{"id":"https://openalex.org/W2954672296","doi":"https://doi.org/10.1080/03610918.2019.1636996","title":"Estimating checkerboard approximations with sample <i>d</i>-copulas","display_name":"Estimating checkerboard approximations with sample <i>d</i>-copulas","publication_year":2019,"publication_date":"2019-07-04","ids":{"openalex":"https://openalex.org/W2954672296","doi":"https://doi.org/10.1080/03610918.2019.1636996","mag":"2954672296"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1636996","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1636996","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/A5060409240","display_name":"Jos\u00e9 M. Gonz\u00e1lez-Barrios","orcid":"https://orcid.org/0000-0002-8967-0304"},"institutions":[{"id":"https://openalex.org/I8961855","display_name":"Universidad Nacional Aut\u00f3noma de M\u00e9xico","ror":"https://ror.org/01tmp8f25","country_code":"MX","type":"education","lineage":["https://openalex.org/I8961855"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Jos\u00e9 M. Gonz\u00e1lez-Barrios","raw_affiliation_strings":["Department of Probability and Statistics, IIMAS, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Mexico City, Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Probability and Statistics, IIMAS, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Mexico City, Mexico","institution_ids":["https://openalex.org/I8961855"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026394057","display_name":"Ricardo Hoyos-Arg\u00fcelles","orcid":"https://orcid.org/0000-0002-6003-2229"},"institutions":[{"id":"https://openalex.org/I29300151","display_name":"Bank of Mexico","ror":"https://ror.org/02xp9d883","country_code":"MX","type":"other","lineage":["https://openalex.org/I29300151"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Ricardo Hoyos-Arg\u00fcelles","raw_affiliation_strings":["Direction of Financial System Information, Banco de M\u00e9xico, Mexico City, Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Direction of Financial System Information, Banco de M\u00e9xico, Mexico City, Mexico","institution_ids":["https://openalex.org/I29300151"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060409240"],"corresponding_institution_ids":["https://openalex.org/I8961855"],"apc_list":null,"apc_paid":null,"fwci":0.8321,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75939062,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"50","issue":"12","first_page":"3992","last_page":"4027"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9983000159263611,"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/T10007","display_name":"Monetary Policy and Economic Impact","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2000","display_name":"General Economics, Econometrics and 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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7593144178390503},{"id":"https://openalex.org/keywords/copula","display_name":"Copula (linguistics)","score":0.7500472664833069},{"id":"https://openalex.org/keywords/checkerboard","display_name":"Checkerboard","score":0.744365930557251},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7262972593307495},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.5111234784126282},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.40862977504730225},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4082449674606323},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.35775530338287354},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.2363903820514679},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1004905104637146}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7593144178390503},{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.7500472664833069},{"id":"https://openalex.org/C2779168147","wikidata":"https://www.wikidata.org/wiki/Q460711","display_name":"Checkerboard","level":2,"score":0.744365930557251},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7262972593307495},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5111234784126282},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.40862977504730225},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4082449674606323},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.35775530338287354},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2363903820514679},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1004905104637146}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1636996","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1636996","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W344847922","https://openalex.org/W1494429120","https://openalex.org/W1966028609","https://openalex.org/W1983748783","https://openalex.org/W1988645907","https://openalex.org/W1991655919","https://openalex.org/W2001843889","https://openalex.org/W2008032819","https://openalex.org/W2024622649","https://openalex.org/W2025533349","https://openalex.org/W2026006993","https://openalex.org/W2030399213","https://openalex.org/W2030797081","https://openalex.org/W2032369139","https://openalex.org/W2033598072","https://openalex.org/W2042281847","https://openalex.org/W2047908315","https://openalex.org/W2062912569","https://openalex.org/W2064417747","https://openalex.org/W2135616188","https://openalex.org/W2158226696","https://openalex.org/W2163402412","https://openalex.org/W2338509365","https://openalex.org/W2394874451","https://openalex.org/W2493756685","https://openalex.org/W2494873755","https://openalex.org/W2801356077","https://openalex.org/W3098364223","https://openalex.org/W3104996773","https://openalex.org/W4292025355","https://openalex.org/W4301225083"],"related_works":["https://openalex.org/W4253840420","https://openalex.org/W3096952425","https://openalex.org/W3083797402","https://openalex.org/W3099790688","https://openalex.org/W1719868181","https://openalex.org/W1981574939","https://openalex.org/W2059475575","https://openalex.org/W2131726918","https://openalex.org/W2152704622","https://openalex.org/W2009129315"],"abstract_inverted_index":{"The":[0,46],"sample":[1,14],"d-copula":[2,44],"of":[3,15,18,34,39,42,77,105,162,176],"order":[4,40,63,178],"m":[5,41,64],"Cn(m)":[6,48,69,157],"is":[7,31,84,144,158],"a":[8,12,20,25,74,121,145],"d-copula,":[9,21],"constructed":[10],"from":[11,23,89,99],"random":[13],"size":[16],"n":[17,53],"C":[19,60],"or":[22],"H":[24],"continuous":[26],"d-dimensional":[27],"distribution":[28],"function,":[29],"which":[30],"an":[32,159],"estimator":[33,47,76,91,161],"C(m)":[35,51],"the":[36,43,62,90,95,103,106,129,133,137,163,177],"checkerboard":[37,164],"approximation":[38,165],"C.":[45,78],"converges":[49,58],"to":[50,59,87,114,123,154],"as":[52,73,128],"increases,":[54],"and":[55,93,132,167],"also":[56,65,119,168],"it":[57,83],"when":[61],"increases.":[66],"In":[67],"fact,":[68],"can":[70],"be":[71],"thought":[72],"quasi-nonparametric":[75],"We":[79,118],"will":[80,150],"see":[81,155],"that":[82,94,141,156],"absolutely":[85],"trivial":[86],"simulate":[88],"Cn(m),":[92],"simulated":[96],"samples":[97],"obtained":[98],"it,":[100],"follow":[101],"closely":[102],"patterns":[104],"original":[107],"samples,":[108],"we":[109,149,169],"even":[110],"use":[111,151],"real":[112],"data":[113],"observe":[115],"this":[116],"fact.":[117],"make":[120],"comparison":[122],"other":[124],"estimation":[125],"methods":[126],"such":[127],"empirical":[130],"copula":[131],"Bernstein":[134],"copula,":[135],"using":[136],"supremum":[138],"distance,":[139],"observing":[140],"our":[142],"proposal":[143],"competitive":[146],"option.":[147],"Finally,":[148],"stronger":[152],"distances":[153],"excellent":[160],"C(m),":[166],"include":[170],"some":[171],"comments":[172],"about":[173],"appropriate":[174],"values":[175],"m.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
