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
RoxygenNote: 7.2.0
Suggests: testthat
Repository: https://archer-yang-lab.r-universe.dev
Date/Publication: 2022-08-14 01:07:36 UTC
RemoteUrl: https://github.com/archer-yang-lab/gcdnet
RemoteRef: HEAD
RemoteSha: 4795e9043805309ea00eb1433b6701be8423e281
NeedsCompilation: yes
Packaged: 2026-07-04 21:14:49 UTC; root