Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models

Identifying the number of classes in Bayesian finite mixture models is a challenging problem. Several criteria have been proposed, such as adaptations of the deviance information criterion, marginal likelihoods, Bayes factors, and reversible jump MCMC techniques. It was recently shown that in overfi...

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Detalles Bibliográficos
Autores principales: Nasserinejad, Kazem, van Rosmalen, Joost, de Kort, Wim, Lesaffre, Emmanuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5231325/
https://www.ncbi.nlm.nih.gov/pubmed/28081166
http://dx.doi.org/10.1371/journal.pone.0168838

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5231325/
https://www.ncbi.nlm.nih.gov/pubmed/28081166
http://dx.doi.org/10.1371/journal.pone.0168838

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