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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/64881

    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:[管理科學學系暨研究所] 期刊論文

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