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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5231325?pdf=render |
| _version_ | 1818986221378994176 |
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| author | Kazem Nasserinejad Joost van Rosmalen Wim de Kort Emmanuel Lesaffre |
| author_facet | Kazem Nasserinejad Joost van Rosmalen Wim de Kort Emmanuel Lesaffre |
| author_sort | Kazem Nasserinejad |
| collection | DOAJ |
| description | 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 overfitted mixture models, the overfitted latent classes will asymptotically become empty under specific conditions for the prior of the class proportions. This result may be used to construct a criterion for finding the true number of latent classes, based on the removal of latent classes that have negligible proportions. Unlike some alternative criteria, this criterion can easily be implemented in complex statistical models such as latent class mixed-effects models and multivariate mixture models using standard Bayesian software. We performed an extensive simulation study to develop practical guidelines to determine the appropriate number of latent classes based on the posterior distribution of the class proportions, and to compare this criterion with alternative criteria. The performance of the proposed criterion is illustrated using a data set of repeatedly measured hemoglobin values of blood donors. |
| first_indexed | 2024-12-20T18:47:21Z |
| format | Article |
| id | doaj.art-6f37a9279182451baf5356caceed957d |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-20T18:47:21Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-6f37a9279182451baf5356caceed957d2022-12-21T19:29:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01121e016883810.1371/journal.pone.0168838Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models.Kazem NasserinejadJoost van RosmalenWim de KortEmmanuel LesaffreIdentifying 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 overfitted mixture models, the overfitted latent classes will asymptotically become empty under specific conditions for the prior of the class proportions. This result may be used to construct a criterion for finding the true number of latent classes, based on the removal of latent classes that have negligible proportions. Unlike some alternative criteria, this criterion can easily be implemented in complex statistical models such as latent class mixed-effects models and multivariate mixture models using standard Bayesian software. We performed an extensive simulation study to develop practical guidelines to determine the appropriate number of latent classes based on the posterior distribution of the class proportions, and to compare this criterion with alternative criteria. The performance of the proposed criterion is illustrated using a data set of repeatedly measured hemoglobin values of blood donors.http://europepmc.org/articles/PMC5231325?pdf=render |
| spellingShingle | Kazem Nasserinejad Joost van Rosmalen Wim de Kort Emmanuel Lesaffre Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models. PLoS ONE |
| title | Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models. |
| title_full | Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models. |
| title_fullStr | Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models. |
| title_full_unstemmed | Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models. |
| title_short | Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models. |
| title_sort | comparison of criteria for choosing the number of classes in bayesian finite mixture models |
| url | http://europepmc.org/articles/PMC5231325?pdf=render |
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