fbroc: Fast Algorithms to Bootstrap Receiver Operating Characteristics Curves

Implements a very fast C++ algorithm to quickly bootstrap receiver operating characteristics (ROC) curves and derived performance metrics, including the area under the curve (AUC) as well as the true and false positive rate. The analysis of paired receiver operating curves is supported as well, so that a comparison of two predictors is possible. You can also plot the results and calculate confidence intervals. Currently the calculation of 100000 bootstrap replicates for 500 observations takes about one second.

Version: 0.3.1
Depends: R (≥ 3.2.0), ggplot2, methods, stats, utils
Imports: Rcpp
LinkingTo: Rcpp
Published: 2015-10-12
Author: Erik Peter [aut, cre]
Maintainer: Erik Peter <jerikpeter at googlemail.com>
BugReports: http://github.com/erikpeter/fbroc/issues
License: GPL-2
URL: http://www.epeter-stats.de/roc-curve-analysis-with-fbroc/
NeedsCompilation: yes
Materials: README
CRAN checks: fbroc results

Downloads:

Reference manual: fbroc.pdf
Package source: fbroc_0.3.1.tar.gz
Windows binaries: r-devel: fbroc_0.3.1.zip, r-release: fbroc_0.3.1.zip, r-oldrel: fbroc_0.2.1.zip
OS X Snow Leopard binaries: r-release: fbroc_0.2.1.tgz, r-oldrel: fbroc_0.1.0.tgz
OS X Mavericks binaries: r-release: fbroc_0.3.1.tgz
Old sources: fbroc archive