This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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25
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Type:
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Topic Contributed
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Date/Time:
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Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #307926 |
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Title:
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Bayesian Thresholding Rules
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Author(s):
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Linda Zhao*+
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Companies:
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University of Pennsylvania
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Address:
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, , ,
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Keywords:
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Normal means ;
Sparsity ;
Thresholding rules ;
Empirical Bayes
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Abstract:
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We consider the problem of estimating independent normal means in a sparse scenario. Empirical Bayes approaches are developed. Two methods will be discussed. The first one employs a mixture loss function having $L_p$ loss plus a $0-1$ loss function. The Bayes procedures under this loss are explicitly given as thresholding rules and easy to compute. The second method uses nonparametric priors. Some simulations indicate very good performance of the methods.
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Authors who are presenting talks have a * after their name.
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