A simultaneous testing of the mean vector and the covariance matrix among two populations for high-dimensional data

被引：4

作者：

Hyodo, Masashi ^{[1
]}

Nishiyama, Takahiro ^{[2
]}

机构：

[1] Osaka Prefecture Univ, Grad Sch Engn, Dept Math Sci, Naka Ku, 1-1 Gakuen Cho, Sakai, Osaka 5998531, Japan

[2] Senshu Univ, Dept Business Adm, Tama Ku, 2-1-1 Higashimita, Kawasaki, Kanagawa 2148580, Japan

来源：

TEST | 2018年 / 27卷 / 03期

基金：

日本学术振兴会;

关键词：

Simultaneous test; High-dimensional data analysis; Asymptotic distribution; Multivariate analysis; CLASSIFICATION;

D O I：

10.1007/s11749-017-0567-x

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 propose an L2-norm-based test for simultaneous testing of the mean vector and the covariance matrix under high-dimensional non-normal populations. To construct this, we derive an asymptotic distribution of a test statistic based on both differences mean vectors and covariance matrices. We also investigate the asymptotic sizes and powers of the proposed test using this result. Finally, we study the finite sample and dimension performance of this test via Monte Carlo simulations.

引用

页码：680 / 699

页数：20

共 50 条

[1] A simultaneous testing of the mean vector and the covariance matrix among two populations for high-dimensional data
Masashi Hyodo
Takahiro Nishiyama
[J]. TEST, 2018, 27 : 680 - 699
[2] Simultaneous testing of the mean vector and covariance matrix among k populations for high-dimensional data
Hyodo, Masashi
Nishiyama, Takahiro
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2021, 50 (03) : 663 - 684
[3] Simultaneous testing of mean vector and covariance matrix for high-dimensional data
Liu, Zhongying
Liu, Baisen
Zheng, Shurong
Shi, Ning-Zhong
[J]. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2017, 188 : 82 - 93
[4] A simultaneous test of mean vector and covariance matrix in high-dimensional settings
Cao, Mingxiang
Sun, Peng
Park, Junyong
[J]. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2021, 212 : 141 - 152
[5] On LR simultaneous test of high-dimensional mean vector and covariance matrix under non-normality
Niu, Zhenzhen
Hu, Jiang
Bai, Zhidong
Gao, Wei
[J]. STATISTICS & PROBABILITY LETTERS, 2019, 145 : 338 - 344
[6] Testing the Mean Matrix in High-Dimensional Transposable Data
Touloumis, Anestis
Tavare, Simon
Marioni, John C.
[J]. BIOMETRICS, 2015, 71 (01) : 157 - 166
[7] Testing identity of high-dimensional covariance matrix
Wang, Hao
Liu, Baisen
Shi, Ning-Zhong
Zheng, Shurong
[J]. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2018, 88 (13) : 2600 - 2611
[8] Mean test for high-dimensional data based on covariance matrix with linear structures
Wang, Guanpeng
Wang, Yuyuan
Cui, Hengjian
[J]. METRIKA, 2024,
[9] Testing high-dimensional mean vector with applications
Zhang, Jin-Ting
Zhou, Bu
Guo, Jia
[J]. STATISTICAL PAPERS, 2022, 63 (04) : 1105 - 1137
[10] A test for testing the equality of two covariance matrices for high-dimensional data
[J]. Chaipitak, S., 2013, Asian Network for Scientific Information (13)

← 1 2 3 4 5 →