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FLP estimation of semi-parametric models for space-time point processes and diagnostic tools

  • Autori: Adelfio, G.; Chiodi, M.
  • Anno di pubblicazione: 2015
  • Tipologia: Articolo in rivista (Articolo in rivista)
  • Parole Chiave: ETAS model; EtasFLP; R package; Space-time point processes; Computers in Earth Sciences; Statistics and Probability; Management, Monitoring, Policy and Law
  • OA Link:


The conditional intensity function of a space-time branching model is defined by the sum of two main components: the long-run term intensity and short-run term one. Their simultaneous estimation is a complex issue that usually requires the use of hard computational techniques. This paper deals with a new mixed estimation approach for a particular space-time branching model, the Epidemic Type Aftershock Sequence model. This approach uses a simultaneous estimation of the different model components, alternating a parametric step for estimating the induced component by Maximum Likelihood and a non-parametric estimation step, for the background intensity, by FLP (Forward Predictive Likelihood).Moreover, proper graphical tools for diagnostics have been developed and collected, together with the used implemented code in a R package here introduced, named etasFLP.