joinet: Multivariate Elastic Net Regression

Implements high-dimensional multivariate regression by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>). 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. If required, install MRCE from GitHub (<>).

Version: 0.0.5
Depends: R (≥ 3.0.0)
Imports: glmnet, palasso, cornet
Suggests: knitr, rmarkdown, testthat, MASS
Enhances: mice, earth, spls, MRCE, remMap, MultivariateRandomForest, SiER, mcen, GPM, RMTL, MTPS
Published: 2020-10-03
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <armin.rauschenberger at>
License: GPL-3
NeedsCompilation: no
Language: en-GB
Materials: README NEWS
CRAN checks: joinet results


Reference manual: joinet.pdf
Vignettes: article
Package source: joinet_0.0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: joinet_0.0.5.tgz, r-oldrel: joinet_0.0.5.tgz
Old sources: joinet archive

Reverse dependencies:

Reverse imports: starnet


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