The performance of classical and robust logistic regression estimators in the presence of outliers
It is now evident that the estimation of logistic regression parameters, using Maximum Likelihood Estimator(MLE), suffers a huge drawback in the presence of outliers. An alternative approach is to use robust logistic regression estimators, such as Mallows type leverage dependent weights estimator (...
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| 格式: | 文件 |
| 语言: | English |
| 出版: |
Universiti Putra Malaysia Press
2012
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| 在线阅读: | http://psasir.upm.edu.my/id/eprint/40467/1/16.%20The%20Performance%20of%20Classical%20and%20Robust%20Logistic%20Regression.pdf |
| _version_ | 1825949606966460416 |
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| author | Midi, Habshah Ariffin @ Mat Zin, Syaiba Balqish |
| author_facet | Midi, Habshah Ariffin @ Mat Zin, Syaiba Balqish |
| author_sort | Midi, Habshah |
| collection | UPM |
| description | It is now evident that the estimation of logistic regression parameters, using Maximum Likelihood Estimator(MLE), suffers a huge drawback in the presence of outliers. An alternative approach is to use robust logistic regression estimators, such as Mallows type leverage dependent weights estimator (MALLOWS, Conditionally Unbiased Bounded Influence Function estimator (CUBIF), Bianco and Yohai estimator (BY), and Weighted Bianco and Yohai estimator (WBY). This paper investigates the robustness of the preceding robust estimators by using real data sets and Monte Carlo simulations. The
results indicate that the MLE behaves poorly in the presence of outliers. On the other hand, the WBY estimator is more efficient than the other existing robust estimators. Thus, it is suggested that the WBY estimator be employed when outliers are present in the data to obtain a reliable estimate. |
| first_indexed | 2024-03-06T08:47:09Z |
| format | Article |
| id | upm.eprints-40467 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T08:47:09Z |
| publishDate | 2012 |
| publisher | Universiti Putra Malaysia Press |
| record_format | dspace |
| spelling | upm.eprints-404672015-11-04T04:01:37Z http://psasir.upm.edu.my/id/eprint/40467/ The performance of classical and robust logistic regression estimators in the presence of outliers Midi, Habshah Ariffin @ Mat Zin, Syaiba Balqish It is now evident that the estimation of logistic regression parameters, using Maximum Likelihood Estimator(MLE), suffers a huge drawback in the presence of outliers. An alternative approach is to use robust logistic regression estimators, such as Mallows type leverage dependent weights estimator (MALLOWS, Conditionally Unbiased Bounded Influence Function estimator (CUBIF), Bianco and Yohai estimator (BY), and Weighted Bianco and Yohai estimator (WBY). This paper investigates the robustness of the preceding robust estimators by using real data sets and Monte Carlo simulations. The results indicate that the MLE behaves poorly in the presence of outliers. On the other hand, the WBY estimator is more efficient than the other existing robust estimators. Thus, it is suggested that the WBY estimator be employed when outliers are present in the data to obtain a reliable estimate. Universiti Putra Malaysia Press 2012 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/40467/1/16.%20The%20Performance%20of%20Classical%20and%20Robust%20Logistic%20Regression.pdf Midi, Habshah and Ariffin @ Mat Zin, Syaiba Balqish (2012) The performance of classical and robust logistic regression estimators in the presence of outliers. Pertanika Journal of Science & Technology, 20 (2). pp. 313-325. ISSN 0128-7680; ESSN: 2231-8526 http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2020%20%282%29%20Jul.%202012/09%20Pg%20313-325.pdf |
| spellingShingle | Midi, Habshah Ariffin @ Mat Zin, Syaiba Balqish The performance of classical and robust logistic regression estimators in the presence of outliers |
| title | The performance of classical and robust logistic regression
estimators in the presence of outliers
|
| title_full | The performance of classical and robust logistic regression
estimators in the presence of outliers
|
| title_fullStr | The performance of classical and robust logistic regression
estimators in the presence of outliers
|
| title_full_unstemmed | The performance of classical and robust logistic regression
estimators in the presence of outliers
|
| title_short | The performance of classical and robust logistic regression
estimators in the presence of outliers
|
| title_sort | performance of classical and robust logistic regression estimators in the presence of outliers |
| url | http://psasir.upm.edu.my/id/eprint/40467/1/16.%20The%20Performance%20of%20Classical%20and%20Robust%20Logistic%20Regression.pdf |
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