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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