One-shot device test data analysis using non-parametric and semi-parametric inferential methods and applications

被引:4
作者
Zhu, Xiaojun [1 ]
Balakrishnan, N. [2 ]
机构
[1] Xian Jiaotong Liverpool Univ, Dept Financial & Actuarial Math, Suzhou 215123, Peoples R China
[2] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada
基金
加拿大自然科学与工程研究理事会; 中国国家自然科学基金;
关键词
Accelerated life-test; Expectation-Maximization algorithm; Kaplan-Meier estimator; Nelson-Aalen estimator; Non-parametric inference; One-shot device test; Proportional hazards model; Semi-parametric inference; COMPETING RISKS; EM ALGORITHM; MODEL; INSPECTION; INTERVALS; SYSTEMS; WEIBULL;
D O I
10.1016/j.ress.2022.108319
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A one-shot device, such as an automobile airbag, electro-explosive unit or munition, is a product that can be used only once. Its actual lifetime is unobservable, rendering the corresponding reliability analysis quite challenging. In this paper, two non-parametric methodologies-maximum likelihood estimation via EM-algorithm and Nelson-Aalen based estimation are developed for identical testing environment on one-shot devices. The EM-algorithm is usually used for unobserved failure times under some specific parametric models. But, here the EM-algorithm is adopted for the number of failures in each time interval in a nonparametric manner. Next, a semi-parametric approach, based on proportional hazards assumption, is developed for nonidentical testing environments, such as under an accelerated life-test. A Monte Carlo simulation study is then carried out for evaluating the performance of the inferential methods developed here. Finally, two data sets are analyzed for illustrative purpose.
引用
收藏
页数:10
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