Two-sided M-Bayesian limits of credibility of reliability parameters in the case of zero-failure data and a case study

Wanyi Dai, Siqi Li, Mei Zhang, Yueming Hu, D. Mei
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引用次数: 1

Abstract

In this paper, a novel method of two-sided M-Bayesian credible limit is proposed to deal with the interval estimation problem of reliability parameters with exponential distribution in the case of zero-failure data. The properties of two-sided M-Bayesian limits of credibility are discussed and some new theorems are proven including the impact of the upper bound c of hyper parameters and the influence of different prior distributions of hyper parameters on two-sided M-Bayesian limits of credibility when the reliability of estimation was determined by the exponential distribution. The paper extended the conclusions drawn in two previous studies regarding the relationships among the many kinds of two-sided M-Bayesian limits of credibility and two-sided classical confidence. Finally, a real dataset about engines is discussed with different model parameters. By means of an example, the presented method of this paper is compared with the classical confidence limits. The results verify the properties of two-sided M-Bayesian limits of credibility and indicate that the method is efficient and easy to perform.
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零失效数据下可靠性参数可信度的双侧m -贝叶斯极限及实例研究
本文提出了一种新的双侧m -贝叶斯可信极限方法,用于处理零失效数据下指数分布的可靠性参数区间估计问题。讨论了双侧m -贝叶斯可信度极限的性质,并证明了一些新的定理,包括超参数上界c的影响,以及当估计的可靠性由指数分布决定时,超参数的不同先验分布对双侧m -贝叶斯可信度极限的影响。本文推广了前两篇关于多种双边m -贝叶斯可信度极限与双边经典置信度之间关系的研究结论。最后,对一个具有不同模型参数的真实引擎数据集进行了讨论。通过实例,将本文提出的方法与经典的置信限进行了比较。结果验证了双侧m -贝叶斯可信度限的性质,表明该方法是一种简便有效的方法。
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