Single-stage sampling procedure of the t best populations under heteroscedasticity

被引：4

作者：

Wen, Miin-Jye ^{[1
]}

Huang, Li-Ching ^{[2
]}

Zhong, Junjiang ^{[1
,3
]}

机构：

[1] Natl Cheng Kung Univ, Dept Stat, 1 Univ Rd, Tainan 70101, Taiwan

[2] Vanderbilt Univ, Ctr Quantitat Sci, 221 Kirkland Hall, Nashville, TN 37235 USA

[3] Xiamen Univ Technol, Sch Appl Math, Xiamen, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2017年 / 46卷 / 18期

关键词：

Normal distribution; t distribution; unknown and unequal variance; INTERVAL ESTIMATION; BEST POPULATIONS; SELECTION; VARIANCES;

D O I：

10.1080/03610926.2016.1206935

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Given k(>= 3) independent normal populations with unknown means and unknown and unequal variances, a single-stage sampling procedure to select the best t out of k populations is proposed and the procedure is completely independent of the unknown means and the unknown variances. For various combinations of k and probability requirement, tables of procedure parameters are provided for practitioners.

引用

页码：9265 / 9273

页数：9

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