A Procedure of Selecting All Good Populations Under Heteroscedasticity

doi:10.1080/03610910802395661

淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 > Item 987654321/69149

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題名:	A Procedure of Selecting All Good Populations Under Heteroscedasticity
作者:	Wu, Shu-Fei;Yu, Yuh-Ru
貢獻者:	淡江大學統計學系
關鍵詞:	One-stage;Percentage points;Percentage points;Select all good populations whose mean does not fall too much below the best one;Simultaneous inference;Student t distribution;Two-stage
日期:	2008-10
上傳時間:	2013-05-31 11:38:12 (UTC+8)
出版者:	Philadelphia: Taylor & Francis Inc.
摘要:	Suppose that k normal populations with means μ1,…, μ k and variances are considered. When variances are unknown and equal, Lam (1986) proposed a procedure to select all good populations, where a population is good if μ i ≥ μ[k] − ϵ and μ[k] is the largest normal mean among k normal means. When variances are unknown and possibly unequal, a two-stage procedure selecting all good populations such that the probability of correct selection being at least a pre-specified value of P* is proposed. Without decreasing the probability of correct selection, the confidence interval of pairwise differences of all means to the largest normal mean is presented with the selection procedure. When the additional samples at the second stage could be costly, a data-analysis one-stage procedure selecting all good population is proposed. At last, one real-life example is given to illustrate all procedures.
關聯:	Communications in Statistics - Simulation and Computation 38(1), pp.46-57
DOI:	10.1080/03610910802395661
顯示於類別:	[統計學系暨研究所] 期刊論文

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