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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41445


    Title: A Bayesian approach to sequential estimation without using the prior information
    Other Titles: 無母數經驗貝氏方法之序列估計
    Authors: 黃連成;Hwang, Leng-cheng
    Contributors: 淡江大學數學學系
    Keywords: asymptotically Bayes;asymptotically non-deficient;asymptotically pointwise optimal;empirical Bayes
    Date: 1997-11
    Issue Date: 2010-01-28 07:35:16 (UTC+8)
    Publisher: Taylor & Francis
    Abstract: The problem of Bayes sequential point estimation without using the prior information is considered. Two sequential procedures of the type of Bickel and Yahav (1967, 1968), for the scale exponential and location normal families respectively, are proposed. It is shown in the present paper that the proposed procedures are asymptotically pointwise optimal (A.P.O.) in the sense of Bickel and Yahav (1967) and the second order approximation of the Bayes risk is established for a large class of prior distributions.
    Relation: Sequential Analysis 16(4), pp.319-343
    DOI: 10.1080/07474949708836391
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

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