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Activity Number:
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495
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Type:
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Invited
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Date/Time:
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Wednesday, August 5, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #302827 |
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Title:
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Computational Methods for Bayesian Model Choice
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Author(s):
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Christian P. Robert*+ and Jean-Michel Marin
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Companies:
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Université Paris Dauphine and University Montpellier II
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Address:
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CREST/INSEE/CEREMADE, Paris Cedex 16, International, 75775, France
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Keywords:
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model choice ; importance sampling ; nested sampling ; Chib's marginal likelihood ; defensive sampling
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Abstract:
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In this talk, we will cover recent developments of ours and of others in the computation of marginal likelihoods for the comparison of statistical models in a Bayesian framework. While the introduction of reversible jump MCMC by Green in 1995 is rightly perceived as the 'second MCMC revolution,' its implementation is often too complex for the problems at stake. When the number of models under study is of a reasonable magnitude, there exist many computational alternatives that avoid model exploration with a reasonable efficiency and we will discuss here the pros and cons of several of those methods.
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