The Location Parameter Estimation of Spherically Distributions with Known Covariance Matrices

M. Afshari, H. Karamikabir
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Abstract

This paper presents shrinkage estimators of the location parameter vector for spherically symmetric distributions. We suppose that the mean vector is non-negative constraint and the components of diagonal covariance matrix is known. We compared the present estimator with natural estimator by using risk function. We show that when the covariance matrices are known, under the balance error loss function, shrinkage estimator has the smaller risk than the natural estimator. Simulation results are provided to examine the shrinkage estimators.
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具有已知协方差矩阵的球面分布的位置参数估计
本文给出了球对称分布的位置参数向量的收缩估计。我们假设均值向量是非负约束,并且对角协方差矩阵的分量是已知的。利用风险函数将现有估计量与自然估计量进行了比较。我们证明了当协方差矩阵已知时,在平衡误差损失函数下,收缩估计量比自然估计量具有更小的风险。提供了仿真结果来检验收缩估计量。
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