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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 RauschenbergerORCID 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.html ,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 formhttps://CRAN.R-project.org/package=joinetto link to this page.


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