NEWS | R Documentation |

Vignette “credibility” now contains an appendix summarizing the formulas in the linear Bayes cases.

`cm`

with`formula = "bayes"`

stopped in the Gamma/Gamma case even though the parameter`shape.lik`

was provided. Thanks to Vincent Masse vincent.masse.4@ulaval.ca for the report.Component

`weights`

of the return value of`cm`

in the`formula = "bayes"`

case was wrong. This had no impact on premium calculation and was visible in the output of`summary`

only. Also, it caused an error when`data`

was`NULL`

or missing.

`cm`

can now fit linear Bayes models for the following combinations of likelihood and prior distributions: Poisson/Gamma, Exponential/Gamma, Bernoulli/Beta, Geometric/Beta, Normal/Normal, Gamma/Gamma, Binomial/Beta, Negative Binomial/Beta and the less common case Single Parameter Pareto/Gamma (where the Bayes estimator is linear, but not a credibility premium). Thanks to Christophe Dutang dutang@ceremade.dauphine.fr for the idea.`rcomphierarc.summaries`

is now an alias for the man page of`simul.summaries`

.

In

`summary`

results for credibility models, a level “section title” is no longer printed for one-level models.All instances of function

`simul`

in vignette`“simulation”`

replaced by`rcomphierarc`

.

Functions

`rcompound`

and`rcomppois`

gain an argument`SIMPLIFY`

that is`TRUE`

by default. When`FALSE`

, the functions return not only variates from the aggregate claim amount random variable, but also the variates from the underlying frequency and severity distributions.Functions

`rcompound`

and`rcomppois`

now admit an object name in argument for`model.sev`

and`model.freq`

.

Display of verbatim blocks in vignettes.

In the man page for

`dgenpareto`

, additional note on the link between the Generalized Pareto distribution in the package and the version used in Embrechts et al. (1997) and Wikipedia. Thanks to Marcel Trevissen kamath1602@gmail.com for the pointer.

Usage of

`R_useDynamicSymbols`

to preclude compilation`NOTE`

s, better registration of native routines and reduced symbol visibility.Vignettes no longer use LaTeX package framed as it was not found on OS X in CRAN builds.

`qinvgauss`

was not computing quantiles as far in the right tail as`statmod:::qinvgauss`

. This is now fixed. Thanks to Gordon Smyth smyth@wehi.edu.au for pointing it out.

Support for the incomplete gamma function and the exponential integral has been moved to package expint. Therefore, actuar now imports these functionalities through the expint API.

Consequence of the above, the non exported functions

`gammaint`

and`expint`

are deleted from the package.Section 6 on special integrals of the

`“distributions”`

package vignette was revised to better introduce the incomplete gamma function, the incomplete beta function and the related integrals.

New support functions

`[dpqrm,lev,mgf]invgauss`

for the inverse Gaussian distribution. The first three functions are C (read: faster) implementations of functions of the same name in package statmod.New support functions

`[dpqrm,mgf]gumbel`

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.New 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.New support functions

`[dpqr]poisinvgauss`

for the Poisson-inverse Gaussian discrete distribution.New support functions

`[dpqr]logarithmic`

and`[dpqr]zmlogarithmic`

for the logarithmic (or log-series) and zero-modified logarithmic distributions.New support functions

`[dpqr]ztpois`

and`[dpqr]zmpois`

for the zero-truncated and zero-modified Poisson distributions.New support functions

`[dpqr]ztnbinom`

and`[dpqr]zmnbinom`

for the zero-truncated and zero-modified negative binomial distributions.New support functions

`[dpqr]ztgeom`

and`[dpqr]zmgeom`

for the zero-truncated and zero-modified geometric distributions.New support functions

`[dpqr]ztbinom`

and`[dpqr]zmbinom`

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.`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.

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

`mgffoo`

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`

.

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. The bug went unnoticed before because there was no example for the*(a, b, 1)*case in the man page.

Functions

`[m,lev,mgf]invGauss`

that complemented functions`[dpqr]invGauss`

of package SuppDists are deprecated in favor of the new complete set of functions`[dpqrm,lev,mgf]invgauss`

.

News for actuar 1.2-2 and earlier can be found in file ‘NEWS.1.Rd’.