Generalized subset selection procedures under heteroscedasticity
學年 90
學期 1
出版(發表)日期 2001-10-01
作品名稱 Generalized subset selection procedures under heteroscedasticity
作品名稱(其他語言)
著者 Chang, Yi-ping; 黃文濤; Huang, Wen-tao
單位 淡江大學經營決策學系
出版者 Elsevier
著錄名稱、卷期、頁數 Journal of Statistical Planning and Inference 98(1-2), pp.239-258
摘要 In this paper, we propose and study a generalized subset selection procedure for selecting the best population. Based on the concept of generalized subset selection procedure, some selection procedures for normal populations are proposed and studied. They are used, respectively, to select the best population (populations) with respect to the largest mean, the largest pth quantile and the largest signal-to-noise ratio. For the case of common unknown variance, the proposed generalized subset selection procedure for selecting the largest mean becomes exactly the same as that has been given in Hsu (in: T.J. Santner, A.C. Tamhane (Eds.), Design of Experiments: Ranking and Selection, Marcel Dekker, New York, 1984, pp. 179–198). A Monte Carlo study shows that the proposed generalized subset selection procedures behave satisfactorily. An illustration of a set of real data is also given.
關鍵字 Ranking and selection;Generalized subset selection procedure;Generalized probability of correct selection;Quantile;Signal-to-noise ratio 1. Introduction
語言 en
ISSN 0378-3758
期刊性質 國內
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產學合作
通訊作者
審稿制度
國別 TWN
公開徵稿
出版型式 ,電子版
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