教師資料查詢 | 類別: 期刊論文 | 教師: 吳碩傑 Shuo-Jye Wu (瀏覽個人網頁)

標題: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 Vol. 376, Article 112823, pp. 1-22
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
語言英文(美國)
ISSN1879-1778
期刊性質國外
收錄於SCI;
產學合作
通訊作者Wang, L.
審稿制度
國別荷蘭
公開徵稿
出版型式,電子版
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