Package: cornet 0.0.9

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.

Authors:Armin Rauschenberger [aut, cre]

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cornet.pdf |cornet.html✨
cornet/json (API)
NEWS

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

Peer review:

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

On CRAN:

2 exports 2 stars 1.54 score 11 dependencies 3 dependents 13 scripts 354 downloads

Last updated 1 years agofrom:3668089f9c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 04 2024
R-4.5-winOKSep 04 2024
R-4.5-linuxOKSep 04 2024
R-4.4-winOKSep 04 2024
R-4.4-macOKSep 04 2024
R-4.3-winOKSep 04 2024
R-4.3-macOKSep 04 2024

Exports:cornetcv.cornet

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixpalassoRcppRcppEigenshapesurvival

reproducibility - application

Rendered fromapplication.Rmdusingknitr::rmarkdownon Sep 04 2024.

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

Article

Rendered fromarticle.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2023-08-11
Started: 2019-03-18

reproducibility - simulation

Rendered fromsimulation.Rmdusingknitr::rmarkdownon Sep 04 2024.

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

Combined Regression

Rendered fromvignette.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2023-02-16
Started: 2018-06-14