Quotation Grün, Bettina, Leisch, Friedrich. 2009. Dealing with label switching in mixture models under genuine multimodality. Journal of Multivariate Analysis 100 (5): 851-861.




The fitting of finite mixture models is an ill-defined estimation problem as completely different parameterizations can induce similar mixture distributions. This leads to multiple modes in the likelihood which is a problem for frequentist maximum likelihood estimation, and complicates statistical inference of Markov chain Monte Carlo draws in Bayesian estimation. For the analysis of the posterior density of these draws a suitable separation into different modes is desirable. In addition, a unique labelling of the component specific estimates is necessary to solve the label switching problem. This paper presents and compares two approaches to achieve these goals: relabelling under multimodality and constrained clustering. The algorithmic details are discussed and their application is demonstrated on artificial and real-world data.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Journal of Multivariate Analysis
Citation Index SCI
WU Journalrating 2009 A
WU-Journal-Rating new FIN-A, VW-D, WH-B
Language English
Title Dealing with label switching in mixture models under genuine multimodality
Volume 100
Number 5
Year 2009
Page from 851
Page to 861
Reviewed? Y
URL http://epub.ub.uni-muenchen.de/6336/1/tr039.pdf


Modelling Unobserved Heterogeneity Using Mixtures
Grün, Bettina (Details)
Leisch, Friedrich (Ludwig-Maximilians-Universität München, Germany)
Institute for Statistics and Mathematics IN (Details)
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