This package is considered a duplicate. The official version of this package is found at:https://archer-yang-lab.r-universe.dev/gglasso
Package: gglasso 1.6
Yi Yang
gglasso: Group Lasso Penalized Learning Using a Unified BMD Algorithm
A unified algorithm, blockwise-majorization-descent (BMD), for efficiently computing the solution paths of the group-lasso penalized least squares, logistic regression, Huberized SVM and squared SVM. The package is an implementation of Yang, Y. and Zou, H. (2015) <doi:10.1007/s11222-014-9498-5>.
Authors:
gglasso_1.6.tar.gz
gglasso_1.6.tar.gz(r-4.7-arm64)gglasso_1.6.tar.gz(r-4.7-x86_64)gglasso_1.6.tar.gz(r-4.6-arm64)gglasso_1.6.tar.gz(r-4.6-x86_64)
gglasso_1.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gglasso/json (API)
| # Install 'gglasso' in R: |
| install.packages('gglasso', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/archer-yang-lab/gglasso/issues
Datasets:
Last updated from:7308913f70. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 148 | ||
| linux-devel-x86_64 | OK | 128 | ||
| source / vignettes | OK | 216 | ||
| linux-release-arm64 | OK | 123 | ||
| linux-release-x86_64 | OK | 1928 | ||
| wasm-release | OK | 101 |
Exports:cv.gglassocv.hsvmcv.logitcv.lscv.sqsvmgglasso
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Simplified gene expression data from Scheetz et al. (2006) | bardet |
| get coefficients or make coefficient predictions from a "cv.gglasso" object. | coef.cv.gglasso |
| get coefficients or make coefficient predictions from an "gglasso" object. | coef.gglasso |
| Simplified gene expression data from Alon et al. (1999) | colon |
| Cross-validation for gglasso | cv.gglasso cv.hsvm cv.logit cv.ls cv.sqsvm |
| Fits the regularization paths for group-lasso penalized learning problems | gglasso |
| plot the cross-validation curve produced by cv.gglasso | plot.cv.gglasso |
| Plot solution paths from a "gglasso" object | plot.gglasso |
| make predictions from a "cv.gglasso" object. | predict.cv.gglasso |
| make predictions from a "gglasso" object. | predict.gglasso |
| print a gglasso object | print.gglasso |
