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-4.7)multiColl_1.0.zip(r-4.6)multiColl_1.0.zip(r-4.5)
multiColl_1.0.tgz(r-4.6-any)multiColl_1.0.tgz(r-4.5-any)
multiColl_1.0.tar.gz(r-4.7-any)multiColl_1.0.tar.gz(r-4.6-any)
multiColl_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
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:

Conda:

2.78 score 1 packages 20 scripts 268 downloads 14 exports 0 dependencies

Last updated from:4246eff3c5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK104
source / vignettesOK134
linux-release-x86_64OK103
macos-release-arm64OK78
macos-oldrel-arm64OK73
windows-develOK60
windows-releaseOK67
windows-oldrelOK85
wasm-releaseOK88

Exports:CNCNsCVCVskilumultiColmultiColLMperturbperturb.nPROPsRdetRSLMVIF

Dependencies: