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adelie: Group Lasso and Elastic Net Solver for Generalized Linear Models

Extremely efficient procedures for fitting the entire group lasso and group elastic net regularization path for GLMs, multinomial, the Cox model and multi-task Gaussian models. Similar to the R package glmnet in scope of models, and in computational speed. This package provides R bindings to the C++ code underlying the corresponding Python package 'adelie'. These bindings offer a general purpose group elastic net solver, a wide range of matrix classes that can exploit special structure to allow large-scale inputs, and an assortment of generalized linear model classes for fitting various types of data. The package includes The package is an implementation of Yang, J. and Hastie, T. (2024) <doi:10.48550/arXiv.2405.08631>.

Version: 1.0.2
Imports: Matrix, r2r, Rcpp, methods, stringr
LinkingTo: Rcpp, RcppEigen
Suggests: ggplot2, gridExtra, testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2024-09-03
DOI: 10.32614/CRAN.package.adelie
Author: James Yang [aut, cph], Trevor Hastie [aut, cph, cre], Balasubramanian Narasimhan [aut]
Maintainer: Trevor Hastie <hastie at stanford.edu>
BugReports: https://github.com/JamesYang007/adelie-r/issues
License: MIT + file LICENSE
URL: https://github.com/JamesYang007/adelie-r
NeedsCompilation: yes
SystemRequirements: C++17
Materials: NEWS
CRAN checks: adelie results

Documentation:

Reference manual: adelie.pdf
Vignettes: An Introduction to 'adelie' (source, R code)

Downloads:

Package source: adelie_1.0.2.tar.gz
Windows binaries: r-devel: adelie_1.0.2.zip, r-release: adelie_1.0.2.zip, r-oldrel: adelie_1.0.2.zip
macOS binaries: r-release (arm64): adelie_1.0.2.tgz, r-oldrel (arm64): adelie_1.0.2.tgz, r-release (x86_64): adelie_1.0.2.tgz, r-oldrel (x86_64): adelie_1.0.2.tgz
Old sources: adelie archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=adelie to link to this page.

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.