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dc.contributor.authorSalmerón Gómez, Román 
dc.contributor.authorGarcía Pérez, José
dc.contributor.authorGarcía García, Catalina 
dc.contributor.authorLópez Martín, María Del Mar 
dc.date.accessioned2024-02-22T13:16:13Z
dc.date.available2024-02-22T13:16:13Z
dc.date.issued2017
dc.identifier.citationPublished version: Salmerón, R., García, J., García, C. et al. Transformation of variables and the condition number in ridge estimation. Comput Stat 33, 1497–1524 (2018). https://doi.org/10.1007/s00180-017-0769-4es_ES
dc.identifier.urihttps://hdl.handle.net/10481/89483
dc.description.abstractRidge estimation (RE) is an alternative method to ordinary least squares (OLS) estimation when collinearity is detected in a linear regression model. After applying RE, it is sensible to determine whether such collinearity has been mitigated. The condition number (CN) is a commonly applied measure to detect the presence of collinearity in econometric models, but to the best of our knowledge, it has not been extended to be applied after RE. In OLS estimation, Belsley et al. (Regression diagnostics: identifying influential data and sources of collinearity, Wiley, New York, 1980) established that the regressors must be of unit length and not centered to correctly calculate the CN. This paper reviews this requirement in the context of RE and presents an expression to calculate the CN in RE.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.subjectCollinearityes_ES
dc.subjectRidge Regressiones_ES
dc.subjectCondition Numberes_ES
dc.subjectEconometric Models es_ES
dc.titleTransformation of variables and the condition number in ridge estimationes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1007/s00180-017-0769-4
dc.type.hasVersioninfo:eu-repo/semantics/submittedVersiones_ES


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