Variable selection in multiple linear regression : the influence of individual cases

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dc.contributor.authorSteel, S. J.en_ZA
dc.contributor.authorUys, D. W.en_ZA
dc.date.accessioned2012-07-18T09:37:06Z
dc.date.available2012-07-18T09:37:06Z
dc.date.issued2007
dc.descriptionCITATION: Steel, S. J. & Uys, D. W. 2007. Variable selection in multiple linear regression : the influence of individual cases. ORiON, 23(2):123–136, doi:10.5784/23-2-52.
dc.descriptionThe original publication is available at http://orion.journals.ac.za
dc.description.abstractENGLISH SUMMARY : The influence of individual cases in a data set is studied when variable selection is applied in multiple linear regression. Two different influence measures, based on the Cp criterion and Akaike’s information criterion, are introduced. The relative change in the selection criterion when an individual case is omitted is proposed as the selection influence of the specific omitted case. Four standard examples from the literature are considered and the selection influence of the cases is calculated. It is argued that the selection procedure may be improved by taking the selection influence of individual data cases into account.en_ZA
dc.description.urihttp://orion.journals.ac.za/pub/article/view/52
dc.description.versionPublisher's version
dc.description.versionORiON
dc.format.extent14 pages ; illustrations
dc.identifier.citationSteel, S. J. & Uys, D. W. 2007. Variable selection in multiple linear regression : the influence of individual cases. ORiON, 23(2):123–136, doi:10.5784/23-2-52
dc.identifier.issn2224-0004 (online)
dc.identifier.issn0259-191X (print)
dc.identifier.otherdoi:10.5784/23-2-52
dc.identifier.urihttp://hdl.handle.net/10019.1/21753
dc.language.isoen_ZAen_ZA
dc.publisherOperations Research Society of South Africa
dc.subjectMultiple linear regressionen_ZA
dc.subjectRegression analysisen_ZA
dc.subjectAkaike Information Criterionen_ZA
dc.subjectMallows' Cpen_ZA
dc.subjectVariables (Mathematics) -- Statistical methodsen_ZA
dc.titleVariable selection in multiple linear regression : the influence of individual casesen_ZA
dc.typeArticleen_ZA
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