椭圆轮廓分布下两样本问题中尺度矩阵的同时估计

Hisayuki Tsukuma, Yoshihiko Konno
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引用次数: 2

摘要

研究了椭圆轮廓分布下p × p尺度矩阵估计的两样本问题。采用两个损失函数;一个是估计正态协方差矩阵的单样本问题的Stein损失函数的和,另一个是Σ2Σ−11的二次损失函数,其中Σ1和Σ2是椭圆轮廓分布模型的p × p尺度矩阵。结果表明,在椭圆轮廓分布模型下,在正态假设下得到的改进估计量仍然是鲁棒的。用蒙特卡罗方法对改进的估计器在三种椭圆分布下的风险性能进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SIMULTANEOUS ESTIMATION OF SCALE MATRICES IN TWO-SAMPLE PROBLEM UNDER ELLIPTICALLY CONTOURED DISTRIBUTIONS
Two-sample problems of estimating p × p scale matrices are investigated under elliptically contoured distributions. Two loss functions are employed; one is sum of Stein’s loss functions of one-sample problem of estimating a normal covariance matrix and the other is a quadratic loss function for Σ2Σ −1 1 , where Σ1 and Σ2 are p × p scale matrices of elliptically contoured distribution models. It is shown that improvement of the estimators obtained under the normality assumption remains robust under elliptically contoured distribution models. A Monte Carlo study is also conducted to evaluate the risk performances of the improved estimators under three elliptically contoured distributions.
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