Title

A test for the equality of covariance matrices when the dimension is large relative to the sample sizes

Authors

Authors

J. R. Schott

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Comput. Stat. Data Anal.

Keywords

equal covariance matrices; high-dimensional data; singular sample; covariance matrix; GENE-EXPRESSION; Computer Science, Interdisciplinary Applications; Statistics &; Probability

Abstract

A simple statistic is proposed for testing the equality of the covariance matrices of several multivariate normal populations. The asymptotic null distribution of this statistic, as both the sample sizes and the number of variables go to infinity, is shown to be normal. Consequently, this test can be used when the number of variables is not small relative to the sample sizes and, in particular, even when the number of variables exceeds the sample sizes. The finite sample size performance of the normal approximation for this method is evaluated in a simulation study. (c) 2007 Elsevier B.V. All rights reserved.

Journal Title

Computational Statistics & Data Analysis

Volume

51

Issue/Number

12

Publication Date

1-1-2007

Document Type

Article

Language

English

First Page

6535

Last Page

6542

WOS Identifier

WOS:000249316000083

ISSN

0167-9473

Share

COinS