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NICOLETTA D'ANGELO

Self-exciting point process modelling of crimes on linear networks

  • Autori: Nicoletta D'Angelo; David Payares; Giada Adelfio; Jorge Mateu
  • Anno di pubblicazione: 2022
  • Tipologia: Articolo in rivista
  • OA Link: http://hdl.handle.net/10447/542463

Abstract

Although there are recent developments for the analysis of first and second-order characteristics of point processes on networks, there are very few attempts in introducing models for network data. Motivated by the analysis of crime data in Bucaramanga (Colombia), we propose a spatio-temporal Hawkes point process model adapted to events living on linear networks. We first consider a non-parametric modelling strategy, for which we follow a non-parametric estimation of both the background and the triggering components. Then we consider a semi-parametric version, including a parametric estimation of the background based on covariates, and a non-parametric one of the triggering effects. Our model can be easily adapted to multi-type processes. Our network model outperforms a planar version, improving the fitting of the self-exciting point process model.