Package: gglasso
Title: Group Lasso Penalized Learning Using a Unified BMD Algorithm
Version: 1.5
Date: 2020-3-01
Authors@R: c(
  person("Yi", "Yang", email = "yi.yang6@mcgill.ca",
  role = c("aut", "cre"), comment = "http://www.math.mcgill.ca/yyang/"),
  person("Hui", "Zou", email = "hzou@stat.umn.edu",
  role = c("aut"), comment = "http://users.stat.umn.edu/~zouxx019/"),
  person("Sahir", "Bhatnagar", email = "sahir.bhatnagar@gmail.com",
  role = c("aut"), comment = "http://sahirbhatnagar.com/")
  )
Maintainer: Yi Yang <yi.yang6@mcgill.ca>
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: <doi:10.1007/s11222-014-9498-5>.
License: GPL-2
Imports: methods
URL: https://github.com/emeryyi/gglasso
BugReports: https://github.com/emeryyi/gglasso/issues
Packaged: 2020-03-18 05:48:51 UTC; yiyang
Repository: CRAN
Date/Publication: 2020-03-18 07:00:08 UTC
RoxygenNote: 7.0.2
Suggests: testthat, knitr, rmarkdown
Encoding: UTF-8
LazyData: TRUE
VignetteBuilder: knitr
NeedsCompilation: yes
Author: 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/)
Built: R 4.0.2; x86_64-apple-darwin17.0; 2020-07-15 13:23:12 UTC; unix
Archs: gglasso.so.dSYM
