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On matrix-variate Birnbaum–Saunders distributions and their estimation and application

dc.creatorSánchez L.spa
dc.creatorLeiva V.spa
dc.creatorCaro-Lopera F.J.spa
dc.creatorCysneiros F.J.A.spa
dc.date.accessioned2015-12-17T19:27:46Z
dc.date.available2015-12-17T19:27:46Z
dc.date.created2015
dc.identifier.issn1030752
dc.identifier.urihttp://hdl.handle.net/11407/1554
dc.descriptionDiverse phenomena from the real-world can be modeled using random matrices, allowing matrix-variate distributions to be considered. The normal distribution is often employed in this modeling, but usually the mentioned random matrices do not follow such a distribution. An asymmetric non-normal model that is receiving considerable attention due to its good properties is the Birnbaum–Saunders (BS) distribution. We propose a statistical methodology based on matrix-variate BS distributions. This methodology is implemented in the statistical software R. A simulation study is conducted to evaluate its performance. Finally, an application with real-world matrix-variate data is carried out to illustrate its potentiality and suitability.eng
dc.language.isoeng
dc.publisherBrazilian Statistical Associationspa
dc.relation.isversionofhttps://projecteuclid.org/euclid.bjps/1442513447spa
dc.sourceScopusspa
dc.titleOn matrix-variate Birnbaum–Saunders distributions and their estimation and applicationeng
dc.typeArticleeng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.contributor.affiliationInstituto de Estadística, Universidad de Valparaíso, Chilespa
dc.contributor.affiliationUniversidad Adolfo Ibáñez, Chilespa
dc.contributor.affiliationDepartamento de Ciencias Básicas, Universidad de Medellín, Colombiaspa
dc.contributor.affiliationDepartamento de Estatística, Universidade Federal de Pernambuco, Brazilspa
dc.identifier.doi10.1214/14-BJPS247
dc.subject.keywordComputer languageeng
dc.subject.keywordData analysiseng
dc.subject.keywordElliptically contoured distributioneng
dc.subject.keywordMaximum likelihood estimatoreng
dc.subject.keywordMonte Carlo methodeng
dc.subject.keywordShape theoryeng
dc.relation.ispartofenBrazilian Journal of Probability and Statistics, 2015, volume 29, issue 4, pp 790-812eng
dc.type.driverinfo:eu-repo/semantics/article


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