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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 RauschenbergerORCID iD [aut, cre]
Maintainer:Armin Rauschenberger <armin.rauschenberger at lih.lu>
BugReports:https://github.com/rauschenberger/sparselink/issues
License:MIT + fileLICENSE
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.html ,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

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=sparselinkto link to this page.


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