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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72247
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dc.contributor.authorCancho, Vicente G.-
dc.contributor.authorLouzada-Neto, Franscisco-
dc.contributor.authorBarriga, Gladys D.C.-
dc.date.accessioned2014-05-27T11:25:26Z-
dc.date.accessioned2016-10-25T18:33:27Z-
dc.date.available2014-05-27T11:25:26Z-
dc.date.available2016-10-25T18:33:27Z-
dc.date.issued2011-01-01-
dc.identifierhttp://dx.doi.org/10.1016/j.csda.2010.05.033-
dc.identifier.citationComputational Statistics and Data Analysis, v. 55, n. 1, p. 677-686, 2011.-
dc.identifier.issn0167-9473-
dc.identifier.urihttp://hdl.handle.net/11449/72247-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72247-
dc.description.abstractIn this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. © 2010 Elsevier B.V. All rights reserved.en
dc.format.extent677-686-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectComplementary risks-
dc.subjectEM algorithm-
dc.subjectExponential distribution-
dc.subjectPoisson distribution-
dc.subjectSurvival analysis-
dc.subjectAsymptotic covariance matrix-
dc.subjectData sets-
dc.subjectEM algorithms-
dc.subjectExponential distributions-
dc.subjectFailure rate functions-
dc.subjectFormal proofs-
dc.subjectIncreasing failure rate-
dc.subjectLife-time distribution-
dc.subjectMaximum likelihood estimate-
dc.subjectAlgorithms-
dc.subjectBioinformatics-
dc.subjectCovariance matrix-
dc.subjectDistribution functions-
dc.subjectFisher information matrix-
dc.subjectMaximum likelihood estimation-
dc.subjectProbability-
dc.subjectProbability density function-
dc.subjectRisk analysis-
dc.subjectRisk assessment-
dc.titleThe Poisson-exponential lifetime distributionen
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationDepartment of Applied Mathematics and Statistics Universidade de São Paulo-
dc.description.affiliationDepartment of Statistics Universidade de São Paulo-
dc.description.affiliationFEB Universidade Estadual Paulista-
dc.description.affiliationUnespFEB Universidade Estadual Paulista-
dc.identifier.doi10.1016/j.csda.2010.05.033-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofComputational Statistics and Data Analysis-
dc.identifier.scopus2-s2.0-77958039812-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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