Employing Ridge Regression Procedure to Remedy the Multicollinearity Problem
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Abstract
In this paper we introduce many different Methods of ridge regression to solve multicollinearity problem in linear regression model. These Methods include two types of ordinary ridge regression (ORR1), (ORR2) according to the choice of ridge parameter as well as generalized ridge regression (GRR). These methods were applied on a dataset suffers from a high degree of multicollinearity, then according to the criterion of mean square error (MSE) and coefficient of determination (R2) it was found that (GRR) method performs better than the other two methods.
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How to Cite
[1]
Gorgees, H. M. and Ali, B. A. 2017. Employing Ridge Regression Procedure to Remedy the Multicollinearity Problem. Ibn AL-Haitham Journal For Pure and Applied Sciences. 26, 1 (May 2017), 320–327.
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Mathematics
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