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: 1.8
Depends: R (≥ 2.14)
Imports: plyr, utils, methods, Rcpp (≥ 0.11.1)
LinkingTo: Rcpp
Suggests: microbenchmark, tcltk, MASS, logcondens, doParallel
Published: 2015-05-05
Author: Xavier Robin, Natacha Turck, Alexandre Hainard, Natalia Tiberti, Frédérique Lisacek, Jean-Charles Sanchez and Markus Müller.
Maintainer: Xavier Robin <robin at>
License: GPL (≥ 3)
NeedsCompilation: yes
Citation: pROC citation info
Materials: README NEWS
CRAN checks: pROC results


Reference manual: pROC.pdf
Package source: pROC_1.8.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: pROC_1.8.tgz, r-oldrel: pROC_1.8.tgz
OS X Mavericks binaries: r-release: pROC_1.8.tgz
Old sources: pROC archive

Reverse dependencies:

Reverse depends: bimixt, FRESA.CAD, RcmdrPlugin.ROC, ThresholdROC
Reverse imports: biomod2, FAMILY, LogisticDx, LOGIT, mlDNA, randomUniformForest, SCGLR
Reverse suggests: aplore3, caret, caretEnsemble, Causata, fscaret, mldr, mlr, RcmdrPlugin.EZR, waffect