Self-exciting point process modelling of crimes on linear networks

Nicoletta D'Angelo*, D. Payares-Garcia, Giada Adelfio, Jorge Mateu

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
88 Downloads (Pure)

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 spatiotemporal 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.

Original languageEnglish
Pages (from-to)1-30
Number of pages30
JournalStatistical modelling
DOIs
Publication statusE-pub ahead of print/First online - 19 May 2022

Keywords

  • 22/3 OA procedure
  • ITC-ISI-JOURNAL-ARTICLE

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