pROC: display and analyze ROC curves

Tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.

Version: 1.7.3
Depends: R (≥ 2.13)
Imports: plyr, utils, methods, Rcpp (≥ 0.11.1)
LinkingTo: Rcpp
Suggests: microbenchmark, tcltk, MASS, logcondens, doMC, doSNOW
Published: 2014-06-13
Author: Xavier Robin, Natacha Turck, Alexandre Hainard, Natalia Tiberti, Frédérique Lisacek, Jean-Charles Sanchez and Markus Müller.
Maintainer: Xavier Robin <robin at lindinglab.org>
License: GPL (≥ 3)
URL: http://expasy.org/tools/pROC/
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: pROC results

Downloads:

Reference manual: pROC.pdf
Package source: pROC_1.7.3.tar.gz
Windows binaries: r-devel: pROC_1.7.3.zip, r-release: pROC_1.7.3.zip, r-oldrel: pROC_1.7.3.zip
OS X Snow Leopard binaries: r-release: pROC_1.7.3.tgz, r-oldrel: pROC_1.7.3.tgz
OS X Mavericks binaries: r-release: pROC_1.7.3.tgz
Old sources: pROC archive

Reverse dependencies:

Reverse depends: bootfs, LogisticDx, RcmdrPlugin.ROC
Reverse imports: biomod2, mlDNA, randomUniformForest
Reverse suggests: caret, Causata, fscaret, mlr, RcmdrPlugin.EZR, waffect