{"id":"https://openalex.org/W2073401015","doi":"https://doi.org/10.1198/004017004000000211","title":"Integrated Analysis of Computer and Physical Experiments","display_name":"Integrated Analysis of Computer and Physical Experiments","publication_year":2004,"publication_date":"2004-04-06","ids":{"openalex":"https://openalex.org/W2073401015","doi":"https://doi.org/10.1198/004017004000000211","mag":"2073401015"},"language":"en","primary_location":{"id":"doi:10.1198/004017004000000211","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017004000000211","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"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":"Technometrics","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/A5113598039","display_name":"C. Shane Reese","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"C. Shane Reese","raw_affiliation_strings":["Department of Statistics, Brigham Young University, Provo, UT 84602","Department of Statistics, Brigham Young University, Provo, UT 84602 ()"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Brigham Young University, Provo, UT 84602","institution_ids":["https://openalex.org/I100005738"]},{"raw_affiliation_string":"Department of Statistics, Brigham Young University, Provo, UT 84602 ()","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049434797","display_name":"Alyson G. Wilson","orcid":"https://orcid.org/0000-0003-1461-6212"},"institutions":[{"id":"https://openalex.org/I1343871089","display_name":"Los Alamos National Laboratory","ror":"https://ror.org/01e41cf67","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I1343871089","https://openalex.org/I198811213","https://openalex.org/I4210120050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alyson G Wilson","raw_affiliation_strings":["Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545","Statistical Sciences Group, Los Alamos National Laboratory , Los Alamos , NM , 87545"],"affiliations":[{"raw_affiliation_string":"Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545","institution_ids":["https://openalex.org/I1343871089"]},{"raw_affiliation_string":"Statistical Sciences Group, Los Alamos National Laboratory , Los Alamos , NM , 87545","institution_ids":["https://openalex.org/I1343871089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091511603","display_name":"Michael S. Hamada","orcid":"https://orcid.org/0000-0003-3206-1695"},"institutions":[{"id":"https://openalex.org/I1343871089","display_name":"Los Alamos National Laboratory","ror":"https://ror.org/01e41cf67","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I1343871089","https://openalex.org/I198811213","https://openalex.org/I4210120050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Hamada","raw_affiliation_strings":["Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545","Statistical Sciences Group, Los Alamos National Laboratory , Los Alamos , NM , 87545"],"affiliations":[{"raw_affiliation_string":"Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545","institution_ids":["https://openalex.org/I1343871089"]},{"raw_affiliation_string":"Statistical Sciences Group, Los Alamos National Laboratory , Los Alamos , NM , 87545","institution_ids":["https://openalex.org/I1343871089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111794917","display_name":"Harry F. Martz","orcid":null},"institutions":[{"id":"https://openalex.org/I1343871089","display_name":"Los Alamos National Laboratory","ror":"https://ror.org/01e41cf67","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I1343871089","https://openalex.org/I198811213","https://openalex.org/I4210120050"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Harry F Martz","raw_affiliation_strings":["Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545","Statistical Sciences Group, Los Alamos National Laboratory , Los Alamos , NM , 87545"],"affiliations":[{"raw_affiliation_string":"Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545","institution_ids":["https://openalex.org/I1343871089"]},{"raw_affiliation_string":"Statistical Sciences Group, Los Alamos National Laboratory , Los Alamos , NM , 87545","institution_ids":["https://openalex.org/I1343871089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113769876","display_name":"Kenneth J. Ryan","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenneth J Ryan","raw_affiliation_strings":["Department of Statistics, University of Illinois, Chicago, IL 60208"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Illinois, Chicago, IL 60208","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5113598039"],"corresponding_institution_ids":["https://openalex.org/I100005738"],"apc_list":null,"apc_paid":null,"fwci":3.1034,"has_fulltext":false,"cited_by_count":107,"citation_normalized_percentile":{"value":0.89665824,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"46","issue":"2","first_page":"153","last_page":"164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9829999804496765,"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/T12161","display_name":"Plant Surface Properties and Treatments","score":0.9742000102996826,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6127777099609375},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.5512955784797668},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5201504826545715},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.49849510192871094},{"id":"https://openalex.org/keywords/experimental-data","display_name":"Experimental data","score":0.49459025263786316},{"id":"https://openalex.org/keywords/design-of-experiments","display_name":"Design of