Package: gglasso 1.4

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: <doi:10.1007/s11222-014-9498-5>.

Authors:Yi Yang <[email protected]>, Hui Zou <[email protected]>

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
gglasso/json (API)

# Install 'gglasso' in R:

install.packages('gglasso', repos = c('https://archer-yang-lab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/emeryyi/gglasso/issues

Uses libs:

fortran– Runtime library for GNU Fortran applications

Datasets:

bardet - Simplified gene expression data from Scheetz et al.
colon - Simplified gene expression data from Alon et al.

On CRAN:

fortran glibc

7.90 score 10 stars 5 packages 311 scripts 1.1k downloads 3 mentions 6 exports 0 dependencies

Last updated from:7d98ba6ffb. Checks:11 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	WARNING	149
linux-devel-x86_64	WARNING	129
source / vignettes	OK	149
linux-release-arm64	WARNING	136
linux-release-x86_64	WARNING	125
macos-release-arm64	WARNING	87
macos-release-x86_64	WARNING	232
macos-oldrel-arm64	WARNING	84
macos-oldrel-x86_64	WARNING	187
windows-devel	WARNING	100
windows-release	WARNING	95
windows-oldrel	WARNING	112
wasm-release	OK	116

Exports:cv.gglasso cv.hsvm cv.logit cv.ls cv.sqsvm gglasso

Dependencies:

Introduction to gglasso

Rendered fromIntroduction_to_gglasso_package.Rmdusingknitr::rmarkdown

Last update: 2020-02-17
Started: 2018-04-19

Citation

Development and contributors

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