{"id":"https://openalex.org/W4381250512","doi":"https://doi.org/10.1080/09540091.2023.2219040","title":"Modification of ARL for detecting changes on the double EWMA chart in time series data with the autoregressive model","display_name":"Modification of ARL for detecting changes on the double EWMA chart in time series data with the autoregressive model","publication_year":2023,"publication_date":"2023-06-19","ids":{"openalex":"https://openalex.org/W4381250512","doi":"https://doi.org/10.1080/09540091.2023.2219040"},"language":"en","primary_location":{"id":"doi:10.1080/09540091.2023.2219040","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2023.2219040","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2219040?needAccess=true&role=button","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2219040?needAccess=true&role=button","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076993579","display_name":"Kotchaporn Karoon","orcid":"https://orcid.org/0009-0009-1404-6134"},"institutions":[{"id":"https://openalex.org/I66200439","display_name":"Naresuan University","ror":"https://ror.org/03e2qe334","country_code":"TH","type":"education","lineage":["https://openalex.org/I66200439"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Kotchaporn Karoon","raw_affiliation_strings":["Department of Mathematics, Faculty of Science, Naresuan University, Phitsanulok, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Faculty of Science, Naresuan University, Phitsanulok, Thailand","institution_ids":["https://openalex.org/I66200439"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069945313","display_name":"Yupaporn Areepong","orcid":"https://orcid.org/0000-0002-5103-9867"},"institutions":[{"id":"https://openalex.org/I82828225","display_name":"King Mongkut's University of Technology North Bangkok","ror":"https://ror.org/04fy6jb97","country_code":"TH","type":"education","lineage":["https://openalex.org/I82828225"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Yupaporn Areepong","raw_affiliation_strings":["Department of Applied Statistics, Faculty of Applied Science, King Mongkut\u2019s University of Technology North Bangkok, Bangkok, Thailand","Department of Applied Statistics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Statistics, Faculty of Applied Science, King Mongkut\u2019s University of Technology North Bangkok, Bangkok, Thailand","institution_ids":["https://openalex.org/I82828225"]},{"raw_affiliation_string":"Department of Applied Statistics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand","institution_ids":["https://openalex.org/I82828225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029932096","display_name":"Saowanit Sukparungsee","orcid":"https://orcid.org/0000-0001-5248-8173"},"institutions":[{"id":"https://openalex.org/I82828225","display_name":"King Mongkut's University of Technology North Bangkok","ror":"https://ror.org/04fy6jb97","country_code":"TH","type":"education","lineage":["https://openalex.org/I82828225"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Saowanit Sukparungsee","raw_affiliation_strings":["Department of Applied Statistics, Faculty of Applied Science, King Mongkut\u2019s University of Technology North Bangkok, Bangkok, Thailand","Department of Applied Statistics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand"],"raw_orcid":"https://orcid.org/0000-0001-5248-8173","affiliations":[{"raw_affiliation_string":"Department of Applied Statistics, Faculty of Applied Science, King Mongkut\u2019s University of Technology North Bangkok, Bangkok, Thailand","institution_ids":["https://openalex.org/I82828225"]},{"raw_affiliation_string":"Department of Applied Statistics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand","institution_ids":["https://openalex.org/I82828225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5069945313"],"corresponding_institution_ids":["https://openalex.org/I82828225"],"apc_list":{"value":1270,"currency":"USD","value_usd":1270},"apc_paid":{"value":1270,"currency":"USD","value_usd":1270},"fwci":1.5023,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.83889234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"35","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9998999834060669,"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":0.9998999834060669,"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/T11890","display_name":"Scientific Measurement and Uncertainty Evaluation","score":0.9932000041007996,"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":0.9909999966621399,"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/ewma-chart","display_name":"EWMA chart","score":0.9817475080490112},{"id":"https://openalex.org/keywords/control-chart","display_name":"Control chart","score":0.7074729800224304},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.6122902035713196},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.5670517683029175},{"id":"https://openalex.org/keywords/moving-average","display_name":"Moving average","score":0.5398300290107727},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5370684266090393},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5191342234611511},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5052624344825745},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.48060867190361023},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39412739872932434},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3819694519042969},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.20140871405601501}],"concepts":[{"id":"https://openalex.org/C74746147","wikidata":"https://www.wikidata.org/wiki/Q5324652","display_name":"EWMA