Regularized Categorial Effects/Categorial Effect Modifiers in
GLMs
Description
The function fits generalized linear models with
categorial effects and categorial effect modifiers. The model
is specified by giving a symbolic description of the linear
predictor and a description of the error distribution.
Estimation employs regularization and model selection
strategies to fuse and/or select a covariate's categories.
These strategies are either a penalty combining the fused and
the pure Lasso or a forward selection strategy employing
AIC/BIC.