Elastic net for single index support vector regression model
The single index model (SIM) is a useful regression tool used to alleviate the so-called curse of dimensionality. In this paper, we propose a variable selection technique for the SIM by combining the estimation method with the Elastic Net penalized method to get sparse estimation of the index parame...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Academy of Economic Studies
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/14233/1/Elastic%20net%20for%20single%20index%20support%20vector%20regression%20model.pdf |
| _version_ | 1825945389453279232 |
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| author | Dhhan, Waleed Rana, Sohel Alshaybawee, Taha Midi, Habshah |
| author_facet | Dhhan, Waleed Rana, Sohel Alshaybawee, Taha Midi, Habshah |
| author_sort | Dhhan, Waleed |
| collection | UPM |
| description | The single index model (SIM) is a useful regression tool used to alleviate the so-called curse of dimensionality. In this paper, we propose a variable selection technique for the SIM by combining the estimation method with the Elastic Net penalized method to get sparse estimation of the index parameters. Furthermore, we propose the support vector regression (SVR) to estimate the unknown nonparametric link function due to its ability to fit the non-linear relationships and the high dimensional problems. This make the proposed work is not only for estimating the parameters and the unknown link function of the single index model, but also for selecting the important variables simultaneously. Simulations of various single index models with nonlinear relationships among variables are conducted to demonstrate the effectiveness of the proposed semi-parametric estimation and the variable selection versus the existing fully parametric SVR method. Moreover, the proposed method is illustrated by analyzing a real data set. A data analysis is given which highlights the utility of the suggested methodology. |
| first_indexed | 2024-03-06T07:30:46Z |
| format | Article |
| id | upm.eprints-14233 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T07:30:46Z |
| publishDate | 2017 |
| publisher | Academy of Economic Studies |
| record_format | dspace |
| spelling | upm.eprints-142332018-10-08T02:45:45Z http://psasir.upm.edu.my/id/eprint/14233/ Elastic net for single index support vector regression model Dhhan, Waleed Rana, Sohel Alshaybawee, Taha Midi, Habshah The single index model (SIM) is a useful regression tool used to alleviate the so-called curse of dimensionality. In this paper, we propose a variable selection technique for the SIM by combining the estimation method with the Elastic Net penalized method to get sparse estimation of the index parameters. Furthermore, we propose the support vector regression (SVR) to estimate the unknown nonparametric link function due to its ability to fit the non-linear relationships and the high dimensional problems. This make the proposed work is not only for estimating the parameters and the unknown link function of the single index model, but also for selecting the important variables simultaneously. Simulations of various single index models with nonlinear relationships among variables are conducted to demonstrate the effectiveness of the proposed semi-parametric estimation and the variable selection versus the existing fully parametric SVR method. Moreover, the proposed method is illustrated by analyzing a real data set. A data analysis is given which highlights the utility of the suggested methodology. Academy of Economic Studies 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/14233/1/Elastic%20net%20for%20single%20index%20support%20vector%20regression%20model.pdf Dhhan, Waleed and Rana, Sohel and Alshaybawee, Taha and Midi, Habshah (2017) Elastic net for single index support vector regression model. Economic Computation and Economic Cybernetics Studies and Research, 51 (2). pp. 195-210. ISSN 0424-267X; ESSN: 1842-3264 http://www.ecocyb.ase.ro/Articles2017_2.htm |
| spellingShingle | Dhhan, Waleed Rana, Sohel Alshaybawee, Taha Midi, Habshah Elastic net for single index support vector regression model |
| title | Elastic net for single index support vector regression model |
| title_full | Elastic net for single index support vector regression model |
| title_fullStr | Elastic net for single index support vector regression model |
| title_full_unstemmed | Elastic net for single index support vector regression model |
| title_short | Elastic net for single index support vector regression model |
| title_sort | elastic net for single index support vector regression model |
| url | http://psasir.upm.edu.my/id/eprint/14233/1/Elastic%20net%20for%20single%20index%20support%20vector%20regression%20model.pdf |
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