conf.fbroc.paired.roc: Generates confidence intervals for the difference in TPR...

In erikpeter/fbroc: Fast Algorithms to Bootstrap Receiver Operating Characteristics Curves

Description

Calculates confidence intervals for the difference in TPR at different FPR values or vice versa. The stepsize at which the TPR or FPR is calculated can be set as needed.

Usage

## S3 method for class 'fbroc.paired.roc'
conf(roc, conf.level = 0.95,
  conf.for = "TPR", steps = 250, ...)

Arguments

roc	An object of class fbroc.paired.roc.
conf.level	Confidence level to be used for the confidence intervals. Defaults to 0.95.
conf.for	Use "tpr" to get confidence regions for the TPR at specific FPRs. Use "fpr" instead for confidence regions for the FPR at specific TPRs.
steps	Number of discrete steps at which the requested rate and the confidence region is calculated. Defaults to 250.
...	Further arguments, that are not used at this time.

Value

A data.frame containing either discrete TPR steps and estimates and confidence bounds for the difference FPR or vice versa, depending upon conf.for.

Details

This function only gives estimates and confidence for the difference in the requested rate (either True Positive Rate or False Positive Rate) between the first and the second classifier. The values given are positive iff the first classifier has a higher rate. To get confidence regions for either of the two underlying ROC curves use conf on the result of extract.roc.

See Also

boot.paired.roc, conf.fbroc.roc,extract.roc

Examples

data(roc.examples)
example <- boot.paired.roc(roc.examples$Cont.Pred, roc.examples$Cont.Pred.Outlier,
                           roc.examples$True.Class, n.boot = 100)
conf(example, conf.for = "tpr", steps = 10) # get confidence regions for Delta TPR at FPR
conf(example, conf.for = "fpr", steps = 10) # get confidence regions for Delta FPR at TPR

erikpeter/fbroc documentation built on May 16, 2019, 8:42 a.m.