{"id":"https://openalex.org/W2001331635","doi":"https://doi.org/10.1198/004017006000000453","title":"Efficient Nearly Orthogonal and Space-Filling Latin Hypercubes","display_name":"Efficient Nearly Orthogonal and Space-Filling Latin Hypercubes","publication_year":2007,"publication_date":"2007-01-23","ids":{"openalex":"https://openalex.org/W2001331635","doi":"https://doi.org/10.1198/004017006000000453","mag":"2001331635"},"language":"en","primary_location":{"id":"doi:10.1198/004017006000000453","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017006000000453","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/A5015344747","display_name":"Thomas M. Cioppa","orcid":null},"institutions":[{"id":"https://openalex.org/I906986114","display_name":"United States Army Command and General Staff College","ror":"https://ror.org/05x8ajk28","country_code":"US","type":"education","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I4389425427","https://openalex.org/I4410514713","https://openalex.org/I906986114"]},{"id":"https://openalex.org/I4389425427","display_name":"U.S. Army Training and Doctrine Command","ror":"https://ror.org/02t7y5s37","country_code":null,"type":"education","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I4389425427"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Thomas M Cioppa","raw_affiliation_strings":["U.S. Army Training and Doctrine Command, Analysis Center, Fort Leavenworth, KS 66027"],"affiliations":[{"raw_affiliation_string":"U.S. Army Training and Doctrine Command, Analysis Center, Fort Leavenworth, KS 66027","institution_ids":["https://openalex.org/I906986114","https://openalex.org/I4389425427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108507540","display_name":"Thomas W. Lucas","orcid":null},"institutions":[{"id":"https://openalex.org/I35364215","display_name":"Naval Postgraduate School","ror":"https://ror.org/033yfkj90","country_code":"US","type":"education","lineage":["https://openalex.org/I1330347796","https://openalex.org/I3130687028","https://openalex.org/I35364215"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas W Lucas","raw_affiliation_strings":["Operations Research Department, Naval Postgraduate School, Monterey, CA 93943"],"affiliations":[{"raw_affiliation_string":"Operations Research Department, Naval Postgraduate School, Monterey, CA 93943","institution_ids":["https://openalex.org/I35364215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015344747"],"corresponding_institution_ids":["https://openalex.org/I4389425427","https://openalex.org/I906986114"],"apc_list":null,"apc_paid":null,"fwci":19.3516,"has_fulltext":false,"cited_by_count":331,"citation_normalized_percentile":{"value":0.99309295,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"49","issue":"1","first_page":"45","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9993000030517578,"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":0.9993000030517578,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9984999895095825,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/latin-hypercube-sampling","display_name":"Latin hypercube sampling","score":0.9371545314788818},{"id":"https://openalex.org/keywords/hypercube","display_name":"Hypercube","score":0.8819111585617065},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.6998040676116943},{"id":"https://openalex.org/keywords/orthogonal-array","display_name":"Orthogonal array","score":0.6628507971763611},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.6116105914115906},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.6074419021606445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.534753680229187},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5274538993835449},{"id":"https://openalex.org/keywords/computer-experiment","display_name":"Computer experiment","score":0.519638180732727},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5144646167755127},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42076972126960754},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.355970561504364},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3524881899356842},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3319002389907837},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.19464436173439026},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1641281545162201},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.12975594401359558},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.11729609966278076},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.083955317735672}],"concepts":[{"id":"https://openalex.org/C20820323","wikidata":"https://www.wikidata.org/wiki/Q6496514","display_name":"Latin hypercube sampling","level":3,"score":0.9371545314788818},{"id":"https://openalex.org/C50820777","wikidata":"https://www.wikidata.org/wiki/Q213723","display_name":"Hypercube","level":2,"score":0.8819111585617065},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6998040676116943},{"id":"https://openalex.org/C42632107","wikidata":"https://www.wikidata.org/wiki/Q2031860","display_name":"Orthogonal array","level":3,"score":0.6628507971763611},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.6116105914115906},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.6074419021606445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.534753680229187},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5274538993835449},{"id":"https://openalex.org/C87466663","wikidata":"https://www.wikidata.org/wiki/Q5157537","display_name":"Computer