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.

Version: 0.0.2
Depends: R (≥ 3.0.0)
Imports: glmnet, palasso, cornet
Suggests: knitr, testthat, MASS
Enhances: spls, SiER, MRCE
Published: 2019-08-08
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <a.rauschenberger at vumc.nl>
BugReports: https://github.com/rauschenberger/joinet/issues
License: GPL-3
URL: https://github.com/rauschenberger/joinet
NeedsCompilation: no
Language: en-GB
Materials: README NEWS
CRAN checks: joinet results

Downloads:

Reference manual: joinet.pdf
Vignettes: article
vignette
Package source: joinet_0.0.2.tar.gz
Windows binaries: r-devel: joinet_0.0.2.zip, r-release: joinet_0.0.2.zip, r-oldrel: joinet_0.0.2.zip
OS X binaries: r-release: joinet_0.0.2.tgz, r-oldrel: joinet_0.0.2.tgz
Old sources: joinet archive

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