multiColl: Collinearity Detection in a Multiple Linear Regression Model

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) <doi:10.1016/0304-4076(82)90020-3>. D. A. Belsley (1991, ISBN: 978-0471528890). C. Garcia, R. Salmeron and C.B. Garcia (2019) <doi:10.1080/00949655.2018.1543423>. R. Salmeron, C.B. Garcia and J. Garcia (2018) <doi:10.1080/00949655.2018.1463376>. G.W. Stewart (1987) <doi:10.1214/ss/1177013444>.

Package details

AuthorR. Salmeron, C.B. Garcia and J. Garcia
MaintainerR. Salmeron <[email protected]>
LicenseGPL (>= 2)
Version1.0
URL http://colldetreat.r-forge.r-project.org/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("multiColl")

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multiColl documentation built on July 18, 2019, 5:03 p.m.