FBST for Mixture Model Selection.
AIP Conference Proceedings 803:121-128 (2005)
Abstract
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.Author's Profile
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