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 is an implementation of Yang, J. and Hastie, T. (2024) .


Reference manual

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install.packages("adelie")

1.0.10 by Trevor Hastie, 4 months ago


https://github.com/JamesYang007/adelie-r


Report a bug at https://github.com/JamesYang007/adelie-r/issues


Browse source code at https://github.com/cran/adelie


Authors: James Yang [aut, cph] , Trevor Hastie [aut, cph, cre] , Balasubramanian Narasimhan [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Matrix, r2r, Rcpp, methods, stringr, utils

Suggests ggplot2, gridExtra, testthat, knitr, rmarkdown

Linking to Rcpp, RcppEigen

System requirements: C++17


See at CRAN