The FGM bivariate lifetime copula model: a bayesian approach

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dc.contributor.authorSuzuki. A. K.
dc.contributor.authorLouzada-Neto Neto, Franscisco
dc.contributor.authorCancho, Vicente G.
dc.contributor.authorBarriga, Gladys Dorotea Cacsire [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2016-03-02T12:58:30Z
dc.date.available2016-03-02T12:58:30Z
dc.date.issued2011
dc.description.abstractIn this paper, we propose a bivariate distribution for the bivariate survival times based on Farlie-Gumbel-Morgenstern copula to model the dependence on a bivariate survival data. The proposed model allows for the presence of censored data and covariates. For inferential purpose a Bayesian approach via Markov Chain Monte Carlo (MCMC) is considered. Further, some discussions on the model selection criteria are given. In order to examine outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. The newly developed procedures are illustrated via a simulation study and a real dataset.en
dc.description.affiliationUniversidade Estadual Paulista Júlio de Mesquita Filho, Departamento de Engenharia de Produção, Faculdade de Engenharia de Bauru, Bauru, Av. Eng. Luiz Edmundo C. Coube 14-01, CEP 17033-360, SP, Brasil
dc.description.affiliationUnespUniversidade Estadual Paulista Júlio de Mesquita Filho, Departamento de Engenharia de Produção, Faculdade de Engenharia de Bauru, Bauru, Av. Eng. Luiz Edmundo C. Coube 14-01, CEP 17033-360, SP, Brasil
dc.format.extent55-76
dc.identifierhttp://www.pphmj.com/abstract/5794.htm
dc.identifier.citationAdvances and Applications in Statistics, v. 21, p. 55-76, 2011.
dc.identifier.issn0972-3617
dc.identifier.lattes3503233632044163
dc.identifier.lattes5267593860042306
dc.identifier.urihttp://hdl.handle.net/11449/134820
dc.language.isoeng
dc.relation.ispartofAdvances and Applications in Statistics
dc.rights.accessRightsAcesso restrito
dc.sourceCurrículo Lattes
dc.subjectCase deletion influence diagnosticsen
dc.subjectCopula modelingen
dc.subjectSurvival dataen
dc.subjectBayesian approachen
dc.titleThe FGM bivariate lifetime copula model: a bayesian approachen
dc.typeArtigo
unesp.author.lattes3503233632044163
unesp.author.lattes5267593860042306
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Engenharia, Baurupt
unesp.departmentEngenharia de Produçãopt

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