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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Detalles Bibliográficos
Autores principales: van Havre, Zoé, White, Nicole, Rousseau, Judith, Mengersen, Kerrie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4503697/
https://www.ncbi.nlm.nih.gov/pubmed/26177375
http://dx.doi.org/10.1371/journal.pone.0131739

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4503697/
https://www.ncbi.nlm.nih.gov/pubmed/26177375
http://dx.doi.org/10.1371/journal.pone.0131739

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