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>).

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