Collinearity: revisiting the variance inflation factor in ridge regression García García, Catalina García Pérez, José López Martín, María Del Mar Salmerón Gómez, Román Multicolinealidad Multicollinearity Ridge Regression Variance inflation factor This paper has been partially supported by the project ‘Valoración de proyectos gubernamentales a largo plazo: obtención de la tasa social de descuento’, reference: P09-SEJ-05404, Proyectos de Excelencia de la Junta de Andalucía and Fondos FEDER. Ridge regression has been widely applied to estimate under collinearity by defining a class of estimators that are dependent on the parameter k. The variance inflation factor (VIF) is applied to detect the presence of collinearity and also as an objective method to obtain the value of k in ridge regression. Contrarily to the definition of the VIF, the expressions traditionally applied in ridge regression do not necessarily lead to values of VIFs equal to or greater than 1. This work presents an alternative expression to calculate the VIF in ridge regression that satisfies the aforementioned condition and also presents other interesting properties. 2024-02-29T09:04:57Z 2024-02-29T09:04:57Z 2014 journal article Published version: C.B. García, J. García, M.M. López Martín & R. Salmerón (2015) Collinearity: revisiting the variance inflation factor in ridge regression, Journal of Applied Statistics, 42:3, 648-661. https://doi.org/10.1080/02664763.2014.980789 https://hdl.handle.net/10481/89668 10.1080/02664763.2014.980789 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Taylor and Francis