Variable selection in multiple linear regression : the influence of individual cases
Date
2007
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Operations Research Society of South Africa
Abstract
ENGLISH 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.
Description
CITATION: 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.
The original publication is available at http://orion.journals.ac.za
The original publication is available at http://orion.journals.ac.za
Keywords
Multiple linear regression, Regression analysis, Akaike Information Criterion, Mallows' Cp, Variables (Mathematics) -- Statistical methods
Citation
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