Estimates sparse regression models (i.e., with few non-zero coefficients) in high-dimensional multi-task learning and transfer learning settings, as proposed by Rauschenberger et al. (2025) <https://orbilu.uni.lu/handle/10993/63425>.
Version: | 1.0.0 |
Depends: | R (≥ 3.0.0) |
Imports: | glmnet, pROC, stats, mvtnorm, spls, xrnet |
Suggests: | knitr, testthat, remotes, glmtrans, rmarkdown |
Published: | 2025-06-03 |
DOI: | 10.32614/CRAN.package.sparselink |
Author: | Armin Rauschenberger
|
Maintainer: | Armin Rauschenberger <armin.rauschenberger at lih.lu> |
BugReports: | https://github.com/rauschenberger/sparselink/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/rauschenberger/sparselink, https://rauschenberger.github.io/sparselink/ |
NeedsCompilation: | no |
Citation: | sparselink citation info |
Materials: | README NEWS |
CRAN checks: | sparselink results |
Reference manual: | sparselink.pdf |
Vignettes: |
Analysis code (source, R code) Sparse regression for related problems (source) |
Package source: | sparselink_1.0.0.tar.gz |
Windows binaries: | r-devel: sparselink_1.0.0.zip, r-release: sparselink_1.0.0.zip, r-oldrel: sparselink_1.0.0.zip |
macOS binaries: | r-release (arm64): sparselink_1.0.0.tgz, r-oldrel (arm64): sparselink_1.0.0.tgz, r-release (x86_64): sparselink_1.0.0.tgz, r-oldrel (x86_64): sparselink_1.0.0.tgz |
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