A modified ridge m-estimator for linear regression model with multicollinearity and outliers

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dc.contributor.authorErtaş, Hasan
dc.date.accessioned2021-04-01T05:28:08Z
dc.date.available2021-04-01T05:28:08Z
dc.date.issued2018
dc.departmentAÇÜ, Orman Fakültesien_US
dc.description.abstractThe ordinary least-square estimators for linear regression analysis with multicollinearity and outliers lead to unfavorable results. In this article, we propose a new robust modified ridge M-estimator (MRME) based on M-estimator (ME) to deal with the combined problem resulting from multicollinearity and outliers in the y-direction. MRME outperforms modified ridge estimator, robust ridge estimator and ME, according to mean squares error criterion. Furthermore, a numerical example and a Monte Carlo simulation experiment are given to illustrate some of the theoretical results.
dc.identifier.citationErtaş, H. (2018). A modified ridge m-estimator for linear regression model with multicollinearity and outliers. Communications in Statistics-Simulation and Computation, 47(4), 1240-1250, DOI: 10.1080/03610918.2017.1310231en_US
dc.identifier.doi10.1080/03610918.2017.1310231
dc.identifier.endpage1250en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityN/A
dc.identifier.startpage1240en_US
dc.identifier.urihttps://hdl.handle.net/11494/2885
dc.identifier.volume47en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorErtaş, Hasan
dc.language.isoenen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.ispartofCommunications in Statistics-Simulation and Computation
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBiased estimatoren_US
dc.subjectMulticollinearityen_US
dc.subjectOutliersen_US
dc.subjectRobust estimatoren_US
dc.titleA modified ridge m-estimator for linear regression model with multicollinearity and outliersen_US
dc.typeArticle

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