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：463-488
DOI：10.1285/i20705948v11n2p463
语种：English
出版社：University of Salento
其他摘要：In recent years, the use of copulas has grown rapidly, especially in survivalanalysis. In this paper, we introduce a bivariate modied Weibull distribu-tion derived from the Farlie{Gumbel{Morgenstern (FGM), a copula functioncommonly used to model very weak linear dependences. Considering thepresence of non censored data and censored data, an extensive simulationstudy was developed to check the performance of the maximum likelihoodmethod in estimating the parameters of the proposed model. Maximum like-lihood and Bayesian approaches for the estimation of the model parametersare presented. In the Bayesian analysis, the posterior distributions of the pa-rameters are estimated using Markov chain Monte Carlo (MCMC) method-ology. An example, considering a real data set, is introduced to illustrate theproposed methodology.
