{"id":"https://openalex.org/W7125925489","doi":"https://doi.org/10.1007/s11222-026-10830-y","title":"Non-parametric estimation techniques of factor copula model using proxies","display_name":"Non-parametric estimation techniques of factor copula model using proxies","publication_year":2026,"publication_date":"2026-01-28","ids":{"openalex":"https://openalex.org/W7125925489","doi":"https://doi.org/10.1007/s11222-026-10830-y"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-026-10830-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-026-10830-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-026-10830-y.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-026-10830-y.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112862798","display_name":"Bahareh Ghanbari","orcid":null},"institutions":[{"id":"https://openalex.org/I2802631561","display_name":"Australian Mathematical Sciences Institute","ror":"https://ror.org/00yn60108","country_code":"AU","type":"other","lineage":["https://openalex.org/I2802631561"]},{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Bahareh Ghanbari","raw_affiliation_strings":["Department of Mathematical Sciences, RMIT University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, RMIT University, Melbourne, Australia","institution_ids":["https://openalex.org/I2802631561","https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072212118","display_name":"Pavel Krupskii","orcid":"https://orcid.org/0000-0001-9658-735X"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Pavel Krupskii","raw_affiliation_strings":["School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076349547","display_name":"Laleh Tafakori","orcid":"https://orcid.org/0000-0002-0815-8094"},"institutions":[{"id":"https://openalex.org/I2802631561","display_name":"Australian Mathematical Sciences Institute","ror":"https://ror.org/00yn60108","country_code":"AU","type":"other","lineage":["https://openalex.org/I2802631561"]},{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Laleh Tafakori","raw_affiliation_strings":["Department of Mathematical Sciences, RMIT University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, RMIT University, Melbourne, Australia","institution_ids":["https://openalex.org/I2802631561","https://openalex.org/I82951845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124135852","display_name":"Yan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I2802631561","display_name":"Australian Mathematical Sciences Institute","ror":"https://ror.org/00yn60108","country_code":"AU","type":"other","lineage":["https://openalex.org/I2802631561"]},{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yan Wang","raw_affiliation_strings":["Department of Mathematical Sciences, RMIT University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, RMIT University, Melbourne, Australia","institution_ids":["https://openalex.org/I2802631561","https://openalex.org/I82951845"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112862798"],"corresponding_institution_ids":["https://openalex.org/I2802631561","https://openalex.org/I82951845"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":{"value":2090,"currency":"EUR","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31591393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.49720001220703125,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.49720001220703125,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.337799996137619,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.01360000018030405,"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/copula","display_name":"Copula (linguistics)","score":0.8295999765396118},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6682000160217285},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6313999891281128},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.5759000182151794},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5091999769210815},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.429500013589859},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.39649999141693115},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.3849000036716461}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.8295999765396118},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6682000160217285},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6313999891281128},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.5759000182151794},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5091999769210815},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4984999895095825},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.47049999237060547},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.429500013589859},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3643999993801117},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3594000041484833},{"id":"https://openalex.org/C10879293","wikidata":"https://www.wikidata.org/wiki/Q726474","display_name":"Factor analysis","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.3075999915599823},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.27970001101493835},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2782999873161316},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C27406209","wikidata":"https://www.wikidata.org/wiki/Q6394203","display_name":"Kernel smoother","level":5,"score":0.2662000060081482},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25429999828338623},{"id":"https://openalex.org/C78297888","wikidata":"https://www.wikidata.org/wiki/Q7449607","display_name":"Semiparametric model","level":3,"score":0.25099998712539673},{"id":"https://openalex.org/C197656967","wikidata":"https://www.wikidata.org/wiki/Q17058458","display_name":"Marginal model","level":3,"score":0.2508000135421753},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11222-026-10830-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-026-10830-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-026-10830-y.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11222-026-10830-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-026-10830-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-026-10830-y.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7125925489.pdf","grobid_xml":"https://content.openalex.org/works/W7125925489.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W204885769","https://openalex.org/W1542792663","https://openalex.org/W1969334981","https://openalex.org/W1975018731","https://openalex.org/W1975717799","https://openalex.org/W1978526075","https://openalex.org/W1987875779","https://openalex.org/W1996388751","https://openalex.org/W2083138969","https://openalex.org/W2085055839","https://openalex.org/W2097068514","https://openalex.org/W2098381731","https://openalex.org/W2101593446","https://openalex.org/W2133097426","https://openalex.org/W2162543061","https://openalex.org/W2212412950","https://openalex.org/W2467760016","https://openalex.org/W2470916415","https://openalex.org/W2607311663","https://openalex.org/W2624583859","https://openalex.org/W2763905213","https://openalex.org/W2912396244","https://openalex.org/W2955186198","https://openalex.org/W2963626190","https://openalex.org/W3032483209","https://openalex.org/W3095040609","https://openalex.org/W3125488103","https://openalex.org/W3194404910","https://openalex.org/W3194623631","https://openalex.org/W3200768790","https://openalex.org/W3207122563","https://openalex.org/W4210702109","https://openalex.org/W4233104424","https://openalex.org/W4295166790","https://openalex.org/W4362503397","https://openalex.org/W4382517074","https://openalex.org/W4387580637","https://openalex.org/W4399549385"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Parametric":[1],"factor":[2],"copula":[3,82],"models":[4,31],"typically":[5],"work":[6],"well":[7],"in":[8,77,123],"modeling":[9,119],"multivariate":[10,120],"dependencies":[11,73],"due":[12],"to":[13,18,69],"their":[14],"flexibility":[15,64],"and":[16,99,127],"ability":[17],"capture":[19,70],"complex":[20,85],"dependency":[21],"structures.":[22],"However,":[23],"accurately":[24],"estimating":[25,47],"the":[26,63,71,80,91,111],"linking":[27,48],"copulas":[28,49],"within":[29],"these":[30],"remains":[32],"challenging,":[33],"especially":[34],"when":[35],"working":[36],"with":[37],"high-dimensional":[38],"data.":[39],"This":[40],"paper":[41],"proposes":[42],"a":[43,52,115],"novel":[44],"approach":[45,61,113],"for":[46,118],"based":[50],"on":[51],"non-parametric":[53],"kernel":[54,66],"estimator.":[55],"Unlike":[56],"conventional":[57],"parametric":[58],"methods,":[59],"our":[60],"utilizes":[62],"of":[65,130],"density":[67],"estimation":[68,129],"underlying":[72,81],"more":[74],"accurately,":[75],"particularly":[76,122],"scenarios":[78],"where":[79],"structure":[83],"is":[84,94],"or":[86],"unknown.":[87],"We":[88],"show":[89],"that":[90,110],"proposed":[92,112],"estimator":[93],"consistent":[95],"under":[96],"mild":[97],"conditions":[98],"demonstrate":[100],"its":[101],"effectiveness":[102],"through":[103],"extensive":[104],"simulation":[105],"studies.":[106],"Our":[107],"findings":[108],"suggest":[109],"offers":[114],"promising":[116],"avenue":[117],"dependencies,":[121],"applications":[124],"requiring":[125],"robust":[126],"efficient":[128],"copula-based":[131],"models.":[132]},"counts_by_year":[],"updated_date":"2026-03-09T07:00:12.390032","created_date":"2026-01-29T00:00:00"}
