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: .


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Reference manual

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install.packages("gglasso")

1.5 by Yi Yang, 7 months ago


https://github.com/emeryyi/gglasso


Report a bug at https://github.com/emeryyi/gglasso/issues


Browse source code at https://github.com/cran/gglasso


Authors: Yi Yang [aut, cre] (http://www.math.mcgill.ca/yyang/) , Hui Zou [aut] (http://users.stat.umn.edu/~zouxx019/) , Sahir Bhatnagar [aut] (http://sahirbhatnagar.com/)


Documentation:   PDF Manual  


GPL-2 license


Imports methods

Suggests testthat, knitr, rmarkdown


Imported by FIT, MLGL, PhylogeneticEM, higlasso, sail.


See at CRAN