Package: multiColl 1.0

R. Salmeron

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>.

Authors:R. Salmeron, C.B. Garcia and J. Garcia

multiColl_1.0.tar.gz
multiColl_1.0.zip(r-4.5)multiColl_1.0.zip(r-4.4)multiColl_1.0.zip(r-4.3)
multiColl_1.0.tgz(r-4.5-any)multiColl_1.0.tgz(r-4.4-any)multiColl_1.0.tgz(r-4.3-any)
multiColl_1.0.tar.gz(r-4.5-noble)multiColl_1.0.tar.gz(r-4.4-noble)
multiColl_1.0.tgz(r-4.4-emscripten)multiColl_1.0.tgz(r-4.3-emscripten)
multiColl.pdf |multiColl.html
multiColl/json (API)

# Install 'multiColl' in R:
install.packages('multiColl', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://r-forge.r-project.org/projects/colldetreat

Datasets:
  • KG - Klein and Goldberger data
  • theil - Henri Theil data

On CRAN:

2.59 score 1 packages 13 scripts 260 downloads 14 exports 0 dependencies

Last updated 2 years agofrom:4246eff3c5. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 29 2025
R-4.5-winOKJan 29 2025
R-4.5-macOKJan 29 2025
R-4.5-linuxOKJan 29 2025
R-4.4-winOKJan 29 2025
R-4.4-macOKJan 29 2025
R-4.3-winOKJan 29 2025
R-4.3-macOKJan 29 2025

Exports:CNCNsCVCVskilumultiColmultiColLMperturbperturb.nPROPsRdetRSLMVIF

Dependencies: