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.
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