{"id":"https://openalex.org/W2904418942","doi":"https://doi.org/10.1007/s11222-018-9845-z","title":"Inference for ETAS models with non-Poissonian mainshock arrival times","display_name":"Inference for ETAS models with non-Poissonian mainshock arrival times","publication_year":2018,"publication_date":"2018-12-13","ids":{"openalex":"https://openalex.org/W2904418942","doi":"https://doi.org/10.1007/s11222-018-9845-z","mag":"2904418942"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-018-9845-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9845-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9845-z.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9845-z.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035967838","display_name":"Aleksandar A. Kolev","orcid":"https://orcid.org/0000-0003-4815-1580"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Aleksandar A. Kolev","raw_affiliation_strings":["Department of Statistical Science, University College London, London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Statistical Science, University College London, London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065768077","display_name":"Gordon J. Ross","orcid":"https://orcid.org/0000-0003-2092-0106"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gordon J. Ross","raw_affiliation_strings":["School of Mathematics, University of Edinburgh, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"School of Mathematics, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035967838"],"corresponding_institution_ids":["https://openalex.org/I45129253"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":{"value":2090,"currency":"EUR","value_usd":2690},"fwci":2.3752,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.90978606,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"29","issue":"5","first_page":"915","last_page":"931"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10110","display_name":"earthquake and tectonic studies","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.6783194541931152},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.4831685423851013},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4704517424106598},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.46694862842559814},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.45693933963775635},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.44027841091156006},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4152262508869171},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.40631136298179626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39298751950263977},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36685729026794434},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3425971269607544},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.341122567653656},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.25318652391433716},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24250072240829468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17165374755859375},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14394459128379822}],"concepts":[{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.6783194541931152},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.4831685423851013},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4704517424106598},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.46694862842559814},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.45693933963775635},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.44027841091156006},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4152262508869171},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.40631136298179626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39298751950263977},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36685729026794434},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3425971269607544},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.341122567653656},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.25318652391433716},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24250072240829468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17165374755859375},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14394459128379822},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s11222-018-9845-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9845-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9845-z.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10069525","is_oa":false,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10069525/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"   Statistics and Computing       (2018)     (In press).  ","raw_type":"Article"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/aa30d1f1-33a1-42e6-9ca9-6378ae24e0f2","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/aa30d1f1-33a1-42e6-9ca9-6378ae24e0f2","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ross, G & Kolev, A A 2019, 'Inference for ETAS Models With Non-Poissonian Mainshock Arrival Times', Statistics and Computing, vol. 29, no. 5, pp. 915-931. https://doi.org/10.1007/s11222-018-9845-z","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.ed.ac.uk:publications/aa30d1f1-33a1-42e6-9ca9-6378ae24e0f2","is_oa":false,"landing_page_url":"http://hdl.handle.net/20.500.11820/aa30d1f1-33a1-42e6-9ca9-6378ae24e0f2","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"doi:10.1007/s11222-018-9845-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-018-9845-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-018-9845-z.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320286","display_name":"University College London","ror":"https://ror.org/02jx3x895"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904418942.pdf","grobid_xml":"https://content.openalex.org/works/W2904418942.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W194111627","https://openalex.org/W601013783","https://openalex.org/W1510085444","https://openalex.org/W1514046945","https://openalex.org/W1626821460","https://openalex.org/W1969238184","https://openalex.org/W1979242667","https://openalex.org/W1985054565","https://openalex.org/W1988612120","https://openalex.org/W1994367483","https://openalex.org/W1998384273","https://openalex.org/W2001552491","https://openalex.org/W2007839873","https://openalex.org/W2019887709","https://openalex.org/W2028944227","https://openalex.org/W2041129400","https://openalex.org/W2043314486","https://openalex.org/W2045656233","https://openalex.org/W2050238052","https://openalex.org/W2064758233","https://openalex.org/W2085512286","https://openalex.org/W2087822214","https://openalex.org/W2093230975","https://openalex.org/W2108207895","https://openalex.org/W2110055968","https://openalex.org/W2110242299","https://openalex.org/W2114311609","https://openalex.org/W2148378080","https://openalex.org/W2149538179","https://openalex.org/W2151689585","https://openalex.org/W2163784148","https://openalex.org/W2168175751","https://openalex.org/W2181393575","https://openalex.org/W2239939964","https://openalex.org/W2324301239","https://openalex.org/W2382529690","https://openalex.org/W2399991609","https://openalex.org/W2488983277","https://openalex.org/W2624781198","https://openalex.org/W3125290923","https://openalex.org/W4248681815","https://openalex.org/W6630117445","https://openalex.org/W6811716405"],"related_works":["https://openalex.org/W3012988968","https://openalex.org/W4287824571","https://openalex.org/W3113268434","https://openalex.org/W2407375987","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W3049691116","https://openalex.org/W2010643158","https://openalex.org/W2106867672","https://openalex.org/W4310268968"],"abstract_inverted_index":{"The":[0],"Hawkes":[1],"process":[2,89],"is":[3,25,116],"a":[4,40,47,100,128,137],"widely":[5],"used":[6,26],"statistical":[7],"model":[8,24],"for":[9,95,133],"point":[10],"processes":[11],"which":[12,61],"produce":[13],"clustered":[14],"event":[15],"times.":[16],"A":[17],"specific":[18],"version":[19],"known":[20],"as":[21,75],"the":[22,35,64,76,86,104,113,121],"ETAS":[23],"in":[27,120],"seismology":[28],"to":[29,93],"forecast":[30],"earthquake":[31],"arrival":[32,65],"times":[33],"under":[34],"assumption":[36,54],"that":[37,63],"mainshocks":[38,68],"follow":[39],"Poisson":[41],"process,":[42],"with":[43],"aftershocks":[44],"triggered":[45],"via":[46],"parametric":[48],"kernel":[49],"function.":[50],"However,":[51],"this":[52],"Poissonian":[53],"contradicts":[55],"several":[56],"aspects":[57],"of":[58,67,112],"seismological":[59],"theory":[60],"suggest":[62],"time":[66],"instead":[69],"follows":[70],"alternative":[71],"renewal":[72],"distributions":[73,97],"such":[74],"Gamma":[77],"or":[78],"Brownian":[79],"Passage":[80],"Time.":[81],"We":[82],"hence":[83],"show":[84],"how":[85],"standard":[87],"ETAS/Hawkes":[88],"can":[90],"be":[91],"extended":[92],"allow":[94],"non-Poissonian":[96],"by":[98],"introducing":[99],"dependence":[101],"based":[102],"on":[103],"underlying":[105],"process\u2019":[106],"behaviour.":[107],"Direct":[108],"maximum":[109],"likelihood":[110],"estimation":[111,135],"resulting":[114],"models":[115],"not":[117],"computationally":[118],"feasible":[119],"general":[122],"case,":[123],"so":[124],"we":[125],"also":[126],"present":[127],"novel":[129],"Bayesian":[130],"MCMC":[131],"algorithm":[132],"efficient":[134],"using":[136],"latent":[138],"variable":[139],"representation.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-17T09:09:15.849793","created_date":"2025-10-10T00:00:00"}
