Package: grpnet
Type: Package
Title: Group Elastic Net Regularized GLMs and GAMs
Version: 0.6
Date: 2024-10-11
Authors@R: person(c("Nathaniel", "E."), "Helwig", email = "helwig@umn.edu", role = c("aut", "cre"))
Description: Efficient algorithms for fitting generalized linear and additive models with group elastic net penalties as described in Helwig (2024) <doi:10.1080/10618600.2024.2362232>. Implements group LASSO, group MCP, and group SCAD with an optional group ridge penalty. Computes the regularization path for linear regression (gaussian), logistic regression (binomial), multinomial logistic regression (multinomial), log-linear count regression (poisson and negative.binomial), and log-linear continuous regression (gamma and inverse gaussian). Supports default and formula methods for model specification, k-fold cross-validation for tuning the regularization parameters, and nonparametric regression via tensor product reproducing kernel (smoothing spline) basis function expansion. 
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.5.0)
NeedsCompilation: yes
Packaged: 2024-10-11 13:49:42 UTC; nate
Author: Nathaniel E. Helwig [aut, cre]
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>
Repository: CRAN
Date/Publication: 2024-10-11 18:10:02 UTC
Built: R 4.4.2; x86_64-apple-darwin24.0.0; 2024-11-21 22:23:37 UTC; unix
