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pROC (version 1.3.2)

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

114,204

Version

1.3.2

License

GPL (>= 3)

Maintainer

Xavier Robin

Last Published

August 24th, 2010

Functions in pROC (1.3.2)

ci.auc

Compute the confidence interval of the AUC
coords

Coordinates of a ROC curve
plot.roc

Plot a ROC curve
roc.test

Compare the AUC of two correlated ROC curves
print

Print a ROC curve object
aSAH

Subarachnoid hemorrhage data
auc

Compute the area under the ROC curve
roc

Build a ROC curve
are.paired

Are two ROC curves paired?
ci.thresholds

Compute the confidence interval of thresholds
smooth.roc

Smooth a ROC curve
plot.ci

Plot confidence intervals
ci.se

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

Compute the confidence interval of specificities at given sensitivities
ci

Compute the confidence interval of a ROC curve
pROC-package

pROC
lines.roc

Add a ROC line to a ROC plot