doi:10.1080/01621459.2020.1796677>. The package allows efficient model fitting on the entire 2-dimensional regularization path for large datasets. The complete set of functions also makes the entire process of tuning regularization parameters and visualizing results hassle-free.">

rare: Linear Model with Tree-Based Lasso Regularization for Rare Features (original) (raw)

Implementation of an alternating direction method of multipliers algorithm for fitting a linear model with tree-based lasso regularization, which is proposed in Algorithm 1 of Yan and Bien (2020) <doi:10.1080/01621459.2020.1796677>. The package allows efficient model fitting on the entire 2-dimensional regularization path for large datasets. The complete set of functions also makes the entire process of tuning regularization parameters and visualizing results hassle-free.

Version: 0.1.2
Depends: R (≥ 3.2.1)
Imports: Matrix, glmnet, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, dendextend, rmarkdown
Published: 2025-06-16
DOI: 10.32614/CRAN.package.rare
Author: Xiaohan Yan [aut, cre], Jacob Bien [aut]
Maintainer: Xiaohan Yan
BugReports: https://github.com/yanxht/rare/issues
License: GPL-3
URL: https://github.com/yanxht/rare
NeedsCompilation: yes
Materials: README
CRAN checks: rare results

Documentation:

Reference manual: rare.html , <rare.pdf>
Vignettes: Using the rare package (source, R code)

Downloads:

Package source: rare_0.1.2.tar.gz
Windows binaries: r-devel: rare_0.1.2.zip, r-release: rare_0.1.2.zip, r-oldrel: rare_0.1.2.zip
macOS binaries: r-release (arm64): rare_0.1.2.tgz, r-oldrel (arm64): rare_0.1.2.tgz, r-release (x86_64): rare_0.1.2.tgz, r-oldrel (x86_64): rare_0.1.2.tgz
Old sources: rare archive

Reverse dependencies:

Reverse imports: protoshiny

Linking:

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