多元线性模型回归系数的压缩LS估计*
The Compression LS Estimate of Regression Coefficient in Multivariate Linear Model
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摘要: 本文采用压缩LS估计 来估计设计矩阵呈病态的多元线性模型的回归系数B.通过k值的选取,可使 =Vec 的均方误差MSB小于β=Vec(B)的LS估计β*的MSE.证明了 具有可容许性、抗干扰性和有效性,并给出了实际应用中选取k值的方法.Abstract: In this paper,compression LS estimate of the regression coefficient B is considered when the design matrix present ill-condition in multivariate linear model.The MSE(mean square error)of the estimate =Vec is less than theMSE of LS estimate β* of the regression coefficient β= Vec(B) by choosing the pa-rameter k.Admissibility,numerical stability and relative efficiency of )are proved.The method of determining k value for practical use is also suggested.
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