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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 |
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.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 |
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These binaries (installable software) and packages are in development.
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