{"id":"https://openalex.org/W3019575017","doi":"https://doi.org/10.1080/03610918.2020.1758941","title":"Evaluation of process capability in gamma regression profiles","display_name":"Evaluation of process capability in gamma regression profiles","publication_year":2020,"publication_date":"2020-04-25","ids":{"openalex":"https://openalex.org/W3019575017","doi":"https://doi.org/10.1080/03610918.2020.1758941","mag":"3019575017"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2020.1758941","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2020.1758941","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","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/A5090652621","display_name":"Vasileios Alevizakos","orcid":"https://orcid.org/0000-0003-3689-2584"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Vasileios Alevizakos","raw_affiliation_strings":["Department of Mathematics, National Technical University of Athens, Zografou, Athens, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, National Technical University of Athens, Zografou, Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001849682","display_name":"Christos Koukouvinos","orcid":"https://orcid.org/0000-0003-1907-2031"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Christos Koukouvinos","raw_affiliation_strings":["Department of Mathematics, National Technical University of Athens, Zografou, Athens, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, National Technical University of Athens, Zografou, Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001849682"],"corresponding_institution_ids":["https://openalex.org/I174458059"],"apc_list":null,"apc_paid":null,"fwci":0.8404,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76357015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"51","issue":"9","first_page":"5174","last_page":"5189"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997000098228455,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997000098228455,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/process-capability","display_name":"Process capability","score":0.7348069548606873},{"id":"https://openalex.org/keywords/process-capability-index","display_name":"Process capability index","score":0.7263661026954651},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5632442235946655},{"id":"https://openalex.org/keywords/weibull-distribution","display_name":"Weibull distribution","score":0.560144305229187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5540270209312439},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5432755351066589},{"id":"https://openalex.org/keywords/log-normal-distribution","display_name":"Log-normal distribution","score":0.5191823244094849},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4576714038848877},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.4436039626598358},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4392206370830536},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.41711172461509705},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.40359097719192505},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39316248893737793},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36543789505958557},{"id":"https://openalex.org/keywords/work-in-process","display_name":"Work in process","score":0.24442484974861145},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1625540554523468}],"concepts":[{"id":"https://openalex.org/C91439571","wikidata":"https://www.wikidata.org/wiki/Q1279773","display_name":"Process capability","level":3,"score":0.7348069548606873},{"id":"https://openalex.org/C190190378","wikidata":"https://www.wikidata.org/wiki/Q1192625","display_name":"Process capability index","level":3,"score":0.7263661026954651},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5632442235946655},{"id":"https://openalex.org/C173291955","wikidata":"https://www.wikidata.org/wiki/Q732332","display_name":"Weibull distribution","level":2,"score":0.560144305229187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5540270209312439},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5432755351066589},{"id":"https://openalex.org/C151620405","wikidata":"https://www.wikidata.org/wiki/Q826116","display_name":"Log-normal distribution","level":2,"score":0.5191823244094849},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4576714038848877},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.4436039626598358},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4392206370830536},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.41711172461509705},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.40359097719192505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39316248893737793},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36543789505958557},{"id":"https://openalex.org/C174998907","wikidata":"https://www.wikidata.org/wiki/Q357662","display_name":"Work in process","level":2,"score":0.24442484974861145},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1625540554523468},{"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2020.1758941","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2020.1758941","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5199999809265137,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1482741012","https://openalex.org/W1542422557","https://openalex.org/W1580673759","https://openalex.org/W1792157322","https://openalex.org/W1898842295","https://openalex.org/W1923243223","https://openalex.org/W1966323584","https://openalex.org/W1968797905","https://openalex.org/W1972614723","https://openalex.org/W1981512258","https://openalex.org/W2003826755","https://openalex.org/W2004766809","https://openalex.org/W2015249241","https://openalex.org/W2027589021","https://openalex.org/W2068871259","https://openalex.org/W2071460053","https://openalex.org/W2087277929","https://openalex.org/W2089947653","https://openalex.org/W2090092366","https://openalex.org/W2095453734","https://openalex.org/W2100456664","https://openalex.org/W2102415224","https://openalex.org/W2131969788","https://openalex.org/W2139356790","https://openalex.org/W2140043816","https://openalex.org/W2158492478","https://openalex.org/W2163248436","https://openalex.org/W2283140615","https://openalex.org/W2303615566","https://openalex.org/W2314774207","https://openalex.org/W2338249799","https://openalex.org/W2345428127","https://openalex.org/W2519082742","https://openalex.org/W2587722271","https://openalex.org/W2789502624","https://openalex.org/W2900728215","https://openalex.org/W2904910310","https://openalex.org/W2908219036","https://openalex.org/W2977620188","https://openalex.org/W3026721701","https://openalex.org/W4210724243","https://openalex.org/W4298327441","https://openalex.org/W4301861531","https://openalex.org/W4376544320","https://openalex.org/W6678334772"],"related_works":["https://openalex.org/W2083138094","https://openalex.org/W2601946939","https://openalex.org/W2143561073","https://openalex.org/W1533475655","https://openalex.org/W2998343105","https://openalex.org/W1537881271","https://openalex.org/W2068101879","https://openalex.org/W2037894001","https://openalex.org/W2940719174","https://openalex.org/W2056820451"],"abstract_inverted_index":{"In":[0,64],"many":[1],"industrial":[2],"and":[3,24,82],"non-industrial":[4],"processes,":[5],"the":[6,34,37,45,55,65,70,75,91,97,110,117,129,132],"quality":[7],"of":[8,44,58,96,120,131],"a":[9,12,17,21,103,123,126],"product":[10],"or":[11,26,125],"process":[13,38,46,56,76],"are":[14],"described":[15],"by":[16],"functional":[18],"relationship":[19],"between":[20],"response":[22],"variable":[23],"one":[25],"more":[27],"independent":[28],"variables,":[29],"known":[30],"as":[31],"profile.":[32],"On":[33],"other":[35],"hand,":[36],"capability":[39,57,77],"indices":[40],"provide":[41],"numerical":[42],"measures":[43],"ability.":[47],"Few":[48],"researches":[49],"have":[50],"been":[51],"done":[52],"to":[53,73],"evaluate":[54],"profiles;":[59],"especially":[60],"for":[61,78],"linear":[62],"profiles.":[63],"present":[66],"article,":[67],"we":[68,83,107],"calculate":[69],"Spmk":[71,111],"index":[72,112,134],"measure":[74],"gamma":[79],"regression":[80],"profiles":[81],"also":[84],"construct":[85],"an":[86],"approximate":[87],"confidence":[88],"interval":[89],"using":[90,137],"bootstrap":[92],"method.":[93],"The":[94],"performance":[95],"proposed":[98,133],"method":[99],"is":[100,113,122,135],"assessed":[101],"through":[102],"simulation":[104],"study.":[105],"Moreover,":[106],"show":[108],"that":[109],"very":[114],"robust":[115],"when":[116],"true":[118],"distribution":[119],"data":[121],"lognormal":[124],"Weibull.":[127],"Finally,":[128],"applicability":[130],"illustrated":[136],"two":[138],"real":[139],"examples.":[140]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}