{"id":"https://openalex.org/W2926367560","doi":"https://doi.org/10.1080/03610918.2019.1586921","title":"Outlier detection using PCA mix based<i>T</i><sup>2</sup>control chart for continuous and categorical data","display_name":"Outlier detection using PCA mix based<i>T</i><sup>2</sup>control chart for continuous and categorical data","publication_year":2019,"publication_date":"2019-04-03","ids":{"openalex":"https://openalex.org/W2926367560","doi":"https://doi.org/10.1080/03610918.2019.1586921","mag":"2926367560"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1586921","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1586921","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/A5028267093","display_name":"Muhammad Ahsan","orcid":"https://orcid.org/0000-0003-3444-2766"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Muhammad Ahsan","raw_affiliation_strings":["Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":"https://orcid.org/0000-0003-3444-2766","affiliations":[{"raw_affiliation_string":"Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027635234","display_name":"Muhammad Mashuri","orcid":"https://orcid.org/0000-0001-9348-4507"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Muhammad Mashuri","raw_affiliation_strings":["Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":"https://orcid.org/0000-0001-9348-4507","affiliations":[{"raw_affiliation_string":"Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058928914","display_name":"Heri Kuswanto","orcid":"https://orcid.org/0000-0003-0300-7286"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Heri Kuswanto","raw_affiliation_strings":["Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":"https://orcid.org/0000-0003-0300-7286","affiliations":[{"raw_affiliation_string":"Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066327096","display_name":"Dedy Dwi Prastyo","orcid":"https://orcid.org/0000-0003-1194-769X"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Dedy Dwi Prastyo","raw_affiliation_strings":["Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":"https://orcid.org/0000-0003-1194-769X","affiliations":[{"raw_affiliation_string":"Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039496197","display_name":"Hidayatul Khusna","orcid":"https://orcid.org/0000-0001-9889-2884"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Hidayatul Khusna","raw_affiliation_strings":["Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"raw_orcid":"https://orcid.org/0000-0001-9889-2884","affiliations":[{"raw_affiliation_string":"Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5027635234"],"corresponding_institution_ids":["https://openalex.org/I166843116"],"apc_list":null,"apc_paid":null,"fwci":1.5261,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.86197049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"50","issue":"5","first_page":"1496","last_page":"1523"},"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":0.9991000294685364,"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":0.9891999959945679,"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/categorical-variable","display_name":"Categorical variable","score":0.8534033298492432},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.839199423789978},{"id":"https://openalex.org/keywords/control-chart","display_name":"Control chart","score":0.8225488662719727},{"id":"https://openalex.org/keywords/control-limits","display_name":"Control limits","score":0.6429681181907654},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5979970097541809},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5836319327354431},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.5802149772644043},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5516364574432373},{"id":"https://openalex.org/keywords/ewma-chart","display_name":"EWMA chart","score":0.5297910571098328},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.44999372959136963},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.43097975850105286},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3404434323310852},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.277004212141037},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16540712118148804},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.09553295373916626}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8534033298492432},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.839199423789978},{"id":"https://openalex.org/C196985124","wikidata":"https://www.wikidata.org/wiki/Q1369242","display_name":"Control chart","level":3,"score":0.8225488662719727},{"id":"https://openalex.org/C166623804","wikidata":"https://www.wikidata.org/wiki/Q5165860","display_name":"Control limits","level":4,"score":0.6429681181907654},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5979970097541809},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5836319327354431},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.5802149772644043},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5516364574432373},{"id":"https://openalex.org/C74746147","wikidata":"https://www.wikidata.org/wiki/Q5324652","display_name":"EWMA chart","level":4,"score":0.5297910571098328},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.44999372959136963},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.43097975850105286},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3404434323310852},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.277004212141037},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16540712118148804},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.09553295373916626},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1586921","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1586921","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":[{"score":0.4699999988079071,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W47198768","https://openalex.org/W64578218","https://openalex.org/W1516550534","https://openalex.org/W1580673759","https://openalex.org/W1607585411","https://openalex.org/W1974222671","https://openalex.org/W1976816660","https://openalex.org/W1987926766","https://openalex.org/W2025534588","https://openalex.org/W2028705130","https://openalex.org/W2032657652","https://openalex.org/W2045731423","https://openalex.org/W2049058890","https://openalex.org/W2067067795","https://openalex.org/W2068302187","https://openalex.org/W2076215481","https://openalex.org/W2090927827","https://openalex.org/W2108365617","https://openalex.org/W2112905617","https://openalex.org/W2133896831","https://openalex.org/W2168956303","https://openalex.org/W2172007646","https://openalex.org/W2320553484","https://openalex.org/W2469441229","https://openalex.org/W2550646841","https://openalex.org/W2556715493","https://openalex.org/W2614654265","https://openalex.org/W2893207594","https://openalex.org/W4236979000","https://openalex.org/W4243563432","https://openalex.org/W4399551446","https://openalex.org/W6679241239"],"related_works":["https://openalex.org/W1985694811","https://openalex.org/W2017044513","https://openalex.org/W2036427829","https://openalex.org/W2001940661","https://openalex.org/W4214626283","https://openalex.org/W3148338915","https://openalex.org/W2207658476","https://openalex.org/W4225012004","https://openalex.org/W1544415648","https://openalex.org/W1980719083"],"abstract_inverted_index":{"Outliers":[0],"presence":[1],"may":[2],"lead":[3],"to":[4,43,101,117],"misdetection":[5],"on":[6],"out-of-control":[7],"observations":[8],"in":[9,17,50,67,79],"Phase":[10,18],"II,":[11],"therefore,":[12],"they":[13],"should":[14],"be":[15],"cleaned":[16],"I.":[19],"This":[20,92],"paper":[21],"proposes":[22],"PCA":[23],"Mix":[24],"based":[25],"T2":[26],"chart":[27,49,60,75,110],"with":[28,89],"Kernel":[29],"Density":[30],"control":[31],"limit":[32],"for":[33,122],"mixed":[34],"continuous":[35],"and":[36,55,97,104],"categorical":[37,82],"data.":[38,57,70],"Simulation":[39],"studies":[40],"are":[41,84],"conducted":[42],"evaluate":[44],"the":[45,65,102,108,123],"performance":[46,63,78,114],"of":[47,126],"proposed":[48,59,74,109],"detecting":[51],"outliers":[52],"from":[53,86],"clean":[54,69],"contaminated":[56,72],"The":[58],"has":[61,76],"better":[62],"than":[64],"benchmark":[66],"monitoring":[68],"For":[71],"data,":[73],"optimal":[77],"situation":[80],"when":[81],"data":[83],"generated":[85],"multinomial":[87],"distribution":[88],"balanced":[90],"parameters.":[91],"is":[93],"confirmed":[94],"by":[95,115],"simulated":[96],"real":[98],"dataset.":[99],"Compared":[100],"conventional":[103],"other":[105],"robust":[106],"charts,":[107],"demonstrated":[111],"a":[112],"great":[113],"success":[116],"detect":[118],"more":[119],"outlier":[120,127],"correctly":[121],"higher":[124],"percentage":[125],"added.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
