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.

引用

页码：184 / 189

页数：6

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