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Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study


Citation

Fitrianto, Anwar and Lee, Ceng Yik (2014) Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study. Journal of Mathematics and Statistics, 10 (1). pp. 25-29. ISSN 1549-3644; ESSN: 1558-6359

Abstract

When independent variables have high linear correlation in a multiple linear regression model, we can have wrong analysis. It happens if we do the multiple linear regression analysis based on common Ordinary Least Squares (OLS) method. In this situation, we are suggested to use ridge regression estimator. We conduct some simulation study to compare the performance of ridge regression estimator and the OLS. We found that Hoerl and Kennard ridge regression estimation method has better performance than the other approaches.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Institute for Mathematical Research
DOI Number: https://doi.org/10.3844/jmssp.2014.25.29
Publisher: Science Publications
Keywords: Multicollinearity; Multiple linear regression; Ridge regression
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 23 Dec 2015 07:07
Last Modified: 23 Dec 2015 07:07
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3844/jmssp.2014.25.29
URI: http://psasir.upm.edu.my/id/eprint/34880
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