On Expectation Propagation and the Probabilistic Editor in some simple mixture problems

Abstract

As for other latent-variable problems, exact Bayesian analysis is typically not practicable for mixture problems and approximate methods have been developed. Variational Bayes tends to produce approximate posterior distributions for parameters that are too tightly concentrated in having variances that are too small. The paper identifies a few mixture problems in which Expectation Propagation and variations thereof lead to approximate posterior distributions that asymptotically exhibit `correct' variances and therefore stand to provide reliable interval estimates for the unknown parameter or parameters.