Publication: The FGM bivariate lifetime copula model: a bayesian approach
Loading...
Date
Advisor
Coadvisor
Graduate program
Undergraduate course
Journal Title
Journal ISSN
Volume Title
Publisher
Type
Article
Access right
Acesso restrito
Abstract
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.
Description
Keywords
Case deletion influence diagnostics, Copula modeling, Survival data, Bayesian approach
Language
English
Citation
Advances and Applications in Statistics, v. 21, p. 55-76, 2011.
