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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/20685

    Title: Multiple Comparision Procedures with the Average for Exponential Location Parameters When Sample Size are Unequel
    Other Titles: 指數分配位置參數與平均比較的多重比較程序當樣本大小不等時
    Authors: Wu, Shu-fei;Chen, Hubert J.
    Contributors: 淡江大學統計學系
    Date: 1997-12-01
    Issue Date: 2009-11-30 12:56:30 (UTC+8)
    Publisher: Taipei : Graduate Institute of Management Science, Tamkang University
    Abstract: In this article, multiple comparison procedures with the average of exponential location parameters when sample sizes are equal are under investigation. A subset selection approach and a simultaneous confidence interval approach with minimum expected length are considered for exponential distributions with common known or unknown scale parameter. These procedures will have broad applications in selecting a subset which includes all better-than-the-average treatments in experimental design and/or in identifying all better-than-the-average, worse-than-the-average and not-much-difference-from-the-average products in agriculture, business, manufacturing and other industries. Some numerical approximation approaches using Bonferroni inequality are proposed in this article. Statistical tables to implement these procedures for the case of equal sample size are provided for use in practice. A simulation result indicates that Bonferroni approximation performs better than the confidence interval with equal-tail probability. Computer software programs for calculating the percentage points and for simulation are available from the authors.
    Relation: International Journal of Information and Management Sciences 8(4), pp.41-54
    DOI: 10.1016/S0167-9473(97)00044-3
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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