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: | 1.17.0.1 |
Depends: | R (≥ 2.14) |
Imports: | methods, plyr, Rcpp (≥ 0.11.1) |
LinkingTo: | Rcpp |
Suggests: | microbenchmark, tcltk, MASS, logcondens, doParallel, testthat, vdiffr, ggplot2 |
Published: | 2021-01-13 |
Author: | Xavier Robin |
Maintainer: | Xavier Robin <pROC-cran at xavier.robin.name> |
BugReports: | https://github.com/xrobin/pROC/issues |
License: | GPL (≥ 3) |
URL: | http://expasy.org/tools/pROC/ |
NeedsCompilation: | yes |
Citation: | pROC citation info |
Materials: | README NEWS |
CRAN checks: | pROC results |
Reference manual: | pROC.pdf |
Package source: | pROC_1.17.0.1.tar.gz |
Windows binaries: | r-devel: pROC_1.17.0.1.zip, r-release: pROC_1.17.0.1.zip, r-oldrel: pROC_1.17.0.1.zip |
macOS binaries: | r-release: pROC_1.17.0.1.tgz, r-oldrel: pROC_1.17.0.1.tgz |
Old sources: | pROC archive |
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