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Self-exciting point process modelling of crimes on linear networks
dc.contributor.author | D'ANGELO, Nicoletta | |
dc.contributor.author | Payares García, David Enrique | |
dc.contributor.author | adelfio, giada | |
dc.contributor.author | Mateu, Jorge | |
dc.date.accessioned | 2022-10-26T14:44:15Z | |
dc.date.available | 2022-10-26T14:44:15Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | D’Angelo N, Payares D, Adelfio G, Mateu J. Self-exciting point process modelling of crimes on linear networks. Statistical Modelling. 2024;24(2):139-168. doi:10.1177/1471082X221094146 | ca_CA |
dc.identifier.issn | 1471-082X | |
dc.identifier.issn | 1477-0342 | |
dc.identifier.uri | http://hdl.handle.net/10234/200600 | |
dc.description.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. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | SAGE Publications | ca_CA |
dc.relation.isPartOf | Statistical Modelling, 2024, 24, 2 | ca_CA |
dc.rights | © 2022 Statistical Modeling Society | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | ca_CA |
dc.subject | covariates | ca_CA |
dc.subject | crime data | ca_CA |
dc.subject | Hawkes processes | ca_CA |
dc.subject | linear networks | ca_CA |
dc.subject | self-exciting point processes | ca_CA |
dc.subject | spatio-temporal point processes | ca_CA |
dc.title | Self-exciting point process modelling of crimes on linear networks | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1177/1471082X221094146 | |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | ca_CA |
dc.relation.publisherVersion | https://journals.sagepub.com/doi/10.1177/1471082X221094146 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
project.funder.identifier | FFR | ca_CA |
project.funder.name | Future Forests Research | ca_CA |
oaire.awardNumber | FFR 2021 | ca_CA |
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