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actuaRE: Handling Single-Level and Hierarchically Structured Risk Factors using Credibility and Random Effects Models

Fits random effects models for multi-level/high-cardinality factors using credibility theory (Buhlmann-Straub for single-level, Jewell for hierarchical structures), GLM extensions following Ohlsson (2008) doi:10.1080/03461230701878612, or Tweedie generalized linear mixed models. Provides functions for model fitting, visualization, and prediction. See Campo, B.D.C. and Antonio, K. (2023) doi:10.1080/03461238.2022.2161413.

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. (2026). The actuaRE package: Handling Single-Level and Hierarchically Structured Risk Factors using Credibility and Random Effects Models. R package version 1.0.0, https://cran.r-project.org/package=actuaRE