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A Regularized Estimator For Linear Regression Model With Possibly Singular Covariance

机译:可能具有奇异协方差的线性回归模型的正则估计

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摘要

A regularized estimator is proposed for regression models in the case where the covariances may be singular. Conditions guaranteeing proximity of a regularized estimator to the optimal estimator are obtained by appropriate choice of regularization parameters by allowing a prescribed level of uncertainty. A simple Monte-Carlo simulation study is reported to highlight some aspects and performance of the proposed approach.
机译:在协方差可能是奇异的情况下,建议对回归模型使用正则估计量。通过允许规定水平的不确定性,通过适当选择正则化参数来获得保证正则化估计量与最佳估计量接近的条件。据报道,一项简单的蒙特卡洛模拟研究突出了该方法的某些方面和性能。

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