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: |
1.3-7 |
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: |
2019-09-09 |
Author: |
Yaohui Zeng [aut,cre], Patrick Breheny [ctb] |
Maintainer: |
Yaohui Zeng <yaohui.zeng at gmail.com> |
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: |
NEWS |
In views: |
MachineLearning |
CRAN checks: |
biglasso results |