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
NeedsCompilation: no
Packaged: 2024-09-27 09:06:52 UTC; armin.rauschenberger
Author: Armin Rauschenberger [aut, cre]
    (<https://orcid.org/0000-0001-6498-4801>)
Maintainer: Armin Rauschenberger <armin.rauschenberger@uni.lu>
Repository: CRAN
Date/Publication: 2024-09-27 15:00:10 UTC
Built: R 4.6.0; ; 2026-04-26 13:39:49 UTC; unix
