Abstract Details
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Activity Number:
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431
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #307682 |
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Title:
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Regularized Empirical Bayes Estimation of Normal Means
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Author(s):
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Xiaoya Pang*+ and Wenhua Jiang
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Companies:
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Soochow University and Soochow University
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Keywords:
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nonparametric empirical Bayes ;
compound estimation ;
isotonic regression ;
shrinkage estimator ;
threshold estimator
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Abstract:
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In this paper, we improve the normal kernel methods for the estimation of a vector of normal mean of Brown and Greenshtein (2009) by implementing the monotone regularization procedure of Jiang(2013). We prove an oracle inequality for the regret of proposed estimator compared with the optimal Bayes risk. We demonstrate the performance of the estimator in simulation experiments with sparse and normal setups. It turns out that the proposed procedure indeed improves over its kernel version.
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Authors who are presenting talks have a * after their name.
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