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Explaining the seismic moment of large earthquakes by heavy and extremely heavy tailed models

datacite.subject.sdg07:Energias Renováveis e Acessíveis
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorFelgueiras, Miguel Martins
dc.date.accessioned2025-11-19T13:23:52Z
dc.date.available2025-11-19T13:23:52Z
dc.date.issued2012-08-15
dc.description.abstractThe search of physical laws that explain the energy released by the great magnitude earthquakes is a relevant question, since as a rule they cause heavy losses. Several statistical distributions have been considered in this process, namely heavy tailed laws, like the Pareto distribution with shape parameter α ≈ 0. 6667. Yet, for the usually considered Californian region (where earthquakes with moment magnitude, MW, greater than 7. 9 were never registered) the Pareto distribution with index near the above mentioned seems to have a "too heavy" tail for explaining the bigger earthquakes seismic moments. Usually an exponential tapper is applied to the distribution right tail (above the so called corner seismic moment), or another distribution is considered to explain these high seismic moment data (like another Pareto with different shape parameter). The situation is different for other regions where seisms of larger magnitudes do occur, leading to data sets for which heavy or even extremely heavy tailed models are appropriated. The purpose of this paper is to reduce the seismic moment, M0, of the very large earthquakes to particular heavy and extremely heavy tailed distributions. Using world seismic moment information, we apply Pareto, Log-Pareto and extended slash Pareto distributions to the data, truncated for M0 ≥ 1021 Nm and for M0 ≥ 1021. 25 Nm. For these great seisms we conclude that extended slash Pareto is a promising alternative to the more traditional Pareto and Log-Pareto distributions as a candidate to the real model underlying the data.eng
dc.description.sponsorshipThis research was partially sponsored by national funds through the Fundação Nacional para a Ciência e Tecnologia, Portugal FCT under the project (PEst-OE/MAT/UI0006/2011).
dc.identifier.citationFelgueiras, M.M. Explaining the seismic moment of large earthquakes by heavy and extremely heavy tailed models. Int J Geomath 3, 209–222 (2012). https://doi.org/10.1007/s13137-012-0042-5
dc.identifier.doi10.1007/s13137-012-0042-5
dc.identifier.issn1869-2672
dc.identifier.issn1869-2680
dc.identifier.urihttp://hdl.handle.net/10400.8/14676
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Science and Business Media LLC
dc.relationStrategic Project - UI 6 - 2011-2012
dc.relation.hasversionhttps://link.springer.com/article/10.1007/s13137-012-0042-5
dc.relation.ispartofGEM - International Journal on Geomathematics
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectExtended slash Pareto
dc.subjectLarge earthquake
dc.subjectLog-Pareto
dc.subjectPareto
dc.subjectSeismic moments fitting
dc.titleExplaining the seismic moment of large earthquakes by heavy and extremely heavy tailed modelseng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleStrategic Project - UI 6 - 2011-2012
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/PEst-OE%2FMAT%2FUI0006%2F2011/PT
oaire.citation.endPage222
oaire.citation.issue2
oaire.citation.startPage209
oaire.citation.titleGEM - International Journal on Geomathematics
oaire.citation.volume3
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFelgueiras
person.givenNameMiguel
person.identifier.ciencia-id0F1B-DE05-36E5
person.identifier.orcid0000-0001-5450-7374
person.identifier.ridM-8134-2019
person.identifier.scopus-author-id50861001200
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublicationb7404fe1-3566-46d5-9d02-341bec92615b
relation.isAuthorOfPublication.latestForDiscoveryb7404fe1-3566-46d5-9d02-341bec92615b
relation.isProjectOfPublication88efb123-47b7-437c-8517-6a736d2db958
relation.isProjectOfPublication.latestForDiscovery88efb123-47b7-437c-8517-6a736d2db958

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