A factor model approach for the joint segmentation with between-series correlation

Understand

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.