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Bayesian Estimation of Common Scale Parameter of Two Exponential Populations with Order Restricted Locations

机译:贝叶斯估计两种指数群体的常见规模参数,订单限制位置

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The problem of estimating the common scale parameter of two exponential populations is considered when it is known a priori that the location parameters follow a certain ordering. The loss function is taken as quadratic or a weighted squared error. Assuming order restrictions on the location parameters, we propose Bayes estimators (exact expressions have been obtained) using a vague prior as well as a conditional inverse gamma prior. The proposed estimators are compared with the estimators obtained by Madi and Leonard (1996). It has been noticed from our numerical study that the proposed Bayes estimators outperform the existing estimators when it is known a priori that the location parameters are ordered. The percentage of relative risk improvements have been tabulated for illustration purposes.
机译:估计两个指数群体的共同规模参数的问题被认为是在已知位置参数遵循一定的排序时的先验之后,考虑了两个指数填充的问题。丢失功能被视为二次或加权平方误差。假设对位置参数的订单限制,我们提出了使用模糊的之前的凸起估计器(已经获得了确切的表达式),并且先前有条件逆伽马。将拟议的估算者与Madi和Leonard(1996年)获得的估算值进行比较。从我们的数值研究中已经注意到,当已知已知位置参数被命令时,所提出的贝叶斯估计器越优于现有的估计。为了说明目的,已经表明了相对风险改进的百分比。

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