A Multidimensional Fractional Hawkes Process for Multiple Earthquake Mainshock Aftershock Sequences

Fuente: arXiv
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Main Authors: Davis, Louis, Baeumer, Boris, Wang, Ting
Format: Preprint
Published: 2024
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author Davis, Louis
Baeumer, Boris
Wang, Ting
author_facet Davis, Louis
Baeumer, Boris
Wang, Ting
contents Most point process models for earthquakes currently in the literature assume the magnitude distribution is i.i.d. potentially hindering the ability of the model to describe the main features of data sets containing multiple earthquake mainshock aftershock sequences in succession. This study presents a novel multidimensional fractional Hawkes process model designed to capture magnitude dependent triggering behaviour by incorporating history dependence into the magnitude distribution. This is done by discretising the magnitude range into disjoint intervals and modelling events with magnitude in these ranges as the subprocesses of a mutually exciting Hawkes process using the Mittag-Leffler density as the kernel function. We demonstrate this model's use by applying it to two data sets, 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 data sets all metrics indicate that the multidimensional fractional Hawkes process performs favourably against the ETAS model. Furthermore, using the multidimensional fractional Hawkes process we are able to infer characteristics of the data sets that are consistent with results currently in the literature and that cannot be found by using the ETAS model.
format Preprint
id arxiv_https___arxiv_org_abs_2404_01478
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Multidimensional Fractional Hawkes Process for Multiple Earthquake Mainshock Aftershock Sequences
Davis, Louis
Baeumer, Boris
Wang, Ting
Applications
Most point process models for earthquakes currently in the literature assume the magnitude distribution is i.i.d. potentially hindering the ability of the model to describe the main features of data sets containing multiple earthquake mainshock aftershock sequences in succession. This study presents a novel multidimensional fractional Hawkes process model designed to capture magnitude dependent triggering behaviour by incorporating history dependence into the magnitude distribution. This is done by discretising the magnitude range into disjoint intervals and modelling events with magnitude in these ranges as the subprocesses of a mutually exciting Hawkes process using the Mittag-Leffler density as the kernel function. We demonstrate this model's use by applying it to two data sets, 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 data sets all metrics indicate that the multidimensional fractional Hawkes process performs favourably against the ETAS model. Furthermore, using the multidimensional fractional Hawkes process we are able to infer characteristics of the data sets that are consistent with results currently in the literature and that cannot be found by using the ETAS model.
title A Multidimensional Fractional Hawkes Process for Multiple Earthquake Mainshock Aftershock Sequences
topic Applications
url https://arxiv.org/abs/2404.01478