rvif
3.2.1Collinearity Detection using Redefined Variance Inflation Factor and Graphical Methods
Overview
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).
Install
Health
- OK2026-08-0413 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-06-0712 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
- OK2026-03-3014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-03-1013 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 75%
- References docs
- 100%
Downloads
Repository
Repository practices
Checks run against github.com/rnoremlas/rvif_package on 2026-08-16.
No development-tooling practices detected in the upstream repository.
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
6 releases. Pick two to compare their code metrics. R releases are shown for context.
- 3.2.1Latest
- RR 4.6.0 released · 2026-04-24
- 3.22025-10-09 · diff ↗
- 3.12025-09-05 · diff ↗
- unarchivedReturned to CRAN2025-09-05
- archivedRemoved from CRAN2025-08-01not corrected in multiple resubmissions
- 3.02025-07-29 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 2.02024-11-14 · diff ↗
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.02022-12-22
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-12-22
- Total releases
- 6 / 4 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 6.5 KB / 7 files
- Download size
- 1.4 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("rvif")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-16, which the citation names so these numbers can be found later. More on citing and the projects behind them.