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hierarchical bayesian estimators
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In this paper, the quasi-moment estimators of the parameters are proposed based on the zero-failure data in Weibull distribution according to the concept "mean residual lifetime". As an application of these estimators, the original problem is transformed into the case that one or more items fail, and the hierarchical Bayesian estimators of the failure probability Pis are obtained with the aid of the result in [1]. Then, the estimators of the unknown parameters are given by the method...

In this paper, the quasi-moment estimators of the parameters are proposed based on the zero-failure data in Weibull distribution according to the concept "mean residual lifetime". As an application of these estimators, the original problem is transformed into the case that one or more items fail, and the hierarchical Bayesian estimators of the failure probability Pis are obtained with the aid of the result in [1]. Then, the estimators of the unknown parameters are given by the method of distribution curve-fitting. In addition, the calculation of a practical problem is illustrated.

本文对Weibull分布场合下的无失效数据(ti,ni),根据“平均剩余寿命”这一概念得到了参数的拟矩估计,进而将其转化至有一个或多个失效数据的情形,利用[1]中的结果给出了失效概率pi的多层Bayes估计,从而利用分布函数曲线拟合方法得到了未知参数的估计,并结合实际问题进行了计算。

In this paper,we use Bayesian method to study the estimation problem of the parametersδ_1 andδ_2 of theδ-shock model associated with a Poisson process with intensityλunder zero- failure data,where the system fails when the length of an interval between two success shocks does not fall in a prespecified interval [δ_1,δ_2].By choosing U(0, 1) and a Beta distribution as the prior distribution of the parameters respectively,we obtain the Bayesian and hierarchical Bayesian estimators of threshold...

In this paper,we use Bayesian method to study the estimation problem of the parametersδ_1 andδ_2 of theδ-shock model associated with a Poisson process with intensityλunder zero- failure data,where the system fails when the length of an interval between two success shocks does not fall in a prespecified interval [δ_1,δ_2].By choosing U(0, 1) and a Beta distribution as the prior distribution of the parameters respectively,we obtain the Bayesian and hierarchical Bayesian estimators of threshold levelδ_1 andδ_2.

在这篇文章中,我们针对一般冲击模型,研究Bayes方法处理无失效数据的问题.所谓一般δ-冲击模型是指系统受到强度为λ的Poisson冲击,当两个连续冲击之间时间间隔的长度不属于某个固定的区间[δ_1,δ_2]时,系统将失效.我们分别选择均匀分布和Beta分布作为先验分布,用Bayes方法和多层Bayes方法得到了参数δ_1和δ_2的估计.

 
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