Asymptotic power of likelihood ratio tests for high dimensional data

被引：4
|
作者：
Wang, Cheng [1 ,2 ]
机构：
[1] Univ Sci & Technol China, Dept Stat & Finance, Hefei 230026, Anhui, Peoples R China
[2] Hong Kong Baptist Univ, Dept Math, Kowloon Tong, Hong Kong, Peoples R China
来源：
STATISTICS & PROBABILITY LETTERS | 2014年 / 88卷
关键词：
Covariance matrix; High dimensional data; Identity test; Likelihood ratio test; Power; Stein's loss; COVARIANCE MATRICES; NORMAL-DISTRIBUTIONS; RMT;
D O I：
10.1016/j.spl.2014.02.010
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：
This paper studies the asymptotic power of the likelihood ratio test (LRT) for the identity test when the dimension p is large compared to the sample size n. The asymptotic distribution under local alternatives is derived and a simulation study is carried out to compare LRT with other tests. All these studies show that LRT is a powerful test to detect small eigenvalues. (C) 2014 Elsevier B.V. All rights reserved.
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页码：184 / 189
页数：6
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