JOURNAL OF APPLIED STATISTICS, v.20, Issue.2, Page.191
Abstract
Latent class models have recently drawn considerable attention among many
researchers and practitioners as a class of useful tools for capturing
heterogeneity across different segments in a target market or population.
In this paper, we consider a latent class logit model with parameter constraints
and deal with two important issues in the latent class models within a
Bayesian framework. A simple Gibbs sampling algorithm is proposed for sample
generation from the posterior distribution of unknown parameters. Using the Gibbs output, we propose a method for
determining an appropriate number of the latent classes. A real-world example as
an application for market segmentation is provided to illustrate the proposed method.