Bayesian Analysis with Python - Second Edition

Finite mixture models

One way to build mixture models is to consider a finite weighted mixture of two or more distributions. This is known as a finite mixture model. Thus, the probability density of the observed data is a weighted sum of the probability density for subgroups of the data:

Here, is the weight of each component (or class). We can interpret as the probability of the component , thus its values are restricted to the interval [0, ...