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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/8861
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dc.contributor.authorCancho, Vicente G.-
dc.contributor.authorOrtega, Edwin M. M.-
dc.contributor.authorBarriga, Gladys Dorotea Cacsire-
dc.contributor.authorHashimoto, Elizabeth M.-
dc.date.accessioned2014-05-20T13:27:10Z-
dc.date.accessioned2016-10-25T16:47:08Z-
dc.date.available2014-05-20T13:27:10Z-
dc.date.available2016-10-25T16:47:08Z-
dc.date.issued2011-01-01-
dc.identifierhttp://dx.doi.org/10.1080/00949655.2010.491827-
dc.identifier.citationJournal of Statistical Computation and Simulation. Abingdon: Taylor & Francis Ltd, v. 81, n. 11, p. 1461-1481, 2011.-
dc.identifier.issn0094-9655-
dc.identifier.urihttp://hdl.handle.net/11449/8861-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/8861-
dc.description.abstractIn this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.en
dc.format.extent1461-1481-
dc.language.isoeng-
dc.publisherTaylor & Francis Ltd-
dc.sourceWeb of Science-
dc.subjectCOM-Poisson distributionsen
dc.subjectcure fraction modelsen
dc.subjectgeneralized gamma distributionsen
dc.subjectsensitivity analysisen
dc.subjectlifetime dataen
dc.titleThe Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivorsen
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationESALQ USP, Dept Ciencias Exatas, Piracicaba, Brazil-
dc.description.affiliationICMC USP, Dept Matemat Aplicada & Estat, BR-13560970 São Carlos, SP, Brazil-
dc.description.affiliationFEB UNESP, Dept Prod Engn, Bauru, Brazil-
dc.description.affiliationUnespFEB UNESP, Dept Prod Engn, Bauru, Brazil-
dc.identifier.doi10.1080/00949655.2010.491827-
dc.identifier.wosWOS:000299726700008-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofJournal of Statistical Computation and Simulation-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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