Package: SGL 1.3

SGL: Fit a GLM (or Cox Model) with a Combination of Lasso and Group Lasso Regularization

Fit a regularized generalized linear model via penalized maximum likelihood. The model is fit for a path of values of the penalty parameter. Fits linear, logistic and Cox models.

Authors:Noah Simon, Jerome Friedman, Trevor Hastie, and Rob Tibshirani

SGL_1.3.tar.gz
SGL_1.3.zip(r-4.5)SGL_1.3.zip(r-4.4)SGL_1.3.zip(r-4.3)
SGL_1.3.tgz(r-4.4-x86_64)SGL_1.3.tgz(r-4.4-arm64)SGL_1.3.tgz(r-4.3-x86_64)SGL_1.3.tgz(r-4.3-arm64)
SGL_1.3.tar.gz(r-4.5-noble)SGL_1.3.tar.gz(r-4.4-noble)
SGL_1.3.tgz(r-4.4-emscripten)SGL_1.3.tgz(r-4.3-emscripten)
SGL.pdf |SGL.html✨
SGL/json (API)

# Install 'SGL' in R:
install.packages('SGL', repos = c('https://nrs02004.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4.03 score 6 stars 1 packages 60 scripts 304 downloads 17 mentions 3 exports 0 dependencies

Last updated 5 years agofrom:3f51a8d0b6. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-win-x86_64OKNov 19 2024
R-4.5-linux-x86_64OKNov 19 2024
R-4.4-win-x86_64OKNov 19 2024
R-4.4-mac-x86_64OKNov 19 2024
R-4.4-mac-aarch64OKNov 19 2024
R-4.3-win-x86_64OKNov 19 2024
R-4.3-mac-x86_64OKNov 19 2024
R-4.3-mac-aarch64OKNov 19 2024

Exports:cvSGLpredictSGLSGL

Dependencies: