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 |