conf

The object for which to calculate the performance.

For using this on individual ROC curves as implemented by objects of class <code>fbroc.roc</code> see 
<code><a rd-options="" href="/link/conf.fbroc.roc?package=fbroc&version=0.4.1" data-mini-rdoc="fbroc::conf.fbroc.roc">conf.fbroc.roc</a></code>. For paired ROC curves (class <code>conf.paired.roc</code>) see 
<code><a rd-options="" href="/link/conf.fbroc.paired.roc?package=fbroc&version=0.4.1" data-mini-rdoc="fbroc::conf.fbroc.paired.roc">conf.fbroc.paired.roc</a></code>.

Implements a very fast C++ algorithm to quickly bootstrap receiver
operating characteristics (ROC) curves and derived performance metrics,
including the area under the curve (AUC) and the partial area under the curve as well as
the true and false positive rate. The analysis of paired receiver operating curves is supported as well,
so that a comparison of two predictors is possible. You can also plot the
results and calculate confidence intervals. On a typical desktop computer the time needed for
the calculation of 100000 bootstrap replicates given 500 observations requires time on the
order of magnitude of one second.

Erik Peter

fbroc

Fast Algorithms to Bootstrap Receiver Operating Characteristics
Curves

conf function

For using this on individual ROC curves as implemented by objects of class <code>fbroc.roc</code> see 
<code><a rd-options='' href='conf.fbroc.roc'>conf.fbroc.roc</a></code>. For paired ROC curves (class <code>conf.paired.roc</code>) see 
<code><a rd-options='' href='conf.fbroc.paired.roc'>conf.fbroc.paired.roc</a></code>.

conf: Generic S3 function to calculate confidence regions for ROC curves

Description

Usage

Arguments

See Also