FBST for Mixture Model Selection
Marcelo de Souza Lauretto · AIP conference proceedings · 2005
The Fully Bayesian Significance Test (FBST) is a coherent Bayesian significance test for sharp hypotheses. This paper proposes the FBST as a model selection tool for general mixture models, and compares its performance with Mclust, a model‐based clustering software. The FBST robust performance strongly encourages further developments and investigations.