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Reliability analysis for q-Weibull distribution with multiply Type-I censored data
Quality and Reliability Engineering International ( IF 2.2 ) Pub Date : 2021-04-26 , DOI: 10.1002/qre.2890
Xiang Jia 1
Affiliation  

The widely used Weibull distribution could be generalized to be q-Weibull distribution. To fill out the gap in existing literature, the reliability is studied for q-Weibull distribution with multiply Type-I censored data, which is the general form of Type-I censored data. The point estimates and confidence intervals (CIs) for q-Weibull parameters and reliability parameters such as the reliability and remaining lifetime are all focused on. The maximum likelihood estimates (MLE) are obtained by maximizing the likelihood function and transforming it to an unconstrained optimization problem. The least-square estimates (LSEs) are proposed by minimizing the single-variable profile error function derived from reducing the previous multivariable error function. These improvements could make the computation of point estimates efficient. Concerning the CIs, the asymptotic normality of log-transformed MLE is used to guarantee they fall into the value ranges. Particularly, the closed form for the Fisher information matrix is derived using the missing information principal and is combined with the delta method to construct the CIs for reliability. Besides, the bias-corrected and accelerated (BCa) bootstrap method is also applied. Further, a Monte Carlo simulation study is conducted to compare different point estimates and CIs. Finally, an illustrative example is presented to show the application of the study in this paper.

中文翻译:

具有多重 I 型删失数据的 q-Weibull 分布的可靠性分析

广泛使用的 Weibull 分布可以推广为 q-Weibull 分布。为了填补现有文献的空白,研究了具有多重 I 型删失数据的 q-Weibull 分布的可靠性,这是 I 型删失数据的一般形式。q-Weibull 参数和可靠性参数(例如可靠性和剩余寿命)的点估计和置信区间 (CI) 都是重点。最大似然估计 (MLE) 是通过最大化似然函数并将其转换为无约束优化问题来获得的。最小二乘估计 (LSE) 是通过最小化从减少先前的多变量误差函数而导出的单变量轮廓误差函数来提出的。这些改进可以使点估计的计算有效。关于 CI,对数变换的 MLE 的渐近正态性用于保证它们落入值范围。特别是,Fisher 信息矩阵的封闭形式是使用缺失信息原则推导出来的,并结合 delta 方法来构建可靠性的 CI。此外,还应用了偏差校正和加速(BCa)自举方法。此外,还进行了蒙特卡罗模拟研究以比较不同的点估计和 CI。最后,给出了一个说明性的例子来说明本文研究的应用。Fisher 信息矩阵的封闭形式是使用缺失信息原理导出的,并与 delta 方法相结合以构建可靠性的 CI。此外,还应用了偏差校正和加速(BCa)自举方法。此外,还进行了蒙特卡罗模拟研究以比较不同的点估计和 CI。最后,给出了一个说明性的例子来说明本文研究的应用。Fisher 信息矩阵的封闭形式是使用缺失信息原理导出的,并与 delta 方法相结合以构建可靠性的 CI。此外,还应用了偏差校正和加速(BCa)自举方法。此外,还进行了蒙特卡罗模拟研究以比较不同的点估计和 CI。最后,给出了一个说明性的例子来说明本文研究的应用。
更新日期:2021-04-26
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