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: 1.4.1
Depends: R (≥ 3.2.0), bigmemory (≥ 4.5.0), Matrix, ncvreg
Imports: Rcpp (≥ 0.12.1), methods
LinkingTo: Rcpp, RcppArmadillo (≥ 0.8.600), bigmemory, BH
Suggests: parallel, testthat, R.rsp, glmnet, survival, knitr, rmarkdown
Published: 2021-01-31
Author: Yaohui Zeng [aut,cre], Chuyi Wang [aut,cre], Patrick Breheny [ctb]
Maintainer: Chuyi Wang <wwaa0208 at>
License: GPL-3
NeedsCompilation: yes
Citation: biglasso citation info
Materials: NEWS
In views: MachineLearning
CRAN checks: biglasso results


Reference manual: biglasso.pdf
Vignettes: biglasso
Package source: biglasso_1.4.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: biglasso_1.4.1.tgz, r-oldrel: biglasso_1.4.1.tgz
Old sources: biglasso archive

Reverse dependencies:

Reverse suggests: bigstatsr, epiGWAS, SuperLearner


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