A Gibbs Sampling Alternative to Reversible Jump MCMC

This note presents a simple and elegant sampler which could be used as an alternative to the reversible jump MCMC methodology.

On rates of convergence for posterior distributions in infinite-dimensional models

This paper introduces a new approach to the study of rates of convergence for posterior distributions. It is a natural extension of a recent approach to the study of Bayesian consistency. In particular, we improve on current rates of convergence for models including the mixture of Dirichlet process model and the random Bernstein polynomial model.