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dc.contributor.authorSalmerón Gómez, Román
dc.contributor.authorGarcía García, Catalina Beatriz
dc.contributor.authorGarcía Pérez, José
dc.date.accessioned2020-06-08T09:41:39Z
dc.date.available2020-06-08T09:41:39Z
dc.date.issued2020-06-07
dc.identifier.issn2227-7390
dc.identifier.urihttp://hdl.handle.net/10835/8293
dc.description.abstractThis paper analyzes the diagnostic of near-multicollinearity in a multiple linear regression from auxiliary centered (with intercept) and noncentered (without intercept) regressions. From these auxiliary regressions, the centered and noncentered variance inflation factors (VIFs) are calculated. An expression is also presented that relates both of them. In addition, this paper analyzes why the VIF is not able to detect the relation between the intercept and the rest of the independent variables of an econometric model. At the same time, an analysis is also provided to determine how the auxiliary regression applied to calculate the VIF can be useful to detect this kind of multicollinearity.es_ES
dc.language.isoenes_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectcentered modeles_ES
dc.subjectnoncentered modeles_ES
dc.subjectinterceptes_ES
dc.subjectessential multicollinearites_ES
dc.subjectnonessential multicollinearityes_ES
dc.titleDetection of Near-Nulticollinearity through Centered and Noncentered Regressiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://www.mdpi.com/2227-7390/8/6/931es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional