R Development Page
Contributed R Packages
Below is a list of all packages provided by project Collinearity detection and treatment.
Important note for package binaries: R-Forge provides these binaries only for the most recent version of R, but not for older versions. In order to successfully install the packages provided on R-Forge, you have to switch to the most recent version of R or, alternatively, install from the package sources (.tar.gz).
Packages
| multiColl | Collinearity Detection in a Multiple Linear Regression Model | |||||||||
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The detection of worrying approximate collinearity in a multiple linear regression model is a problem addressed in all existing statistical packages. However, we have detected deficits regarding to the incorrect treatment of qualitative independent variables and the role of the intercept of the model. The objective of this package is to correct these deficits. In this package will be available detection and treatment techniques traditionally used as the recently developed.
D.A. Belsley (1982) | ||||||||||
| Version: 1.0 | Last change: 2019-07-15 20:37:09+02 | Rev.: 26 | ||||||||||
Download:
 (.tar.gz) |
 (.zip) |
Build status: Current | Stable Release: Get multiColl 2.0 from CRAN | ||||||||||
R install command:
install.packages("multiColl", repos="http://R-Forge.R-project.org") | ||||||||||
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| rvif | Collinearity Detection using RVIF and Graphical Methods | |||||||||
| 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. | ||||||||||
| Version: 1.0 | Last change: 2022-11-09 08:41:05+01 | Rev.: 31 | ||||||||||
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get rvif 1.0 from CRAN | ||||||||||
R install command:
install.packages("rvif", repos="http://R-Forge.R-project.org") | ||||||||||
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Build status codes
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