experiment","level":2,"score":0.519638180732727},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5144646167755127},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42076972126960754},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.355970561504364},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3524881899356842},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3319002389907837},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.19464436173439026},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1641281545162201},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.12975594401359558},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.11729609966278076},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.083955317735672},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C83469408","wikidata":"https://www.wikidata.org/wiki/Q2036525","display_name":"Taguchi methods","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1198/004017006000000453","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017006000000453","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"},{"id":"pmh:oai:calhoun.nps.edu:10945/35341","is_oa":false,"landing_page_url":"http://hdl.handle.net/10945/35341","pdf_url":null,"source":{"id":"https://openalex.org/S4306400952","display_name":"Calhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35364215","host_organization_name":"Naval Postgraduate School","host_organization_lineage":["https://openalex.org/I35364215"],"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":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.44999998807907104,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"},{"id":"https://openalex.org/F4320332447","display_name":"U.S. Army","ror":"https://ror.org/00afsp483"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W103650626","https://openalex.org/W115850967","https://openalex.org/W1487010959","https://openalex.org/W1532838894","https://openalex.org/W1964971655","https://openalex.org/W1969545943","https://openalex.org/W1973166102","https://openalex.org/W1975680434","https://openalex.org/W2003657827","https://openalex.org/W2006901874","https://openalex.org/W2014018052","https://openalex.org/W2014648900","https://openalex.org/W2018044188","https://openalex.org/W2026824186","https://openalex.org/W2033105553","https://openalex.org/W2038669746","https://openalex.org/W2040396531","https://openalex.org/W2044771513","https://openalex.org/W2051591670","https://openalex.org/W2053934160","https://openalex.org/W2055591121","https://openalex.org/W2056145269","https://openalex.org/W2076059798","https://openalex.org/W2078495506","https://openalex.org/W2116798985","https://openalex.org/W2117690866","https://openalex.org/W2136047985","https://openalex.org/W2142635246","https://openalex.org/W2143022286","https://openalex.org/W2148080122","https://openalex.org/W2165351046","https://openalex.org/W2221667408","https://openalex.org/W2325956640","https://openalex.org/W2331011396","https://openalex.org/W2519881875","https://openalex.org/W2798909945","https://openalex.org/W4229696631","https://openalex.org/W4236546113","https://openalex.org/W4243645092","https://openalex.org/W4245516440"],"related_works":["https://openalex.org/W3142442494","https://openalex.org/W4290004782","https://openalex.org/W3101215367","https://openalex.org/W2072920569","https://openalex.org/W1972403778","https://openalex.org/W2487094411","https://openalex.org/W4210503633","https://openalex.org/W3151333979","https://openalex.org/W2100862776","https://openalex.org/W1524930983"],"abstract_inverted_index":{"This":[0],"article":[1],"presents":[2],"an":[3],"algorithm":[4],"for":[5],"constructing":[6],"orthogonal":[7],"Latin":[8,36],"hypercubes,":[9],"given":[10],"a":[11,25,82],"fixed":[12],"sample":[13],"size,":[14],"in":[15,48,70],"more":[16],"dimensions":[17],"than":[18],"previous":[19],"approaches.":[20],"In":[21],"addition,":[22],"we":[23],"detail":[24],"method":[26],"that":[27],"dramatically":[28],"improves":[29],"the":[30,34,39,46,49,53,86,89],"space-filling":[31],"properties":[32],"of":[33,41,66,88],"resultant":[35],"hypercubes":[37],"at":[38],"expense":[40],"inducing":[42],"small":[43],"correlations":[44],"between":[45],"columns":[47],"design":[50],"matrix.":[51],"Although":[52],"designs":[54],"are":[55],"applicable":[56],"to":[57,63],"many":[58],"situations,":[59],"they":[60],"were":[61],"developed":[62],"provide":[64],"Department":[65],"Defense":[67],"analysts":[68],"flexibility":[69],"fitting":[71],"models":[72],"when":[73],"exploring":[74],"high-dimensional":[75],"computer":[76],"simulations":[77],"where":[78],"there":[79],"is":[80],"considerable":[81],"priori":[83],"uncertainty":[84],"about":[85],"forms":[87],"response":[90],"surfaces.":[91]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":21},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":16},{"year":2016,"cited_by_count":20},{"year":2015,"cited_by_count":17},{"year":2014,"cited_by_count":21},{"year":2013,"cited_by_count":15},{"year":2012,"cited_by_count":26}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
