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.
Fits large-scale regression models with a penalty that restricts the maximum number of non-zero regression coefficients to a prespecified value. While Chu et al (2020) <doi:10.1093/gigascience/giaa044> describe the basic algorithm, this package uses Cyclops for an efficient implementation.
| Version: | 1.0.2 |
| Depends: | R (≥ 3.2.2), Cyclops (≥ 1.3.0) |
| Imports: | ParallelLogger |
| Suggests: | testthat, knitr, rmarkdown |
| Published: | 2022-09-08 |
| Author: | Marc A. Suchard [aut, cre], Patrick Ryan [aut], Observational Health Data Sciences and Informatics [cph] |
| Maintainer: | Marc A. Suchard <msuchard at ucla.edu> |
| License: | Apache License 2.0 |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | IterativeHardThresholding results |
| Reference manual: | IterativeHardThresholding.pdf |
| Package source: | IterativeHardThresholding_1.0.2.tar.gz |
| Windows binaries: | r-devel: IterativeHardThresholding_1.0.2.zip, r-release: IterativeHardThresholding_1.0.2.zip, r-oldrel: IterativeHardThresholding_1.0.2.zip |
| macOS binaries: | r-release (arm64): IterativeHardThresholding_1.0.2.tgz, r-oldrel (arm64): IterativeHardThresholding_1.0.2.tgz, r-release (x86_64): IterativeHardThresholding_1.0.2.tgz, r-oldrel (x86_64): IterativeHardThresholding_1.0.2.tgz |
Please use the canonical form https://CRAN.R-project.org/package=IterativeHardThresholding 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.