Abstract Details
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Activity Number:
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658
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Type:
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Contributed
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Date/Time:
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Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #312297
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View Presentation
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Title:
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Bayesian Model Selection Methods in Linear Models
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Author(s):
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Arnab Maity*+ and Sanjib Basu and Santu Ghosh
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Companies:
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Northern Illinois University and Northern Illinois University and Wayne State University
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Keywords:
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Bayes Factor ;
Cross Validation ;
Model Comparison ;
Linear Models ;
LASSO
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Abstract:
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Various popular Bayesian model selection criteria, such as those based on the conditional predictive ordinates, are based on the general notion of one-deleted cross-validation. These criteria can often be estimated from Markov chain samples with reasonable ease. The Deviance Information Criterion (DIC) is another popular model selection criterion We investigate the performance of these model selection criteria in detecting the correct model and compare them with other competing criteria. Furthermore, the insight of Highest Posterior Model is also discussed.
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Authors who are presenting talks have a * after their name.
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