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gglasso
View on CRAN: Click
here
Download and install gglasso package within the R console
Install from CRAN:
install.packages("gglasso")
Install from Github:
library("remotes")
install_github("cran/gglasso")
Install by package version:
library("remotes")
install_version("gglasso", "1.5.1")
Attach the package and use:
library("gglasso")
Maintained by
Yi Yang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-04-30
Latest Update: 2020-03-18
Description:
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: .
How to cite:
Yi Yang (2012). gglasso: Group Lasso Penalized Learning Using a Unified BMD Algorithm. R package version 1.5.1, https://cran.r-project.org/web/packages/gglasso. Accessed 21 Nov. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for gglasso
Functions, R codes and Examples using
the gglasso R package
Some associated functions: bardet . coef.cv.gglasso . coef.gglasso . colon . cv.gglasso . gglasso . plot.cv.gglasso . plot.gglasso . predict.cv.gglasso . predict.gglasso . print.gglasso .
Some associated R codes: auxiliary.R . bardet-data.R . colon-data.R . cv.R . gglasso.R . imports.R . loss.R . model.R . plot.cv.gglasso.R . plot.gglasso.R . tools.R . utilities.R . Full gglasso package functions and examples
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