{"id":"https://openalex.org/W3080985181","doi":"https://doi.org/10.1002/sta4.311","title":"Randomized estimation of functional covariance operator via subsampling","display_name":"Randomized estimation of functional covariance operator via subsampling","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3080985181","doi":"https://doi.org/10.1002/sta4.311","mag":"3080985181"},"language":"en","primary_location":{"id":"doi:10.1002/sta4.311","doi":"https://doi.org/10.1002/sta4.311","is_oa":false,"landing_page_url":"https://doi.org/10.1002/sta4.311","pdf_url":null,"source":{"id":"https://openalex.org/S4210193439","display_name":"Stat","issn_l":"2049-1573","issn":["2049-1573"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Stat","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5038978605","display_name":"Shiyuan He","orcid":"https://orcid.org/0000-0003-2593-4566","observed_orcids":["https://orcid.org/0000-0003-2593-4566"]},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shiyuan He","raw_affiliation_strings":["Institute of Statistics and Big Data, Renmin University of China, Beijing, 100872 China"],"raw_orcid":"https://orcid.org/0000-0003-2593-4566","affiliations":[{"raw_affiliation_string":"Institute of Statistics and Big Data, Renmin University of China, Beijing, 100872 China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050822798","display_name":"Xiaomeng Yan","orcid":"https://orcid.org/0000-0002-6375-6310","observed_orcids":["https://orcid.org/0000-0002-6375-6310"]},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaomeng Yan","raw_affiliation_strings":["Department of Statistics, Texas A&M University, College Station, 77843 TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-6375-6310","affiliations":[{"raw_affiliation_string":"Department of Statistics, Texas A&M University, College Station, 77843 TX, USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038978605"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":{"value":2700,"currency":"USD","value_usd":2700},"apc_paid":null,"fwci":0.1645,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.45705356,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":"9","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9496999979019165,"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"}},"topics":[{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9496999979019165,"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/T10136","display_name":"Statistical Methods and Inference","score":0.017799999564886093,"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/T13141","display_name":"Statistical Methods and Applications","score":0.004000000189989805,"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/randomized-algorithms","display_name":"randomized algorithms","score":0.7070000171661377},{"id":"https://openalex.org/keywords/subsampling","display_name":"subsampling","score":0.9580000042915344},{"id":"https://openalex.org/keywords/sketching","display_name":"sketching","score":0.8220000267028809},{"id":"https://openalex.org/keywords/functional-data-analysis","display_name":"functional data analysis","score":0.8460000157356262},{"id":"https://openalex.org/keywords/nonasymptotic-bounds","display_name":"non-asymptotic bounds","score":0.8050000071525574},{"id":"https://openalex.org/keywords/frobenius-norm","display_name":"Frobenius norm","score":0.9959999918937683},{"id":"https://openalex.org/keywords/operator-norm","display_name":"operator norm","score":0.9330000281333923},{"id":"https://openalex.org/keywords/functional-principal-component-analysis","display_name":"functional principal component analysis","score":0.824999988079071}],"concepts":[{"id":"https://openalex.org/C103692563","wikidata":"https://www.wikidata.org/wiki/Q5178900","display_name":"Covariance operator","level":3,"score":0.8765048980712891},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7075152397155762},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6205778121948242},{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.5622985363006592},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.5585106611251831},{"id":"https://openalex.org/C148893098","wikidata":"https://www.wikidata.org/wiki/Q7295778","display_name":"Rational quadratic covariance function","level":5,"score":0.5472426414489746},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5119946599006653},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.4713049829006195},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.469632625579834},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.45441707968711853},{"id":"https://openalex.org/C51820054","wikidata":"https://www.wikidata.org/wiki/Q5508814","display_name":"Functional data analysis","level":2,"score":0.42457205057144165},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4074874520301819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3943159878253937},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38413485884666443},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3684043884277344},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27574506402015686},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/sta4.311","doi":"https://doi.org/10.1002/sta4.311","is_oa":false,"landing_page_url":"https://doi.org/10.1002/sta4.311","pdf_url":null,"source":{"id":"https://openalex.org/S4210193439","display_name":"Stat","issn_l":"2049-1573","issn":["2049-1573"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Stat","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W621923488","https://openalex.org/W1493199243","https://openalex.org/W1629785033","https://openalex.org/W1762703698","https://openalex.org/W1938444229","https://openalex.org/W1970576574","https://openalex.org/W1979379324","https://openalex.org/W2003690406","https://openalex.org/W2042465463","https://openalex.org/W2070330801","https://openalex.org/W2095649984","https://openalex.org/W2102600871","https://openalex.org/W2104151829","https://openalex.org/W2117756735","https://openalex.org/W2147927736","https://openalex.org/W2597846060","https://openalex.org/W2789922433","https://openalex.org/W2798816298","https://openalex.org/W2799544692","https://openalex.org/W2883693466","https://openalex.org/W2963060476","https://openalex.org/W4244219114"],"related_works":["https://openalex.org/W7167489117","https://openalex.org/W2962800683","https://openalex.org/W3084435116","https://openalex.org/W7070744867","https://openalex.org/W3198889734","https://openalex.org/W4285596540","https://openalex.org/W7147158117","https://openalex.org/W2765827710","https://openalex.org/W2883420083","https://openalex.org/W4281381817"],"abstract_inverted_index":{"Covariance":[0],"operators":[1],"are":[2,143],"fundamental":[3],"concepts":[4],"and":[5,53,70,95,107,139],"modelling":[6],"tools":[7],"for":[8,44],"many":[9],"functional":[10,16,34,59],"data":[11,60,141],"analysis":[12],"methods,":[13],"such":[14],"as":[15],"principal":[17],"component":[18],"analysis.":[19],"However,":[20],"the":[21,33,57,74,78,93,96,104,108,115,121,127,133,147,150],"empirical":[22,80,98],"(or":[23],"estimated)":[24],"covariance":[25,45,81,99],"operator":[26,46,100,109],"becomes":[27],"too":[28],"costly":[29],"to":[30,62,76,145],"compute":[31],"when":[32],"dataset":[35],"gets":[36],"big.":[37],"This":[38],"paper":[39],"studies":[40],"a":[41,64],"randomized":[42],"algorithm":[43,49,85],"estimation.":[47],"The":[48,83],"works":[50],"by":[51,132],"sampling":[52,117],"rescaling":[54],"observations":[55],"from":[56],"large":[58],"collection":[61],"form":[63],"sketch":[65,75],"of":[66,103,126,135,149],"much":[67],"smaller":[68],"size":[69],"performs":[71],"computation":[72],"on":[73],"obtain":[77],"subsampled":[79,94],"operator.":[82],"proposed":[84,151],"is":[86,112,130],"theoretically":[87],"justified":[88],"via":[89],"nonasymptotic":[90],"bounds":[91],"between":[92],"full\u2010sample":[97],"in":[101],"terms":[102],"Hilbert\u2010Schmidt":[105,124],"norm":[106,125,134],"norm.":[110],"It":[111],"shown":[113],"that":[114,119],"optimal":[116],"probability":[118],"minimizes":[120],"expected":[122],"squared":[123],"subsampling":[128],"error":[129],"determined":[131],"each":[136],"function.":[137],"Simulated":[138],"real":[140],"examples":[142],"used":[144],"illustrate":[146],"effectiveness":[148],"algorithm.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2020-09-01T00:00:00"}