Bayesian clustering and product partition models

A decision theoretic formulation of product partition models (PPMs) is presented that allows a formal treatment of different decision problems such as estimation or hypothesis testing and clustering methods simultaneously, and an algorithm is proposed that yields Bayes estimates of the quantities of interest and the groups of experimental units.