Stress–strength inference on the multicomponent model based on generalized exponential distributions under type-I hybrid censoring

doi:10.3390/math11051249

淡江大學機構典藏 > 商管學院 > 統計學系暨研究所 > 期刊論文 > Item 987654321/123293

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题名:	Stress–strength inference on the multicomponent model based on generalized exponential distributions under type-I hybrid censoring
作者:	Tsai, Tzong-Ru;Lio, YL;Chiang, J-Y;Chang, Y-W
关键词:	multicomponent stress–strength model;generalized exponential distribution;Bayesian method;Markov chain Monte Carlo method;highest probability density interval
日期:	2023-03-04
上传时间:	2023-04-28 17:33:34 (UTC+8)
出版者:	MDPI AG
摘要:	The stress–strength analysis is investigated for a multicomponent system, where all strength variables of components follow a generalized exponential distribution and are subject to the generalized exponential distributed stress. The estimation methods of the maximum likelihood and Bayesian are utilized to infer the system reliability. For the Bayesian estimation method, informative and non-informative priors combined with three loss functions are considered. Because the computational difficulty on working posteriors, the Markov chain Monte Carlo method is adopted to obtain the approximation of the reliability estimator posterior. In addition, the bootstrap method and highest probability density interval are used to obtain the reliability confidence intervals. The simulation study shows that the Bayes estimator with informative prior is superior to other competitors. Finally, two real examples are given to illustrate the proposed estimation methods.
關聯:	Mathematics 2023 11(5), 1249
DOI:	10.3390/math11051249
显示于类别:	[統計學系暨研究所] 期刊論文

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