Bayesian Inference on Mixtures of Distributions
Kate Lee, Jean‐Michel Marin, Kerrie Lee Mengersen, Christian P. Robert · arXiv (Cornell University) · 2008
This survey covers state-of-the-art Bayesian techniques for the estimation of mixtures. It complements the earlier Marin, Mengersen and Robert (2005) by studying new types of distributions, the multinomial, latent class and t distributions. It also exhibits closed form solutions for Bayesian inference in some discrete setups. Lastly, it sheds a new light on the computation of Bayes factors via the approximation of Chib (1995).