{"id":"https://openalex.org/W3003679289","doi":"https://doi.org/10.1109/ieem44572.2019.8978829","title":"A Sparse Leading-Eigenvalue-Driven Control Chart for Phase I Analysis of High-Dimensional Covariance Matrices","display_name":"A Sparse Leading-Eigenvalue-Driven Control Chart for Phase I Analysis of High-Dimensional Covariance Matrices","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3003679289","doi":"https://doi.org/10.1109/ieem44572.2019.8978829","mag":"3003679289"},"language":"en","primary_location":{"id":"doi:10.1109/ieem44572.2019.8978829","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem44572.2019.8978829","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-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/A5038361618","display_name":"Jinyu Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I201459984","display_name":"Guangdong University Of Finances and Economics","ror":"https://ror.org/0459pv085","country_code":"CN","type":"education","lineage":["https://openalex.org/I201459984"]},{"id":"https://openalex.org/I4210149618","display_name":"Guangdong University of Finance","ror":"https://ror.org/04grzdh47","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210149618"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"J. Y. Fan","raw_affiliation_strings":["School of Mathematics and Statistics, Guangdong University of Finance and Economics,Guangzhou,China","School of Mathematics and Statistics, Guangdong University of Finance and Economics, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Guangdong University of Finance and Economics,Guangzhou,China","institution_ids":["https://openalex.org/I201459984"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Guangdong University of Finance and Economics, Guangzhou, China","institution_ids":["https://openalex.org/I201459984","https://openalex.org/I4210149618"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076373662","display_name":"Lianjie Shu","orcid":"https://orcid.org/0000-0001-6860-698X"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"L. J. Shu","raw_affiliation_strings":["Faculty of Business Administration, University of Macau,Macau,China","Faculty of Business Administration, University of Macau, Macau, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Business Administration, University of Macau,Macau,China","institution_ids":["https://openalex.org/I204512498"]},{"raw_affiliation_string":"Faculty of Business Administration, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038361618"],"corresponding_institution_ids":["https://openalex.org/I201459984","https://openalex.org/I4210149618"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1871341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1300","last_page":"1304"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9933000206947327,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.6844700574874878},{"id":"https://openalex.org/keywords/control-chart","display_name":"Control chart","score":0.6637536287307739},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6489500999450684},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.563223123550415},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5631018280982971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5173922777175903},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5125803351402283},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.4565032422542572},{"id":"https://openalex.org/keywords/statistical-process-control","display_name":"Statistical process control","score":0.44929447770118713},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3864653706550598},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3357078433036804},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32488059997558594},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.262315571308136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23956194519996643},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07803577184677124}],"concepts":[{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.6844700574874878},{"id":"https://openalex.org/C196985124","wikidata":"https://www.wikidata.org/wiki/Q1369242","display_name":"Control chart","level":3,"score":0.6637536287307739},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6489500999450684},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.563223123550415},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5631018280982971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5173922777175903},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5125803351402283},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.4565032422542572},{"id":"https://openalex.org/C113644684","wikidata":"https://www.wikidata.org/wiki/Q1356717","display_name":"Statistical process control","level":3,"score":0.44929447770118713},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3864653706550598},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3357078433036804},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32488059997558594},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.262315571308136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23956194519996643},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07803577184677124},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieem44572.2019.8978829","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem44572.2019.8978829","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W79455595","https://openalex.org/W1992362262","https://openalex.org/W2010212762","https://openalex.org/W2011005606","https://openalex.org/W2029171385","https://openalex.org/W2035531503","https://openalex.org/W2041062137","https://openalex.org/W2059290350","https://openalex.org/W2080795935","https://openalex.org/W2087467445","https://openalex.org/W2091825839","https://openalex.org/W2106632614","https://openalex.org/W2111036668","https://openalex.org/W2130900471","https://openalex.org/W2339469603","https://openalex.org/W2553631888","https://openalex.org/W2571123389","https://openalex.org/W3100989718","https://openalex.org/W3105104252"],"related_works":["https://openalex.org/W2346052352","https://openalex.org/W2181685535","https://openalex.org/W2260512244","https://openalex.org/W2752333462","https://openalex.org/W2080586055","https://openalex.org/W2051163852","https://openalex.org/W3106703763","https://openalex.org/W2911502181","https://openalex.org/W161582973","https://openalex.org/W2040862285"],"abstract_inverted_index":{"In":[0],"statistical":[1],"process":[2,67],"control":[3,80,95],"(SPC),":[4],"a":[5,44,75],"proper":[6],"Phase":[7,16,29,50,59,89],"I":[8,30,51,60],"analysis":[9,31],"is":[10,36,102,141,156,159,164],"essential":[11],"to":[12,47,103,116],"the":[13,40,48,93,107,117,130,144,154,166],"success":[14],"of":[15,32,100],"II":[17],"monitoring.":[18],"With":[19],"recent":[20],"progresses":[21],"in":[22,62,88,106,168],"sensor":[23],"technology":[24],"and":[25,123,158],"data":[26,35],"collection":[27],"systems,":[28],"high-dimensional":[33],"(HP)":[34],"increasingly":[37],"encountered.":[38],"However,":[39],"high":[41,149],"dimensionality":[42],"presents":[43],"new":[45],"challenge":[46],"traditional":[49],"techniques.":[52],"A":[53],"literature":[54],"review":[55],"reveals":[56],"nearly":[57],"no":[58],"techniques":[61],"existence":[63],"for":[64,82],"analyzing":[65],"HP":[66,85],"variability.":[68],"Motivated":[69],"by":[70],"this,":[71],"this":[72],"paper":[73],"develops":[74],"Sparse":[76],"Leading":[77],"Eigenvalue":[78],"Driven":[79],"chart":[81],"retrospectively":[83],"monitoring":[84],"covariance":[86,113],"matrices":[87],"I,":[90],"denoted":[91],"as":[92],"SLED":[94],"chart.":[96],"The":[97],"key":[98],"idea":[99],"it":[101],"track":[104],"changes":[105],"sparse":[108],"leading":[109],"eigenvalue":[110],"between":[111],"two":[112],"matrices.":[114],"Compared":[115],"L":[118,124],"<sub":[119,125],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[120,126],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sub>":[121],"-type":[122,128],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u221e</sub>":[127],"methods,":[129],"proposed":[131,145],"method":[132,146],"can":[133,147],"extract":[134],"stronger":[135],"signal":[136],"with":[137],"less":[138],"noise.":[139],"It":[140],"shown":[142],"that":[143],"gain":[148],"detection":[150],"power,":[151],"especially":[152],"when":[153],"shift":[155],"weak":[157],"not":[160],"very":[161],"dense,":[162],"which":[163],"often":[165],"case":[167],"practical":[169],"applications.":[170]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}