Objective Bayesian Analysis for Change Point Problems

Hinoveanu, Laurentiu, Leisen, Fabrizio, Villa, Cristiano

arXiv.org Machine Learning 

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.

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