Package: MTest 1.0.4

MTest: A Procedure for Multicollinearity Testing using Bootstrap

Functions for detecting multicollinearity. This test gives statistical support to two of the most famous methods for detecting multicollinearity in applied work: Klein’s rule and Variance Inflation Factor (VIF). See the URL for the papers associated with this package, as for instance, Morales-Oñate and Morales-Oñate (2015) <doi:10.33333/rp.vol51n2.05>.

Authors:Víctor Morales-Oñate [aut, cre], Bolívar Morales-Oñate [aut]

MTest_1.0.4.tar.gz
MTest_1.0.4.zip(r-4.7)MTest_1.0.4.zip(r-4.6)MTest_1.0.4.zip(r-4.5)
MTest_1.0.4.tgz(r-4.6-any)MTest_1.0.4.tgz(r-4.5-any)
MTest_1.0.4.tar.gz(r-4.7-any)MTest_1.0.4.tar.gz(r-4.6-any)
MTest_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MTest/json (API)

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

Bug tracker:https://github.com/vmoprojs/mtest/issues

Datasets:

On CRAN:

Conda:

2.70 score 1 stars 1 scripts 518 downloads 2 exports 64 dependencies

Last updated from:d53df1cece. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK144
source / vignettesOK181
linux-release-x86_64OK137
macos-release-arm64OK91
macos-oldrel-arm64OK87
windows-develOK114
windows-releaseOK86
windows-oldrelOK87
wasm-releaseOK133

Exports:MTestpairwiseKStest

Dependencies:askpassbase64encbslibcachemclicpp11crosstalkcurldata.tabledigestdplyrevaluatefarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlazyevallifecyclemagrittrmemoisemimeopensslotelpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcpprlangrmarkdownS7sassscalesstringistringrsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml