Obadina, O. G. and Adedotun, Adedayo F. and Odusanya, Oluwaseun A. (2021) Ridge Estimation’s E�ectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations. Journal of the Nigerian Society of Physical Sciences, 3. pp. 278-281.
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Abstract
The goal of this research is to compare multiple linear regression coe�cient estimation technique with multicollinearity. In order to quantify the e�ectiveness of estimations by the mean of average mean square error, the ordinary least squares technique (OLS), modified ridge regression method (MRR), and generalized Liu-Kejian method (LKM) are compared with the Average Mean Square Error (AMSE). For this study, the simulation scenarios are 3 and 5 independent variables with zero mean normally distributed random error of variance 1, 5, and 10, three correlation coe�cient levels; i.e., low (0.2), medium (0.5), and high (0.8) are determined for independent variables, and all combinations are performed with sample sizes 15, 55, and 95 by Monte Carlo simulation technique for 1,000 times in total. As the sample size rises, the AMSE decreased. The MRR and LKM both outperformed the OLS. At random error of variance 10, the MRR is the most suitable for all circumstances
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Monte-Carlo, Multicollinearity, Regression Model, Ridge Estimation, Simulations |
| Subjects: | Q Science > QA Mathematics |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Mathematics |
| Depositing User: | nwokealisi |
| Date Deposited: | 10 Nov 2023 16:51 |
| Last Modified: | 10 Nov 2023 16:51 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/17577 |
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