{"id":"https://openalex.org/W2942505090","doi":"https://doi.org/10.1080/03610918.2019.1602647","title":"Model diagnostic procedures for copula-based Markov chain models for statistical process control","display_name":"Model diagnostic procedures for copula-based Markov chain models for statistical process control","publication_year":2019,"publication_date":"2019-05-02","ids":{"openalex":"https://openalex.org/W2942505090","doi":"https://doi.org/10.1080/03610918.2019.1602647","mag":"2942505090"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1602647","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1602647","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/A5063231461","display_name":"Xin-Wei Huang","orcid":"https://orcid.org/0000-0003-4238-3081"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Xin-Wei Huang","raw_affiliation_strings":["Graduate Institute of Statistics, National Central University, Taoyuan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Statistics, National Central University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020629689","display_name":"Takeshi Emura","orcid":"https://orcid.org/0000-0002-3904-4014"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Takeshi Emura","raw_affiliation_strings":["Graduate Institute of Statistics, National Central University, Taoyuan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Statistics, National Central University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I22265921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5020629689","https://openalex.org/A5063231461"],"corresponding_institution_ids":["https://openalex.org/I22265921"],"apc_list":null,"apc_paid":null,"fwci":2.1366,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.90229143,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"50","issue":"8","first_page":"2345","last_page":"2367"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9991999864578247,"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":0.9991999864578247,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9639999866485596,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/copula","display_name":"Copula (linguistics)","score":0.8120465874671936},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.7580746412277222},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6425689458847046},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.541287362575531},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5010664463043213},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.4480769634246826},{"id":"https://openalex.org/keywords/markov-property","display_name":"Markov property","score":0.44261816143989563},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.43031471967697144},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.35065215826034546},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2998068332672119},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28075653314590454},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2500011920928955}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.8120465874671936},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.7580746412277222},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6425689458847046},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.541287362575531},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5010664463043213},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.4480769634246826},{"id":"https://openalex.org/C189973286","wikidata":"https://www.wikidata.org/wiki/Q176695","display_name":"Markov property","level":4,"score":0.44261816143989563},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.43031471967697144},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.35065215826034546},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2998068332672119},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28075653314590454},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2500011920928955}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1602647","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1602647","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":[],"awards":[{"id":"https://openalex.org/G4587418714","display_name":null,"funder_award_id":"-M-008-003-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1485399950","https://openalex.org/W1587041568","https://openalex.org/W1734452708","https://openalex.org/W1974733093","https://openalex.org/W1976676576","https://openalex.org/W1978290902","https://openalex.org/W1989728017","https://openalex.org/W1993964106","https://openalex.org/W2028115777","https://openalex.org/W2064186236","https://openalex.org/W2077627303","https://openalex.org/W2078237481","https://openalex.org/W2117332156","https://openalex.org/W2142219037","https://openalex.org/W2155899991","https://openalex.org/W2195125035","https://openalex.org/W2337332154","https://openalex.org/W2507039649","https://openalex.org/W2575176051","https://openalex.org/W2753701780","https://openalex.org/W2775736374","https://openalex.org/W2793454360","https://openalex.org/W2794783457","https://openalex.org/W2898514383","https://openalex.org/W2900497781","https://openalex.org/W2909138707","https://openalex.org/W2911641922","https://openalex.org/W2937194229","https://openalex.org/W4210653751","https://openalex.org/W4233494161","https://openalex.org/W4243923385","https://openalex.org/W4253708194"],"related_works":["https://openalex.org/W1976065452","https://openalex.org/W2130519334","https://openalex.org/W3166133680","https://openalex.org/W4360597163","https://openalex.org/W2393621008","https://openalex.org/W3022014775","https://openalex.org/W2540690809","https://openalex.org/W2100055350","https://openalex.org/W2353273130","https://openalex.org/W2129435535"],"abstract_inverted_index":{"Investigating":[0],"serial":[1],"dependence":[2],"is":[3,15,105],"an":[4,28],"important":[5],"step":[6],"in":[7,98,117],"statistical":[8],"process":[9],"control":[10],"(SPC).":[11],"One":[12],"recent":[13],"approach":[14,64,86,103],"to":[16,23,31,93],"fit":[17],"a":[18,66,81,106],"copula-based":[19,58],"Markov":[20,59,90,96],"chain":[21,60,91],"model":[22,39,54,92],"perform":[24],"SPC,":[25],"which":[26],"provides":[27],"attractive":[29],"alternative":[30],"the":[32,71,74,88,95,99,113,118],"traditional":[33],"AR1":[34],"model.":[35,100],"However,":[36],"methodologies":[37,115],"for":[38,53,57,132],"diagnostic":[40,55],"have":[41],"not":[42],"been":[43],"considered.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48],"develop":[49],"two":[50],"different":[51],"approaches":[52],"procedures":[56],"models.":[61],"The":[62,84],"first":[63],"employs":[65,87],"formal":[67],"test":[68],"based":[69],"on":[70],"Kolmogorov-Smirnov":[72],"or":[73],"Cram\u00e9r-von":[75],"Mises":[76],"statistics":[77],"with":[78],"aid":[79],"of":[80],"parametric":[82],"bootstrap.":[83],"second":[85,102],"second-order":[89],"examine":[94],"property":[97],"This":[101],"itself":[104],"new":[107],"SPC":[108],"method.":[109],"We":[110,128],"made":[111],"all":[112],"computing":[114],"available":[116],"R":[119],"Copula.Markov":[120],"package,":[121],"and":[122],"check":[123],"their":[124],"performance":[125],"by":[126],"simulations.":[127],"analyze":[129],"three":[130],"datasets":[131],"illustration.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
