Grün, Bettina, Leisch, Friedrich. 2009. Dealing with label switching in mixture models under genuine multimodality. Journal of Multivariate Analysis 100 (5): 851-861.
BibTeX
Abstract
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.
Tags
Press 'enter' for creating the tagPublication'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 |
Associations
- Projects
- Modelling Unobserved Heterogeneity Using Mixtures
- People
- Grün, Bettina (Details)
- External
- Leisch, Friedrich (Ludwig-Maximilians-Universität München, Germany)
- Organization
- Institute for Statistics and Mathematics IN (Details)