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Two-sided M-Bayesian credible limits of reliability parameters in the case of zero-failure data for exponential distribution

机译:在零失效数据指数分布的情况下,可靠性参数的两侧M-贝叶斯可信极限

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In this paper, we study the interval estimation of failure rate and reliability for exponential distribution, in the case of zero-failure data, using the method of two-sided Modified Bayesian (M-Bayesian) credible limit. We discuss the properties of two-sided M-Bayesian credible limits which include the impact of the value of upper bound c of hyper parameter, and the influence of different prior distributions of hyper parameter on two-sided M-Bayesian credible limits. The paper obtains the relationship between three kinds of two-sided M-Bayesian credible limits and two-sided classical confidence limits. Finally, we use a real data set to verify the properties of two-sided M-Bayesian credible limits, and the computing results indicate that the method is efficient and easy to operate.
机译:在本文中,我们使用双向修正贝叶斯(M-Bayesian)可信极限方法研究零故障数据情况下的故障率和指数分布可靠性的区间估计。我们讨论了双面M-贝叶斯可信极限的性质,包括超参数上限c的值的影响,以及超参数的不同先验分布对双面M-贝叶斯可信极限的影响。得出了三种双面M-贝叶斯可信极限与双面经典置信极限之间的关系。最后,我们使用一个真实的数据集来验证两侧M-贝叶斯可信极限的性质,计算结果表明该方法高效且易于操作。

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