Combining principal component and robust ridge estimators in linear regression model with multicollinearity and outlier

被引:7
|
作者
Arum, Kingsley Chinedu [1 ]
Ugwuowo, Fidelis Ifeanyi [1 ]
机构
[1] Univ Nigeria, Dept Stat, Nsukka, Nigeria
来源
关键词
M-estimator; multicollinearity; outliers; principal component; ridge estimator; LIU-TYPE ESTIMATOR; COMBAT;
D O I
10.1002/cpe.6803
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The method of least squared suffers a setback when there is multicollinearity and outliers in the linear regression model. In this article, we developed a new estimator to jointly handle multicollinearity and outliers by pooling the following estimators together: the M-estimator, the principal component and the ridge estimator. The new estimator is called the robust r-k estimator and is employed. We established theoretically that the new estimator is better than some of the existing ones. The simulation studies and real-life application supports the efficiency of the new method.
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页数:14
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