experiments","score":0.4920644164085388},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47755035758018494},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4729078710079193},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.46389034390449524},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4104686975479126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34774261713027954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3409029245376587},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25885623693466187},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1995924413204193}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6127777099609375},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.5512955784797668},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5201504826545715},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.49849510192871094},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.49459025263786316},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.4920644164085388},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47755035758018494},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4729078710079193},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.46389034390449524},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4104686975479126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34774261713027954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3409029245376587},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25885623693466187},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1995924413204193},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1198/004017004000000211","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017004000000211","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"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":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W36993322","https://openalex.org/W1490324987","https://openalex.org/W1917457462","https://openalex.org/W1973333099","https://openalex.org/W1999649023","https://openalex.org/W2015925788","https://openalex.org/W2018044188","https://openalex.org/W2026170388","https://openalex.org/W2034562813","https://openalex.org/W2034731753","https://openalex.org/W2038669746","https://openalex.org/W2045656233","https://openalex.org/W2053090661","https://openalex.org/W2083027289","https://openalex.org/W2098043077","https://openalex.org/W2123579535","https://openalex.org/W2126112546","https://openalex.org/W2129905273","https://openalex.org/W2130416410","https://openalex.org/W2138309709","https://openalex.org/W2221667408","https://openalex.org/W2314674797","https://openalex.org/W2530261910","https://openalex.org/W2892077551","https://openalex.org/W3214323364","https://openalex.org/W4239692665","https://openalex.org/W4243645092","https://openalex.org/W4251142591","https://openalex.org/W4300025484"],"related_works":["https://openalex.org/W2116312697","https://openalex.org/W2362353273","https://openalex.org/W3184080862","https://openalex.org/W4320010348","https://openalex.org/W4390146674","https://openalex.org/W2948616127","https://openalex.org/W3009997745","https://openalex.org/W4316276477","https://openalex.org/W4383108770","https://openalex.org/W2020256641"],"abstract_inverted_index":{"Scientific":[0],"investigations":[1],"frequently":[2],"involve":[3],"data":[4,14,72,183],"from":[5,173,184],"computer":[6,176,191],"experiment(s)":[7],"as":[8,10,93],"well":[9],"related":[11,20],"physical":[12,162,186],"experimental":[13,163],"on":[15],"the":[16,33,70,113,130,135,151,185,189],"same":[17],"factors":[18,167],"and":[19,50,99,140,188],"response":[21,34,145,199],"variable(s).":[22],"There":[23],"may":[24],"also":[25,179],"be":[26,58,67],"one":[27],"or":[28],"more":[29,62],"expert":[30,100],"opinions":[31],"regarding":[32],"of":[35,42,117,137,147,161],"interest.":[36],"Traditional":[37],"statistical":[38,52,64],"approaches":[39],"consider":[40],"each":[41],"these":[43,97],"datasets":[44],"separately":[45],"with":[46],"corresponding":[47],"separate":[48],"analyses":[49],"fitted":[51],"models.":[53],"A":[54],"compelling":[55],"argument":[56],"can":[57,66],"made":[59],"that":[60],"better,":[61],"precise":[63],"models":[65,177,192],"obtained":[68],"if":[69],"combined":[71],"are":[73,127,178,193],"analyzed":[74],"simultaneously":[75],"using":[76,109],"a":[77,118,159],"hierarchical":[78],"Bayesian":[79],"integrated":[80,86,106,182],"modeling":[81],"approach.":[82],"However,":[83],"such":[84,92],"an":[85,197],"approach":[87],"must":[88],"recognize":[89],"important":[90,143],"differences,":[91],"possible":[94],"biases,":[95],"in":[96,129],"experiments":[98],"opinions.":[101],"We":[102],"illustrate":[103],"our":[104],"proposed":[105],"methodology":[107],"by":[108],"it":[110],"to":[111,133,158,169,195],"model":[112,202],"thermodynamic":[114,144],"operation":[115],"point":[116],"top-spray":[119],"fluidized":[120],"bed":[121],"microencapsulation":[122],"processing":[123],"unit.":[124],"Such":[125],"units":[126],"used":[128,168,194],"food":[131],"industry":[132],"tune":[134],"effect":[136],"functional":[138],"ingredients":[139],"additives.":[141],"An":[142],"variable":[146],"interest,":[148],"Y,":[149],"is":[150],"steady-state":[152],"outlet":[153],"air":[154],"temperature.":[155],"In":[156],"addition":[157],"set":[160],"observations":[164],"involving":[165],"six":[166],"predictY,":[170],"similar":[171],"results":[172],"three":[174,190],"different":[175],"available.":[180],"The":[181],"experiment":[187],"fit":[196],"appropriate":[198],"surface":[200],"(regression)":[201],"for":[203],"predicting":[204],"Y.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":8}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}