Group Variable Selection Methods with Quantile Regression: A Simulation Study.
In many cases, covariates have a grouping structure that can be used in the analysis to identify important groups and the significant members of those groups. This paper reviews some group variable selection methods that utilize quantile regression. The study compares seven previously proposed group...
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| Format: | Article |
| Language: | Arabic |
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College of Computer Science and Mathematics, University of Mosul
2025-06-01
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| Series: | المجلة العراقية للعلوم الاحصائية |
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| Online Access: | https://stats.uomosul.edu.iq/article_187759_4911919339b73a13b131ebcd6427170e.pdf |
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| _version_ | 1839651070608932864 |
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| author | Hussein Hashem |
| author_facet | Hussein Hashem |
| author_sort | Hussein Hashem |
| collection | DOAJ |
| description | In many cases, covariates have a grouping structure that can be used in the analysis to identify important groups and the significant members of those groups. This paper reviews some group variable selection methods that utilize quantile regression. The study compares seven previously proposed group variable selection methods, namely the group Lasso estimate, the quantile group Lasso (median group Lasso) estimate, the quantile group adaptive Lasso estimate, the sparse group Lasso estimate, the group scad estimate, the group mcp estimate, and the group gel estimate through a simulation study. The simulation study helps determine which methods perform best in all linear regression scenarios. |
| format | Article |
| id | doaj-art-6fb8d6b324f048158f78e8d4649b3b51 |
| institution | Matheson Library |
| issn | 1680-855X 2664-2956 |
| language | Arabic |
| publishDate | 2025-06-01 |
| publisher | College of Computer Science and Mathematics, University of Mosul |
| record_format | Article |
| series | المجلة العراقية للعلوم الاحصائية |
| spelling | doaj-art-6fb8d6b324f048158f78e8d4649b3b512025-06-26T12:33:11ZaraCollege of Computer Science and Mathematics, University of Mosulالمجلة العراقية للعلوم الاحصائية1680-855X2664-29562025-06-0122111412610.33899/iqjoss.2025.187759187759Group Variable Selection Methods with Quantile Regression: A Simulation Study.Hussein Hashem0Department of Mathematics, College of Science, University of Duhok, Kurdistan Region, Iraq.In many cases, covariates have a grouping structure that can be used in the analysis to identify important groups and the significant members of those groups. This paper reviews some group variable selection methods that utilize quantile regression. The study compares seven previously proposed group variable selection methods, namely the group Lasso estimate, the quantile group Lasso (median group Lasso) estimate, the quantile group adaptive Lasso estimate, the sparse group Lasso estimate, the group scad estimate, the group mcp estimate, and the group gel estimate through a simulation study. The simulation study helps determine which methods perform best in all linear regression scenarios.https://stats.uomosul.edu.iq/article_187759_4911919339b73a13b131ebcd6427170e.pdfvariable selection؛ group variable selection؛ quantile regressiongroup lassoregularization |
| spellingShingle | Hussein Hashem Group Variable Selection Methods with Quantile Regression: A Simulation Study. المجلة العراقية للعلوم الاحصائية variable selection؛ group variable selection؛ quantile regression group lasso regularization |
| title | Group Variable Selection Methods with Quantile Regression: A Simulation Study. |
| title_full | Group Variable Selection Methods with Quantile Regression: A Simulation Study. |
| title_fullStr | Group Variable Selection Methods with Quantile Regression: A Simulation Study. |
| title_full_unstemmed | Group Variable Selection Methods with Quantile Regression: A Simulation Study. |
| title_short | Group Variable Selection Methods with Quantile Regression: A Simulation Study. |
| title_sort | group variable selection methods with quantile regression a simulation study |
| topic | variable selection؛ group variable selection؛ quantile regression group lasso regularization |
| url | https://stats.uomosul.edu.iq/article_187759_4911919339b73a13b131ebcd6427170e.pdf |
| work_keys_str_mv | AT husseinhashem groupvariableselectionmethodswithquantileregressionasimulationstudy |