  We consider the multiple breakpoint detection problem, which is concerned
with detecting the locations of several distinct changes in a one-dimensional
noisy data series. We propose the breakpointError, a function that can be used
to evaluate estimated breakpoint locations, given the known locations of true
breakpoints. We discuss an application of the breakpointError for finding
optimal penalties for breakpoint detection in simulated data. Finally, we show
how to relax the breakpointError to obtain an annotation error function which
can be used more readily in practice on real data. A fast C implementation of
an algorithm that computes the breakpointError is available in an R package on
R-Forge.
