Reliability inference for the multicomponent system based on progressively type II censored samples from generalized Pareto distributions
學年 108
學期 2
出版（發表）日期 2020-07-17
作品名稱 Reliability inference for the multicomponent system based on progressively type II censored samples from generalized Pareto distributions
作品名稱（其他語言）
著者 Lauren Sauer; Yuhlong Lio; Tzong-Ru Tsai
單位
出版者
著錄名稱、卷期、頁數 Mathematics 8(7), p.1176
摘要 In this paper, the reliability of a k-component system, in which all components are subject to common stress, is considered. The multicomponent system will continue to survive if at least s out of k components’ strength exceed the common stress. The system reliability is investigated by utilizing the maximum likelihood estimator based on progressively type II censored samples from generalized Pareto distributions. The confidence interval of the system reliability can be obtained by using asymptotic normality with Fisher information matrix or bootstrap method approximation. An intensive simulation study is conducted to evaluate the performance of maximum likelihood estimators of the model parameters and system reliability for a variety of cases. For the confidence interval of the system reliability, simulation results indicate the bootstrap method approximation outperforms over the asymptotic normality approximation in terms of coverage probability.
關鍵字 bootstrap procedure;delta method;maximum likelihood estimation;stress-strength
語言 en
ISSN
期刊性質 國外
收錄於 SCI Scopus
產學合作
通訊作者
審稿制度 否
國別 AUS
公開徵稿
出版型式 ,電子版,紙本
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