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dc.contributor.authorSuzuki, Adriano K.
dc.contributor.authorBarriga, Gladys D. C. [UNESP]
dc.contributor.authorLouzada, Francisco
dc.contributor.authorCancho, Vicente G.
dc.date.accessioned2018-11-26T15:37:38Z
dc.date.available2018-11-26T15:37:38Z
dc.date.issued2017-01-01
dc.identifierhttp://dx.doi.org/10.1080/03610926.2015.1053945
dc.identifier.citationCommunications In Statistics-theory And Methods. Philadelphia: Taylor & Francis Inc, v. 46, n. 6, p. 3080-3098, 2017.
dc.identifier.issn0361-0926
dc.identifier.urihttp://hdl.handle.net/11449/159252
dc.description.abstractIn this paper we propose a general cure rate aging model. Our approach enables different underlying activation mechanisms which lead to the event of interest. The number of competing causes of the event of interest is assumed to follow a logarithmic distribution. The model is parameterized in terms of the cured fraction which is then linked to covariates. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis for the proposed model. Moreover, some discussions on the model selection to compare the fitted models are given, as well as case deletion influence diagnostics are developed for the joint posterior distribution based on the -divergence, which has several divergence measures as particular cases, such as the Kullback-Leibler (K-L), J-distance, L-1 norm, and (2)-square divergence measures. Simulation studies are performed and experimental results are illustrated based on a real malignant melanoma data.en
dc.format.extent3080-3098
dc.language.isoeng
dc.publisherTaylor & Francis Inc
dc.relation.ispartofCommunications In Statistics-theory And Methods
dc.sourceWeb of Science
dc.subjectCompeting risks
dc.subjectcure rate models
dc.subjectcured fraction
dc.subjectlogarithmic distribution
dc.subjectlong-term aging models
dc.titleA general long-term aging model with different underlying activation mechanisms: Modeling, Bayesian estimation, and case influence diagnosticsen
dc.typeArtigo
dcterms.licensehttp://journalauthors.tandf.co.uk/permissions/reusingOwnWork.asp
dcterms.rightsHolderTaylor & Francis Inc
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.description.affiliationUniv Sao Paulo, Dept Appl Math & Stat, Sao Carlos, SP, Brazil
dc.description.affiliationSao Paulo State Univ, Fac Engn Bauru, Bauru, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Fac Engn Bauru, Bauru, Brazil
dc.identifier.doi10.1080/03610926.2015.1053945
dc.identifier.wosWOS:000390425800037
dc.rights.accessRightsAcesso aberto
dc.identifier.fileWOS000390425800037.pdf
unesp.author.orcid0000-0001-7815-9554[3]
dc.relation.ispartofsjr0,352
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