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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/66896

    Title: Selecting the Best Population: An Empirical Bayes Approach
    Authors: Huang, Wen-Tao;Lai, Yao-Tsung
    Contributors: 淡江大學經營決策學系
    Keywords: Selection;multiple criteria;empirical Bayes;asymptotic optimality
    Date: 2004-06
    Issue Date: 2013-05-01 18:48:26 (UTC+8)
    Publisher: 臺北縣淡水鎮 : 淡江大學
    Abstract: Consider k(k~2) populations whose meanei and variance a} are all unknown. For
    given control values θand σ²'";, 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 toθ
    and whose variance is less than or equal to σ²; . In this paper we focus on the case of
    normal populations. However, the analogous method can be applied for the cases other
    than normal. A Bayes approach is set up and an empirical Bayes procedure is proposed
    which has been shown to be asymptotically optimal.
    Relation: 2004年兩岸管理科學暨經營決策學術研討會論文集, pp.43-52
    Appears in Collections:[管理科學學系暨研究所] 會議論文

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