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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: Fitrianto, Anwar, Lee, Ceng Yik
Format: Article
Published: Science Publications 2014
Online Access:http://psasir.upm.edu.my/id/eprint/34880/
http://thescipub.com/abstract/10.3844/jmssp.2014.25.29
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spelling my.upm.eprints.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
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
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.
format Article
author Fitrianto, Anwar
Lee, Ceng Yik
spellingShingle Fitrianto, Anwar
Lee, Ceng Yik
Performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study
author_facet Fitrianto, Anwar
Lee, Ceng Yik
author_sort Fitrianto, Anwar
title 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_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_sort performance of ridge regression estimator methods on small sample size by varying correlation coefficients: a simulation study
publisher Science Publications
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/34880/
http://thescipub.com/abstract/10.3844/jmssp.2014.25.29
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score 13.214268

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