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Equivariant estimation for the parameters of location-scale multivariate exponential models and its application in reliability analysis

机译:地点级多变量指数模型参数的等意大动估计及其在可靠性分析中的应用

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摘要

By considering an absolutely continuous location-scale multivariate exponential model (Weier and Basu, 1980), we obtain minimum risk equivariant estimator(s) of the parameter(s). Given a location-scale multivariate exponential random vector, it is shown that the normalized spacings associated with the random vector are independent standard exponential. The distribution of the complete sufficient statistic is derived. We derive the performance measures of standby, parallel, and series systems and also obtain the minimum risk equivariant estimator of the mean time before failure of the three systems. Some of the results of this article are extensions of those of Chandrasekar and Sajesh (2010).
机译:通过考虑绝对连续的位置规模多变量指数模型(Weier和Basu,1980),我们获得了参数的最低风险等值估计器。给定位置级多变量指数随机向量,结果表明与随机向量相关的归一化间距是独立的标准指数。衍生完整足够统计的分布。我们推出了待机,平行和系列系统的性能测量,并在三个系统失败前获得了平均时间的最低风险等值估计。本文的一些结果是Chandrasekar和Sajesh(2010)的扩展。

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