On testing the equality of high dimensional mean vectors with unequal covariance matrices

被引:39
|
作者
Hu, Jiang [1 ,2 ]
Bai, Zhidong [1 ,2 ]
Wang, Chen [3 ]
Wang, Wei [1 ,2 ]
机构
[1] Northeast Normal Univ, KLASMOE, Changchun 130024, Jilin, Peoples R China
[2] Northeast Normal Univ, Sch Math & Stat, Changchun 130024, Jilin, Peoples R China
[3] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117546, Singapore
关键词
High-dimensional data; Hypothesis testing; MANOVA; LIKELIHOOD RATIO TESTS; FEWER OBSERVATIONS; MULTIVARIATE-ANALYSIS; NORMAL-DISTRIBUTIONS; NONNORMALITY; VARIANCE; MANOVA;
D O I
10.1007/s10463-015-0543-8
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, we focus on the problem of testing the equality of several high dimensional mean vectors with unequal covariance matrices. This is one of the most important problems in multivariate statistical analysis and there have been various tests proposed in the literature. Motivated by Bai and Saranadasa (Stat Sin 6:311-329, 1996) and Chen and Qin (Ann Stat 38:808-835, 2010), we introduce a test statistic and derive the asymptotic distributions under the null and the alternative hypothesis. In addition, it is compared with a test statistic recently proposed by Srivastava and Kubokawa (J Multivar Anal 115:204-216, 2013). It is shown that our test statistic performs better especially in the large dimensional case.
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页码:365 / 387
页数:23
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