Introduction | cv_vif function | A first example: how to use the function | A second example: construction of the design matrix | A third example: checking some errors | A fourth example: the special case of the simple linear regression model | Final warning regarding the presence of binary variables in the model | plot.cv_vif function | Some examples | rvifs function | multicollinearity function | A first example: Wissel data | A second example: Klein and Goldberger data | A third example: the case of the simple linear regresion | A fourth example: soil characteristics data | Bibliography
Package: rvif 3.2
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>).
Authors:
rvif_3.2.tar.gz
rvif_3.2.tar.gz(r-4.7-any)rvif_3.2.tar.gz(r-4.6-any)
rvif_3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rvif/json (API)
| # Install 'rvif' in R: |
| install.packages('rvif', repos = c('https://rnoremlas.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rnoremlas/rvif_package/issues
Datasets:
Last updated from:7d7a5263a9. Checks:2 ERROR, 2 OK, 5 FAIL. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | ERROR | 199 | ||
| source / vignettes | OK | 197 | ||
| linux-release-x86_64 | ERROR | 202 | ||
| macos-release-arm64 | FAIL | 87 | ||
| macos-oldrel-arm64 | FAIL | 98 | ||
| windows-devel | FAIL | 62 | ||
| windows-release | FAIL | 54 | ||
| windows-oldrel | FAIL | 66 | ||
| wasm-release | OK | 169 |
Exports:cv_vifmulticollinearityplot.cv_vifrvifs
Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvminqamodelrmultiCollnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Detecting multicollinearity using RVIF and graphical methods. | rvif-package rvif |
| Cobb-Douglas data | CDpf |
| VIF and CV calculation | cv_vif |
| VIF, CV and a common scatter plot | CV_VIF |
| Scatterplot of CV vs VIF | cv_vif_plot |
| Spanish company employee data | employees |
| Euribor data | euribor |
| Decision Rule to Detect Troubling Multicollinearity | multicollinearity |
| Scatterplot of CV vs VIF | plot.cv_vif |
| RVIF calculation | RVIF |
| RVIF calculation | rvifs |
| First simulated data for the simple linear regression model | SLM1 |
| Second simulated data for the simple linear regression model | SLM2 |
| Soil characteristics data | soil |
| Theorem | Theorem |
| Wissel data | Wissel |
