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dc.creatorCaro-Lopera F.J.spa
dc.creatorDíaz-García J.A.spa
dc.date.accessioned2016-06-23T14:01:38Z
dc.date.available2016-06-23T14:01:38Z
dc.date.created2015
dc.identifier.issn2331888
dc.identifier.urihttp://hdl.handle.net/11407/2283
dc.description.abstractSome matrix representations of diverse diagonal arrays are studied in this work; the results allow new definitions of classes of elliptical distributions indexed by kernels mixing Hadamard and usual products. A number of applications are derived in the setting of prior densities from the Bayesian multivariate regression model and families of non-elliptical distributions, such as the matrix multivariate generalized Birnbaum–Saunders density. The philosophy of the research about matrix representations of quadratic and inverse quadratic forms can be extended as a methodology for exploring possible new applications in non-standard distributions, matrix transformations and inference.eng
dc.language.isoeng
dc.publisherTaylor and Francis Ltd.spa
dc.relation.isversionofhttp://www.tandfonline.com/doi/abs/10.1080/02331888.2015.1104312?journalCode=gsta20spa
dc.sourceScopusspa
dc.titleDiagonalization matrix and its application in distribution theoryspa
dc.typeArticle in Presseng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.contributor.affiliationDepartment of Basic Sciences, Universidad de Medellín, Carrera 87 No.30-65, of. 5-103, Medellín, Colombiaspa
dc.contributor.affiliationUniversidad Autónoma Agraria Antonio Narro, Calzada Antonio Narro 1923, Col. Buenavista, 25315 Saltillo, Coahuila, Méxicospa
dc.identifier.doi10.1080/02331888.2015.1104312
dc.relation.ispartofenStatistics 24 October 2015, 11peng
dc.type.driverinfo:eu-repo/semantics/article


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