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Abstract: In a Bayesian analysis of finite mixture models, parameter estimation and clustering are sometimes less straightforward that might be expected. In particular, the common practice of estimating parameters by their posterior mean, and summarising joint posterior distributions by marginal distributions, often leads to nonsensical answers. This is due to the so-called "labelswitching " problem, which is caused by symmetry in the likelihood of the model parameters. A frequent response to this... (Update)
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BibTeX entry: (Update)
Stephens, M. (2000b) Dealing with label switching in mixture models. J. Roy. Statist. Soc. Ser. http://citeseer.ist.psu.edu/article/stephens00dealing.html More
@misc{ stephens-dealing,
author = "M. Stephens",
title = "Dealing with label switching in mixture models",
text = "Stephens, M. (2000b) Dealing with label switching in mixture models. J.
Roy. Statist. Soc. Ser.",
url = "citeseer.ist.psu.edu/article/stephens00dealing.html" }
Citations (may not include all citations):461 Markov Chain Monte Carlo in Practice (context) - Gilks, Richardson et al. - 1996
150 On Bayesian analysis of mixtures with an unknown number of c.. - Richardson, Green - 1997
140 Bayesian density estimation and inference using mixtures - Escobar, West - 1995
134 Marginal likelihood from the Gibbs output (context) - Chib - 1995
125 Bayesian model choice via Markov Chain Monte Carlo methods (context) - Carlin, Chib - 1995
54 Estimation of finite mixture distributions through Bayesian .. (context) - Diebolt, Robert - 1994
42 Mixture densities (context) - Redner, Walker - 1984
28 Bayesian model comparison via jump diffusions (context) - Phillips, Smith - 1996
25 Operations Research: An Introduction (context) - Taha - 1989
21 Density estimation with confidence sets exemplified by super.. (context) - Roeder - 1990
20 Bayesian Methods for Mixtures of Normal Distributions - Stephens
12 Bayesian inference in hidden Markov models through reversibl.. - Robert, Ryden et al. - 2000
10 An application of the Laplace method to finite mixture distr.. (context) - Crawford - 1994
8 Computational and inferential difficulties with mixture post.. - Celeux, Hurn et al. - 2000
6 Bayesian analysis of mixtures with an unknown number of comp.. (context) - Stephens - 2000
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