Package: gcdnet
Title: The (Adaptive) LASSO and Elastic Net Penalized Least Squares,
        Logistic Regression, Hybrid Huberized Support Vector Machines,
        Squared Hinge Loss Support Vector Machines and Expectile
        Regression using a Fast Generalized Coordinate Descent
        Algorithm
Version: 1.0.6
Author: Yi Yang <yi.yang6@mcgill.ca>, Yuwen Gu <yuwen.gu@uconn.edu>, Hui Zou
    <hzou@stat.umn.edu>
Maintainer: Yi Yang <yi.yang6@mcgill.ca>
Imports: grDevices, graphics, stats, methods, Matrix
Description: Implements a generalized coordinate descent (GCD) algorithm
    for computing the solution paths of the hybrid Huberized support vector
    machine (HHSVM) and its generalizations. Supported models include the
    (adaptive) LASSO and elastic net penalized least squares, logistic
    regression, HHSVM, squared hinge loss SVM and expectile regression.
License: GPL (>= 2)
Encoding: UTF-8
URL: https://github.com/emeryyi/gcdnet
Repository: CRAN
Date/Publication: 2022-08-14 02:30:02 UTC
RoxygenNote: 7.2.0
Suggests: testthat
NeedsCompilation: yes
Packaged: 2022-08-14 01:06:43 UTC; yuwen
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 00:18:52 UTC; unix
Archs: gcdnet.so.dSYM
