## 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.

### Value

### Note

### 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))

[Package

*ROC* version 1.4.0

Index]