Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models
The widely used least absolute deviation (LAD) estimator with the smoothly clipped absolute deviation (SCAD) penalty function (abbreviated as LAD-SCAD) is known to produce corrupt estimates in the presence of outlying observations. The problem becomes more complicated when the number of predictors d...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Universiti Putra Malaysia Press
2021
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| Online Access: | http://psasir.upm.edu.my/id/eprint/90419/1/19%20JST-2149-2020.pdf |
| _version_ | 1796982315170136064 |
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| author | Baba, Ishaq Abdullahi Midi, Habshah Leong, Wah June Ibragimov, Gafurjan I. |
| author_facet | Baba, Ishaq Abdullahi Midi, Habshah Leong, Wah June Ibragimov, Gafurjan I. |
| author_sort | Baba, Ishaq Abdullahi |
| collection | UPM |
| description | The widely used least absolute deviation (LAD) estimator with the smoothly clipped absolute deviation (SCAD) penalty function (abbreviated as LAD-SCAD) is known to produce corrupt estimates in the presence of outlying observations. The problem becomes more complicated when the number of predictors diverges. To overcome these problems, the LAD-SCAD based on sure independence screening (SIS) technique is put forward. The SIS method uses the rank correlation screening (RCS) algorithm in the pre-screening step and the traditional Pathwise coordinate descent algorithm for computing the sequence of the regularization parameters in the post screening step for onward model selection. It is now evident that the rank correlation is less robust against outliers. Motivated by these inadequacies, we propose to improvise the LAD-SCAD estimator using robust wrapped correlation screening (WCS) method by replacing the rank correlation in the SIS method with robust wrapped correlation. The proposed estimator is denoted as WCS+LAD-SCAD and will be employed for variable selection. The simulation study and real-life data examples show that the proposed procedure produces more efficient results compared to the existing methods. |
| first_indexed | 2024-03-06T10:50:13Z |
| format | Article |
| id | upm.eprints-90419 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:50:13Z |
| publishDate | 2021 |
| publisher | Universiti Putra Malaysia Press |
| record_format | dspace |
| spelling | upm.eprints-904192021-09-10T09:00:03Z http://psasir.upm.edu.my/id/eprint/90419/ Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models Baba, Ishaq Abdullahi Midi, Habshah Leong, Wah June Ibragimov, Gafurjan I. The widely used least absolute deviation (LAD) estimator with the smoothly clipped absolute deviation (SCAD) penalty function (abbreviated as LAD-SCAD) is known to produce corrupt estimates in the presence of outlying observations. The problem becomes more complicated when the number of predictors diverges. To overcome these problems, the LAD-SCAD based on sure independence screening (SIS) technique is put forward. The SIS method uses the rank correlation screening (RCS) algorithm in the pre-screening step and the traditional Pathwise coordinate descent algorithm for computing the sequence of the regularization parameters in the post screening step for onward model selection. It is now evident that the rank correlation is less robust against outliers. Motivated by these inadequacies, we propose to improvise the LAD-SCAD estimator using robust wrapped correlation screening (WCS) method by replacing the rank correlation in the SIS method with robust wrapped correlation. The proposed estimator is denoted as WCS+LAD-SCAD and will be employed for variable selection. The simulation study and real-life data examples show that the proposed procedure produces more efficient results compared to the existing methods. Universiti Putra Malaysia Press 2021-04-30 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/90419/1/19%20JST-2149-2020.pdf Baba, Ishaq Abdullahi and Midi, Habshah and Leong, Wah June and Ibragimov, Gafurjan I. (2021) Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models. Pertanika Journal of Science & Technology, 29 (2). pp. 1053-1070. ISSN 0128-7680; ESSN: 2231-8526 http://www.pertanika.upm.edu.my/resources/files/Pertanika%20PAPERS/JST%20Vol.%2029%20(2)%20Apr.%202021/19%20JST-2149-2020.pdf |
| spellingShingle | Baba, Ishaq Abdullahi Midi, Habshah Leong, Wah June Ibragimov, Gafurjan I. Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models |
| title | Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models |
| title_full | Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models |
| title_fullStr | Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models |
| title_full_unstemmed | Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models |
| title_short | Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models |
| title_sort | penalized lad scad estimator based on robust wrapped correlation screening method for high dimensional models |
| url | http://psasir.upm.edu.my/id/eprint/90419/1/19%20JST-2149-2020.pdf |
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