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-4.7)SGL_1.3.zip(r-4.6)SGL_1.3.zip(r-4.5)
SGL_1.3.tgz(r-4.6-x86_64)SGL_1.3.tgz(r-4.6-arm64)SGL_1.3.tgz(r-4.5-x86_64)SGL_1.3.tgz(r-4.5-arm64)
SGL_1.3.tar.gz(r-4.7-arm64)SGL_1.3.tar.gz(r-4.7-x86_64)SGL_1.3.tar.gz(r-4.6-arm64)SGL_1.3.tar.gz(r-4.6-x86_64)
SGL_1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
SGL/json (API)

# Install 'SGL' in R:
install.packages('SGL', repos = c('https://nrs02004.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

cpp

3.63 score 6 stars 71 scripts 710 downloads 17 mentions 3 exports 0 dependencies

Last updated from:3f51a8d0b6. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK104
linux-devel-x86_64OK121
source / vignettesOK117
linux-release-arm64OK93
linux-release-x86_64OK94
macos-release-arm64OK128
macos-release-x86_64OK191
macos-oldrel-arm64OK174
macos-oldrel-x86_64OK280
windows-develOK83
windows-releaseOK82
windows-oldrelOK78
wasm-releaseOK72

Exports:cvSGLpredictSGLSGL

Dependencies: