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fbroc (version 0.3.1)

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. 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.

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Version

Install

install.packages('fbroc')

Monthly Downloads

244

Version

0.3.1

License

GPL-2

Maintainer

Erik Peter

Last Published

October 12th, 2015

Functions in fbroc (0.3.1)

perf

Generic S3 function to calculate performance estimates for ROC curves
boot.tpr.at.fpr

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

Extracts one from two paired ROC curves from a fbroc.paired.roc object
plot.fbroc.conf.paired

Plots function for object of class fbroc.conf.paired
conf.fbroc.roc

Generates confidence intervals for the TPR for a range of FPRs or vice versa
plot.fbroc.roc

Plots a fbroc.roc object
boot.roc

Bootstrap ROC curve
conf

Generic S3 function to calculate confidence regions for ROC curves
fbroc

fbroc: A package for fast bootstrap analysis and comparison of ROC curves
plot.fbroc.conf

Plots function for object of class{fbroc.conf}
plot.fbroc.paired.roc

Plots a fbroc.paired.roc object
perf.fbroc.paired.roc

Calculate performance for paired bootstrapped ROC curves
print.fbroc.roc

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

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

Prints information about a fbroc.perf.paired object
roc.examples

Examples of predictions for ROC curve construction
plot.fbroc.perf.paired

Plots the difference between the bootstrapped performance estimate of the first and the second classifier.
boot.paired.roc

Bootstrap paired ROC curves
perf.fbroc.roc

Calculate performance for bootstrapped ROC curve
plot.fbroc.perf

Plots ROC based performance metric as histogram
conf.fbroc.paired.roc

Generates confidence intervals for the difference in TPR between two predictors for a range of FPRs or vice versa