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...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2015-01-01
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Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4503697?pdf=render |