## Mixture Model

A simple mixture model has a probability density function

Posterior density. Given the data of independent observations from the mixture density and the flat prior, the posterior density of weight parameter is proportional to

Latent Variables. Then we introduce the following latent variable setup: Let be a latent variable indicating to which component the -th observation belongs, and let be the vector of latent variables on the space

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