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auRoc: Various Methods to Estimate the AUC

Estimate the AUC using a variety of methods as follows: (1) frequentist nonparametric methods based on the Mann-Whitney statistic or kernel methods. (2) frequentist parametric methods using the likelihood ratio test based on higher-order asymptotic results, the signed log-likelihood ratio test, the Wald test, or the approximate ”t” solution to the Behrens-Fisher problem. (3) Bayesian parametric MCMC methods.

Version: 0.2-1
Depends: R (≥ 3.0.2), rjags (≥ 3-11), ProbYX (≥ 1.1)
Imports: coda (≥ 0.16-1), MBESS (≥ 3.3.3)
Published: 2020-04-04
DOI: 10.32614/CRAN.package.auRoc
Author: Dai Feng [aut, cre], Damjan Manevski [auc], Maja Pohar Perme [auc]
Maintainer: Dai Feng <daifeng.stat at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: auRoc results

Documentation:

Reference manual: auRoc.pdf

Downloads:

Package source: auRoc_0.2-1.tar.gz
Windows binaries: r-devel: auRoc_0.2-1.zip, r-release: auRoc_0.2-1.zip, r-oldrel: auRoc_0.2-1.zip
macOS binaries: r-release (arm64): auRoc_0.2-1.tgz, r-oldrel (arm64): auRoc_0.2-1.tgz, r-release (x86_64): auRoc_0.2-1.tgz, r-oldrel (x86_64): auRoc_0.2-1.tgz
Old sources: auRoc archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.