Tukey M鲁棒回归方法抗多重共线性的脆弱性

F. Karadag, H. Sazak
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引用次数: 0

摘要

在这项研究中,我们研究了Tukey M稳健回归方法是否为遭受多重共线性问题的数据集提供了解决方案。可以观察到,方差膨胀因子(VIF)的高值是解释变量之间多重线性联系的标志,不能通过处理残差值的稳健方法来控制。这一事实的原因是多重共线性和作为多重共线性的结果的VIF的高值不会产生极端残差。因此,鲁棒方法不能为高VIF问题提供解决方案。一项广泛的模拟研究表明了这一事实。在模拟研究中,解释变量是根据三个不同相关值的三元正态分布得出的。在这项研究中,我们还使用了两个真实的数据示例,我们观察到结果支持模拟研究的结果。由于所有这些原因,我们可以得出结论,在多重共线性的情况下应该使用专门的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vulnerability of the Tukey M Robust Regression Method Against Multicollinearity
In this study, we investigate whether the Tukey M robust regression method provides a solution for the data sets suffering from multicollinearity problem. It is observed that high values of variance inflation factors (VIF) which is a sign of the multiple linear link among the explanatory variables, cannot be controlled by the robust methods which work through the residual values. The reason for this fact is that multicollinearity and high values of VIF which is a result of multicollinearity do not produce extreme residuals. For this reason, the robust methods cannot provide a solution for the high VIF problem. This fact is shown by an extensive simulation study. In the simulation study, the explanatory variables were derived from trivariate normal distribution for three different correlation values. In this study, we also used two real-life data examples and we observed that the results support the findings of the simulation study. For all these reasons, we can conclude that specialized methods should be utilized in the case of multicollinearity.
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