Self-exciting point process modelling of crimes on linear networks

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...

Full description

Saved in:
Bibliographic Details
Published inStatistical modelling Vol. 24; no. 2; pp. 139 - 168
Main Authors D’Angelo, Nicoletta, Payares, David, Adelfio, Giada, Mateu, Jorge
Format Journal Article
LanguageEnglish
Published New Delhi, India SAGE Publications 01.04.2024
Subjects
spatio-temporal point processes
covariates
self-exciting point processes
crime data
Hawkes processes
linear networks
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:1471-082X
1477-0342
DOI:10.1177/1471082X221094146