biglasso: Extending Lasso Model Fitting to Big Data

Extend lasso and elastic-net model fitting for ultrahigh-dimensional, multi-gigabyte data sets that cannot be loaded into memory. It's much more memory- and computation-efficient as compared to existing lasso-fitting packages like 'glmnet' and 'ncvreg', thus allowing for very powerful big data analysis even with an ordinary laptop.

Version: 1.3-3
Depends: R (≥ 3.2.0), bigmemory (≥ 4.5.0), Matrix, ncvreg
Imports: Rcpp (≥ 0.12.1), methods
LinkingTo: Rcpp, RcppArmadillo, bigmemory, BH
Suggests: parallel, testthat, R.rsp
Published: 2017-01-26
Author: Yaohui Zeng [aut,cre], Patrick Breheny [ctb]
Maintainer: Yaohui Zeng <yaohui-zeng at uiowa.edu>
BugReports: https://github.com/YaohuiZeng/biglasso/issues
License: GPL-3
URL: https://github.com/YaohuiZeng/biglasso, https://arxiv.org/abs/1701.05936
NeedsCompilation: yes
Citation: biglasso citation info
Materials: README NEWS
In views: MachineLearning
CRAN checks: biglasso results

Downloads:

Reference manual: biglasso.pdf
Vignettes: Tutorial
Package source: biglasso_1.3-3.tar.gz
Windows binaries: r-devel: biglasso_1.3-3.zip, r-release: biglasso_1.3-3.zip, r-oldrel: biglasso_1.3-3.zip
OS X Mavericks binaries: r-release: biglasso_1.3-3.tgz, r-oldrel: biglasso_1.3-3.tgz
Old sources: biglasso archive

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