淡江大學機構典藏:Item 987654321/50415
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    题名: Selecting the best process based on capability index via empirical Bayes approach
    作者: 黃文濤;Huang, Wen-tao;Lai, Yao-tsung
    贡献者: 淡江大學經營決策學系
    关键词: Asymptotic optimality;Empirical Bayes rule;Process capability index;Ranking and selection;Cpw
    日期: 2009-06-01
    上传时间: 2010-08-09 17:05:14 (UTC+8)
    出版者: Taylor & Francis
    摘要: Consider k (k ≥ 2) manufacturing processes whose mean θi, variance and process capability index Cpw (i), i = 1,…, k, are all unknown. For two given control values Cpw (0) and , we are interested in selecting some process whose capability index is no less than Cpw (0) and is the largest in the qualified subset in which each process variance is no larger than . Under a Bayes framework, we consider the normally distributed manufacturing processes taking normal-gamma as its conjugate prior. A Bayes approach is set up and an empirical Bayes procedure is proposed which has been shown to be asymptotically optimal. A simulation study is carried out for the performance of the proposed procedure and it is found practically useful.
    關聯: Communications in Statistics : Theory and Methods 38(10), pp.1576-1588
    DOI: 10.1080/03610920802715024
    显示于类别:[管理科學學系暨研究所] 期刊論文

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