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fbroc (version 0.2.1)

Fast Algorithms to Bootstrap Receiver Operating Characteristics Curves

Description

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. You can also plot the results and calculate confidence intervals. Currently the calculation of 100000 bootstrap replicates for 500 observations takes about one second.

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Version

Install

install.packages('fbroc')

Monthly Downloads

244

Version

0.2.1

License

GPL-2

Maintainer

Erik Peter

Last Published

June 7th, 2015

Functions in fbroc (0.2.1)

print.fbroc.perf

Prints information about a fbroc.perf object
print.fbroc.roc

Prints information about a fbroc.roc object
roc.examples

Examples of predictions for ROC curve construction
fbroc

fbroc: A package for fast bootstrap analysis of ROC curves
plot.fbroc.roc

Plots a fbroc.roc object
boot.tpr.at.fpr

Process bootstrapped TPR/FPR at thresholds matrix into TPR at FPR matrix
perf.roc

Calculate performance for bootstrapped ROC curve
plot.fbroc.perf

Plots ROC based performance metric as histogram
boot.roc

Bootstrap ROC curve
conf.roc

Generates confidence intervals for the TPR for a range of FPRs