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) and the partial area under the curve 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. On a typical desktop computer the time needed for the calculation of 100000 bootstrap replicates given 500 observations requires time on the order of magnitude of one second.

Version: 0.4.1
Depends: R (≥ 3.2.0), ggplot2, methods, stats, utils
Imports: Rcpp
LinkingTo: Rcpp
Published: 2019-03-24
DOI: 10.32614/CRAN.package.fbroc
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: NEWS
CRAN checks: fbroc results


Reference manual: fbroc.pdf


Package source: fbroc_0.4.1.tar.gz
Windows binaries: r-devel: fbroc_0.4.1.zip, r-release: fbroc_0.4.1.zip, r-oldrel: fbroc_0.4.1.zip
macOS binaries: r-release (arm64): fbroc_0.4.1.tgz, r-oldrel (arm64): fbroc_0.4.1.tgz, r-release (x86_64): fbroc_0.4.1.tgz, r-oldrel (x86_64): fbroc_0.4.1.tgz
Old sources: fbroc archive


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