Por favor, use este identificador para citar o enlazar este ítem:
https://repositorio.ufba.br/handle/ri/14179
Registro completo de metadatos
Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Silva, Giovana Oliveira | - |
dc.contributor.author | Ortega, Edwin Moises Marcos | - |
dc.contributor.author | Cancho, Vicente Garibay | - |
dc.contributor.author | Barreto, Mauricio Lima | - |
dc.creator | Silva, Giovana Oliveira | - |
dc.creator | Ortega, Edwin Moises Marcos | - |
dc.creator | Cancho, Vicente Garibay | - |
dc.creator | Barreto, Mauricio Lima | - |
dc.date.accessioned | 2013-12-16T12:25:55Z | - |
dc.date.issued | 2008 | - |
dc.identifier.issn | 0167-9473 | - |
dc.identifier.uri | http://repositorio.ufba.br/ri/handle/ri/14179 | - |
dc.description | Texto completo: acesso restrito. p. 3820-3842 | pt_BR |
dc.description.abstract | In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Burr XII regression models. | pt_BR |
dc.language.iso | en | pt_BR |
dc.rights | Acesso Aberto | pt_BR |
dc.source | http://dx.doi.org/10.1016/j.csda.2008.01.003 | pt_BR |
dc.title | Log-Burr XII regression models with censored data | pt_BR |
dc.title.alternative | Computational Statistics and Data Analysis | pt_BR |
dc.type | Artigo de Periódico | pt_BR |
dc.identifier.number | v. 52, n. 7 | pt_BR |
dc.embargo.liftdate | 10000-01-01 | - |
Aparece en las colecciones: | Artigo Publicado em Periódico Estrangeiro (ISC) |
Ficheros en este ítem:
No hay ficheros asociados a este ítem.
Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.