Ridgelized Hotelling's T2 test on mean vectors of large dimension

被引：1
|
作者：
Ha, Gao-Fan [1 ,2 ]
Zhang, Qiuyan [3 ]
Bai, Zhidong [1 ,2 ]
Wang, You-Gan [4 ]
机构：
[1] Northeast Normal Univ, KLASMOE, Changchun, Jilin, Peoples R China
[2] Northeast Normal Univ, Sch Math & Stat, Changchun, Jilin, Peoples R China
[3] Capital Univ Econ & Business, Sch Stat, Beijing, Peoples R China
[4] Queensland Univ Technol, Sch Math & Sci, Brisbane, Qld, Australia
来源：
RANDOM MATRICES-THEORY AND APPLICATIONS | 2022年 / 11卷 / 01期
基金：
澳大利亚研究理事会;
关键词：
Random matrices; Hotelling's T-2 test; four moment theorem; central limit theorem; LIMITING SPECTRAL DISTRIBUTION; COVARIANCE MATRICES; EIGENVALUES; STATISTICS; THEOREM; CLT;
D O I：
10.1142/S2010326322500113
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In this paper, a ridgelized Hotelling's T-2 test is developed for a hypothesis on a large-dimensional mean vector under certain moment conditions. It generalizes the main result of Chen et al. [A regularized Hotelling's t(2) test for pathway analysis in proteomic studies, J. Am. Stat. Assoc. 106(496) (2011) 1345-1360.] by relaxing their Gaussian assumption. This is achieved by establishing an exact four-moment theorem that is a simplified version of Tao and Vu's [Random matrices: universality of local statistics of eigenvalues, Ann. Probab. 40(3) (2012) 1285-1315] work. Simulation results demonstrate the superiority of the proposed test over the traditional Hotelling's T2 test and its several extensions in high-dimensional situations.
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页数：29
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