Show simple item record

dc.contributor.authorSalmerón Gómez, Román
dc.contributor.authorRodríguez Sánchez, Ainara
dc.contributor.authorGarcía García, Catalina
dc.contributor.authorGarcía Pérez, José
dc.date.accessioned2020-04-28T08:07:23Z
dc.date.available2020-04-28T08:07:23Z
dc.date.issued2020-04-16
dc.identifier.issn2227-7390
dc.identifier.urihttp://hdl.handle.net/10835/8101
dc.description.abstractThe raise regression has been proposed as an alternative to ordinary least squares estimation when a model presents collinearity. In order to analyze whether the problem has been mitigated, it is necessary to develop measures to detect collinearity after the application of the raise regression. This paper extends the concept of the variance inflation factor to be applied in a raise regression. The relevance of this extension is that it can be applied to determine the raising factor which allows an optimal application of this technique. The mean square error is also calculated since the raise regression provides a biased estimator. The results are illustrated by two empirical examples where the application of the raise estimator is compared to the application of the ridge and Lasso estimators that are commonly applied to estimate models with multicollinearity as an alternative to ordinary least squares.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.subjectdetectiones_ES
dc.subjectmean square errores_ES
dc.subjectmulticollinearityes_ES
dc.subjectraise regressiones_ES
dc.subjectvariance inflation factores_ES
dc.titleThe VIF and MSE in Raise Regressiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://www.mdpi.com/2227-7390/8/4/605es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


Files in this item

This item appears in the following Collection(s)

Show simple item record

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