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gcdnet  

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 Coordin
View on CRAN: Click here


Download and install gcdnet package within the R console
Install from CRAN:
install.packages("gcdnet")

Install from Github:
library("remotes")
install_github("cran/gcdnet")

Install by package version:
library("remotes")
install_version("gcdnet", "1.0.6")



Attach the package and use:
library("gcdnet")
Maintained by
Yi Yang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-03-01
Latest Update: 2022-08-14
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.
How to cite:
Yi Yang (2012). gcdnet: 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 Coordin. R package version 1.0.6, https://cran.r-project.org/web/packages/gcdnet. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:41), 1.0.0 (2012-03-01 17:55), 1.0.1 (2012-04-23 07:16), 1.0.2 (2013-02-24 08:36), 1.0.3 (2013-07-26 11:05), 1.0.4 (2013-11-19 07:35), 1.0.5 (2017-11-20 14:45)
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Complete documentation for gcdnet
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