文章基本信息

标题：Bivariate Weibull Distributions Derived From Copula Functions In The Presence Of Cure Fraction And Censored Data
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作者：Emílio Coelho-Barros ; Jorge Achcar ; Josmar Mazucheli 等
期刊名称：Journal of Data Science
印刷版ISSN：1680-743X
电子版ISSN：1683-8602
出版年度：2016
卷号：14
期号：2
页码：295-316
出版社：Tingmao Publish Company
摘要：In this paper we introduce bivariate Weibull distributions derived from copula functions in presence of cure fraction, censored data and covariates. Two copula functions are explored: the FGM (Farlie - Gumbel Morgenstern) copula and the Gumbel copula. Inferences for the proposed models are obtained under the Bayesian approach, using standard MCMC (Markov Chain Monte Carlo) methods. An illustration of the proposed methodology is given considering a medical data set.
关键词：Bayesian methods; Bivariate Weibull; Censored observations; Copula functions; Cure fraction.