cornet: Elastic Net with Dichotomised Outcomes

Implements lasso and ridge regression for dichotomised outcomes (Rauschenberger et al. 2022). Such outcomes are not naturally but artificially binary. They indicate whether an underlying measurement is greater than a threshold.

Version: 0.0.6
Depends: R (≥ 3.0.0)
Imports: glmnet, palasso
Suggests: knitr, testthat, rmarkdown
Enhances: RColorBrewer, MASS, mvtnorm
Published: 2022-08-17
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_0.0.6.tar.gz
Windows binaries: r-devel: cornet_0.0.6.zip, r-release: cornet_0.0.6.zip, r-oldrel: cornet_0.0.6.zip
macOS binaries: r-release (arm64): cornet_0.0.6.tgz, r-oldrel (arm64): cornet_0.0.6.tgz, r-release (x86_64): cornet_0.0.6.tgz, r-oldrel (x86_64): cornet_0.0.6.tgz
Old sources: cornet archive

Reverse dependencies:

Reverse imports: joinet, starnet

Linking:

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