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Functions for detecting multicollinearity. This test gives statistical support to two of the most famous methods for detecting multicollinearity in applied work: Klein’s rule and Variance Inflation Factor (VIF). See the URL for the papers associated with this package, as for instance, Morales-Oñate and Morales-Oñate (2015) <doi:10.33333/rp.vol51n2.05>.
Version: | 1.0.2 |
Depends: | R (≥ 4.1.0) |
Imports: | car, ggplot2, plotly |
Published: | 2023-10-06 |
DOI: | 10.32614/CRAN.package.MTest |
Author: | Víctor Morales-Oñate [aut, cre], Bolívar Morales-Oñate [aut] |
Maintainer: | Víctor Morales-Oñate <victor.morales at uv.cl> |
BugReports: | https://github.com/vmoprojs/MTest/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/vmoprojs/MTest |
NeedsCompilation: | no |
CRAN checks: | MTest results |
Reference manual: | MTest.pdf |
Package source: | MTest_1.0.2.tar.gz |
Windows binaries: | r-devel: MTest_1.0.2.zip, r-release: MTest_1.0.2.zip, r-oldrel: MTest_1.0.2.zip |
macOS binaries: | r-release (arm64): MTest_1.0.2.tgz, r-oldrel (arm64): MTest_1.0.2.tgz, r-release (x86_64): MTest_1.0.2.tgz, r-oldrel (x86_64): MTest_1.0.2.tgz |
Old sources: | MTest archive |
Please use the canonical form https://CRAN.R-project.org/package=MTest to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.