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Two New Relative Efficiencies of the Weighted Mixed Estimator with Respect to the Ordinary Least Squares Estimator in Linear Regression Models

ISSN号：2095-2651
期刊名称：《数学研究及应用：英文版》
时间：0
分类：O212.1[理学—概率论与数理统计;理学—数学] O178[理学—数学;理学—基础数学]
作者机构：[1]School of Mathematics and Finances, Chongqing University of Arts and Sciences, Chongqing 402160, P. R. China, [2]Key Laboratory of Group & Graph Theories and Applications, Chongqing University of Arts and Sciences, Chongqing 402160, P. R. China
相关基金：Supported by the National Natural Science Foundation of China （Grant Nos. 11501072 11501254）, the Natural Science Foundation Project of CQ CSTC （Grant No. cstc2015jcyjA00001） and the Scientific and Technological Research Program of Chongqing Municipal Education Commission （Grant No. KJ1501114）.

作者： Min LI[1], Jibo WU[1,2]

关键词：相对效率, 混合估计, 线性回归模型, 加权, 最小二乘估计, ordinary least squares estimator, weighted mixed estimator, relative efficiency, linear regression models

中文摘要：

In this paper, we present two relative efficiency of the weighted mixed estimator in respect of least squares estimator. We also derive the lower and upper bounds of those relative efficiencies.

英文摘要：

In this paper, we present two relative efficiency of the weighted mixed estimator in respect of least squares estimator. We also derive the lower and upper bounds of those relative efficiencies.

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