{"id":"https://openalex.org/W4213095490","doi":"https://doi.org/10.1080/10618600.2022.2039160","title":"Adaptive Design and Analysis Via Partitioning Trees for Emulation of a Complex Computer Code","display_name":"Adaptive Design and Analysis Via Partitioning Trees for Emulation of a Complex Computer Code","publication_year":2022,"publication_date":"2022-02-14","ids":{"openalex":"https://openalex.org/W4213095490","doi":"https://doi.org/10.1080/10618600.2022.2039160"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2022.2039160","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2022.2039160","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033307098","display_name":"Sonja Isberg","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Sonja Isberg","raw_affiliation_strings":["Department of Statistics, The University of British Columbia, Vancouver, British Columbia, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, The University of British Columbia, Vancouver, British Columbia, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043650697","display_name":"William J. Welch","orcid":"https://orcid.org/0000-0002-4575-3124"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"William J. Welch","raw_affiliation_strings":["Department of Statistics, The University of British Columbia, Vancouver, British Columbia, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, The University of British Columbia, Vancouver, British Columbia, Canada","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033307098"],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03346412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":"4","first_page":"1280","last_page":"1291"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9973999857902527,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7630130052566528},{"id":"https://openalex.org/keywords/emulation","display_name":"Emulation","score":0.7396384477615356},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.6062530279159546},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.5095420479774475},{"id":"https://openalex.org/keywords/computer-experiment","display_name":"Computer experiment","score":0.4764842689037323},{"id":"https://openalex.org/keywords/space-partitioning","display_name":"Space partitioning","score":0.43999195098876953},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4363086521625519},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.43394023180007935},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4057009816169739},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34618550539016724},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3358456790447235},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31483179330825806},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13433369994163513},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.12957453727722168},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12046587467193604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7630130052566528},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.7396384477615356},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.6062530279159546},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.5095420479774475},{"id":"https://openalex.org/C87466663","wikidata":"https://www.wikidata.org/wiki/Q5157537","display_name":"Computer experiment","level":2,"score":0.4764842689037323},{"id":"https://openalex.org/C13670688","wikidata":"https://www.wikidata.org/wiki/Q3500548","display_name":"Space partitioning","level":2,"score":0.43999195098876953},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4363086521625519},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.43394023180007935},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4057009816169739},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34618550539016724},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3358456790447235},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31483179330825806},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13433369994163513},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.12957453727722168},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12046587467193604},{"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/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/10618600.2022.2039160","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2022.2039160","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W54587910","https://openalex.org/W1510052597","https://openalex.org/W1567512734","https://openalex.org/W1914588449","https://openalex.org/W1969106574","https://openalex.org/W1995584797","https://openalex.org/W1996433205","https://openalex.org/W2018044188","https://openalex.org/W2054095248","https://openalex.org/W2058852146","https://openalex.org/W2071379353","https://openalex.org/W2074889471","https://openalex.org/W2083027289","https://openalex.org/W2092271904","https://openalex.org/W2125275885","https://openalex.org/W2142863015","https://openalex.org/W2150705946","https://openalex.org/W2152915424","https://openalex.org/W2188391450","https://openalex.org/W2514303448","https://openalex.org/W2582743722","https://openalex.org/W2592279581","https://openalex.org/W2602518026","https://openalex.org/W2794313876","https://openalex.org/W2954735198","https://openalex.org/W2963242019","https://openalex.org/W2983590566","https://openalex.org/W3031275541","https://openalex.org/W3098133464","https://openalex.org/W3127149079","https://openalex.org/W4212774754","https://openalex.org/W4240805545","https://openalex.org/W4251846842","https://openalex.org/W4388289800","https://openalex.org/W4399569887"],"related_works":["https://openalex.org/W2376400003","https://openalex.org/W2365970899","https://openalex.org/W4301077210","https://openalex.org/W2274450582","https://openalex.org/W2949087396","https://openalex.org/W3112839114","https://openalex.org/W2798972612","https://openalex.org/W4362553939","https://openalex.org/W4320473302","https://openalex.org/W4309804938"],"abstract_inverted_index":{"Computer":[0],"models":[1,146],"are":[2,147,199],"used":[3],"as":[4],"replacements":[5],"for":[6,22,47,52,65,79,99,196],"physical":[7],"experiments":[8],"in":[9,115,150,174,187],"a":[10,48,54,124,159,166,182],"large":[11,80],"variety":[12],"of":[13,18,35,67,90,106,153,165,177,185],"applications.":[14],"Nevertheless,":[15],"direct":[16],"use":[17],"the":[19,23,31,36,43,88,91,141,154,163,172,175],"computer":[20,55,145],"model":[21],"ultimate":[24],"scientific":[25],"objective":[26],"is":[27,138],"often":[28],"limited":[29],"by":[30,140],"complexity":[32],"and":[33,62,108,112,129,168,190],"cost":[34],"model.":[37],"Gaussian":[38],"process":[39],"regression":[40],"has":[41],"been":[42,97],"almost":[44],"ubiquitous":[45],"choice":[46],"fast":[49],"statistical":[50,73],"emulator":[51,74],"such":[53],"model,":[56],"due":[57,82],"to":[58,83,162,170],"its":[59],"flexible":[60],"form":[61],"analytical":[63],"expressions":[64],"measures":[66],"predictive":[68,111],"uncertainty.":[69],"However,":[70],"even":[71],"this":[72,101,121,197],"can":[75],"be":[76],"computationally":[77],"intractable":[78],"designs,":[81],"computing":[84],"time":[85],"increasing":[86],"with":[87],"cube":[89],"design":[92,128],"size.":[93],"Multiple":[94],"methods":[95],"have":[96],"proposed":[98],"addressing":[100],"problem.":[102],"We":[103,118],"discuss":[104],"several":[105,116],"them,":[107],"compare":[109],"their":[110],"computational":[113],"performance":[114],"scenarios.":[117],"propose":[119],"solving":[120],"problem":[122],"using":[123],"new":[125,136],"method,":[126],"adaptive":[127],"analysis":[130],"via":[131],"partitioning":[132],"trees":[133],"(ADAPT).":[134],"The":[135],"approach":[137,161],"motivated":[139],"idea":[142],"that":[143],"most":[144],"only":[148],"complex":[149],"particular":[151],"regions":[152,176,189],"input":[155],"space.":[156],"By":[157],"taking":[158],"data-adaptive":[160],"development":[164],"design,":[167],"choosing":[169],"partition":[171],"space":[173],"highest":[178],"variability,":[179],"we":[180],"obtain":[181],"higher":[183],"density":[184],"points":[186],"these":[188],"hence":[191],"accurate":[192],"prediction.":[193],"Supplemental":[194],"files":[195],"article":[198],"available":[200],"online.":[201]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
