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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41452

    Title: A robust asymptotically optimal procedure in Bayes sequential estimation
    Other Titles: 具有穩健漸進最優法則之貝氏序列估計
    Authors: 黃連成;Hwang, Leng-cheng
    Contributors: 淡江大學數學學系
    Keywords: Asymptotically Bayes;Bayes sequential estimation;Bayes risk;optimal sequential procedure;prior distributions
    Date: 1999-07-01
    Issue Date: 2010-01-28 07:36:02 (UTC+8)
    Publisher: Statistica Sinica
    Abstract: The problem of sequential estimation of the mean, subject to the loss defined as the sum of squared error loss and sampling costs, is considered within the Bayesian framework. It is shown that the sequential procedure, as proposed by Chow and Yu (1981) in classical non-Bayesian sequential estimation, is, in fact, asymptotically Bayes for a large class of prior distributions. The proposed procedure, without using any auxiliary data, is robust in the sense that it does not depend on the distribution of outcome variables and the prior.
    Relation: Statistica Sinica 9(3), pp.893-904
    DOI: 10.1007/s00184-009-0293-9
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

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