Effects of a single outlier on the coefficient of determination: an empirical study
This article investigates the effects of outliers on the coefficient of determination, R2 which is computed by Ordinary Least Squares (OLS) estimator. It is now evident that the OLS is greatly affected by outliers and hence the R2 is also affected. This problem can be solved by using the robust esti...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
AIP Publishing LLC
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/57301/1/Effects%20of%20a%20single%20outlier%20on%20the%20coefficient%20of%20determination%20an%20empirical%20study.pdf http://psasir.upm.edu.my/id/eprint/57301/ |
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| Summary: | This article investigates the effects of outliers on the coefficient of determination, R2 which is computed by Ordinary Least Squares (OLS) estimator. It is now evident that the OLS is greatly affected by outliers and hence the R2 is also affected. This problem can be solved by using the robust estimators such as Least Trimmed Squares (LTS) estimator. In this article, we compare the value of R2 which is computed by OLS and LTS estimators. We modify a regression data set to effectively generate outliers in both X and Y directions. Then the coefficient of determination (OLS and LTS) is investigated from the modified data sets (data with outliers). The numerical results show the merit of using the LTS based R2 estimator compared to the OLS estimator. |
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