A Multivariate Fractional Hawkes Process for Multiple Earthquake Mainshock Aftershock Sequences.
Most point process models for earthquakes in the literature assume that the magnitude is independent and identically distributed. This potentially hinders the ability of the model to describe the main features of datasets containing multiple earthquake mainshock aftershock sequences in succession. T...
| Publicado en: | American Statistician Vol. 80; no. 3; pp. 453 - 463 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Taylor & Francis Ltd
Aug2026
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=195622624&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 195622624 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: Y pubinfo: dt: Aug2026 vid: 80 iid: 3 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 195622624 10.1080/00031305.2025.2588128 ppf: 453 ppct: 10 formats: tig: atl: A Multivariate Fractional Hawkes Process for Multiple Earthquake Mainshock Aftershock Sequences. aug: au: Davis, Louis Baeumer, Boris Wang, Ting affil: Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand Department of Statistics, Stanford University, Stanford, CA su: Japan Earthquake aftershocks Point processes Earthquake hazard analysis Earthquake magnitude measurement Probability density function Earthquake prediction sug: subj: Japan Earthquake aftershocks Point processes Earthquake hazard analysis Earthquake magnitude measurement Probability density function Earthquake prediction keyword: Information gain Maximum likelihood Point process Residual analysis Seismic activity Information gain Maximum likelihood Point process Residual analysis Seismic activity ab: Most point process models for earthquakes in the literature assume that the magnitude is independent and identically distributed. This potentially hinders the ability of the model to describe the main features of datasets containing multiple earthquake mainshock aftershock sequences in succession. This study presents a novel multivariate fractional Hawkes process model designed to capture magnitude dependent triggering behavior by incorporating history dependence into the magnitude distribution. This is done by discretizing the magnitude range into disjoint intervals and modeling events with magnitude in these ranges as the subprocesses of a mutually exciting Hawkes process using the Mittag-Leffler density as the kernel function so that the point process has a history dependent mark distribution. We apply this model to two datasets, Japan and the Middle America Trench, both containing multiple mainshock aftershock sequences and compare it to the existing ETAS model by using information criteria, residual diagnostics and retrospective prediction performance. We find that for both datasets all metrics indicate that the multivariate fractional Hawkes process performs favorably against the ETAS model due to its history dependent magnitude distribution. Furthermore, we are able to infer characteristics of the datasets that cannot be inferred from the ETAS model. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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