calcAUC {puma} | R Documentation

## Calculate Area Under Curve (AUC) for a standard ROC plot.

### Description

Calculates the AUC values for one or more ROC plots.

### Usage

    calcAUC(scores, truthValues, includedProbesets = 1:length(truthValues))

### Arguments

`scores` | A vector of scores. This could be, e.g. one of the columns of the statistics of a `DEResult` object.
`truthValues` | A boolean vector indicating which scores are True Positives.
`includedProbesets` | A vector of indices indicating which scores (and truthValues) are to be used in the calculation. The default is to use all, but a subset can be used if, for example, you only want a subset of the probesets which are not True Positives to be treated as False Positives.

### Value

A single number which is the AUC value.

### Author(s)

Richard D. Pearson

### See Also

Related methods `plotROC` and `numFP`.

### Examples

    class1a <- rnorm(1000,0.2,0.1)
    class2a <- rnorm(1000,0.6,0.2)
    class1b <- rnorm(1000,0.3,0.1)
    class2b <- rnorm(1000,0.5,0.2)
    scores_a <- c(class1a, class2a)
    scores_b <- c(class1b, class2b)
    classElts <- c(rep(FALSE,1000), rep(TRUE,1000))
    print(calcAUC(scores_a, classElts))
    print(calcAUC(scores_b, classElts))

[Package puma version 3.22.0 Index]