{"id":"https://openalex.org/W2746613421","doi":"https://doi.org/10.1137/17m1161397","title":"Global Sensitivity Analysis for Statistical Model Parameters","display_name":"Global Sensitivity Analysis for Statistical Model Parameters","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2746613421","doi":"https://doi.org/10.1137/17m1161397","mag":"2746613421"},"language":"en","primary_location":{"id":"doi:10.1137/17m1161397","is_oa":false,"landing_page_url":"https://doi.org/10.1137/17m1161397","pdf_url":null,"source":{"id":"https://openalex.org/S2911293512","display_name":"SIAM/ASA Journal on Uncertainty Quantification","issn_l":"2166-2525","issn":["2166-2525"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM/ASA Journal on Uncertainty Quantification","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1708.07441","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009518158","display_name":"Joseph Hart","orcid":"https://orcid.org/0000-0001-6932-7894"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Joseph L. Hart","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091899229","display_name":"Julie Bessac","orcid":"https://orcid.org/0000-0001-6407-2423"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Julie Bessac","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5011371760","display_name":"Emil M. Constantinescu","orcid":"https://orcid.org/0000-0002-7003-6899"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emil M. Constantinescu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7003-6899","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009518158"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0023785,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":"1","first_page":"67","last_page":"92"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9641000032424927,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.7260761260986328},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.6451709866523743},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5485115051269531},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5029415488243103},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.46568503975868225},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4556484818458557},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45411989092826843},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.45335710048675537},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4407355785369873},{"id":"https://openalex.org/keywords/model-parameter","display_name":"Model parameter","score":0.41866233944892883},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3324320912361145},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3304937779903412},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30112797021865845},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29329198598861694},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.29324203729629517},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13527262210845947}],"concepts":[{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.7260761260986328},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.6451709866523743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5485115051269531},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5029415488243103},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.46568503975868225},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4556484818458557},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45411989092826843},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.45335710048675537},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4407355785369873},{"id":"https://openalex.org/C2983447341","wikidata":"https://www.wikidata.org/wiki/Q1413083","display_name":"Model parameter","level":2,"score":0.41866233944892883},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3324320912361145},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3304937779903412},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30112797021865845},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29329198598861694},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29324203729629517},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13527262210845947},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1137/17m1161397","is_oa":false,"landing_page_url":"https://doi.org/10.1137/17m1161397","pdf_url":null,"source":{"id":"https://openalex.org/S2911293512","display_name":"SIAM/ASA Journal on Uncertainty Quantification","issn_l":"2166-2525","issn":["2166-2525"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM/ASA Journal on Uncertainty Quantification","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1708.07441","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.07441","pdf_url":"https://arxiv.org/pdf/1708.07441","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2746613421","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/1708.07441.