A useful approach to identify the multicollinearity in the presence of outliers

dc.contributor.authorSinan, Alper
dc.contributor.authorAlkan, B. Baris
dc.date.accessioned2025-03-23T19:35:19Z
dc.date.available2025-03-23T19:35:19Z
dc.date.issued2015
dc.departmentSinop Üniversitesi
dc.description.abstractThe presence of outliers in the data sets affects the structure of multicollinearity which arises from a high degree of correlation between explanatory variables in a linear regression analysis. This affect could be seen as an increase or decrease in the diagnostics used to determine multicollinearity. Thus, the cases of outliers reduce the reliability of diagnostics such as variance inflation factors, condition numbers and variance decomposition proportions. In this study, we propose to use a robust estimation of the correlation matrix obtained by the minimum covariance determinant method to determine the diagnostics of multicollinearity in the presence of outliers. As a result, the present paper demonstrates that the diagnostics of multicollinearity obtained by the robust estimation of the correlation matrix are more reliable in the presence of outliers.
dc.identifier.doi10.1080/02664763.2014.993369
dc.identifier.endpage993
dc.identifier.issn0266-4763
dc.identifier.issn1360-0532
dc.identifier.issue5
dc.identifier.scopus2-s2.0-84924246613
dc.identifier.scopusqualityQ1
dc.identifier.startpage986
dc.identifier.urihttps://doi.org/10.1080/02664763.2014.993369
dc.identifier.urihttps://hdl.handle.net/11486/5841
dc.identifier.volume42
dc.identifier.wosWOS:000349904500005
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Ltd
dc.relation.ispartofJournal of Applied Statistics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250323
dc.subjectminimum covariance determinant
dc.subjectoutliers
dc.subjectmulticollinearity
dc.titleA useful approach to identify the multicollinearity in the presence of outliers
dc.typeArticle

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