Bayesian estimation of parameters for the bivariate Gompertz regression model with shared gamma frailty under random censoring

被引:2
|
作者
Hanagal, David D. [1 ]
Sharma, Richa [1 ]
机构
[1] Univ Pune, Dept Stat, Pune 411007, Maharashtra, India
关键词
Gamma frailty; Gompertz distribution; Markov Chain Monte Carlo (MCMC); Shared frailty; DISTRIBUTIONS; ASSOCIATION;
D O I
10.1016/j.spl.2012.03.028
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, we consider the shared gamma frailty model with Gompertz distribution as baseline hazard for bivariate survival times. The problem of analyzing and estimating parameters of bivariate Gompertz distribution with shared gamma frailty is of interest and the focus of this paper. We solve the inferential problem in a Bayesian framework with the help of a comprehensive simulation study. We introduce Bayesian estimation procedure using the Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in the proposed model and then compare the true values of the parameters with the estimated values for different sample sizes. A search of the literature suggests there is currently no work that has been done for Bayesian estimation of parameters of bivariate Gompertz distribution with shared frailty. (C) 2012 Elsevier B.V. All rights reserved.
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页码:1310 / 1317
页数:8
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