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folda: Forward Stepwise Discriminant Analysis with Pillai's Trace

A novel forward stepwise discriminant analysis framework that integrates Pillai's trace with Uncorrelated Linear Discriminant Analysis (ULDA), providing an improvement over traditional stepwise LDA methods that rely on Wilks' Lambda. A stand-alone ULDA implementation is also provided, offering a more general solution than the one available in the 'MASS' package. It automatically handles missing values and provides visualization tools. For more details, see Wang (2024) <doi:10.48550/arXiv.2409.03136>.

Version: 0.1.0
Imports: ggplot2, grDevices, Rcpp, stats
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-09-11
DOI: 10.32614/CRAN.package.folda
Author: Siyu Wang ORCID iD [aut, cre, cph]
Maintainer: Siyu Wang <iamwangsiyu at gmail.com>
BugReports: https://github.com/Moran79/folda/issues
License: MIT + file LICENSE
URL: https://github.com/Moran79/folda, http://iamwangsiyu.com/folda/
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: folda results

Documentation:

Reference manual: folda.pdf
Vignettes: Introduction to folda (source, R code)

Downloads:

Package source: folda_0.1.0.tar.gz
Windows binaries: r-devel: folda_0.1.0.zip, r-release: folda_0.1.0.zip, r-oldrel: folda_0.1.0.zip
macOS binaries: r-release (arm64): folda_0.1.0.tgz, r-oldrel (arm64): folda_0.1.0.tgz, r-release (x86_64): folda_0.1.0.tgz, r-oldrel (x86_64): folda_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.