Research Article Open Access

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

Anwar Fitrianto1 and Lee Ceng Yik1
  • 1 Universiti Putra Malaysia, Malaysia

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.

Journal of Mathematics and Statistics
Volume 10 No. 1, 2014, 25-29

DOI: https://doi.org/10.3844/jmssp.2014.25.29

Submitted On: 5 November 2013 Published On: 3 January 2014

How to Cite: Fitrianto, A. & Yik, L. C. (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), 25-29. https://doi.org/10.3844/jmssp.2014.25.29

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Keywords

  • Multicollinearity
  • Multiple Linear Regression
  • Ridge Regression