chart","level":4,"score":0.9817475080490112},{"id":"https://openalex.org/C196985124","wikidata":"https://www.wikidata.org/wiki/Q1369242","display_name":"Control chart","level":3,"score":0.7074729800224304},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.6122902035713196},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5670517683029175},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.5398300290107727},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5370684266090393},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5191342234611511},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5052624344825745},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.48060867190361023},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39412739872932434},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3819694519042969},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.20140871405601501},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/09540091.2023.2219040","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2023.2219040","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2219040?needAccess=true&role=button","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a59d962cee044f8091468c2dd0b91842","is_oa":true,"landing_page_url":"https://doaj.org/article/a59d962cee044f8091468c2dd0b91842","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Connection Science, Vol 35, Iss 1 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/09540091.2023.2219040","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2023.2219040","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2219040?needAccess=true&role=button","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322817","display_name":"National Research Council of Thailand","ror":"https://ror.org/018wfhg78"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4381250512.pdf"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W650955901","https://openalex.org/W2009029483","https://openalex.org/W2013627071","https://openalex.org/W2051903196","https://openalex.org/W2091311817","https://openalex.org/W2543670800","https://openalex.org/W2738252577","https://openalex.org/W2901360602","https://openalex.org/W2934813202","https://openalex.org/W3009665652","https://openalex.org/W3085751006","https://openalex.org/W3086185107","https://openalex.org/W3125588191","https://openalex.org/W3132856834","https://openalex.org/W3133790401","https://openalex.org/W3167096866","https://openalex.org/W3192634934","https://openalex.org/W4205390674","https://openalex.org/W4211256688","https://openalex.org/W4229980202","https://openalex.org/W4282925529","https://openalex.org/W4284883226","https://openalex.org/W4291972581","https://openalex.org/W4319596048","https://openalex.org/W4319601426","https://openalex.org/W6904872897"],"related_works":["https://openalex.org/W2048800900","https://openalex.org/W2022867152","https://openalex.org/W2410415934","https://openalex.org/W2341208862","https://openalex.org/W3201367114","https://openalex.org/W2360776031","https://openalex.org/W3006471751","https://openalex.org/W2126524872","https://openalex.org/W1982010548","https://openalex.org/W1972277994"],"abstract_inverted_index":{"This":[0],"research":[1],"aims":[2],"to":[3,121],"derive":[4],"the":[5,12,54,58,62,72,77,80,90,93,107,115,125,128,146,155,164,168,173,179,182],"average":[6,17,97],"run":[7],"length":[8],"(ARL)":[9],"evaluation":[10],"of":[11,76,85,92,114,127,181],"double":[13,100,116,156,183],"exponentially":[14,94],"weighted":[15,95],"moving":[16,96],"(double":[18],"EWMA)":[19],"control":[20],"chart":[21,118,130,158,185],"for":[22,194],"observation":[23],"data":[24,42],"that":[25,71,154],"follows":[26],"exponential":[27],"white":[28],"noise":[29],"in":[30,83,131,186],"a":[31,177,191],"time":[32],"series":[33],"model":[34],"with":[35,172,197],"an":[36],"autoregressive":[37,46],"model.":[38],"Since":[39],"most":[40],"real-world":[41,198],"is":[43,103],"automatically":[44],"correlated,":[45],"models":[47],"are":[48,170],"available.":[49],"Comparisons":[50],"were":[51],"made":[52],"between":[53],"ARLs":[55],"obtained":[56],"using":[57,106],"explicit":[59,73,109],"formula":[60],"and":[61,99,139,167],"numerical":[63],"integral":[64],"equation":[65],"(NIE)":[66],"approach.":[67],"The":[68,112,151],"results":[69,152,169],"showed":[70],"formula's":[74],"use":[75],"ARL":[78,110,113,126],"outperformed":[79],"NIE":[81],"approach":[82],"terms":[84],"computation":[86],"time.":[87],"After":[88],"that,":[89],"efficacy":[91],"(EWMA)":[98],"EWMA":[101,117,129,157,165,184],"charts":[102],"then":[104],"compared":[105],"suggested":[108],"formula.":[111],"was":[119],"found":[120],"perform":[122],"better":[123,160],"than":[124,163],"all":[132],"situations.":[133],"It":[134],"also":[135],"uses":[136],"natural":[137],"gas":[138],"diesel":[140],"prices":[141],"on":[142],"stock":[143],"exchanges":[144],"around":[145],"world":[147],"as":[148],"cases":[149],"studies.":[150],"show":[153],"has":[159],"detection":[161],"sensitivity":[162,180],"chart,":[166],"consistent":[171],"experimental":[174],"results.":[175],"As":[176],"result,":[178],"detecting":[187],"changes":[188],"makes":[189],"it":[190],"good":[192],"alternative":[193],"monitoring":[195],"processes":[196],"data.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}
