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Description

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.

Travis-CI BuildStatus AppVeyor buildstatus CoverageStatus

Scope

Lasso and ridge regression for dichotomised outcomes (extending glmnet).

Installation

Install the current release from CRAN:

install.packages("cornet")

or the latest development version from GitHub:

#install.packages("devtools")
devtools::install_github("rauschenberger/cornet")

Reference

Armin Rauschenberger and Enrico Glaab (2023). “Predicting artificial binary outcomes from high-dimensional data in biomedicine”. Journal or Applied Statistics. In press. doi: 10.1080/02664763.2023.2233057

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Metadata

Version

0.0.9

License

Unknown

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