Testing Equality of Several Correlation Matrices

In this article we show that the Kullbacks 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 chi-s...

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Main Authors: ARJUN K. GUPTA, BRUCE E. JOHNSON, DAYA K. NAGAR
Format: Article
Language:English
Published: Universidad Nacional de Colombia 2013-12-01
Series:Revista Colombiana de Estadística
Subjects:
Online Access:http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512013000200004&lng=en&tlng=en
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author ARJUN K. GUPTA
BRUCE E. JOHNSON
DAYA K. NAGAR
author_facet ARJUN K. GUPTA
BRUCE E. JOHNSON
DAYA K. NAGAR
author_sort ARJUN K. GUPTA
collection DOAJ
description In this article we show that the Kullbacks 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 chi-square variables by expanding L* in terms of other random variables and then inverting the expansion term by term. An example is also given to exhibit the procedure to be used when testing the equality of correlation matrices using the statistic L\ast.
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spelling doaj.art-1dc624e2a6404db09742f38564db29cd2022-12-21T18:21:05ZengUniversidad Nacional de ColombiaRevista Colombiana de Estadística0120-17512013-12-01362237258S0120-17512013000200004Testing Equality of Several Correlation MatricesARJUN K. GUPTA0BRUCE E. JOHNSON1DAYA K. NAGAR2Bowling Green State UniversityExperient Research GroupUniversidad de AntioquiaIn this article we show that the Kullbacks 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 chi-square variables by expanding L* in terms of other random variables and then inverting the expansion term by term. An example is also given to exhibit the procedure to be used when testing the equality of correlation matrices using the statistic L\ast.http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512013000200004&lng=en&tlng=endistribución asintótica nulamatriz de correlaciónmatriz de covarianzarazón de verosimilitud
spellingShingle ARJUN K. GUPTA
BRUCE E. JOHNSON
DAYA K. NAGAR
Testing Equality of Several Correlation Matrices
Revista Colombiana de Estadística
distribución asintótica nula
matriz de correlación
matriz de covarianza
razón de verosimilitud
title Testing Equality of Several Correlation Matrices
title_full Testing Equality of Several Correlation Matrices
title_fullStr Testing Equality of Several Correlation Matrices
title_full_unstemmed Testing Equality of Several Correlation Matrices
title_short Testing Equality of Several Correlation Matrices
title_sort testing equality of several correlation matrices
topic distribución asintótica nula
matriz de correlación
matriz de covarianza
razón de verosimilitud
url http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512013000200004&lng=en&tlng=en
work_keys_str_mv AT arjunkgupta testingequalityofseveralcorrelationmatrices
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AT dayaknagar testingequalityofseveralcorrelationmatrices