  In this paper we present a loss-based approach to change point analysis. In
particular, we look at the problem from two perspectives. The first focuses on
the definition of a prior when the number of change points is known a priori.
The second contribution aims to estimate the number of change points by using a
loss-based approach recently introduced in the literature. The latter considers
change point estimation as a model selection exercise. We show the performance
of the proposed approach on simulated data and real data sets.
