Empirical bayes procedures for selecting the best population with multiple criteria

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Title:	Empirical bayes procedures for selecting the best population with multiple criteria
Authors:	Huang, Wen Tao;Lai, Yao Tsung
Contributors:	淡江大學經營決策學系
Keywords:	Best population;multiple criteria;asymptotical optimality;empirical Bayes rule;convergence rate
Date:	1999-01
Issue Date:	2013-05-31 11:36:02 (UTC+8)
Publisher:	Norwell: Kluwer Academic Publishers
Abstract:	Consider k (k ≥ 2) populations whose mean θ i and variance σ i 2 are all unknown. For given control values θ0 and σ 0 2, we are interested in selecting some population whose mean is the largest in the qualified subset in which each mean is larger than or equal to θ0 and whose variance is less than or equal to σ 0 2. In this paper we focus on the normal populations in details. However, the analogous method can be applied for the cases other than normal in some situations. A Bayes approach is set up and an empirical Bayes procedure is proposed which has been shown to be asymptotically optimal with convergence rate of order O(ln2 n/n). A simulation study is carried out for the performance of the proposed procedure and it is found satisfactory.
Relation:	Annals of the Institute of Statistical Mathematics 51(2), pp.281-299
DOI:	10.1023/A:1003858124810
Appears in Collections:	[Department of Management Sciences] Journal Article

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