{"id":"https://openalex.org/W2001983875","doi":"https://doi.org/10.1198/004017007000000029","title":"Optimal Compound Orthogonal Arrays and Single Arrays for Robust Parameter Design Experiments","display_name":"Optimal Compound Orthogonal Arrays and Single Arrays for Robust Parameter Design Experiments","publication_year":2007,"publication_date":"2007-10-28","ids":{"openalex":"https://openalex.org/W2001983875","doi":"https://doi.org/10.1198/004017007000000029","mag":"2001983875"},"language":"en","primary_location":{"id":"doi:10.1198/004017007000000029","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017007000000029","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/A5112890006","display_name":"Yu Zhu","orcid":"https://orcid.org/0009-0006-6480-8924"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yu Zhu","raw_affiliation_strings":["Department of Statistics, Purdue University, West Lafayette, IN 47907","Purdue University"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Purdue University, West Lafayette, IN 47907","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032565190","display_name":"Peng Zeng","orcid":"https://orcid.org/0000-0002-0306-6713"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peng Zeng","raw_affiliation_strings":["Department of Mathematics and Statistics, Auburn University, Auburn, AL 36849","Auburn.University"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Auburn University, Auburn, AL 36849","institution_ids":["https://openalex.org/I82497590"]},{"raw_affiliation_string":"Auburn.University","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033969355","display_name":"Kristofer Jennings","orcid":"https://orcid.org/0000-0002-5442-9326"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kristofer Jennings","raw_affiliation_strings":["Department of Statistics, Purdue University, West Lafayette, IN 47907","Purdue University"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Purdue University, West Lafayette, IN 47907","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112890006"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":1.1865,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.81432795,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"49","issue":"4","first_page":"440","last_page":"453"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":1.0,"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":0.9962000250816345,"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":0.9794999957084656,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/orthogonal-array","display_name":"Orthogonal array","score":0.8736700415611267},{"id":"https://openalex.org/keywords/taguchi-methods","display_name":"Taguchi methods","score":0.781140923500061},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6145460605621338},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5126165747642517},{"id":"https://openalex.org/keywords/optimal-design","display_name":"Optimal design","score":0.4834481179714203},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44679924845695496},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44563719630241394},{"id":"https://openalex.org/keywords/design-of-experiments","display_name":"Design of experiments","score":0.43281054496765137},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3508552610874176},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24212652444839478},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08584010601043701}],"concepts":[{"id":"https://openalex.org/C42632107","wikidata":"https://www.wikidata.org/wiki/Q2031860","display_name":"Orthogonal array","level":3,"score":0.8736700415611267},{"id":"https://openalex.org/C83469408","wikidata":"https://www.wikidata.org/wiki/Q2036525","display_name":"Taguchi methods","level":2,"score":0.781140923500061},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6145460605621338},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5126165747642517},{"id":"https://openalex.org/C186394612","wikidata":"https://www.wikidata.org/wiki/Q7098942","display_name":"Optimal design","level":2,"score":0.4834481179714203},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44679924845695496},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44563719630241394},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.43281054496765137},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3508552610874176},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24212652444839478},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08584010601043701}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1198/004017007000000029","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017007000000029","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:CiteSeerX.psu:10.1.1.131.1593","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.1593","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.stat.purdue.edu/~yuzhu/Papers/optimalcoa0720.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W295779321","https://openalex.org/W651150315","https://openalex.org/W1479802788","https://openalex.org/W1550183740","https://openalex.org/W1551800824","https://openalex.org/W1552554589","https://openalex.org/W1565294287","https://openalex.org/W1568545116","https://openalex.org/W1976474629","https://openalex.org/W1992015558","https://openalex.org/W1999142305","https://openalex.org/W2004341041","https://openalex.org/W2009045521","https://openalex.org/W2018296773","https://openalex.org/W2034798338","https://openalex.org/W2051988007","https://openalex.org/W2080317910","https://openalex.org/W2122077678","https://openalex.org/W2283688205","https://openalex.org/W2336928119","https://openalex.org/W2494717495","https://openalex.org/W2987849413","https://openalex.org/W2993740710","https://openalex.org/W4235471047","https://openalex.org/W4243442908","https://openalex.org/W4255773678","https://openalex.org/W4256394954"],"related_works":["https://openalex.org/W186921175","https://openalex.org/W3171028201","https://openalex.org/W2954115956","https://openalex.org/W2039304284","https://openalex.org/W2099748434","https://openalex.org/W2142112859","https://openalex.org/W2378907112","https://openalex.org/W1996339794","https://openalex.org/W2584075324","https://openalex.org/W2015985874"],"abstract_inverted_index":{"Compound":[0],"orthogonal":[1],"arrays":[2,6,12,40,46,51],"(COAs)":[3],"and":[4,29,48,59,81,85],"single":[5,45,50,75],"are":[7,41,70,83],"alternatives":[8],"to":[9,35,54],"the":[10,25,66],"inner\u2013outer":[11],"advocated":[13],"by":[14],"Taguchi":[15],"for":[16,72,90],"robust":[17],"parameter":[18],"design":[19],"experiments.":[20],"A":[21],"criterion":[22],"based":[23,64],"on":[24,65],"word":[26,67],"type":[27,68],"pattern":[28],"strength":[30],"of":[31],"COAs":[32],"is":[33],"proposed":[34,71],"select":[36],"optimal":[37,74,78],"COAs.":[38],"Single":[39],"classified":[42],"into":[43],"prodigal":[44],"(PSAs)":[47],"economical":[49],"(ESAs)":[52],"according":[53],"their":[55],"relative":[56],"estimation":[57],"capacities,":[58],"various":[60],"optimality":[61],"criteria,":[62],"again":[63],"pattern,":[69],"selecting":[73],"arrays.":[76],"Useful":[77],"COAs,":[79],"PSAs,":[80],"ESAs":[82],"constructed":[84],"tabulated":[86],"as":[87],"convenient":[88],"references":[89],"experimenters":[91],"in":[92],"practice.":[93]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
