Weighted LAD-Liu-LASSO for robust estimation and sparsity

dc.contributor.authorGenc, Murat
dc.contributor.authorLukman, Adewale
dc.date.accessioned2025-03-17T12:27:39Z
dc.date.available2025-03-17T12:27:39Z
dc.date.issued2025
dc.departmentTarsus Üniversitesi
dc.description.abstractThe Least Absolute Shrinkage and Selection Operator (LASSO) is widely used for parameter estimation and variable selection but can encounter challenges with outliers and heavy-tailed error distributions. Integrating variable selection methods such as LASSO with Weighted Least Absolute Deviation (WLAD) has been explored in limited studies to handle these problems. In this study, we proposed the integration of Weighted Least Absolute Deviation with Liu-LASSO to handle variable selection, parameter estimation, and heavy-tailed error distributions due to the advantages of the Liu-LASSO approach over traditional LASSO methods. This approach is demonstrated through a simple simulation study and real-world application. Our findings showcase the superiority of our method over existing techniques while maintaining the asymptotic efficiency comparable to the unpenalized LAD estimator.
dc.identifier.doi10.1007/s00180-025-01605-6
dc.identifier.issn0943-4062
dc.identifier.issn1613-9658
dc.identifier.scopus2-s2.0-85217248985
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1007/s00180-025-01605-6
dc.identifier.urihttps://hdl.handle.net/20.500.13099/2377
dc.identifier.wosWOS:001410183800001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Heidelberg
dc.relation.ispartofComputational Statistics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250316
dc.subjectLasso
dc.subjectLeast absolute deviation
dc.subjectWeighted estimator
dc.subjectLiu-Lasso
dc.subjectOutliers
dc.subjectVariable selection
dc.titleWeighted LAD-Liu-LASSO for robust estimation and sparsity
dc.typeArticle

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