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. © 2007 Elsevier B.V. All rights reserved
A simple statistic is proposed for testing the complete independence of random variables having a mu...
For the test of sphericity, Ledoit and Wolf [Ann. Statist. 30 (2002) 1081-1102] proposed a statistic...
AbstractFor the test of sphericity, Ledoit and Wolf [Ann. Statist. 30 (2002) 1081–1102] proposed a s...
A simple statistic is proposed for testing the equality of the covariance matrices of several multiv...
In this paper, tests are developed for testing certain hypotheses on the covari-ance matrix Σ, when ...
A test for proportionality of two covariance matrices with large dimension, possibly larger than the...
AbstractFor normally distributed data from the k populations with m×m covariance matrices Σ1,…,Σk, w...
Test statistics for sphericity and identity of the covariance matrix are presented, when the data ar...
summary:A test statistic for homogeneity of two or more covariance matrices is presented when the di...
In this paper we proposed a new statistical test for testing the covariance matrix in one population...
A statistic is proposed for testing the equality of the mean vectors in a one-way multivariate analy...
This article considers testing equality of two population covariance matrices when the data dimensio...
A statistic is proposed for testing the equality of the mean vectors in a one-way multivariate analy...
This paper analyzes whether standard covariance matrix tests work when dimensionality is large, and ...
For the test of sphericity, Ledoit and Wolf [Ann. Statist. 30 (2002) 1081-1102] proposed a statistic...
A simple statistic is proposed for testing the complete independence of random variables having a mu...
For the test of sphericity, Ledoit and Wolf [Ann. Statist. 30 (2002) 1081-1102] proposed a statistic...
AbstractFor the test of sphericity, Ledoit and Wolf [Ann. Statist. 30 (2002) 1081–1102] proposed a s...
A simple statistic is proposed for testing the equality of the covariance matrices of several multiv...
In this paper, tests are developed for testing certain hypotheses on the covari-ance matrix Σ, when ...
A test for proportionality of two covariance matrices with large dimension, possibly larger than the...
AbstractFor normally distributed data from the k populations with m×m covariance matrices Σ1,…,Σk, w...
Test statistics for sphericity and identity of the covariance matrix are presented, when the data ar...
summary:A test statistic for homogeneity of two or more covariance matrices is presented when the di...
In this paper we proposed a new statistical test for testing the covariance matrix in one population...
A statistic is proposed for testing the equality of the mean vectors in a one-way multivariate analy...
This article considers testing equality of two population covariance matrices when the data dimensio...
A statistic is proposed for testing the equality of the mean vectors in a one-way multivariate analy...
This paper analyzes whether standard covariance matrix tests work when dimensionality is large, and ...
For the test of sphericity, Ledoit and Wolf [Ann. Statist. 30 (2002) 1081-1102] proposed a statistic...
A simple statistic is proposed for testing the complete independence of random variables having a mu...
For the test of sphericity, Ledoit and Wolf [Ann. Statist. 30 (2002) 1081-1102] proposed a statistic...
AbstractFor the test of sphericity, Ledoit and Wolf [Ann. Statist. 30 (2002) 1081–1102] proposed a s...