument for freedom_1 or freedom_2
  • FisherSnedecor::cdf no longer accepts arguments outside the domain of [0, +inf)
  • Geometric::cdf no longer accepts non-positive arguments
  • Normal now uses the Ziggurat method to generate random samples. This also affects all distributions depending on Normal for sampling including Chi, LogNormal, Gamma, and StudentsT
  • Exponential now uses the Ziggurat methd to generate random samples.
  • Binomial now implements Univariate<u64, f64> rather than Univariate<i64, f64>, meaning Binomial::min and Binomial::max now return u64
  • Bernoulli now implements Univariate<u64, f64> rather than Univariate<i64, f64>, meaning Bernoulli::min and Bernoulli::min now return u64
  • Geometric now implements Univariate<u64, f64> rather than Univariate<i64, f64>, meaning Geometric::min and Geometric::min now return u64
  • Poisson now implements Univariate<u64, f64> rather than Univariate<i64, f64>, meaning Poisson::min and Poisson::min now return u64
  • Binomial now implements Mode<u64> instead of Mode<i64>
  • Bernoulli now implements Mode<u64> instead of Mode<i64>
  • Poisson now implements Mode<u64> instead of Mode<i64>
  • Geometric now implements Mode<u64> instead of Mode<i64>
  • Hypergeometric now implements Mode<u64> instead of Mode<i64>
  • Binomial now implements Discrete<u64, f64> rather than Discrete<i64, f64>
  • Bernoulli now implements Discrete<u64, f64> rather than Discrete<i64, f64>
  • Geometric now implements Discrete<u64, f64> rather than Discrete<i64, f64>
  • Hypergeometric now implements Discrete<u64, f64> rather than Discrete<i64, f64>
  • Poisson now implements Discrete<u64, f64> rather than Discrete<i64, f64>

v0.5.1

  • Fixed critical bug in normal::sample_unchecked where it was returning NaN

v0.5.0

  • Implemented the logistic::logistic special function
  • Implemented the logistic::logit special function
  • Implemented the factorial::multinomial special function
  • Implemented the harmonic::harmonic special function
  • Implemented the harmonic::gen_harmonic special function
  • Implemented the InverseGamma distribution
  • Implemented the Geometric distribution
  • Implemented the Hypergeometric distribution
  • gamma::gamma_ur now panics when x > 0 or a == f64::NEG_INFINITY. In addition, it also returns f64::NAN when a == f64::INFINITY and 0.0 when x == f64::INFINITY
  • Gamma::pdf and Gamma::ln_pdf now return f64::NAN if any of shape, rate, or x are f64::INFINITY
  • Binomial::pdf and Binomial::ln_pdf now panic if x > n or x < 0
  • Bernoulli::pdf and Bernoulli::ln_pdf now panic if x > 1 or x < 0

[v0.4.0]

  • Implemented the exponential::integral special function
  • Implemented the Cauchy (otherwise known as the Lorenz) distribution
  • Implemented the Dirichlet distribution
  • Continuous and Discrete traits no longer dependent on Distribution trait

[v0.3.2]

  • Implemented the FisherSnedecor (F) distribution

[v0.3.1]

  • Removed print statements from ln_pdf method in Beta distribution

[v0.3.0]

  • Moved methods min and max out of trait Univariate into their own respective traits Min and Max
  • Traits Min, Max, Mean, Variance, Entropy, Skewness, Median, and Mode moved from distribution module to statistics module
  • Mean, Variance, Entropy, Skewness, Median, and Mode no longer depend on Distribution trait
  • Mean, Variance, Skewness, and Mode are now generic over only one type, the return type, due to not depending on Distribution anymore
  • order_statistic, median, quantile, percentile, lower_quartile, upper_quartile, interquartile_range, and ranks methods removed from Statistics trait.
  • min, max, mean, variance, and std_dev methods added to Statistics trait
  • Statistics trait now implemented for all types implementing IntoIterator where Item implements Borrow<f64>. Slice now implicitly implements Statistics through this new implementation.
  • Slice still implements Min, Max, Mean, and Variance but now through the Statistics implementation rather than its own implementation
  • InplaceStatistics renamed to OrderStatistics, all methods in InplaceStatistics have _inplace trimmed from method name.
  • Inverse DiGamma function implemented with signature gamma::inv_digamma(x: f64) -> f64

[v0.2.0]

  • Created statistics module and Statistics trait
  • Statistics trait implementation for [f64]
  • Implemented Beta distribution
  • Added Modulus trait and implementations for f32, f64, i32, i64, u32, and u64 in euclid module
  • Added periodic and sinusoidal vector generation functions in generate module