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AUC

functionals of ROC curve


Description

various functionals of ROC (Receiver Operating Characteristic) curves

Usage

AUC(rocobj)
AUCi(rocobj)
pAUC(rocobj,t0)
pAUCi(rocobj,t0)

Arguments

rocobj

element of class rocc

t0

FPR point at which TPR is evaluated or limit in (0,1) to integrate to

Details

AUC, pAUC, AUCi and pAUCi compute the Area Under the Curve.

AUC and pAUC employ the trapezoidal rule. AUCi and pAUCi use integrate().

AUC and AUCi compute the area under the curve from 0 to 1 on the x-axis (i.e., the 1 - specificity axis).

pAUC and pAUCi compute the are under the curve from 0 to argument t0 on the x-axis (i.e., the 1 - specificity axis).

Elements of class rocc can be created by rocdemo.sca() or other constructors you might make using the code of rocdemo.sca() as a template.

Author(s)

Vince Carey (stvjc@channing.harvard.edu)

References

Rosner, B., 2000, Fundamentals of Biostatistics, 5th Ed., pp. 63–65

Duda, R. O., Hart, P. E., Stork, D. G., 2001 Pattern Classification, 2nd Ed., p. 49

See Also

rocdemo.sca

Examples

set.seed(123)
R1 <- rocdemo.sca( rbinom(40,1,.3), rnorm(40), dxrule.sca,
   caseLabel="new case", markerLabel="demo Marker" )
print(AUC(R1))
print(pAUC(R1,.3))
print(pAUCi(R1,.3))
print(ROC(R1,.3))

ROC

utilities for ROC, with microarray focus

v1.66.0
Artistic-2.0
Authors
Vince Carey <stvjc@channing.harvard.edu>, Henning Redestig for C++ language enhancements
Initial release

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