While Bayesian methods have attracted considerable interest in actuarial science, they are yet to be embraced in large-scaled insurance predictive modeling applications, due to inefficiencies of Bayesian estimation procedures. The paper presents an efficient method that parallelizes Bayesian...

We give a general discussion of linear mixed models and continue with illustrating specific actuarial applications of this type of models. Technical details on linear mixed models follow: model assumptions, specifications, estimation techniques and methods of inference. We include three worked...

We start with a discussion of model families for multilevel data outside the Gaussian framework. We continue with Generalized Linear Mixed Models ([GLMMs]), which enable generalized linear modeling with multilevel data. The Chapter includes highlights of estimation techniques for GLMMs, in the...