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On the performance of two parameter ridge estimator under the mean square error criterion

机译:均方误差准则下两参数岭估计的性能

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摘要

Lipovetsky and Conklin [12] proposed an estimator, two parameter ridge (ridge-2) estimator, as an alternative to the ordinary least squares (OLS) and the ordinary ridge (ridge-1) estimators in the presence of multicollinearity. Lipovetsky [13] improved the two parameter model and investigated various characteristics of ridge-2 solutions. In this paper, we compare ridge-2 estimator with the OLS, ridge-1 and contraction estimators with respect to matrix mean square error (MSE) criterion. A numerical example from the literature has been analyzed to evaluate the performance of mentioned estimators in the theoretical results.
机译:Lipovetsky和Conklin [12]提出了一种估计器,即在存在多重共线性的情况下,两个参数脊(ridge-2)估计器可以替代普通最小二乘(OLS)和普通脊(ridge-1)估计器。 Lipovetsky [13]改进了两个参数模型并研究了ridge-2解的各种特征。在本文中,我们就矩阵均方误差(MSE)准则比较了ridge-2估计量与OLS,ridge-1和收缩估计量。分析了文献中的一个数值示例,以评估理论结果中提到的估计量的性能。

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