Optimal confidence interval for the largest normal mean under heteroscedasticity

被引：6

作者：

Chen, Hubert J.

Wen, Miin-Jye ^{[1
]}

机构：

[1] Natl Cheng Kung Univ, Dept Stat, Tainan 701, Taiwan

[2] Natl Cheng Kung Univ, Dept Stat & Accountancy, Tainan 701, Taiwan

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2006年 / 51卷 / 02期

关键词：

student t distribution; two-stage; one-stage; percentage points; least favorable configuration;

D O I：

10.1016/j.csda.2005.10.004

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A two-stage sampling procedure for obtaining an optimal confidence interval for the largest or smallest mean of k independent normal populations is proposed, where the population variances are unknown and possibly unequal. The optimal confidence interval is obtained by maximizing the coverage probability with a fixed width at a least favorable configuration of means. Then, the sample sizes can be determined by this procedure. It has been shown that the optimal interval is globally optimal over all possible choices of symmetric and asymmetric intervals. In situations where the two-stage sampling procedure cannot be completely carried through, a one-stage sampling procedure can be implemented, and their relationship is discussed. A numerical example to demonstrate the use of these sampling procedures is given. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：982 / 1001

页数：20

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