Mixture model

Summary

A mixture model describes a population made of several subpopulations, each with its own distribution. The density of an observation is a weighted average of the component densities, with weights equal to the subpopulation proportions. It is a latent variable model in which the hidden variable is the label of the subpopulation. Mixture models are usually fitted by the expectation–maximization algorithm and are a basis of model-based cluster analysis.