[aut, cre],
Juan Pablo Lewinger [ctb, ths]Fits hierarchical regularized regression models to incorporate potentially informative external data, Weaver and Lewinger (2019) <doi:10.21105/joss.01761>. Utilizes coordinate descent to efficiently fit regularized regression models both with and without external information with the most common penalties used in practice (i.e. ridge, lasso, elastic net). Support for standard R matrices, sparse matrices and big.matrix objects.
| Version: | 0.1.7 |
| Depends: | R (≥ 3.5) |
| Imports: | Rcpp (≥ 0.12.19), foreach, bigmemory, methods |
| LinkingTo: | Rcpp, RcppEigen, BH, bigmemory |
| Suggests: | knitr, rmarkdown, testthat, Matrix, doParallel |
| Published: | 2020-03-01 |
| Author: | Garrett Weaver
[aut, cre],
Juan Pablo Lewinger [ctb, ths] |
| Maintainer: | Garrett Weaver <gmweaver.usc at gmail.com> |
| License: | GPL-2 |
| URL: | https://github.com/USCbiostats/xrnet |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11 |
| Materials: | README NEWS |
| CRAN checks: | xrnet results |
| Reference manual: | xrnet.pdf |
| Package source: | xrnet_0.1.7.tar.gz |
| Windows binaries: | r-devel: xrnet_0.1.7.zip, r-release: xrnet_0.1.7.zip, r-oldrel: xrnet_0.1.7.zip |
| macOS binaries: | r-release: xrnet_0.1.7.tgz, r-oldrel: xrnet_0.1.7.tgz |
| Old sources: | xrnet archive |
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