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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...
Tallennettuna:
| Julkaisussa: | PLoS One |
|---|---|
| Päätekijät: | , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Public Library of Science
2015
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4503697/ https://ncbi.nlm.nih.gov/pubmed/26177375 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0131739 |
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