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A Guide to Using the R Package “multiColl” for Detecting Multicollinearity

dc.contributor.authorSalmerón Gómez, Román 
dc.contributor.authorGarcía García, Catalina 
dc.contributor.authorGarcía Pérez, José
dc.date.accessioned2024-02-22T13:02:19Z
dc.date.available2024-02-22T13:02:19Z
dc.date.issued2020
dc.identifier.citationPublished version: Salmerón-Gómez, R., García-García, C. & García-Pérez, J. A. Guide to Using the R Package “multiColl” for Detecting Multicollinearity. Comput Econ 57, 529–536 (2021). https://doi.org/10.1007/s10614-019-09967-yes_ES
dc.identifier.urihttps://hdl.handle.net/10481/89480
dc.description.abstractThe detection of problematic collinearity in a linear regression model is treated in all the existing statistical software packages. However, such detection is not always done adequately. The main shortcomings relate to treatment of independent qualitative variables and completely ignoring the role of the intercept in the model (consequently, ignoring the nonessential collinearity). This paper presents the R package multiColl, which implements the usually applied measures for detecting near collinearity while overcoming the weaknesses observed in other existing packages.es_ES
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMulticollinearityes_ES
dc.subjectDetectiones_ES
dc.subjectInterceptes_ES
dc.subjectDummyes_ES
dc.subjectSoftwarees_ES
dc.titleA Guide to Using the R Package “multiColl” for Detecting Multicollinearityes_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1007/s10614-019-09967-y
dc.type.hasVersionSMURes_ES


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