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