Combining univariate tests for multivariate location problem

被引：2

作者：

Wu, Samuel S. ^{[1
]}

机构：

[1] Univ Florida, Div Biostat, Gainesville, FL 32611 USA

[2] Malcom Randall VA Med Ctr, Gainesville, FL USA

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2006年 / 35卷 / 08期

关键词：

Bahadur approximate efficiency; Fisher's method of combining tests; multivariate location problem; nonparametric tests;

D O I：

10.1080/03610920600694496

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：

In this article, three methods of combining dependent univariate tests are studied. The Bahadur approximate efficiencies are derived under the asymptotic normal assumption. These procedures are applied to the multivariate location problem and compared with two Hotelling-type tests. A Monte Carlo study indicates that in certain cases the powers of the combination methods are much better than Hotelling's T-2 and other multivariate nonparametric tests.

引用

页码：1483 / 1494

页数：12

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