Latent Class Models for Categorical Data
Résumé
This chapter deals with mixture models for clustering categorical and mixed-type data, which are in the literature often referred to as latent class models. The chapter introduces the maximum-likelihood approach and the EM algorithm. It introduces Bayesian approaches and has a comprehensive discussion of parsimonious models and methods for model selection and estimating the number of clusters such as information criteria. This chapter concludes with techniques for ordinal-and mixed-type data.