Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study
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 esti...
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| Main Authors: | , |
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| Format: | Article |
| Published: |
Science Publications
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/34880/ http://thescipub.com/abstract/10.3844/jmssp.2014.25.29 |
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| Summary: | 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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