Discrimination for two-way models with insurance applications

Abstract

We review and apply several approaches to model selection for analysis of variance models which are used in a credibility and insurance context. The reversible jump algorithm is employed for model selection, where posterior model probabilities are computed. We then apply this method to insurance data from workers' compensation insurance schemes. The reversible jump results are compared with the Deviance Information Criterion, and are shown to be consistent.