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

机译:带阶次限制位置的两个指数种群公共尺度参数的贝叶斯估计

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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:当先验地知道位置参数遵循一定的顺序时,便会考虑估计两个指数总体的公共尺度参数的问题。损失函数被视为二次误差或加权平方误差。假设位置参数受顺序限制,我们提出了使用模糊先验和条件逆伽马先验的贝叶斯估计器(已获得精确表达式)。将提议的估计量与Madi和Leonard(1996)获得的估计量进行比较。从我们的数值研究中已经注意到,当先验地知道位置参数是有序的时,建议的贝叶斯估计器优于现有估计器。出于说明目的,已将相对风险改善的百分比列表化。

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