{"id":"https://openalex.org/W2951230649","doi":"https://doi.org/10.1080/03610918.2019.1622720","title":"Copula density estimation by finite mixture of parametric copula densities","display_name":"Copula density estimation by finite mixture of parametric copula densities","publication_year":2019,"publication_date":"2019-06-07","ids":{"openalex":"https://openalex.org/W2951230649","doi":"https://doi.org/10.1080/03610918.2019.1622720","mag":"2951230649"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1622720","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1622720","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1906.09388","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Leming Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I120156002","display_name":"Boise State University","ror":"https://ror.org/02e3zdp86","country_code":"US","type":"education","lineage":["https://openalex.org/I120156002"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Leming Qu","raw_affiliation_strings":["Department of Mathematics, Boise State University, Boise, Idaho, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Boise State University, Boise, Idaho, USA","institution_ids":["https://openalex.org/I120156002"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yang Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I120156002","display_name":"Boise State University","ror":"https://ror.org/02e3zdp86","country_code":"US","type":"education","lineage":["https://openalex.org/I120156002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Lu","raw_affiliation_strings":["Department of Civil Engineering, Boise State University, Boise, Idaho, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Boise State University, Boise, Idaho, USA","institution_ids":["https://openalex.org/I120156002"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I120156002"],"apc_list":null,"apc_paid":null,"fwci":0.254,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.59098724,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"50","issue":"11","first_page":"3315","last_page":"3337"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.7652000188827515,"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":0.7652000188827515,"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":0.12939999997615814,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.012400000356137753,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/copula","display_name":"Copula (linguistics)","score":0.8919000029563904},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6539999842643738},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.49559998512268066},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.48919999599456787},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.4652000069618225},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.448199987411499}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.8919000029563904},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6539999842643738},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5936999917030334},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.49559998512268066},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.49140000343322754},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.48919999599456787},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.4652000069618225},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.448199987411499},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4153999984264374},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.40720000863075256},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.33230000734329224},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3230000138282776},{"id":"https://openalex.org/C162392398","wikidata":"https://www.wikidata.org/wiki/Q272404","display_name":"Finite set","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2676999866962433},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.266400009393692}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/03610918.2019.1622720","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1622720","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"},{"id":"pmh:oai:arXiv.org:1906.09388","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.09388","pdf_url":"https://arxiv.org/pdf/1906.09388","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:scholarworks.boisestate.edu:math_facpubs-1259","is_oa":false,"landing_page_url":"https://scholarworks.boisestate.edu/math_facpubs/259","pdf_url":null,"source":{"id":"https://openalex.org/S4377196366","display_name":"Scholar Works  (Boise State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I120156002","host_organization_name":"Boise State University","host_organization_lineage":["https://openalex.org/I120156002"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Mathematics Faculty Publications and Presentations","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1906.09388","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.09388","pdf_url":"https://arxiv.org/pdf/1906.09388","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W204885769","https://openalex.org/W306662213","https://openalex.org/W390686421","https://openalex.org/W1120194648","https://openalex.org/W1518039036","https://openalex.org/W1542792663","https://openalex.org/W1558013848","https://openalex.org/W1731560272","https://openalex.org/W1963566461","https://openalex.org/W1971536112","https://openalex.org/W1972790352","https://openalex.org/W1976362364","https://openalex.org/W1984570338","https://openalex.org/W1990860515","https://openalex.org/W2031775363","https://openalex.org/W2035072927","https://openalex.org/W2035756456","https://openalex.org/W2038885294","https://openalex.org/W2041684917","https://openalex.org/W2042645953","https://openalex.org/W2044146548","https://openalex.org/W2053226409","https://openalex.org/W2058343378","https://openalex.org/W2060512288","https://openalex.org/W2072872252","https://openalex.org/W2078237481","https://openalex.org/W2078484714","https://openalex.org/W2087101057","https://openalex.org/W2110785335","https://openalex.org/W2133000564","https://openalex.org/W2134902673","https://openalex.org/W2141280361","https://openalex.org/W2157590940","https://openalex.org/W2157979130","https://openalex.org/W2804760238","https://openalex.org/W2909913858","https://openalex.org/W3022380717","https://openalex.org/W3121687142","https://openalex.org/W4255932839"],"related_works":[],"abstract_inverted_index":{"A":[0],"copula":[1,15,32],"density":[2],"estimation":[3],"method":[4],"that":[5,84],"is":[6,17,70,88],"based":[7],"on":[8],"a":[9],"finite":[10],"mixture":[11,23],"of":[12,37],"heterogeneous":[13],"parametric":[14],"densities":[16],"proposed":[18,86],"here.":[19],"More":[20],"specifically,":[21],"the":[22,62,73,85],"components":[24],"are":[25,35,55],"Clayton,":[26],"Frank,":[27],"Gumbel,":[28],"T,":[29],"and":[30,47,79],"normal":[31],"densities,":[33],"which":[34],"capable":[36],"capturing":[38],"lower":[39],"tail,":[40,44,46],"strong":[41],"central,":[42],"upper":[43],"heavy":[45],"symmetrical":[48],"elliptical":[49],"dependence,":[50],"respectively.":[51],"The":[52,67],"model":[53,91],"parameters":[54],"estimated":[56],"by":[57],"an":[58],"interior-point":[59,68],"algorithm":[60,69],"for":[61,94],"constrained":[63],"maximum":[64],"likelihood":[65],"problem.":[66],"compared":[71],"with":[72],"commonly":[74],"used":[75],"EM":[76],"algorithm.":[77],"Simulation":[78],"real":[80],"data":[81,95],"application":[82],"show":[83],"approach":[87],"effective":[89],"to":[90],"complex":[92],"dependencies":[93],"in":[96],"dimensions":[97],"beyond":[98],"two":[99],"or":[100],"three.":[101]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2019-06-27T00:00:00"}