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Statistical analysis of middle censored competing risks data with exponential distribution

机译:具有指数分布的中删失竞争风险数据的统计分析

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摘要

In this paper, we consider some problems of estimation and reconstruction based on middle censored competing risks data. It is assumed that the lifetime distributions of the latent failure times are independent and exponential distributed with different parameters and also that the censoring mechanism is independent. The maximum likelihood estimators (MLEs) of the unknown parameters are obtained. We then use the asymptotic distribution of the MLEs to construct approximate confidence intervals. Based on gamma priors, Lindley's approximation method is applied to obtain the Bayesian estimates of the unknown parameters under squared error loss function. Since it is not possible to construct the credible intervals, we propose and implement the Gibbs sampling technique to construct the credible intervals. Several point reconstructors for failure time of censored units are provided. Finally, a simulation study is given by Monte-Carlo simulations to evaluate the performances of the different methods and a data set is analysed to illustrate the proposed procedures.
机译:本文考虑了基于中间删失竞争风险数据的估计和重构问题。假定潜在失效时间的寿命分布是独立的,并且具有不同参数的指数分布,并且假设检查机制是独立的。获得未知参数的最大似然估计器(MLE)。然后,我们使用MLE的渐近分布构造近似的置信区间。基于伽玛先验,在平方误差损失函数下,采用Lindley逼近方法获得未知参数的贝叶斯估计。由于不可能构造可信区间,因此我们建议并实施Gibbs采样技术来构造可信区间。提供了一些用于检查单元故障时间的点重构器。最后,通过蒙特卡洛仿真进行了仿真研究,以评估不同方法的性能,并分析了数据集以说明所提出的程序。

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