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:osti.gov:1510482","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/1510482","pdf_url":null,"source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"doi:10.48550/arxiv.1708.07441","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1708.07441","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1708.07441","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.07441","pdf_url":"https://arxiv.org/pdf/1708.07441","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7954425250","display_name":null,"funder_award_id":"DE-AC02-06CH11357","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8492689677","display_name":null,"funder_award_id":"DMS-1127914","funder_id":"https://openalex.org/F4320337380","funder_display_name":"Division of Mathematical Sciences"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320337380","display_name":"Division of Mathematical Sciences","ror":"https://ror.org/051fftw81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W930421","https://openalex.org/W100464641","https://openalex.org/W999207820","https://openalex.org/W1493921296","https://openalex.org/W1498636830","https://openalex.org/W1567885833","https://openalex.org/W1963591457","https://openalex.org/W1984925443","https://openalex.org/W1992265879","https://openalex.org/W1994080277","https://openalex.org/W2001195867","https://openalex.org/W2002661807","https://openalex.org/W2008870058","https://openalex.org/W2011587268","https://openalex.org/W2016493615","https://openalex.org/W2025175130","https://openalex.org/W2029767409","https://openalex.org/W2035363534","https://openalex.org/W2038012176","https://openalex.org/W2040612054","https://openalex.org/W2041619292","https://openalex.org/W2043432627","https://openalex.org/W2050518533","https://openalex.org/W2071544114","https://openalex.org/W2081375966","https://openalex.org/W2093223772","https://openalex.org/W2097441841","https://openalex.org/W2101589741","https://openalex.org/W2102862543","https://openalex.org/W2111963426","https://openalex.org/W2143476164","https://openalex.org/W2148402438","https://openalex.org/W2149426898","https://openalex.org/W2159473410","https://openalex.org/W2163174637","https://openalex.org/W2163669663","https://openalex.org/W2168475168","https://openalex.org/W2188388411","https://openalex.org/W2341440935","https://openalex.org/W2343051744","https://openalex.org/W2344769335","https://openalex.org/W2479909395","https://openalex.org/W2518039540","https://openalex.org/W2530685584","https://openalex.org/W2544972693","https://openalex.org/W2954040150","https://openalex.org/W2963358185","https://openalex.org/W2963766850","https://openalex.org/W2963956685","https://openalex.org/W2964075504","https://openalex.org/W2964320047","https://openalex.org/W2995161752"],"related_works":["https://openalex.org/W2809245284","https://openalex.org/W3158988754","https://openalex.org/W2884839891","https://openalex.org/W3023276807","https://openalex.org/W1497611183","https://openalex.org/W3124852082","https://openalex.org/W3048230050","https://openalex.org/W85179170","https://openalex.org/W2600510234","https://openalex.org/W2949418918","https://openalex.org/W1750536449","https://openalex.org/W2043371662","https://openalex.org/W2950773260","https://openalex.org/W1998160957","https://openalex.org/W2734565492","https://openalex.org/W1998523300","https://openalex.org/W2976116815","https://openalex.org/W2905342837","https://openalex.org/W2972883761","https://openalex.org/W2125090308"],"abstract_inverted_index":{"Global":[0],"sensitivity":[1],"analysis":[2],"(GSA)":[3],"is":[4,114,145],"frequently":[5],"used":[6],"to":[7,27,70,88,116],"analyze":[8,28],"the":[9,29,80,122],"influence":[10,30],"of":[11,31,67],"uncertain":[12],"parameters":[13,32,130],"in":[14,33],"mathematical":[15],"models":[16],"and":[17,44,59,92,101,106,135],"simulations.":[18],"In":[19],"principle,":[20],"tools":[21,69],"from":[22,121],"GSA":[23,68,95],"may":[24,38],"be":[25],"extended":[26],"statistical":[34,71,81,97],"models.":[35,72],"Such":[36],"analyses":[37],"enable":[39,93],"reduced":[40,137],"or":[41,141],"parsimonious":[42],"modeling":[43],"greater":[45],"predictive":[46,143],"capability.":[47],"However,":[48],"difficulties":[49,91],"such":[50],"as":[51],"parameter":[52,61],"correlation,":[53],"model":[54,57,98,120,138],"stochasticity,":[55],"multivariate":[56],"output,":[58],"unknown":[60],"distributions":[62],"prohibit":[63],"a":[64,75,85,109,117,136],"direct":[65],"application":[66],"By":[73],"leveraging":[74],"loss":[76],"function":[77],"associated":[78],"with":[79,139],"model,":[82],"we":[83],"introduce":[84],"novel":[86],"framework":[87,113],"address":[89],"these":[90],"efficient":[94],"for":[96],"parameters.":[99,128,151],"Theoretical":[100],"computational":[102],"properties":[103],"are":[104,131],"considered":[105],"illustrated":[107],"on":[108,126],"synthetic":[110],"example.":[111],"The":[112],"applied":[115],"Gaussian":[118],"process":[119],"literature,":[123],"which":[124],"depends":[125],"95":[127],"Noninfluential":[129],"discovered":[132],"through":[133],"GSA,":[134],"equal":[140],"stronger":[142],"capability":[144],"constructed":[146],"by":[147],"using":[148],"only":[149],"79":[150]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}