[R-pkgs] Major update of package actuar

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[R-pkgs] Major update of package actuar

Vincent Goulet
Dear useRs,

I'm happy to announce a substantial update of package actuar that bumps the version number to 2.0-0. This release focuses on additional support for continuous and discrete distributions, new functions to simulate data from compound models and mixtures, and revised and improved documentation.

A slightly shortened version of the NEWS file follows:

NEW FEATURES

• Support for the inverse Gaussian distribution. The pdf, cdf and
  quantile functions are C (read: faster) implementations of otherwise
  equivalent functions in package ‘statmod’.

• Support for the Gumbel extreme value distribution.

• Extended range of admissible values for many limited
  expected value functions thanks to new C-level functions
  ‘expint’, ‘betaint’ and ‘gammaint’. These provide special
  integrals presented in the introduction of Appendix A of
  Klugman et al. (2012); see also ‘vignette("distributions")’.

  Affected functions are: ‘levtrbeta’, ‘levgenpareto’,
  ‘levburr’, ‘levinvburr’, ‘levpareto’, ‘levinvpareto’,
  ‘levllogis’, ‘levparalogis’, ‘levinvparalogis’ in the
  Transformed Beta family, and ‘levinvtrgamma’, ‘levinvgamma’,
  ‘levinvweibull’ in the Transformed Gamma family.

• Functions ‘expint’, ‘betaint’ and ‘gammaint’ to compute
  the special integrals mentioned above. These are merely
  convenience R interfaces to the C level functions. They are
  _not_ exported by the package.

• Support for the Poisson-inverse Gaussian discrete distribution.

• Support for the logarithmic (or log-series) and zero-modified
  logarithmic distributions.

• Support for the zero-truncated and zero-modified Poisson
  distributions.

• Support for the zero-truncated and zero-modified negative
  binomial distributions.

• Support for the zero-truncated and zero-modified geometric
  distributions.

• Support for the zero-truncated and zero-modified binomial
  distributions.

• New vignette ‘"distributions"’ that reviews in great detail the
  continuous and discrete distributions provided in the
  package, along with implementation details.

• ‘aggregateDist’ now accepts ‘"zero-truncated binomial"’,
  ‘"zero-truncated geometric"’, ‘"zero-truncated negative
  binomial"’, ‘"zero-truncated poisson"’, ‘"zero-modified
  binomial"’, ‘"zero-modified geometric"’, ‘"zero-modified
  negative binomial"’, ‘"zero-modified poisson"’ and
  ‘"zero-modified logarithmic"’ for argument ‘model.freq’ with
  the ‘"recursive"’ method.

• New function ‘rmixture’ to generate random variates from
  discrete mixtures, that is from random variables with
  densities of the form f(x) = p_1 f_1(x) + ... + p_n f_n(x).

• New function ‘rcompound’ to generate random variates from (non
  hierarchical) compound models of the form S = X_1 + ... + X_N.
  Function ‘simul’ could already do that, but ‘rcompound’ is
  substantially faster for non hierarchical models.

• New function 'rcomppois' that is a simplified version of
  ‘rcompound’ for the very common compound Poisson case.

• Function ‘simul’ now accepts an atomic (named or not) vector for
  argument ‘nodes’ when simulating from a non hierarchical
  compound model. But really, one should use ‘rcompound’ for
  such cases.

• New alias ‘rcomphierarc’ for ‘simul’ that better fits within
  the usual naming scheme of random generation functions.

• Functions ‘grouped.data’ and ‘ogive’ now accept individual
  data in argument. The former will group the data using
  ‘hist’ (therefore, all the algorithms to compute the number
  of breakpoints available in ‘hist’ are also available in
  ‘grouped.data’). ‘ogive’ will first create a grouped data
  object and then compute the ogive.

  While there is no guarantee that the two functions are
  backward compatible (the number and position of the
  arguments have changed), standard calls should not be
  affected.

USER VISIBLE CHANGES

• The material on probability laws in vignette ‘"lossdist"’
  has been moved to the new vignette ‘"distributions"’ (see
  the previous section).

• The first argument of the ‘mgf<dist>’ functions has changed
  from ‘x’ to ‘t’. This is a more common notation for moment
  generating functions.

• In ‘aggregateDist’ with the ‘"recursive"’ method, if the
  length of ‘p0’ is greater than one, only the first element
  is used, with a warning.

• ‘aggregateDist’ with the ‘"recursive"’ method and
  ‘model.freq = "logarithmic"’ now uses the new ‘dlogarithmic’
  family of functions. Therefore, parametrization has changed
  from the one of Klugman et al. (2012) to the standard
  parametrization for the logarithmic distribution. Basically,
  any value of ‘prob’ for the logarithmic parameter in
  previous versions of ‘actuar’ should now be ‘1 - prob’.

• The aim of vignette ‘"simulation"’ is changed from
  “simulation of compound hierarchical models” to “simulation
  of insurance data with ‘actuar’” as it also covers the new
  functions ‘rmixture’ and ‘rcompound’.

• Vignette ‘"lossdist"’ is renamed to ‘"modeling"’ and it is
  revised to cover the new functionalities of ‘grouped.data’
  and ‘ogive’.

BUG FIX

•  An old and nasty out-of-bounds bug could crash R when using
  the "recursive" method of 'aggregateDist' with a frequency
  distribution from the (a, b, 1) family.


I hope this update will prove useful.

Vincent Goulet, Ph.D.
Professeur titulaire
École d'actuariat, Université Laval

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