期刊名称：Electronic Journal of Applied Statistical Analysis
电子版ISSN：2070-5948
出版年度：2018
卷号：11
期号：2
页码：655-673
DOI：10.1285/i20705948v11n2p655
语种：English
出版社：University of Salento
其他摘要：Under a context of survival lifetime analysis, we introduce in this paper Bayesian and maximum likelihood approaches for the bivariate Basu-Dhar geometric model in the presence of covariates and a cure fraction. This distribution is useful to model bivariate discrete lifetime data. In the Bayesian estimation, posterior summaries of interest were obtained using standard Markov Chain Monte Carlo methods in the OpenBUGS software. Maximum likelihood estimates for the parameters of interest were computed using the extquotedblleft maxLik" package of the R software. Illustrations of the proposed approaches are given for two real data sets.
关键词：Basu-Dhar distribution;cure fraction;discrete distributions;MCMC methods;lifetime data
