Handling Hierarchically Structured Risk Factors using Random Effects Models
tools:::Rd_package_title("actuaRE")
Adjust the intercept to regain the balance property
Balance property
Add random effects to the data frame
Determine random-effects expressions from a formula
Extract the fixed-effects estimates from a fitted random effects model
Extract fixed-effects estimates
Class "hierCredGLM" of fitted random effects models estimated with Ohl...
Combining the hierarchical credibility model with a GLM (Ohlsson, 2008...
Class "hierCredibility" of fitted hierarchical credibility models
Hierarchical credibility model of Jewell
Class "hierCredTweedie" of fitted random effects models estimated with...
Combining the hierarchical credibility model with a GLM (Ohlsson, 2008...
Formula
Is f1 nested within f2?
Modular Functions for Mixed Model Fits
Omit terms separated by vertical bars in a formula
Number of unique elements in a vector
Visualizing the random effect estimates using ggplot2
Model predictions
Model predictions
Model predictions
Print method for an object of class BalanceProperty
Extract the random effect estimates from a fitted random effects model
Extract the modes of the random effects
Fitting a Tweedie GLMM, using the initial estimates of hierCredTweedie
Extract the model weights
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>.