A bivariate generalized exponential distribution derived from copula functions in the presence of censored data and covariates

• Autor(a) principal: Achcar, Jorge Alberto [UNESP]
• Data de Publicação: 2015
• Outros Autores: Moala, Fernando Antônio [UNESP], Tarumoto, Mario Hissamitsu [UNESP], Coladello, Leandro Fernandes [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1590/0101-7438.2015.035.01.0165; http://hdl.handle.net/11449/177361
• topic: Bayesian analysis; Bivariate generalized exponential distribution; Censored data; Copula function; Covariates

In this paper, we introduce a Bayesian analysis for a bivariate generalized exponential distribution in the presence of censored data and covariates derived from Copula functions. The generalized exponential distribution could be a good alternative to analyze lifetime data in comparison to usual existing parametric lifetime distributions as Weibull or Gamma distributions. We have being using standard existing MCMC (Markov Chain Monte Carlo) methods to simulate samples for the joint posterior of interest. Two examples are introduced to illustrate the proposed methodology: an example with simulated bivariate lifetime data and an example with a real lifetime data set.