date: 2022-08-27T07:35:53Z pdf:PDFVersion: 1.6 pdf:docinfo:title: Solving three major biases of the ETAS model to improve forecasts of the 2019 Ridgecrest sequence xmp:CreatorTool: Springer access_permission:can_print_degraded: true subject: Stochastic Environmental Research and Risk Assessment, https://doi.org/10.1007/s00477-022-02221-2 pdfa:PDFVersion: A-2b xmpMM:History:Action: converted dc:format: application/pdf; version=1.6 pdf:docinfo:custom:robots: noindex pdf:docinfo:creator_tool: Springer access_permission:fill_in_form: true xmpMM:History:When: 2022-08-27T13:04:54Z pdf:encrypted: false dc:title: Solving three major biases of the ETAS model to improve forecasts of the 2019 Ridgecrest sequence modified: 2022-08-27T07:35:53Z cp:subject: Stochastic Environmental Research and Risk Assessment, https://doi.org/10.1007/s00477-022-02221-2 xmpMM:History:SoftwareAgent: pdfToolbox pdf:docinfo:custom:CrossMarkDomains[1]: springer.com robots: noindex pdf:docinfo:subject: Stochastic Environmental Research and Risk Assessment, https://doi.org/10.1007/s00477-022-02221-2 xmpMM:History:InstanceID: uuid:10e612ba-1fe0-44e1-88ad-fa9c1555054f pdf:docinfo:creator: Christian Grimm meta:author: Sebastian Hainzl meta:creation-date: 2022-04-15T13:36:58Z pdf:docinfo:custom:CrossmarkMajorVersionDate: 2010-04-23 created: Fri Apr 15 15:36:58 CEST 2022 access_permission:extract_for_accessibility: true Creation-Date: 2022-04-15T13:36:58Z pdfaid:part: 2 pdf:docinfo:custom:CrossMarkDomains[2]: springerlink.com pdf:docinfo:custom:doi: 10.1007/s00477-022-02221-2 pdf:docinfo:custom:CrossmarkDomainExclusive: true Author: Sebastian Hainzl producer: Acrobat Distiller 10.1.8 (Windows) CrossmarkDomainExclusive: true pdf:docinfo:producer: Acrobat Distiller 10.1.8 (Windows) doi: 10.1007/s00477-022-02221-2 dc:description: Stochastic Environmental Research and Risk Assessment, https://doi.org/10.1007/s00477-022-02221-2 Keywords: ETAS; Short-term incompleteness; Anisotropic spatial kernel; Ridgecrest access_permission:modify_annotations: true dc:creator: Sebastian Hainzl description: Stochastic Environmental Research and Risk Assessment, https://doi.org/10.1007/s00477-022-02221-2 dcterms:created: 2022-04-15T13:36:58Z Last-Modified: 2022-08-27T07:35:53Z dcterms:modified: 2022-08-27T07:35:53Z title: Solving three major biases of the ETAS model to improve forecasts of the 2019 Ridgecrest sequence xmpMM:DocumentID: uuid:949ef4fe-2a14-4e1c-92c2-98bbf7ccd353 Last-Save-Date: 2022-08-27T07:35:53Z CrossMarkDomains[1]: springer.com pdf:docinfo:keywords: ETAS; Short-term incompleteness; Anisotropic spatial kernel; Ridgecrest pdf:docinfo:modified: 2022-08-27T07:35:53Z meta:save-date: 2022-08-27T07:35:53Z Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Sebastian Hainzl pdfaid:conformance: B dc:subject: ETAS; Short-term incompleteness; Anisotropic spatial kernel; Ridgecrest access_permission:assemble_document: true xmpTPg:NPages: 20 access_permission:extract_content: true access_permission:can_print: true CrossMarkDomains[2]: springerlink.com meta:keyword: ETAS; Short-term incompleteness; Anisotropic spatial kernel; Ridgecrest access_permission:can_modify: true pdf:docinfo:created: 2022-04-15T13:36:58Z CrossmarkMajorVersionDate: 2010-04-23