On Modeling Change Points in Non-Homogeneous Poisson Processes

Failures in repairable systems are often described by means of non-homogeneous Poisson processes, identified by their intensity and mean value functions. Intervention on the systems are likely to modify their reliability, and changes in intensities and mean value functions are therefore induced. We consider different scenarios in which interventions take places and propose models describing each of them. Bayesian analyses, relying on Markov-chain Monte Carlo methods, are illustrated along with applications to simulated and real, widely-known, data.