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cornet: Penalised Regression for Dichotomised Outcomes

Implements lasso and ridge regression for dichotomised outcomes (<doi:10.1080/02664763.2023.2233057>), i.e., numerical outcomes that were transformed to binary outcomes. Such artificial binary outcomes indicate whether an underlying measurement is greater than a threshold.

Version: 1.0.0
Depends: R (≥ 3.0.0)
Imports: glmnet, palasso
Suggests: knitr, testthat, rmarkdown, RColorBrewer, MASS, mvtnorm, randomForest, xgboost, MLmetrics
Published: 2024-09-26
DOI: 10.32614/CRAN.package.cornet
Author: Armin Rauschenberger ORCID iD [aut, cre]
Maintainer: Armin Rauschenberger <armin.rauschenberger at uni.lu>
BugReports: https://github.com/rauschenberger/cornet/issues
License: GPL-3
URL: https://github.com/rauschenberger/cornet, https://rauschenberger.github.io/cornet/
NeedsCompilation: no
Citation: cornet citation info
Materials: README NEWS
CRAN checks: cornet results

Documentation:

Reference manual: cornet.pdf
Vignettes: application (source, R code)
article (source)
simulation (source, R code)
vignette (source, R code)

Downloads:

Package source: cornet_1.0.0.tar.gz
Windows binaries: r-devel: cornet_1.0.0.zip, r-release: cornet_1.0.0.zip, r-oldrel: cornet_1.0.0.zip
macOS binaries: r-release (arm64): cornet_1.0.0.tgz, r-oldrel (arm64): cornet_1.0.0.tgz, r-release (x86_64): cornet_1.0.0.tgz, r-oldrel (x86_64): cornet_1.0.0.tgz
Old sources: cornet archive

Reverse dependencies:

Reverse imports: joinet, starnet

Linking:

Please use the canonical form https://CRAN.R-project.org/package=cornet to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.