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pROC (version 1.4.1)

display and analyze ROC curves

Description

Tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.

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Version

Install

install.packages('pROC')

Monthly Downloads

164,956

Version

1.4.1

License

GPL (>= 3)

Maintainer

Xavier Robin

Last Published

January 27th, 2011

Functions in pROC (1.4.1)

print

Print a ROC curve object
roc

Build a ROC curve
lines.roc

Add a ROC line to a ROC plot
are.paired

Are two ROC curves paired?
coords

Coordinates of a ROC curve
plot.roc

Plot a ROC curve
ci.auc

Compute the confidence interval of the AUC
ci.se

Compute the confidence interval of sensitivities at given specificities
plot.ci

Plot confidence intervals
pROC-package

pROC
ci.sp

Compute the confidence interval of specificities at given sensitivities
ci

Compute the confidence interval of a ROC curve
smooth.roc

Smooth a ROC curve
aSAH

Subarachnoid hemorrhage data
multiclass.roc

Multi-class AUC
ci.thresholds

Compute the confidence interval of thresholds
roc.test

Compare the AUC of two correlated ROC curves
auc

Compute the area under the ROC curve