Functions and data sets for actuarial science: modeling of loss distributions; risk theory and ruin theory; simulation of compound models, discrete mixtures and compound hierarchical models; credibility theory. Support for many additional probability distributions to model insurance loss amounts and loss frequency: 19 continuous heavy tailed distributions; the Poisson-inverse Gaussian discrete distribution; zero-truncated and zero-modified extensions of the standard discrete distributions. Support for phase-type distributions commonly used to compute ruin probabilities.
| Version: | 2.3-1 |
| Depends: | R (≥ 3.3.0) |
| Imports: | stats, graphics, expint |
| LinkingTo: | expint |
| Suggests: | MASS |
| Published: | 2018-03-19 |
| Author: | Vincent Goulet [cre, aut], Sébastien Auclair [ctb], Christophe Dutang [aut], Xavier Milhaud [ctb], Tommy Ouellet [ctb], Alexandre Parent [ctb], Mathieu Pigeon [aut], Louis-Philippe Pouliot [ctb] |
| Maintainer: | Vincent Goulet <vincent.goulet at act.ulaval.ca> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Citation: | actuar citation info |
| Materials: | NEWS |
| In views: | Distributions, Finance |
| CRAN checks: | actuar results |
| Reference manual: | actuar.pdf |
| Vignettes: |
Introduction to actuar Complete formulas used by coverage Credibility theory Additional continuous and discrete distributions Loss distributions modeling Risk and ruin theory Simulation of insurance data |
| Package source: | actuar_2.3-1.tar.gz |
| Windows binaries: | r-devel: actuar_2.3-1.zip, r-release: actuar_2.3-1.zip, r-oldrel: actuar_2.3-1.zip |
| OS X binaries: | r-release: actuar_2.3-1.tgz, r-oldrel: actuar_2.3-1.tgz |
| Old sources: | actuar archive |
| Reverse depends: | lbiassurv, stratifyR |
| Reverse imports: | AnnuityRIR, BTSPAS, ChainLadder, CompDist, episensr, fitur, kendallRandomWalks, mbbefd, OpVaR, ReliabilityTheory, teachingApps |
| Reverse suggests: | extraDistr, fitdistrplus, fitteR, flexmix, GeneralizedHyperbolic, HyperbolicDist, PhaseType, raw |
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