EXAMPLES OF BAYESIAN MIXTURE MODELS

Mixture models can be used to model complex distributions of "target"
values, without any dependence on input values.  The mixture
components that are found by the model might also be interpretable as
representing underlying "latent classes" in the data.  Examples are
given here of how this can be done for binary and for real-valued
data.

The data and command files for these examples are in the "ex-mix"
directory.  This directory also contains the data and command files
used for the example in my tech report on "Markov chain sampling
methods for Dirichlet process mixture models".