Model based labeling for mixture models

DOI10.1007/s11222-010-9226-8zbMath1322.62047OpenAlexW2110656936MaRDI QIDQ746210

Weixin Yao

Publication date: 16 October 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2097/13831

zbMATH Keywords

Markov chain Monte Carlomixture modelBayesian mixtureslabel switchinglabeling probabilities

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Bayesian inference (62F15)

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Cites Work

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• Dealing with label switching in mixture models under genuine multimodality
• Interpretation and inference in mixture models: simple MCMC works
• A stochastic EM algorithm for a semiparametric mixture model
• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• Finite mixture and Markov switching models.
• An Application of the Laplace Method to Finite Mixture Distributions
• Dealing With Label Switching in Mixture Models
• Computational and Inferential Difficulties with Mixture Posterior Distributions
• Markov chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models
• Bayesian Mixture Labeling by Highest Posterior Density