Package: autotune
Type: Package
Title: Faster and more Efficient Lasso (than 'glmnet' and 'scalreg')
        with Data-Driven Tuning
Version: 0.1.0
Maintainer: Tathagata Sadhukhan <ts767@cornell.edu>
Description: Fits Lasso paths for high-dimensional regression using
        coordinate descent with automatic, data-driven tuning of the
        regularization parameter. The implementation is 10 to 50 times
        faster than the standard 'glmnet' implementation of Lasso and
        over 100 times faster than scaled Lasso. It also provides a
        reliable estimate of the regression noise level.
License: GPL (>=2)
Encoding: UTF-8
Depends: R (>= 2.10)
Imports: Rcpp (>= 1.0.13)
LinkingTo: Rcpp
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown, glmnet, AUC, ggplot2, ggExtra, dplyr,
        tidyr, Matrix
VignetteBuilder: knitr
Authors@R: c(person(given = "Tathagata",
                        family = "Sadhukhan",
                        role = c("aut", "cre"),
                        email = "ts767@cornell.edu"),
                 person(given = "Ines",
                        family = "Wilms",
                        role = "aut"),
                 person(given = "Stephan",
                        family = "Smeekes",
                        role = "aut"),
                 person(given = "Sumanta",
                        family = "Basu",
                        role = "aut"))
Repository: https://tathagata-s.r-universe.dev
Date/Publication: 2026-08-20 01:40:21 UTC
RemoteUrl: https://github.com/tathagata-s/autotune
RemoteRef: HEAD
RemoteSha: 9d4d570df560c9f77f89a7b81fb53a9ab4320501
NeedsCompilation: yes
Packaged: 2026-10-21 09:18:39 UTC; root
Author: Tathagata Sadhukhan [aut, cre],
  Ines Wilms [aut],
  Stephan Smeekes [aut],
  Sumanta Basu [aut]