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Gauss-Markoff估计的协方差改进形式及其在SUR模型中的应用 被引量:2

The Covariance Adjustment Version of Gauss-Markoff Estimator and Its Application to Seemingly Unrelated Regression Equations
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摘要 本文采用并推广Rao[1]的协方差改进原理,证明了线性模型(1.1)的Gauaa-Markoff估计(1.2)具有协方差改进形式=(X′X)-1X′Y-(X′X)-1X′VN[NVN]+NY,其中N=I-X(X′X)-1X′.这一结果用于SUR系统yi=Xiβi+εi(i=1,2,…,m),容易得到Zellner两步估计的有限样本性质.本文得到了一类系统的有限样本方差结果,从而完善了一些已有结果. A lemma of Rao’s covariance adjustment theory is extended, and the Gauss-Markoff estimator β of β in linear model Y = Xβ+ ε,ε~ (0, V) is given as β= (X′X)-1X′Y - (X′X)-1X′VN.(NVN)+NY, where N = I - X(X′X)-1X′. The application of this version to the system of Seemingly Unrelated Regression (SUR) equations: yi = Xiβi +εi(i = 1,…, m) is considered, and some exact finite sample results in a class of SUR system with P1=…= Pk, Pk+1 =…= Pm,P1Pm = Pm P1 are obtained
作者 刘金山
机构地区 五邑大学
出处 《应用概率统计》 CSCD 北大核心 1997年第4期413-420,共8页 Chinese Journal of Applied Probability and Statistics
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