Overfitting Bayesian Mixture Models with an Unknown Number of Components.

This paper proposes solutions to three issues pertaining to the estimation of finite mixture models with an unknown number of components: the non-identifiability induced by overfitting the number of components, the mixing limitations of standard Markov Chain Monte Carlo (MCMC) sampling techniques, a...

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Bibliographic Details
Main Authors: Zoé van Havre, Nicole White, Judith Rousseau, Kerrie Mengersen
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4503697?pdf=render