Abstract Details
Activity Number:
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503
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 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 #313578
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Title:
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Robust Bayes Analysis with Hierarchical Classes of Priors
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Author(s):
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Xiaomu Wang*+ and Mark Berliner
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Companies:
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Ohio State University and Ohio State University
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Keywords:
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robust bayes ;
contaminated prior ;
hierarchical priors ;
unimodal contamination ;
posterior measure
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Abstract:
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We do robust bayes and empirical bayes analysis with hierarchical classes of priors with the second stage prior having uncertainty being epsilon-contaminated.
This study is motivated by a situation that we want to study the robustness of a large number of parameters associated with big data. With those many parameters depending on a much smaller number of hyperparameters which have contaminated priors.
We derive ranges of posterior measures, such as posterior mean, variance, and probability of a set, for a family of priors with unimodal contaminations.
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Authors who are presenting talks have a * after their name.
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