@misc{10481/62392,
year = {2020},
month = {4},
url = {http://hdl.handle.net/10481/62392},
abstract = {The 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.},
publisher = {MDPI},
keywords = {Detection},
keywords = {Mean square error},
keywords = {Multicollinearity},
keywords = {Raise regression},
keywords = {Variance inflation factor},
title = {The VIF and MSE in Raise Regression},
doi = {doi:10.3390/math8040605},
author = {Salmerón Gómez, Román  and Rodríguez Sánchez, Ainara and García García, Catalina},
}