Description
Handling Hierarchically Structured Risk Factors using Random Effects Models.
Description
Using this package, you can fit a random effects model using either the hierarchical credibility model, a combination of the hierarchical credibility model with a generalized linear model or a Tweedie generalized linear mixed model. See Campo, B.D.C. and Antonio, K. (2023) <doi:10.1080/03461238.2022.2161413>.
README.md
actuaRE: Handling hierarchically structured
risk factors using random effects models. 
Installation
On current R (>= 3.0.0)
- Development version from Github:
library("devtools"); install_github("BavoDC/actuaRE", dependencies = TRUE, build_vignettes = TRUE)
(This requires devtools >= 1.6.1, and installs the "master" (development) branch.) This approach builds the package from source, i.e. make and compilers must be installed on your system -- see the R FAQ for your operating system; you may also need to install dependencies manually. Specify build_vignettes=FALSE if you have trouble because your system is missing some of the LaTeX/texi2dvi tools.
Documentation
The basic functionality of the package is explained and demonstrated in the vignette, which you can access using
vignette("actuaRE")
or via the homepage of the package.
Citation
If you use this package, please cite:
- Campo, B.D.C. and Antonio, Katrien (2023). Insurance pricing with hierarchically structured data an illustration with a workers' compensation insurance portfolio. Scandinavian Actuarial Journal, doi: 10.1080/03461238.2022.2161413
- Campo, B.D.C. (2023). The actuaRE package: Handling Hierarchically Structured Risk Factors using Random Effects Models. R package version 0.1.3, https://cran.r-project.org/package=actuaRE.