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biglasso
View on CRAN: Click
here
Download and install biglasso package within the R console
Install from CRAN:
install.packages("biglasso")
Install from Github:
library("remotes")
install_github("cran/biglasso") Install by package version:
library("remotes")
install_version("biglasso", "1.6.1") Attach the package and use:
library("biglasso")
Maintained by
Patrick Breheny
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-03-02
Latest Update: 2025-03-05
Description:
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.
How to cite:
Patrick Breheny (2016). biglasso: Extending Lasso Model Fitting to Big Data. R package version 1.6.1, https://cran.r-project.org/web/packages/biglasso. Accessed 25 Jun. 2026.
Previous versions and publish date:
1.0-1 (2016-03-02 11:10), 1.2-3 (2016-11-14 11:15), 1.3-0 (2016-12-21 23:26), 1.3-1 (2016-12-31 22:01), 1.3-3 (2017-01-26 01:02), 1.3-5 (2017-04-04 08:12), 1.3-6 (2017-05-04 09:19), 1.3-7 (2019-09-09 09:50), 1.4.0 (2021-01-16 07:10), 1.4.1 (2021-01-31 16:30), 1.5.0 (2022-02-08 08:40), 1.5.1 (2022-03-09 09:00), 1.5.2 (2022-10-06 00:40), 1.6.0 (2024-04-21 19:12)
Other packages that cited biglasso R package
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Other R packages that biglasso depends,
imports, suggests or enhances
Complete documentation for biglasso
Functions, R codes and Examples using
the biglasso R package
Some associated functions: biglasso-package . biglasso . colon . cv.biglasso . loss.biglasso . plot.biglasso . plot.cv.biglasso . plot.mbiglasso . predict.biglasso . predict.cv.biglasso . setupX . summary.cv.biglasso .
Some associated R codes: RcppExports.R . biglasso-package.R . biglasso.R . cv.biglasso.R . data.R . loss.R . plot.biglasso.R . plot.cv.biglasso.R . plot.mbiglasso.R . predict.R . predict.cv.R . setupX.R . summary.cv.biglasso.R . Full biglasso package functions and examples
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