Hypothesis testing for the identity of high-dimensional covariance matrices

被引：1
|
作者：
Qian, Manling [1 ]
Tao, Li [1 ]
Li, Erqian [1 ]
Tian, Maozai [1 ,2 ,3 ]
机构：
[1] Renmin Univ China, Ctr Appl Stat, Sch Stat, Beijing 100872, Peoples R China
[2] Xinjiang Univ Finance & Econ, Sch Stat & Informat, Urumqi 830012, Xinjiang, Peoples R China
[3] Lanzhou Univ Finance & Econ, Sch Stat, Lanzhou 730101, Gansu, Peoples R China
来源：
STATISTICS & PROBABILITY LETTERS | 2020年 / 161卷
关键词：
Covariance matrix; High-dimensional data; Hypothesis testing; Identity matrix; SPHERICITY;
D O I：
10.1016/j.spl.2020.108699
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：
A new test statistic is proposed by utilizing the eigenvalues of the sample covariance matrix for the identity test. Under some general assumptions, asymptotic distributions of the proposed test statistic T and tests proposed in previous literature (denoted as T-s, T-1,T-2) are given. Simulations are also conducted to evaluate their performance in a finite sample. (C) 2020 Elsevier B.V. All rights reserved.
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页数：12
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