Bayesian Estimation Based on Sequential Order Statistics for Heterogeneous Baseline Gompertz Distributions
學年 109
學期 1
出版（發表）日期 2021-01-11
作品名稱 Bayesian Estimation Based on Sequential Order Statistics for Heterogeneous Baseline Gompertz Distributions
作品名稱（其他語言）
著者 Tzong-Ru Tsai; Hua Xin; Chiun-How Kao
單位
出版者
著錄名稱、卷期、頁數 Mathematics 9(2), p.145
摘要 A composite dynamic system (CDS) is composed of multiple components. Each component failure can equally induce higher loading on the surviving components and, hence, enhances the hazard rate of each surviving component. The applications of CDS and the reliability evaluation of CDS has earned more attention in the recent two decades. Because the lifetime quality of components could be inconsistent, the lifetimes of components in the CDS is considered to follow heterogeneous baseline Gompertz distributions in this study. A power-trend hazard rate function is used in order to characterize the hazard rate of the CDS. In order to overcome the difficulty of obtaining reliable estimates of the parameters in the CDS model, the Bayesian estimation method utilizing a hybrid Gibbs sampling and Metropolis-Hasting algorithm to implement the Markov chain Monte Carlo approach is proposed for obtaining the Bayes estimators of the CDS parameters. An intensive simulation study is carried out to evaluate the performance of the proposed estimation method. The simulation results show that the proposed estimation method is reliable in providing reliability evaluation information for the CDS. An example regarding the service system of small electric carts is used for illustration.
關鍵字 composite dynamic system;hazard rate;heterogeneity;Markov chain Monte Carlo;sequential order statistics
語言 en_US
ISSN 2227-7390
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 否
國別 USA
公開徵稿
出版型式 ,電子版,紙本
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