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multiColl (version 2.0)

Collinearity Detection in a Multiple Linear Regression Model

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.

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Version

Install

install.packages('multiColl')

Monthly Downloads

253

Version

2.0

License

GPL (>= 2)

Maintainer

R. Salmeron

Last Published

July 21st, 2022

Functions in multiColl (2.0)

PROPs

Proportions
theil

Henri Theil data
perturb.n

Perturbation and estimation in a multiple linear model
perturb

Perturbation
lu

Unit length data
multiCol

Collinearity detection in a linear regression model
ki

Stewart's index
multiColl-package

Collinearity detection in a multiple linear regression model.
VIF

Variance Inflation Factor
multiColLM

All detection measures
KG

Klein and Goldberger data
CV

Coeficient of Variation
CN

Condition Number
CVs

Coeficients of Variation
CNs

Condition Number with and without intercept
SLM

Simple linear regression model and multicollinearity
RdetR

Correlation matrix and it's determinat