Reliability estimation of multicomponent stress-strength model based on copula function under progressively hybrid censoring
Reliability estimation of multicomponent stress-strength model based on copula function under progressively hybrid censoring
复制标题
渐进混合删失下基于Copula函数的多分量应力-强度模型可靠性估计
DOI：
10.1016/j.cam.2018.04.066
复制
发表时间：
2018-12-15
影响因子：
2.4
通讯作者：
Liu, Bin
中科院分区：
文献类型：
--
作者：
Bai, Xuchao;Shi, Yimin;Liu, Bin
在应力-强度模型的可靠性分析中，应力和强度变量通常被假定为独立的。然而，这样的假设在某些应用中可能是不现实的。对于应力和强度相关变量的应力-强度模型的可靠性估计是一个有意义的问题。本文基于Gumbel copula假设应力变量和强度变量均为相依的Weibull分布，在逐步混合定数截尾下，对多组分应力-强度模型的可靠性进行了估计。利用极大似然估计方法，得到了未知参数和可靠度的估计量。导出了应力-强度模型未知参数的渐近置信区间和Bootstrap百分位数置信区间，以及模型的可靠度。蒙特卡罗模拟用于评估最大似然估计，渐近置信区间和Bootstrap百分位数置信区间的性能。最后，通过对真实的数据进行分析，验证了本文应力-强度模型的实用性。(C)2018爱思唯尔B. V.保留所有权利。
In reliability analysis of the stress-strength models, the stress and strength variables are typically assumed as independent. However, such an assumption may be unrealistic in some applications. It is a meaningful issue to estimate the reliability of the stress strength model for dependent stress and strength variables. In this paper, we estimate the reliability of multicomponent stress-strength model by assuming the dependent Weibull stress variables and exponential strength variables based on Gumbel copula under Type-I progressively hybrid censoring scheme. The estimators of the unknown parameters and reliability are obtained by using the maximum likelihood estimation method. Also, the asymptotic confidence intervals and Bootstrap percentile confidence intervals of the unknown parameters and reliability of stress-strength model are derived. Monte Carlo simulations are used to evaluate the performance of the maximum likelihood estimators, asymptotic confidence intervals and Bootstrap percentile confidence intervals. Finally, real data are analyzed to demonstrate the practicability of the stress-strength model in this article. (C) 2018 Elsevier B.V. All rights reserved.