cornet: Elastic Net with Dichotomised Outcomes

Implements lasso and ridge regression for dichotomised outcomes (Rauschenberger et al. 2023, <doi:10.1080/02664763.2023.2233057>). Such outcomes are not naturally but artificially binary. They indicate whether an underlying measurement is greater than a threshold.

Version: 0.0.9
Depends: R (≥ 3.0.0)
Imports: glmnet, palasso
Suggests: knitr, testthat, rmarkdown
Enhances: RColorBrewer, MASS, mvtnorm, randomForest, xgboost, MLmetrics
Published: 2023-08-11
Author: Armin Rauschenberger [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
NeedsCompilation: no
Language: en-GB
Materials: README NEWS
CRAN checks: cornet results

Documentation:

Reference manual: cornet.pdf
Vignettes: application
article
simulation
vignette

Downloads:

Package source: cornet_0.0.9.tar.gz
Windows binaries: r-devel: cornet_0.0.9.zip, r-release: cornet_0.0.9.zip, r-oldrel: cornet_0.0.9.zip
macOS binaries: r-release (arm64): cornet_0.0.9.tgz, r-oldrel (arm64): cornet_0.0.9.tgz, r-release (x86_64): cornet_0.0.9.tgz
Old sources: cornet archive

Reverse dependencies:

Reverse imports: joinet, starnet

Linking:

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