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multiColl  

Collinearity Detection in a Multiple Linear Regression Model
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("multiColl", "2.0")



Attach the package and use:
library("multiColl")
Maintained by
R. Salmeron
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-07-18
Latest Update: 2022-07-21
Description:
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.
How to cite:
R. Salmeron (2019). multiColl: Collinearity Detection in a Multiple Linear Regression Model. R package version 2.0, https://cran.r-project.org/web/packages/multiColl
Previous versions and publish date:
1.0 (2019-07-18 13:14)
Other packages that cited multiColl R package
View multiColl citation profile
Other R packages that multiColl depends, imports, suggests or enhances
Functions, R codes and Examples using the multiColl R package
Some associated functions: CN . CNs . CV . CVs . KG . PROPs . RdetR . SLM . VIF . ki . lu . multiCol . multiColLM . multiColl-package . perturb.n . perturb . theil . 
Some associated R codes: CN.R . CNs.R . CV.R . CVs.R . PROPs.R . RdetR.R . SLM.R . VIF.R . ki.R . lu.R . multiCol.R . multiColLM.R . perturb.R . perturb.n.R .  Full multiColl package functions and examples
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