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dc.contributor.authorKan Kılınç, Betül
dc.contributor.authorAlpu, Özlem
dc.date.accessioned2019-10-20T09:31:45Z
dc.date.available2019-10-20T09:31:45Z
dc.date.issued2015
dc.identifier.issn0120-1751
dc.identifier.urihttps://dx.doi.org/10.15446/rce.v38n2.51675
dc.identifier.urihttps://hdl.handle.net/11421/17780
dc.description.abstractIn the case of multicollinearity and outliers in regression analysis, the researchers are encouraged to deal with two problems simultaneously. Biased methods based on robust estimators are useful for estimating the regression coefficients for such cases. In this study we examine some robust biased estimators on the datasets with outliers in x direction and outliers in both x and y direction from literature by means of the R package ltsbase. Instead of a complete data analysis, robust biased estimators are evaluated using capabilities and features of this packageen_US
dc.language.isoengen_US
dc.publisherUniversidad Nacional de Colombiaen_US
dc.relation.isversionof10.15446/rce.v38n2.51675en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBiased Estimatoren_US
dc.subjectLeast Trimmed Squaresen_US
dc.subjectRobust Estimationen_US
dc.titleCombining some biased estimation methods with least trimmed squares regression and its application [Combinación de algunos métodos de estimación sesgados con regression de mínimos cuadrados recortados y su aplicación]en_US
dc.typearticleen_US
dc.relation.journalRevista Colombiana de Estadisticaen_US
dc.contributor.departmentAnadolu Üniversitesi, Fen Fakültesi, İstatistik Bölümüen_US
dc.identifier.volume38en_US
dc.identifier.issue2en_US
dc.identifier.startpage485en_US
dc.identifier.endpage502en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorKan Kılınç, Betül


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