rare: Linear Model with Tree-Based Lasso Regularization for Rare Features

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 (2018) <doi:10.48550/arXiv.1803.06675>. 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:	0.1.1
Depends:	R (≥ 3.2.1)
Imports:	Matrix, glmnet, Rcpp
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	knitr, dendextend, rmarkdown
Published:	2018-08-03
DOI:	10.32614/CRAN.package.rare
Author:	Xiaohan Yan [aut, cre], Jacob Bien [aut, cre]
Maintainer:	Xiaohan Yan <xy257 at cornell.edu>
BugReports:	https://github.com/yanxht/rare/issues
License:	GPL-3
URL:	https://github.com/yanxht/rare
NeedsCompilation:	yes
CRAN checks:	rare results

Documentation:

Reference manual:	rare.pdf
Vignettes:	Using the rare package

Downloads:

Package source:	rare_0.1.1.tar.gz
Windows binaries:	r-devel: rare_0.1.1.zip, r-release: rare_0.1.1.zip, r-oldrel: rare_0.1.1.zip
macOS binaries:	r-release (arm64): rare_0.1.1.tgz, r-oldrel (arm64): rare_0.1.1.tgz, r-release (x86_64): rare_0.1.1.tgz, r-oldrel (x86_64): rare_0.1.1.tgz
Old sources:	rare archive

Reverse dependencies:

Reverse imports:

protoshiny

Linking:

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