Bayesian Mixture Labeling and Clustering

DOI10.1080/03610926.2010.526741zbMath1244.62038OpenAlexW2062126350MaRDI QIDQ2903830

Weixin Yao

Publication date: 2 August 2012

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2097/14025

zbMATH Keywords

clusteringMarkov chain Monte CarloBayesian mixturesK-meanslabel switching

Mathematics Subject Classification ID

Related Items (10)

Label switching and its solutions for frequentist mixture models ⋮ Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering ⋮ A simple root selection method for univariate finite normal mixture models ⋮ Robust fitting of mixtures of factor analyzers using the trimmed likelihood estimator ⋮ Outlier detection and robust mixture modeling using nonconvex penalized likelihood ⋮ A Simple Solution to Bayesian Mixture Labeling ⋮ An online Bayesian mixture labelling method by minimizing deviance of classification probabilities to reference labels ⋮ Relabelling algorithms for mixture models with applications for large data sets ⋮ Mixture of linear mixed models using multivariatetdistribution ⋮ Mixtures of Linear Regression with Measurement Errors

Cites Work

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• Interpretation and inference in mixture models: simple MCMC works
• A robust method for cluster analysis
• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• Density Estimation With Confidence Sets Exemplified by Superclusters and Voids in the Galaxies
• Dealing With Label Switching in Mixture Models
• Markov chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models
• Bayesian Mixture Labeling by Highest Posterior Density

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