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    Title: Multiple comparison procedures with the average for exponential location parameters
    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相等時
    Authors: 吳淑妃;Wu, Shu-fei;Chen, Hubert J.
    Contributors: 淡江大學統計學系
    Keywords: Subset selection;Simultaneous confidence interval;Bonferroni inequality;Monte Carlo technique
    Date: 1998-02-06
    Issue Date: 2009-11-30 12:54:54 (UTC+8)
    Publisher: Elsevier
    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: Computational Statistics and Data Analysis 26(4), pp.461-484
    DOI: 10.1016/S0167-9473(97)00044-3
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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