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Abstract Details
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Activity Number:
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209
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Type:
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Invited
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Date/Time:
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Monday, August 1, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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International Indian Statistical Association
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| Abstract - #300350 |
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Title:
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Comparing Different Points of View for Analyzing Finite Mixture Models
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Author(s):
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Gilles Celeux*+
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Companies:
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INRIA
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Address:
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Université d'Orsay, Bât. 425, Orsay, F91405, France
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Keywords:
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Conditional Completed Likelihood ;
Integrated Completed Likelihood ;
Variational Bayes
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Abstract:
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Abstract: Mixture models are an efficient tool to deal with heterogeneity or for model-based cluster analysis. These two points of view could lead to different methods for statistical inference (parameter estimation and model selection). After a survey highlighting their differences, the consequences of those two points of view on statistical analysis will be discussed. On the other hand, in a Bayesian perspective, the differences between a Bayesian inference through MCMC and variational approximation will be discussed.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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