The FGM bivariate lifetime copula model: a bayesian approach
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
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Data(s) |
02/03/2016
02/03/2016
2011
|
Resumo |
In this paper, we propose a bivariate distribution for the bivariate survival times based on Farlie-Gumbel-Morgenstern copula to model the dependence on a bivariate survival data. The proposed model allows for the presence of censored data and covariates. For inferential purpose a Bayesian approach via Markov Chain Monte Carlo (MCMC) is considered. Further, some discussions on the model selection criteria are given. In order to examine outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. The newly developed procedures are illustrated via a simulation study and a real dataset. |
Formato |
55-76 |
Identificador |
http://www.pphmj.com/abstract/5794.htm Advances and Applications in Statistics, v. 21, p. 55-76, 2011. 0972-3617 http://hdl.handle.net/11449/134820 5267593860042306 3503233632044163 |
Idioma(s) |
eng |
Relação |
Advances and Applications in Statistics |
Direitos |
closedAccess |
Palavras-Chave | #Case deletion influence diagnostics #Copula modeling #Survival data #Bayesian approach |
Tipo |
info:eu-repo/semantics/article |