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dc.contributor.authorMoala, Fernando Antonio [UNESP]
dc.contributor.authorRamos, Pedro Luiz [UNESP]
dc.contributor.authorAchcar, Jorge Alberto
dc.date.accessioned2014-12-03T13:09:11Z
dc.date.available2014-12-03T13:09:11Z
dc.date.issued2013-12-01
dc.identifierhttp://revistas.unal.edu.co/index.php/estad/article/view/44351
dc.identifier.citationRevista Colombiana de Estadistica. Bogota Dc: Univ Nac Colombia, Dept Estadistica, v. 36, n. 2, p. 321-338, 2013.
dc.identifier.issn0120-1751
dc.identifier.urihttp://hdl.handle.net/11449/112051
dc.description.abstractIn this paper distinct prior distributions are derived in a Bayesian inference of the two-parameters Gamma distribution. Noniformative priors, such as Jeffreys, reference, MDIP, Tibshirani and an innovative prior based on the copula approach are investigated. We show that the maximal data information prior provides in an improper posterior density and that the different choices of the parameter of interest lead to different reference priors in this case. Based on the simulated data sets, the Bayesian estimates and credible intervals for the unknown parameters are computed and the performance of the prior distributions are evaluated. The Bayesian analysis is conducted using the Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions under the above priors.en
dc.format.extent321-338
dc.language.isoeng
dc.publisherUniv Nac Colombia, Dept Estadistica
dc.relation.ispartofRevista Colombiana De Estadistica
dc.sourceWeb of Science
dc.subjectGamma distributionen
dc.subjectnoninformative prioren
dc.subjectcopulaen
dc.subjectconjugateen
dc.subjectJeffreys prioren
dc.subjectreferenceen
dc.subjectMDIPen
dc.subjectorthogonalen
dc.subjectMCMCen
dc.titleBayesian inference for two-parameter gamma distribution assuming different noninformative priorsen
dc.typeArtigo
dcterms.rightsHolderUniv Nac Colombia, Dept Estadistica
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.description.affiliationUniv Estadual Paulista, Fac Ciencia & Tecnol, Dept Estadist, Presidente Prudente, Brazil
dc.description.affiliationUniv Sao Paulo, Fac Med Ribeirao Preto, Dept Social Med, BR-14049 Ribeirao Preto, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Fac Ciencia & Tecnol, Dept Estadist, Presidente Prudente, Brazil
dc.identifier.wosWOS:000331380600009
dc.rights.accessRightsAcesso aberto
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências e Tecnologia, Presidente Prudentept
dc.identifier.fileWOS000331380600009.pdf
dc.identifier.lattes1621269552366697
unesp.author.lattes1621269552366697
dc.relation.ispartofsjr0,361
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