Bayesian inference for mixture models via monte carlo computation

Ajay Jasra
In the past fifteen years there has been a dramatic increase of interest in Bayesian mixture models. This is because we are now able to apply Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. This thesis is concerned with Bayesian mixture modelling via such approaches. The following topics are considered. Firstly, an important problem with Bayesian mixture models is that of label switch- ing. This is caused by the nonidentifiability of the...
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