{"id":"https://openalex.org/W3192634934","doi":"https://doi.org/10.1080/03610918.2021.1958847","title":"Run length distribution for a modified EWMA scheme fitted with a stationary AR(p) model","display_name":"Run length distribution for a modified EWMA scheme fitted with a stationary AR(p) model","publication_year":2021,"publication_date":"2021-08-06","ids":{"openalex":"https://openalex.org/W3192634934","doi":"https://doi.org/10.1080/03610918.2021.1958847","mag":"3192634934"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2021.1958847","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.1958847","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/A5076482072","display_name":"Piyatida Phanthuna","orcid":null},"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":"Piyatida Phanthuna","raw_affiliation_strings":["Department of Applied Statistics, Faculty of Applied Science, King Mongkut\u2019s University of Technology, North Bangkok, Thailand","Department of Applied Statistics, Faculty of Applied Science, King Mongkut's University of Technology, North 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, 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, Thailand","institution_ids":["https://openalex.org/I82828225"]}]},{"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, Thailand","Department of Applied Statistics, Faculty of Applied Science, King Mongkut's University of Technology, North Bangkok, Thailand"],"raw_orcid":"https://orcid.org/0000-0002-5103-9867","affiliations":[{"raw_affiliation_string":"Department of Applied Statistics, Faculty of Applied Science, King Mongkut\u2019s University of Technology, North 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, 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, Thailand","Department of Applied Statistics, Faculty of Applied Science, King Mongkut's University of Technology, North 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, 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, Thailand","institution_ids":["https://openalex.org/I82828225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5069945313"],"corresponding_institution_ids":["https://openalex.org/I82828225"],"apc_list":null,"apc_paid":null,"fwci":0.3333,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7475542,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"52","issue":"9","first_page":"4260","last_page":"4279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9760000109672546,"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/T11890","display_name":"Scientific Measurement and Uncertainty Evaluation","score":0.9753000140190125,"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/ewma-chart","display_name":"EWMA chart","score":0.9824256896972656},{"id":"https://openalex.org/keywords/control-chart","display_name":"Control chart","score":0.7704899311065674},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7338740825653076},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.6698028445243835},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.5524017810821533},{"id":"https://openalex.org/keywords/exponential-distribution","display_name":"Exponential distribution","score":0.5153924226760864},{"id":"https://openalex.org/keywords/moving-average","display_name":"Moving average","score":0.5106166005134583},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5047250986099243},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4964666962623596},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.47463688254356384},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.46200841665267944},{"id":"https://openalex.org/keywords/x-bar-chart","display_name":"X-bar chart","score":0.4339931905269623},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4235832989215851},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4186880886554718},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.4181153476238251},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.21701115369796753},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.06646192073822021}],"concepts":[{"id":"https://openalex.org/C74746147","wikidata":"https://www.wikidata.org/wiki/Q5324652","display_name":"EWMA chart","level":4,"score":0.9824256896972656},{"id":"https://openalex.org/C196985124","wikidata":"https://www.wikidata.org/wiki/Q1369242","display_name":"Control chart","level":3,"score":0.7704899311065674},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7338740825653076},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.6698028445243835},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.5524017810821533},{"id":"https://openalex.org/C55350006","wikidata":"https://www.wikidata.org/wiki/Q237193","display_name":"Exponential distribution","level":2,"score":0.5153924226760864},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.5106166005134583},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5047250986099243},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4964666962623596},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.47463688254356384},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.46200841665267944},{"id":"https://openalex.org/C167779127","wikidata":"https://www.wikidata.org/wiki/Q8041542","display_name":"X-bar chart","level":5,"score":0.4339931905269623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4235832989215851},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4186880886554718},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.4181153476238251},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.21701115369796753},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.06646192073822021},{"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:10.1080/03610918.2021.1958847","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.1958847","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/G2548735310","display_name":null,"funder_award_id":"KMUTNB-FF-65-45.","funder_id":"https://openalex.org/F4320324344","funder_display_name":"King Mongkut's University of Technology North Bangkok"}],"funders":[{"id":"https://openalex.org/F4320324344","display_name":"King Mongkut's University of Technology North Bangkok","ror":"https://ror.org/04fy6jb97"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W133785115","https://openalex.org/W204225513","https://openalex.org/W1531802194","https://openalex.org/W1582294222","https://openalex.org/W1585261948","https://openalex.org/W1992881802","https://openalex.org/W1997443318","https://openalex.org/W2024760831","https://openalex.org/W2033361390","https://openalex.org/W2048043560","https://openalex.org/W2093113419","https://openalex.org/W2107847131","https://openalex.org/W2108675195","https://openalex.org/W2127084686","https://openalex.org/W2267987627","https://openalex.org/W2501323269","https://openalex.org/W2543670800","https://openalex.org/W2738252577","https://openalex.org/W2762147577","https://openalex.org/W2764161872","https://openalex.org/W2770665450","https://openalex.org/W2780398160","https://openalex.org/W2791196439","https://openalex.org/W2799463416","https://openalex.org/W2947069497","https://openalex.org/W2949326498","https://openalex.org/W3039675639","https://openalex.org/W3085751006","https://openalex.org/W4236667696","https://openalex.org/W4255375128","https://openalex.org/W4302420972","https://openalex.org/W4388318273","https://openalex.org/W6631773183","https://openalex.org/W6676090195","https://openalex.org/W6992022558"],"related_works":["https://openalex.org/W2022867152","https://openalex.org/W2126524872","https://openalex.org/W4318317915","https://openalex.org/W2410415934","https://openalex.org/W2036352556","https://openalex.org/W1982010548","https://openalex.org/W3006471751","https://openalex.org/W1886720398","https://openalex.org/W4245271849","https://openalex.org/W2072506223"],"abstract_inverted_index":{"A":[0],"modified":[1,39],"exponentially":[2],"weighted":[3],"moving":[4],"average":[5,33],"(EWMA)":[6],"scheme":[7,79],"is":[8,28,53,80,100],"a":[9,38,56,62,83,103],"quality":[10],"control":[11,86],"chart":[12,41,87],"which":[13],"can":[14,71],"quickly":[15],"detect":[16],"small":[17],"shifts":[18],"in":[19],"autocorrelated":[20],"data.":[21],"In":[22],"this":[23,78],"article,":[24],"an":[25,43],"explicit":[26,69,96],"formula":[27,70,97],"presented":[29],"to":[30,65,102,111],"calculate":[31],"the":[32,68,74,89,95,108,113],"run":[34],"length":[35],"(ARL)":[36],"for":[37,98],"EWMA":[40,85],"with":[42,55],"autoregressive":[44],"AR(p)":[45],"model":[46],"involving":[47],"exponential":[48],"white":[49],"noise.":[50],"Its":[51],"performance":[52],"compared":[54],"numerical":[57,105],"integral":[58],"equation":[59],"method":[60],"via":[61],"simulation":[63],"study":[64],"determine":[66],"whether":[67],"help":[72],"decrease":[73],"processing":[75],"time.":[76],"Moreover,":[77],"tested":[81],"against":[82],"classical":[84],"using":[88],"ARL":[90,99],"and":[91],"RMI":[92],"results.":[93],"Finally,":[94],"applied":[101],"real":[104],"example":[106],"from":[107],"health":[109],"field":[110],"demonstrate":[112],"efficacy":[114],"of":[115],"our":[116],"method.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}