Testing Several Correlation Matrices Using Robust Approach

Testing Equality of Several Correlation Matrices Prueba de Igualdad de Varias Matrices de Correlación

In this article we show that the Kullback’s statistic for testing equality of several correlation matrices may be considered a modified likelihood ratio statistic when sampling from multivariate normal populations. We derive the asymptotic null distribution of L∗ in series involving independent chisquare variables by expanding L∗ in terms of other random variables and then inverting the expansi...

A multiple testing approach to the regularisation of large sample correlation matrices

This paper proposes a regularisation method for the estimation of large covariance matrices that uses insights from the multiple testing (MT ) literature. The approach tests the statistical signi…cance of individual pair-wise correlations and sets to zero those elements that are not statistically signi…cant, taking account of the multiple testing nature of the problem. By using the inverse of t...

Supplementary appendix to: A multiple testing approach to the regularisation of large sample correlation matrices

An Extreme-Value Approach for Testing the Equality of Large U-Statistic Based Correlation Matrices

An Extreme-Value Approach for Testing the Equality of Large U-Statistic Based Correlation Matrices CHENG ZHOU FANG HAN XIN-SHENG ZHANG1,† HAN LIU3,‡ Department of Statistics, Management School, Fudan University, Shanghai, China. E-mail: [email protected]; †[email protected] Department of Statistics, University of Washington, Seattle, WA 98195, USA. E-mail: [email protected] Department of Op...

A robust testing procedure for the equality of covariance matrices

In classical statistics the likelihood ratio statistic used in testing hypotheses about covariance matrices does not have a closed form distribution, but asymptotically under strong normality assumptions is a function of the 2-distribution. This distributional approximation totally fails if the normality assumption is not completely met. In this paper we will present multivariate robust testing...