  We consider the segmentation of set of correlated time-series, the
correlation being allowed to take an arbitrary form but being the same at each
time-position. We show that encoding the dependency in a factor model enables
us to use the dynamic programming algorithm for the inference of the
breakpoints, which remains one the most efficient algorithm. We propose a model
selection procedure to determine both the number of breakpoints and the number
of factors. This proposed method is implemented in the FASeg R package, which
is available on the CRAN. We demonstrate the performances of our procedure
through simulation experiments and an application to geodesic data is
presented.
