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biglasso: Extending Lasso Model Fitting to Big Data

Extend lasso and elastic-net model fitting for ultra high-dimensional, multi-gigabyte data sets that cannot be loaded into memory. Designed to be more memory- and computation-efficient than existing lasso-fitting packages like 'glmnet' and 'ncvreg', thus allowing the user to analyze big data analysis even on an ordinary laptop.

Version: 1.6.0
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, glmnet, survival, knitr, rmarkdown
Published: 2024-04-21
DOI: 10.32614/CRAN.package.biglasso
Author: Yaohui Zeng [aut], Chuyi Wang [aut], Tabitha Peter [aut], Patrick Breheny ORCID iD [aut, cre]
Maintainer: Patrick Breheny <patrick-breheny at uiowa.edu>
BugReports: https://github.com/pbreheny/biglasso/issues
License: GPL-3
URL: https://pbreheny.github.io/biglasso/index.html, https://github.com/pbreheny/biglasso, https://arxiv.org/abs/1701.05936
NeedsCompilation: yes
Citation: biglasso citation info
Materials: NEWS
CRAN checks: biglasso results

Documentation:

Reference manual: biglasso.pdf
Vignettes: biglasso

Downloads:

Package source: biglasso_1.6.0.tar.gz
Windows binaries: r-devel: biglasso_1.6.0.zip, r-release: biglasso_1.6.0.zip, r-oldrel: biglasso_1.6.0.zip
macOS binaries: r-release (arm64): biglasso_1.6.0.tgz, r-oldrel (arm64): biglasso_1.6.0.tgz, r-release (x86_64): biglasso_1.6.0.tgz, r-oldrel (x86_64): biglasso_1.6.0.tgz
Old sources: biglasso archive

Reverse dependencies:

Reverse imports: plmmr
Reverse suggests: SuperLearner

Linking:

Please use the canonical form https://CRAN.R-project.org/package=biglasso to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.