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sparselink: Sparse Regression for Related Problems

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 ORCID iD [aut, cre]
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

Documentation:

Reference manual: sparselink.pdf
Vignettes: Analysis code (source, R code)
Sparse regression for related problems (source)

Downloads:

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