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 Rauschenberger [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 |
Reference manual: | joinet.pdf |
Vignettes: |
article (source) analysis (source, R code) vignette (source, R code) |
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 imports: | transreg |
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