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transreg: Penalised Regression with Multiple Sets of Prior Effects ('Transfer Learning')

Improves the predictive performance of ridge and lasso regression exploiting one or more sources of prior information on the importance and direction of effects (Rauschenberger and others 2023, <doi:10.1093/bioinformatics/btad680>). For running the vignette (optional), install 'fwelnet' from 'GitHub' <https://github.com/kjytay/fwelnet>.

Version: 1.0.3
Depends: R (≥ 3.0.0)
Imports: glmnet, starnet, joinet
Suggests: knitr, testthat, rmarkdown, markdown, mvtnorm, remotes, glmtrans, xrnet, ecpc, fwelnet, doMC, palasso, xtable, devtools, CVXR
Published: 2024-09-27
DOI: 10.32614/CRAN.package.transreg
Author: Armin Rauschenberger ORCID iD [aut, cre]
Maintainer: Armin Rauschenberger <armin.rauschenberger at uni.lu>
BugReports: https://github.com/rauschenberger/transreg/issues
License: GPL-3
URL: https://github.com/rauschenberger/transreg, https://rauschenberger.github.io/transreg/
NeedsCompilation: no
Citation: transreg citation info
Materials: README NEWS
CRAN checks: transreg results

Documentation:

Reference manual: transreg.pdf
Vignettes: article (source)
analysis (source, R code)

Downloads:

Package source: transreg_1.0.3.tar.gz
Windows binaries: r-devel: transreg_1.0.3.zip, r-release: transreg_1.0.3.zip, r-oldrel: transreg_1.0.3.zip
macOS binaries: r-release (arm64): transreg_1.0.3.tgz, r-oldrel (arm64): transreg_1.0.3.tgz, r-release (x86_64): transreg_1.0.3.tgz, r-oldrel (x86_64): transreg_1.0.3.tgz
Old sources: transreg archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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