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pROC (version 1.5.4)

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

138,160

Version

1.5.4

License

GPL (>= 3)

Maintainer

ORPHANED

Last Published

September 10th, 2012

Functions in pROC (1.5.4)

roc

Build a ROC curve
aSAH

Subarachnoid hemorrhage data
has.partial.auc

Does the ROC curve have a partial AUC?
roc.test

Compare the AUC of two ROC curves
auc

Compute the area under the ROC curve
plot.roc

Plot a ROC curve
ci.sp

Compute the confidence interval of specificities at given sensitivities
cov.roc

Covariance of two paired ROC curves
ci.thresholds

Compute the confidence interval of thresholds
lines.roc

Add a ROC line to a ROC plot
are.paired

Are two ROC curves paired?
print

Print a ROC curve object
ci.auc

Compute the confidence interval of the AUC
ci

Compute the confidence interval of a ROC curve
coords

Coordinates of a ROC curve
var.roc

Variance of a ROC curve
ci.se

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

Plot confidence intervals
multiclass.roc

Multi-class AUC
pROC-package

pROC
smooth.roc

Smooth a ROC curve