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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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| Publicado no: | PLoS One |
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| Principais autores: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5231325/ https://ncbi.nlm.nih.gov/pubmed/28081166 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0168838 |
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