Package: joinet
Version: 1.0.0
Title: Penalised Multivariate Regression ('Multi-Target Learning')
Description: 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>).
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
Authors@R: person(given="Armin",family="Rauschenberger",email="armin.rauschenberger@uni.lu",role=c("aut","cre"),comment=c(ORCID="0000-0001-6498-4801"))
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 7.3.2
URL: https://github.com/rauschenberger/joinet,
        https://rauschenberger.github.io/joinet/
BugReports: https://github.com/rauschenberger/joinet/issues
Repository: https://rauschenberger.r-universe.dev
Date/Publication: 2024-09-27 06:01:46 UTC
RemoteUrl: https://github.com/rauschenberger/joinet
RemoteRef: HEAD
RemoteSha: d5f0b581288f0231a6c9d5e4d1d7de3a412a1aa9
NeedsCompilation: no
Packaged: 2026-10-10 14:39:15 UTC; root
Author: Armin Rauschenberger [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-6498-4801>)
Maintainer: Armin Rauschenberger <armin.rauschenberger@uni.lu>