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Some Matrix Norm Kantorovich Inequalities and Their Applications

机译:一些矩阵常态kantorovich不等式及其应用

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摘要

In this article, we first present four matrix norm Kantorovich-type inequalities involving non negative definite matrix. Then, based on these inequalities, we propose four new efficiency criteria and present their lower bounds to make efficiency comparisons between the ordinary least squares estimator and the best linear unbiased estimator in a singular linear model.
机译:在本文中,我们首先提出四个矩阵常态kantorovich型涉及非负定向矩阵的kantorovich型不等式。然后,基于这些不等式,我们提出了四种新的效率标准,并呈现它们的下部界限,以使普通最小二乘估计器和单个线性模型中最佳线性无偏估计之间的效率比较。

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