Package: cornet 1.0.0

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.

Authors:Armin Rauschenberger [aut, cre]

cornet_1.0.0.tar.gz
cornet_1.0.0.zip(r-4.7-any)cornet_1.0.0.zip(r-4.6-any)cornet_1.0.0.zip(r-4.5-any)
cornet_1.0.0.tgz(r-4.6-any)cornet_1.0.0.tgz(r-4.5-any)
cornet_1.0.0.tar.gz(r-4.7-any)cornet_1.0.0.tar.gz(r-4.6-any)
cornet_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cornet/json (API)

# Install 'cornet' in R:
install.packages('cornet', repos = c('https://rauschenberger.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/rauschenberger/cornet/issues

Pkgdown/docs site:https://rauschenberger.github.io

On CRAN:

Conda:

5.73 score 2 stars 3 packages 15 scripts 501 downloads 2 exports 11 dependencies

Last updated from:cd95458f51. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK134
source / vignettesOK195
linux-releaseOK114
macos-releaseOK415
macos-oldrelOK128
windows-develOK92
windows-releaseOK96
windows-oldrelOK93
wasm-releaseOK107

Exports:cornetcv.cornet

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixpalassoRcppRcppEigenshapesurvival

Article
Title | Authors | Abstract | Reference

Last update: 2024-09-26
Started: 2019-03-18

Combined Regression
Introduction | Installation | Example | References

Last update: 2024-09-26
Started: 2018-06-14

reproducibility - application
Processing | Analysis | Results | Figures

Last update: 2023-06-02
Started: 2019-09-13

reproducibility - simulation
Graphical abstract | Examples | (not included)

Last update: 2023-06-01
Started: 2019-09-13