影响因子：1.118
所属单位：数学与统计学院
教研室：统计教研室
发表刊物：Communications in Statistics – Simulation and Computation
关键字：Bayesian-based empirical likelihood, Estimating equation, Metropolis– Hasting algorithm, Proportional hazards model, Right-censored data
摘要：Statistical analysis of right-censored failure time data has been extensively discussed in the literature as such data often occur in many fields. In this article, we propose a new Bayesian-based empirical likelihood approach for the problem under the proportional hazards model. The new method allows one to take into account the existing prior information among other advantages, and for the implementation of the method, a Metropolis–Hasting algorithm is developed. To assess the performance of the proposed approach, a simulation study is conducted and suggests that it works well. The method is applied to a set of kidney dialysis data.
论文类型：期刊论文
是否译文：否
发表时间：2021-09-01
收录刊物：SCI