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rvif  

Collinearity Detection using Redefined Variance Inflation Factor and Graphical Methods
View on CRAN: Click here


Download and install rvif package within the R console
Install from CRAN:
install.packages("rvif")

Install from Github:
library("remotes")
install_github("cran/rvif")

Install by package version:
library("remotes")
install_version("rvif", "1.0")



Attach the package and use:
library("rvif")
Maintained by
R. Salmerón
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-22
Latest Update: 2022-12-22
Description:
The detection of troubling approximate collinearity in a multiple linear regression model is a classical problem in Econometrics. The objective of this package is to detect it 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. "Limitations in Detecting Multicollinearity due to Scaling Issues in the mcvis Package" (2022, to appear in The R Journal) and Salmerón, R., García, C.B, García J. (2023, working paper) <doi:10.48550/arXiv.2005.02245>.
How to cite:
R. Salmerón (2022). rvif: Collinearity Detection using Redefined Variance Inflation Factor and Graphical Methods. R package version 1.0, https://cran.r-project.org/web/packages/rvif
Previous versions and publish date:
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Functions, R codes and Examples using the rvif R package
Some associated functions: CV_VIF . RVIF . rvif-package . 
Some associated R codes: CV_VIF.R . RVIF.R .  Full rvif package functions and examples
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