Inference for simple step stress accelerated life test model under progressively censored Gompertz data
學年 114
學期 1
出版（發表）日期 2025-08-25
作品名稱 Inference for simple step stress accelerated life test model under progressively censored Gompertz data
作品名稱（其他語言）
著者 Rajat Das; Yogesh Mani Tripathi; Liang Wang; Shuo-Jye Wu
單位
出版者
著錄名稱、卷期、頁數 Applied Stochastic Models in Business and Industry 41(5), p. e70037
摘要 In this article analysis of a simple step-stress accelerated life test is considered under progressive type-II censoring. A cumulative exposure model is considered when the latent lifetimes of test units follow the Gompertz distribution with different shape parameters and a common scale parameter. We explore the study by estimating all unknown parameters using classical and Bayesian techniques. The model parameters are estimated using maximum likelihood and Bayesian methods. Subsequently, interval estimates are derived based on the observed Fisher information matrix. Bayesian estimates are obtained using squared error and linear exponential loss functions. Subsequently highest posterior density intervals are also constructed. We examine the efficiency of all estimators through simulation studies. Finally, we provide a real-life example in support of the considered model.
關鍵字
語言 en_US
ISSN
期刊性質 國外
收錄於 SCI Scopus
產學合作
通訊作者 Shuo-Jye Wu
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/128898 )