Advances and Applications in Statistics
Volume 21, Issue 1, Pages 55 - 76
(March 2011)
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THE FGM BIVARIATE LIFETIME COPULA MODEL: A BAYESIAN APPROACH
Adriano K. Suzuki, Francisco Louzada, Vicente G. Cancho and Gladys D. C. Barriga
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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. |
Keywords and phrases: case deletion influence diagnostics, copula modeling, survival data, Bayesian approach. |
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