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Research Article · Free to read · Published 3 January 2014

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

Anwar Fitrianto1 & Lee Ceng Yik1

Journal of Mathematics and Statistics, Volume 10, Issue 1, pp. 25–29 · doi.org/10.3844/jmssp.2014.25.29

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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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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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PERFORMANCE OF RIDGE REGRESSION ESTIMATOR METHODS ON SMALL SAMPLE SIZE BY VARYING CORRELATION COEFFICIENTS: A SIMULATION STUDYJournal of Mathematics and Statistics · Volume 10, Issue 1 · pp. 25–29 · © Science PublicationsDownload