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: | 1.0.3 |
| Depends: | R (≥ 3.2.2), Cyclops (≥ 1.3.0) |
| Imports: | ParallelLogger |
| Suggests: | testthat, knitr, rmarkdown |
| Published: | 2025-07-21 |
| DOI: | 10.32614/CRAN.package.IterativeHardThresholding |
| 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.html , IterativeHardThresholding.pdf |
| Package source: | IterativeHardThresholding_1.0.3.tar.gz |
| Windows binaries: | r-devel: IterativeHardThresholding_1.0.3.zip, r-release: IterativeHardThresholding_1.0.3.zip, r-oldrel: IterativeHardThresholding_1.0.3.zip |
| macOS binaries: | r-release (arm64): IterativeHardThresholding_1.0.3.tgz, r-oldrel (arm64): IterativeHardThresholding_1.0.3.tgz, r-release (x86_64): IterativeHardThresholding_1.0.3.tgz, r-oldrel (x86_64): IterativeHardThresholding_1.0.3.tgz |
| Old sources: | IterativeHardThresholding archive |
| Reverse suggests: | PatientLevelPrediction |
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