FORD: Feature Ordering by Integrated R Square Dependence

Feature Ordering by Integrated R square Dependence (FORD) is a variable selection algorithm based on the new measure of dependence: Integrated R2 Dependence Coefficient (IRDC). For more information, see the paper: Azadkia and Roudaki (2025),"A New Measure Of Dependence: Integrated R2" <doi:10.48550/arXiv.2505.18146>.

Version: 0.1.2
Depends: R (≥ 3.6.0), data.table
Imports: RANN, parallel
Suggests: knitr, rmarkdown, markdown, xfun, testthat, minerva, devtools, FOCI, XICOR, KPC, dplyr, ggplot2
Published: 2025-05-30
DOI: 10.32614/CRAN.package.FORD
Author: Pouya Roudaki [aut, cre], Mona Azadkia [aut, ctb]
Maintainer: Pouya Roudaki <roudaki.pouya at gmail.com>
BugReports: https://github.com/PouyaRoudaki/FORD/issues
License: GPL-3
URL: https://github.com/PouyaRoudaki/FORD
NeedsCompilation: no
Materials: README
CRAN checks: FORD results

Documentation:

Reference manual: FORD.pdf
Vignettes: ford-demo (source, R code)
indep-test (source, R code)
irdc-demo (source, R code)

Downloads:

Package source: FORD_0.1.2.tar.gz
Windows binaries: r-devel: not available, r-release: FORD_0.1.2.zip, r-oldrel: FORD_0.1.2.zip
macOS binaries: r-release (arm64): FORD_0.1.2.tgz, r-oldrel (arm64): FORD_0.1.2.tgz, r-release (x86_64): FORD_0.1.2.tgz, r-oldrel (x86_64): FORD_0.1.2.tgz

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