Advances and Applications in Statistics
Volume 15, Issue 1, Pages 1 - 25
(March 2010)
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A BAYESIAN ANALYSIS FOR BIVARIATE WEIBULL DISTRIBUTIONS DERIVED FROM COPULA FUNCTIONS IN THE PRESENCE OF COVARIATES AND CENSORED DATA
Carlos Aparecido Dos Santos and Jorge Alberto Achcar
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Abstract: In this paper, we introduce a Bayesian analysis for bivariate lifetime data in the presence of covariates and censoring data assuming different bivariate Weibull distributions derived from copula functions. Posterior summaries of interest are obtained using MCMC (Markov Chain Monte Carlo) methods as the popular Gibbs sampling algorithm and the Metropolis-Hastings algorithm. Two medical data sets are analysed to exemplify the proposed methodology. |
Keywords and phrases: bivariate Weibull distributions, copula functions, MCMC methods, Bayesian analysis, censoring data, covariates. |
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