异方差下OLS方差的极大极小偏估计

Mumtaz Ahmed, A. Zaman
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引用次数: 0

摘要

异方差一致性协方差矩阵估计(HCCME)的分析评价由于现有公式的复杂性而变得困难。我们得到了标准线性回归模型中OLS协方差矩阵的一类估计量的偏差的新的解析公式。这些公式提供了对这些估计器的属性和性能特征的深入了解。特别是,我们发现了一个新的估计量,它最小化了最大可能偏差,并且在标准的Eicker-White估计的基础上有了很大的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Minimax Bias Estimator for OLS Variances Under Heteroskedasticity
Analytic evaluation of heteroskedasticity consistent covariance matrix estimates (HCCME) is difficult because of the complexity of the formulae currently available. We obtain new analytic formulae for the bias of a class of estimators of the covariance matrix of OLS in a standard linear regression model. These formulae provide substantial insight into the properties and performance characteristics of these estimators. In particular, we find a new estimator which minimizes the maximum possible bias and improves substantially on the standard Eicker-White estimate.
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