Matrix-variate distribution theory under elliptical models-4: Joint distribution of latent roots of covariance matrix and the largest and smallest latent roots

dc.contributor.affiliationUniversidad de Medellín, Department of Basic Sciences, Carrera 87 No. 30-65, of. 5-103, Medellín, Colombiaspa
dc.contributor.affiliationCIMAT A. C., Department of Probability and Statistics, Callejón de Jalisco s/n, Mineral de Valenciana, Guanajuato, Guanajuato, Mexicospa
dc.contributor.affiliationMcMaster University, Department of Mathematics and Statistics, Hamilton, ON, Canadaspa
dc.contributor.authorCaro-Lopera F.J.
dc.contributor.authorGonzález Farías G.
dc.contributor.authorBalakrishnan N.
dc.date.accessioned2016-06-23T14:01:37Z
dc.date.available2016-06-23T14:01:37Z
dc.date.issued2016
dc.description.abstractIn this work, we derive the joint distribution of the latent roots of a sample covariance matrix under elliptical models. We then obtain the distributions of the largest and smallest latent roots. In the process of these derivations, we also correct some results present in the literature.eng
dc.identifier.doi10.1016/j.jmva.2015.12.012
dc.identifier.issn0047259X
dc.identifier.urihttp://hdl.handle.net/11407/2280
dc.language.isoeng
dc.publisherAcademic Press Inc.spa
dc.relation.ispartofJournal of Multivariate Analysis Volume 145, March 2016, Pages 224–235eng
dc.relation.isversionofhttp://www.sciencedirect.com/science/article/pii/S0047259X15003383
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceScopusspa
dc.titleMatrix-variate distribution theory under elliptical models-4: Joint distribution of latent roots of covariance matrix and the largest and smallest latent rootsspa
dc.typeArticle
dc.type.driverinfo:eu-repo/semantics/article

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