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Robust Regression-Ratio Estimators of the Mean Utilizing Two Auxiliary Variables: A Simulation Study

dc.authorscopusid55961568600
dc.authorscopusid57191925575
dc.authorscopusid57215302839
dc.authorscopusid57219597501
dc.authorscopusid57194596974
dc.authorscopusid58588147300
dc.authorwosidAudu, Ahmed/Ada-1598-2022
dc.authorwosidHanif, Muhammad/Hjh-5889-2023
dc.authorwosidAlilah, David/Aba-4492-2021
dc.authorwosidShahzad, Usman/Abi-5322-2020
dc.contributor.authorZaman, Tolga
dc.contributor.authorDünder, Emre
dc.contributor.authorAudu, Ahmed
dc.contributor.authorAlilah, David Anekeya
dc.contributor.authorShahzad, Usman
dc.contributor.authorHanif, Muhammad
dc.contributor.authorIDZaman, Tolga/0000-0001-8780-3655
dc.contributor.authorID0000-0002-6520-4464
dc.contributor.authorIDAudu, Ahmed/0000-0002-6915-7589
dc.contributor.authorIDShahzad, Usman/0000-0002-0178-5298
dc.contributor.authorIDAlilah, David/0000-0002-3306-4786
dc.date.accessioned2025-12-11T01:35:14Z
dc.date.issued2021
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Zaman, Tolga] Cankiri Karatekin Univ, Fac Sci, Dept Stat, Cankiri, Turkey; [Dunder, Emre] Ondokuz Mayis Univ, Fac Sci, Dept Stat, Samsun, Turkey; [Audu, Ahmed] Usmanu Danfodiyo Univ, Dept Math, Sokoto, Nigeria; [Alilah, David Anekeya] Masinde Muliro Univ Sci & Technol, Dept Math, Kakamega, Kenya; [Shahzad, Usman; Hanif, Muhammad] PMAS Arid Agr Univ, Dept Math & Stat, Rawalpindi, Pakistanen_US
dc.descriptionZaman, Tolga/0000-0001-8780-3655; , Muhammad Hanif/0000-0002-6520-4464; Audu, Ahmed/0000-0002-6915-7589; Shahzad, Usman/0000-0002-0178-5298; Alilah, David/0000-0002-3306-4786en_US
dc.description.abstractMany authors defined the modified version of the mean estimator by using two auxiliary variables. These proposed estimators highly depend on the calculated regression coefficients. In the presence of outliers, these estimators do not give satisfactory results. In this study, we improve the suggested estimators using several robust regression techniques while obtaining the regression coefficients. We compared the efficiencies between the suggested estimators and the estimators presented in the literature. We used two numerical examples and a simulation study to support these theoretical results. Empirical results show that the modified ratio estimator performs well in the presence of outliers when adopting robust regression techniques.en_US
dc.description.woscitationindexScience Citation Index Expanded
dc.identifier.doi10.1155/2021/6383927
dc.identifier.issn1024-123X
dc.identifier.issn1563-5147
dc.identifier.scopus2-s2.0-85115744572
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1155/2021/6383927
dc.identifier.urihttps://hdl.handle.net/20.500.12712/44695
dc.identifier.volume2021en_US
dc.identifier.wosWOS:000727211500006
dc.language.isoenen_US
dc.publisherHindawi Ltden_US
dc.relation.ispartofMathematical Problems in Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleRobust Regression-Ratio Estimators of the Mean Utilizing Two Auxiliary Variables: A Simulation Studyen_US
dc.typeArticleen_US
dspace.entity.typePublication

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