PERFORMANCE OF RIDGE REGRESSION ESTIMATOR METHODS ON SMALL SAMPLE SIZE BY VARYING CORRELATION COEFFICIENTS: A SIMULATION STUDY | Science Publications

Journal of Mathematics and Statistics

PERFORMANCE OF RIDGE REGRESSION ESTIMATOR METHODS ON SMALL SAMPLE SIZE BY VARYING CORRELATION COEFFICIENTS: A SIMULATION STUDY

Anwar Fitrianto and Lee Ceng Yik

DOI : 10.3844/jmssp.2014.25.29

Journal of Mathematics and Statistics

Volume 10, Issue 1

Pages 25-29

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.

Copyright

© 2014 Anwar Fitrianto and Lee Ceng Yik. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.