Reliability inference for a multicomponent stress-strength model based on Kumaraswamy distribution
學年 109
學期 1
出版（發表）日期 2020-10-01
作品名稱 Reliability inference for a multicomponent stress-strength model based on Kumaraswamy distribution
作品名稱（其他語言）
著者 Liang Wang; Sanku Dey; Yogesh Mani Tripathi; Shuo-Jye Wu
單位
出版者
著錄名稱、卷期、頁數 Journal of Computational and Applied Mathematics 376, 112823
摘要 In this paper, inference for a multicomponent stress–strength (MSS) model is studied under censored data. When both latent strength and stress random variables follow Kumaraswamy distributions with common shape parameters, the maximum likelihood estimate of MSS reliability is established and associated approximate confidence interval is constructed using the asymptotic distribution theory and delta method. Moreover, pivotal quantities based generalized point and confidence interval estimates are presented for the MSS reliability. Furthermore, likelihood and generalized pivotal based estimates are also presented when the strength and stress variables have unequal shape parameters. For complementary and comparison, bootstrap confidence intervals are provided as well under common and unequal parameter cases. In addition, to compare the equivalence between strength and stress shape parameters, the likelihood ratio test for hypothesis of interest is also discussed. Finally, simulation study and a real data example are provided to investigate the performance of proposed procedures.
關鍵字 Multicomponent stress–strength model;Kumaraswamy distribution;Maximum likelihood estimation;Generalized pivotal quantity;Asymptotic theory;Bootstrap interval
語言 en_US
ISSN 1879-1778
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Wang, L.
審稿制度 是
國別 NLD
公開徵稿
出版型式 ,電子版,紙本
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