rvif - Collinearity Detection using Redefined Variance Inflation Factor
and Graphical Methods
The detection of troubling approximate collinearity in a
multiple linear regression model is a classical problem in
Econometrics. This package is focused on determining whether or
not the degree of approximate multicollinearity in a multiple
linear regression model is of concern, meaning that it affects
the statistical analysis (i.e. individual significance tests)
of the model. This objective is achieved by using the variance
inflation factor redefined and the scatterplot between the
variance inflation factor and the coefficient of variation. For
more details see Salmerón R., García C.B. and García J. (2018)
<doi:10.1080/00949655.2018.1463376>, Salmerón, R., Rodríguez,
A. and García C. (2020) <doi:10.1007/s00180-019-00922-x>,
Salmerón, R., García, C.B, Rodríguez, A. and García, C. (2022)
<doi:10.32614/RJ-2023-010>, Salmerón, R., García, C.B. and
García, J. (2025) <doi:10.1007/s10614-024-10575-8> and
Salmerón, R., García, C.B, García J. (2023, working paper)
<doi:10.48550/arXiv.2005.02245>. You can also view the package
vignette using 'browseVignettes("rvif")', the package website
(<https://www.ugr.es/local/romansg/rvif/index.html>) using
'browseURL(system.file("docs/index.html", package = "rvif"))'
or version control on GitHub
(<https://github.com/rnoremlas/rvif_package>).
