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...
| Main Authors: | , |
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| Format: | Article |
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Science Publications
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/34880/ |
| _version_ | 1848847897234243584 |
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| author | Fitrianto, Anwar Lee, Ceng Yik |
| author_facet | Fitrianto, Anwar Lee, Ceng Yik |
| author_sort | Fitrianto, Anwar |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T09:25:54Z |
| format | Article |
| id | upm-34880 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T09:25:54Z |
| publishDate | 2014 |
| publisher | Science Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-348802015-12-23T07:07:39Z http://psasir.upm.edu.my/id/eprint/34880/ Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study Fitrianto, Anwar Lee, Ceng Yik 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. Science Publications 2014 Article PeerReviewed 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 http://thescipub.com/abstract/10.3844/jmssp.2014.25.29 10.3844/jmssp.2014.25.29 |
| spellingShingle | Fitrianto, Anwar Lee, Ceng Yik Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study |
| title | Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study |
| title_full | Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study |
| title_fullStr | Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study |
| title_full_unstemmed | Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study |
| title_short | Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study |
| title_sort | performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study |
| url | http://psasir.upm.edu.my/id/eprint/34880/ http://psasir.upm.edu.my/id/eprint/34880/ http://psasir.upm.edu.my/id/eprint/34880/ |