2Mixture models for discrete data
In this chapter, we introduce finite mixture models for discrete data, including categorical data (nominal or ordinal), counts (univariate or multivariate), rankings, and so on. Both univariate and multivariate cases are considered.
In fact, the finite mixture models for discrete data are similar to those designed for continuous data, since many types of discrete data can be considered as discretized versions of some continuous latent data. Therefore, the idea of the EM algorithm can be readily applied to this chapter for model estimation. However, as the dimension of the data increases, it becomes much more difficult to model discrete multivariate data than continuous data. For ...
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