A Bayesian Binary reciprocal LASSO quantile regression (with practical application)
Quantile regression is one of the methods that has taken a wide space in application in the previous two decades because of the attractive features of these methods to researchers, as it is not affected by outliers values, meaning that it is considered one of the robust methods, and it gives more d...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Faculty of Computer Science and Mathematics, University of Kufa
2023-03-01
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| Series: | Journal of Kufa for Mathematics and Computer |
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| Online Access: | https://journal.uokufa.edu.iq/index.php/jkmc/article/view/10380 |
| _version_ | 1797756498594496512 |
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| author | Mohammed Kahnger Ahmad Naeem Flaih |
| author_facet | Mohammed Kahnger Ahmad Naeem Flaih |
| author_sort | Mohammed Kahnger |
| collection | DOAJ |
| description |
Quantile regression is one of the methods that has taken a wide space in application in the previous two decades because of the attractive features of these methods to researchers, as it is not affected by outliers values, meaning that it is considered one of the robust methods, and it gives more details of the effect of explanatory variables on the dependent variable.In this paper, a Bayesian hierarchical model for variable selection and estimation in the context of binary quantile regression is proposed. Current approaches to variable selection in the context of binary classification are sensitive to outliers, heterogeneous values, and other anomalies. The proposed method in this study overcomes these problems in an attractive and direct way.
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| first_indexed | 2024-03-12T18:02:23Z |
| format | Article |
| id | doaj.art-52193c7a04c345f1acd739ed22903c11 |
| institution | Directory Open Access Journal |
| issn | 2076-1171 2518-0010 |
| language | English |
| last_indexed | 2024-03-12T18:02:23Z |
| publishDate | 2023-03-01 |
| publisher | Faculty of Computer Science and Mathematics, University of Kufa |
| record_format | Article |
| series | Journal of Kufa for Mathematics and Computer |
| spelling | doaj.art-52193c7a04c345f1acd739ed22903c112023-08-02T09:35:46ZengFaculty of Computer Science and Mathematics, University of KufaJournal of Kufa for Mathematics and Computer2076-11712518-00102023-03-0110110.31642/JoKMC/2018/100102A Bayesian Binary reciprocal LASSO quantile regression (with practical application) Mohammed Kahnger0Ahmad Naeem Flaih1University of KufaUniversity of Al-Qadisiyah Quantile regression is one of the methods that has taken a wide space in application in the previous two decades because of the attractive features of these methods to researchers, as it is not affected by outliers values, meaning that it is considered one of the robust methods, and it gives more details of the effect of explanatory variables on the dependent variable.In this paper, a Bayesian hierarchical model for variable selection and estimation in the context of binary quantile regression is proposed. Current approaches to variable selection in the context of binary classification are sensitive to outliers, heterogeneous values, and other anomalies. The proposed method in this study overcomes these problems in an attractive and direct way. https://journal.uokufa.edu.iq/index.php/jkmc/article/view/10380Quantile regression variable selectionbinary quantile regression. |
| spellingShingle | Mohammed Kahnger Ahmad Naeem Flaih A Bayesian Binary reciprocal LASSO quantile regression (with practical application) Journal of Kufa for Mathematics and Computer Quantile regression variable selection binary quantile regression. |
| title | A Bayesian Binary reciprocal LASSO quantile regression (with practical application) |
| title_full | A Bayesian Binary reciprocal LASSO quantile regression (with practical application) |
| title_fullStr | A Bayesian Binary reciprocal LASSO quantile regression (with practical application) |
| title_full_unstemmed | A Bayesian Binary reciprocal LASSO quantile regression (with practical application) |
| title_short | A Bayesian Binary reciprocal LASSO quantile regression (with practical application) |
| title_sort | bayesian binary reciprocal lasso quantile regression with practical application |
| topic | Quantile regression variable selection binary quantile regression. |
| url | https://journal.uokufa.edu.iq/index.php/jkmc/article/view/10380 |
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