SLASSO: a scaled LASSO for multicollinear situations

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dc.authoridArashi, Mohammad/0000-0002-5881-9241
dc.authoridYuzbasi, Bahadir/0000-0002-6196-3201
dc.authoridAsar, Yasin/0000-0003-1109-8456
dc.authorwosidArashi, Mohammad/ABD-3395-2020
dc.authorwosidYuzbasi, Bahadir/F-6907-2013
dc.authorwosidAsar, Yasin/V-5701-2017
dc.contributor.authorArashi, Mohammad
dc.contributor.authorAsar, Yasin
dc.contributor.authorYuzbasi, Bahadir
dc.date.accessioned2024-08-04T20:50:15Z
dc.date.available2024-08-04T20:50:15Z
dc.date.issued2021
dc.departmentİnönü Üniversitesien_US
dc.description.abstractWe propose a re-scaled LASSO by pre-multiplying the LASSO with a matrix term, namely, scaled LASSO (SLASSO), for multicollinear situations. Our numerical study has shown that the SLASSO is comparable with other sparse modeling techniques and often outperforms the LASSO and elastic net. Our findings open new visions about using the LASSO still for sparse modeling and variable selection. We conclude our study by pointing that the same efficient algorithm can solve the SLASSO for solving the LASSO and suggest following the same construction technique for other penalized estimatorsen_US
dc.description.sponsorshipFerdowsi University of Mashhad [N.2/54466]en_US
dc.description.sponsorshipThis work was supported by Ferdowsi University of Mashhad [N.2/54466].en_US
dc.identifier.doi10.1080/00949655.2021.1924174
dc.identifier.endpage3183en_US
dc.identifier.issn0094-9655
dc.identifier.issn1563-5163
dc.identifier.issue15en_US
dc.identifier.scopus2-s2.0-85106308953en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage3170en_US
dc.identifier.urihttps://doi.org/10.1080/00949655.2021.1924174
dc.identifier.urihttps://hdl.handle.net/11616/99944
dc.identifier.volume91en_US
dc.identifier.wosWOS:000649187700001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofJournal of Statistical Computation and Simulationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBiasing parameteren_US
dc.subjectL-1-penaltyen_US
dc.subjectLASSOen_US
dc.subjectLiu estimationen_US
dc.subjectMulticollinearityen_US
dc.subjectvariable selectionen_US
dc.titleSLASSO: a scaled LASSO for multicollinear situationsen_US
dc.typeArticleen_US

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