论文标题
基于广义的渐进式混合审查数据，对微生组件的N系统的可靠性分析
Reliability analysis of K-out-of-N system for Weibull components based on generalized progressive hybrid censored data
论文作者
论文摘要
在本文中，我们研究了基于广义的渐进式混合审查数据，遵循Weibull分布的组件的K-OUT系统对组件的可靠性。我们获得了未知参数的最大似然估计（MLE）和系统的可靠性函数。使用MLE的渐近正态性能，构建了相应的渐近置信区间。此外，通过使用马尔可夫链蒙特卡洛（MCMC）技术，在平方误差损失函数下得出了贝叶斯估计。获得最高的后密度（HPD）可信间隔。进行了蒙特卡洛模拟研究，以比较既定估计值的性能。最后，出于说明目的，考虑了一个真实的数据集。
In this paper, we have investigated the reliability of a K-out-of-N system for the components following Weibull distribution based on the generalized progressive hybrid censored data. We have obtained the maximum likelihood estimates (MLEs) of the unknown parameters and the reliability function of the system. Using asymptotic normality property of MLEs, the corresponding asymptotic confidence intervals are constructed. Furthermore, Bayes estimates are derived under squared error loss function with informative prior by using Markov Chain Monte Carlo (MCMC) technique. Highest posterior density (HPD) credible intervals are obtained. A Monte Carlo simulation study is carried out to compare performance of the established estimates. Finally, a real data set is considered for illustrative purposes.
