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joinet: Penalised Multivariate Regression ('Multi-Target Learning')

Implements penalised multivariate regression (i.e., for multiple outcomes and many features) by stacked generalisation (<doi:10.1093/bioinformatics/btab576>). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement. For optional comparisons, install 'remMap' from GitHub (<https://github.com/cran/remMap>).

Version: 1.0.0
Depends: R (≥ 3.0.0)
Imports: glmnet, palasso, cornet
Suggests: knitr, rmarkdown, testthat, MASS, mice, earth, spls, MRCE, remMap, MultivariateRandomForest, SiER, mcen, GPM, RMTL, MTPS
Published: 2024-09-27
DOI: 10.32614/CRAN.package.joinet
Author: Armin Rauschenberger ORCID iD [aut, cre]
Maintainer: Armin Rauschenberger <armin.rauschenberger at uni.lu>
BugReports: https://github.com/rauschenberger/joinet/issues
License: GPL-3
URL: https://github.com/rauschenberger/joinet, https://rauschenberger.github.io/joinet/
NeedsCompilation: no
Citation: joinet citation info
Materials: README NEWS
In views: MachineLearning
CRAN checks: joinet results

Documentation:

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

Downloads:

Package source: joinet_1.0.0.tar.gz
Windows binaries: r-devel: joinet_1.0.0.zip, r-release: joinet_1.0.0.zip, r-oldrel: joinet_1.0.0.zip
macOS binaries: r-release (arm64): joinet_1.0.0.tgz, r-oldrel (arm64): joinet_1.0.0.tgz, r-release (x86_64): joinet_1.0.0.tgz, r-oldrel (x86_64): joinet_1.0.0.tgz
Old sources: joinet archive

Reverse dependencies:

Reverse imports: transreg

Linking:

Please use the canonical form https://CRAN.R-project.org/package=joinet to link to this page.

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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