The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Sparsity Oriented Importance Learning (SOIL) provides a new variable importance measure for high dimensional linear regression and logistic regression from a sparse penalization perspective, by taking into account the variable selection uncertainty via the use of a sensible model weighting. The package is an implementation of Ye, C., Yang, Y., and Yang, Y. (2017+).
| Version: | 1.1 |
| Imports: | stats, glmnet, ncvreg, MASS, parallel, brglm2 |
| Published: | 2017-09-20 |
| Author: | Chenglong Ye, Yi Yang, Yuhong Yang |
| Maintainer: | Yi Yang <yi.yang6 at mcgill.ca> |
| License: | GPL-2 |
| URL: | https://github.com/emeryyi/SOIL |
| NeedsCompilation: | no |
| Materials: | ChangeLog |
| CRAN checks: | SOIL results |
| Reference manual: | SOIL.pdf |
| Package source: | SOIL_1.1.tar.gz |
| Windows binaries: | r-devel: SOIL_1.1.zip, r-release: SOIL_1.1.zip, r-oldrel: SOIL_1.1.zip |
| macOS binaries: | r-release (arm64): SOIL_1.1.tgz, r-oldrel (arm64): SOIL_1.1.tgz, r-release (x86_64): SOIL_1.1.tgz, r-oldrel (x86_64): SOIL_1.1.tgz |
| Old sources: | SOIL archive |
Please use the canonical form https://CRAN.R-project.org/package=SOIL 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.
Health stats visible at Monitor.