KFAS version 1.0.4 for CRAN

Changes from version 1.0.3 to 1.0.4:

• Tweaked the underlying algorithms for increased numerical stability of filtering and smoothing
  in KFS. Note that it is still possible that exact diffuse initialization fails due to to numerical
  issues whereas traditional 'big value' approach works and vice versa.
• Corrected a bug in residuals.KFS which threw an error when computing recursive residuals without
  diffuse initialization.
• Corrected output of LogLik method for non-Gaussian models: It now returns -Inf only when the
  approximation algoritm failedcompletely (resulting NA), and issues only warning about
  non-convergence in other cases.
• Added checks of degenerate model to LogLik method. If all elements in R, Q and H/u are zero, or
  they contain any non-finite values, -Inf is returned.
• Fixed a bug in approximation algorithm which caused the approximation to fail for seemingly
  random models.
• Fixed a bug in SSMcycle which caused error with common components.
• Fixed bug in SSMcycle which resulted erroneus system matrix T in all cases.
• Fixed a bug in SSMseasonal which caused error in SSModel when using common components.
• SSMseasonal with trigonometric seasonal now works properly when period is odd.
• Fixed a bug in coef.KFS which caused function to return smoothed states even with argument
  filtered=TRUE if they were present in KFS object.
• Added argument "maxiter" to predict.SSModel and changed its default value in all functions to 50.
• Corrected a bug in function ldl which caused the decomposition of semidefinite matrices to fail
  silently.
• Changed variable mu to m for mean filtering for non-Gaussian models without simulation just like
  in other cases.
• Changed convergence criterion in Gaussian approximation algorithm from linear predictor based to
  deviance based.
• Properly exported assigment using subset method. See ?subset.SSModel for details.