A batesian semiparametric generalized linear model with random effects using Dirichlet process priors

Abstract

The purpose of this paper is to propose a parameter estimation method that doesn't need to set the number of heterogeneous populations in generalized linear models.We use a finite dimensional Dirichlet process mixed model (Ishwaran and James 2001). Due to the use of Dirichlet process, we make no assumption about the number of subgroups that are mixed. The proposed model can be considered as the direct extension of the model of Lenk and DeSarbo (2000) in the sense that the proposed method needs no assumption for the number of mixed latent classes in their model. © 2010 Springer-Verlag Berlin Heidelberg.