Package: fbroc 0.4.1

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.

Authors:Erik Peter [aut, cre]

fbroc_0.4.1.tar.gz
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fbroc.pdf |fbroc.html✨
fbroc/json (API)
NEWS

# Install 'fbroc' in R:
install.packages('fbroc', repos = c('https://erikpeter.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/erikpeter/fbroc/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • roc.examples - Examples of predictions for ROC curve construction

On CRAN:

Conda:

cpp

4.28 score 7 stars 18 scripts 431 downloads 3 mentions 6 exports 29 dependencies

Last updated 6 years agofrom:14dbfa1750. Checks:4 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-win-x86_64NOTEMar 06 2025
R-4.5-mac-x86_64NOTEMar 06 2025
R-4.5-mac-aarch64NOTEMar 06 2025
R-4.5-linux-x86_64NOTEMar 06 2025
R-4.4-win-x86_64NOTEMar 06 2025
R-4.4-mac-x86_64NOTEMar 06 2025
R-4.4-mac-aarch64NOTEMar 06 2025
R-4.4-linux-x86_64NOTEMar 06 2025
R-4.3-win-x86_64OKMar 06 2025
R-4.3-mac-aarch64OKMar 06 2025
R-4.3-mac-x86_64OKFeb 04 2025

Exports:boot.paired.rocboot.rocboot.tpr.at.fprconfextract.rocperf

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcpprlangscalestibbleutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Bootstrap paired ROC curvesboot.paired.roc
Bootstrap ROC curveboot.roc
Process bootstrapped TPR/FPR at thresholds matrix into TPR at FPR matrixboot.tpr.at.fpr
Generic S3 function to calculate confidence regions for ROC curvesconf
Generates confidence intervals for the difference in TPR between two predictors for a range of FPRs or vice versaconf.fbroc.paired.roc
Generates confidence intervals for the TPR for a range of FPRs or vice versaconf.fbroc.roc
Extracts one from two paired ROC curves from a 'fbroc.paired.roc' objectextract.roc
fbroc: A package for fast bootstrap analysis and comparison of ROC curvesfbroc-package fbroc
Generic S3 function to calculate performance estimates for ROC curvesperf
Calculate performance for paired bootstrapped ROC curvesperf.fbroc.paired.roc
Calculate performance for bootstrapped ROC curveperf.fbroc.roc
Plots function for object of classfbroc.confplot.fbroc.conf
Plots function for object of class 'fbroc.conf.paired'plot.fbroc.conf.paired
Plots a 'fbroc.paired.roc' objectplot.fbroc.paired.roc
Plots ROC based performance metric as histogramplot.fbroc.perf
Plots the difference between the bootstrapped performance estimate of the first and the second classifier.plot.fbroc.perf.paired
Plots a 'fbroc.roc' objectplot.fbroc.roc
Prints information about a 'fbroc.perf' objectprint.fbroc.perf
Prints information about a 'fbroc.perf.paired' objectprint.fbroc.perf.paired
Prints information about a 'fbroc.roc' objectprint.fbroc.roc
Examples of predictions for ROC curve constructionroc.examples