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...

A recent addition to the literature in psychology concerns individuals' forecasts of the affective states they predict will arise in the future. Affective forecasts are extremely relevant to marketing and consumer behavior as they impact choice as well as a set of other marketing-relevant...