{"id":"https://openalex.org/W4223902922","doi":"https://doi.org/10.1080/03610918.2022.2061514","title":"Computational methods for a copula-based Markov chain model with a binomial time series","display_name":"Computational methods for a copula-based Markov chain model with a binomial time series","publication_year":2022,"publication_date":"2022-04-18","ids":{"openalex":"https://openalex.org/W4223902922","doi":"https://doi.org/10.1080/03610918.2022.2061514"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2061514","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2061514","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","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/dataset/Computational_methods_for_a_copula-based_Markov_chain_model_with_a_binomial_time_series/19609586","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063231461","display_name":"Xin-Wei Huang","orcid":"https://orcid.org/0000-0003-4238-3081"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin-Wei Huang","raw_affiliation_strings":["Department of Biostatistics, University at Buffalo, State University of New York, Buffalo, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, University at Buffalo, State University of New York, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020629689","display_name":"Takeshi Emura","orcid":"https://orcid.org/0000-0002-3904-4014"},"institutions":[{"id":"https://openalex.org/I105296287","display_name":"Kurume University","ror":"https://ror.org/057xtrt18","country_code":"JP","type":"education","lineage":["https://openalex.org/I105296287"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takeshi Emura","raw_affiliation_strings":["Biostatistics Center, Kurume University, Kurume, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Biostatistics Center, Kurume University, Kurume, Japan","institution_ids":["https://openalex.org/I105296287"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5020629689"],"corresponding_institution_ids":["https://openalex.org/I105296287"],"apc_list":null,"apc_paid":null,"fwci":0.8221,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72703535,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"53","issue":"4","first_page":"1973","last_page":"1990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9966999888420105,"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":0.9966999888420105,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9962999820709229,"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"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9945999979972839,"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":0.8487259149551392},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.7685622572898865},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.5742579102516174},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5579845309257507},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.5011932849884033},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.42787453532218933},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.41321954131126404},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.41037824749946594},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3264148533344269},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32350242137908936},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29310306906700134},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20783844590187073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1888621747493744},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.07677498459815979}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.8487259149551392},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.7685622572898865},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.5742579102516174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5579845309257507},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.5011932849884033},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.42787453532218933},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.41321954131126404},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41037824749946594},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3264148533344269},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32350242137908936},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29310306906700134},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20783844590187073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1888621747493744},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.07677498459815979}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/03610918.2022.2061514","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2061514","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:figshare.com:article/19609586","is_oa":true,"landing_page_url":"https://figshare.com/articles/dataset/Computational_methods_for_a_copula-based_Markov_chain_model_with_a_binomial_time_series/19609586","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Dataset"},{"id":"doi:10.6084/m9.figshare.19609586.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.19609586.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/19609586","is_oa":true,"landing_page_url":"https://figshare.com/articles/dataset/Computational_methods_for_a_copula-based_Markov_chain_model_with_a_binomial_time_series/19609586","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Dataset"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2516010674","display_name":"Generalized linear mixed models for copula-based bivariate survival analysis","funder_award_id":"22K11948","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W31734411","https://openalex.org/W1485399950","https://openalex.org/W1493503622","https://openalex.org/W1648456516","https://openalex.org/W1734452708","https://openalex.org/W1968442909","https://openalex.org/W1969248194","https://openalex.org/W1969981565","https://openalex.org/W1975995381","https://openalex.org/W1982732343","https://openalex.org/W1983074539","https://openalex.org/W1994267238","https://openalex.org/W1994907950","https://openalex.org/W2000355354","https://openalex.org/W2001063175","https://openalex.org/W2025921222","https://openalex.org/W2028115777","https://openalex.org/W2062708010","https://openalex.org/W2078237481","https://openalex.org/W2090499758","https://openalex.org/W2116775230","https://openalex.org/W2122066903","https://openalex.org/W2136264975","https://openalex.org/W2141479936","https://openalex.org/W2142219037","https://openalex.org/W2162637951","https://openalex.org/W2195125035","https://openalex.org/W2263581110","https://openalex.org/W2396000217","https://openalex.org/W2466892432","https://openalex.org/W2477834368","https://openalex.org/W2507039649","https://openalex.org/W2606892876","https://openalex.org/W2626945353","https://openalex.org/W2724114697","https://openalex.org/W2891161212","https://openalex.org/W2900497781","https://openalex.org/W2906850869","https://openalex.org/W2909138707","https://openalex.org/W2914599834","https://openalex.org/W2942505090","https://openalex.org/W2949400589","https://openalex.org/W2959816377","https://openalex.org/W2967502806","https://openalex.org/W2975360357","https://openalex.org/W2997864270","https://openalex.org/W3088579130","https://openalex.org/W3092985826","https://openalex.org/W3120742959","https://openalex.org/W3182634474","https://openalex.org/W3192522190","https://openalex.org/W3206218649","https://openalex.org/W3206701744","https://openalex.org/W4205431151","https://openalex.org/W4210977276","https://openalex.org/W4214597110","https://openalex.org/W4221009672","https://openalex.org/W4229598638","https://openalex.org/W4233494161","https://openalex.org/W4234580748","https://openalex.org/W4246555007","https://openalex.org/W4298104588","https://openalex.org/W4301048281","https://openalex.org/W6748500362","https://openalex.org/W6827996105","https://openalex.org/W6996584577"],"related_works":["https://openalex.org/W2130519334","https://openalex.org/W2118728396","https://openalex.org/W1985664346","https://openalex.org/W3126873283","https://openalex.org/W2393621008","https://openalex.org/W2540690809","https://openalex.org/W4386839846","https://openalex.org/W2353273130","https://openalex.org/W3022014775","https://openalex.org/W2100055350"],"abstract_inverted_index":{"A":[0],"copula-based":[1,19],"Markov":[2,20],"chain":[3],"model":[4,57],"can":[5],"flexibly":[6],"capture":[7],"serial":[8],"dependence":[9],"in":[10,66],"a":[11,40,90],"time":[12,42],"series.":[13],"However,":[14],"the":[15,45,53,64,77,80,84],"computational":[16,37],"developments":[17],"for":[18,24,39],"models":[21,27],"remain":[22],"insufficient":[23],"discrete":[25],"marginal":[26],"compared":[28],"with":[29],"continuous":[30],"ones.":[31],"In":[32],"this":[33],"article,":[34],"we":[35],"develop":[36],"methods":[38,51,65],"binomial":[41],"series":[43],"under":[44],"Clayton":[46],"and":[47,59],"Joe":[48],"copulas.":[49],"The":[50],"include":[52],"data-generation,":[54],"parameter":[55],"estimation,":[56],"selection,":[58],"goodness-of-fit":[60],"tests.":[61],"We":[62,72],"implement":[63],"our":[67],"R":[68],"package":[69],"Copula.Markov":[70],"(https://CRAN.R-project.org/package=Copula.Markov).":[71],"conduct":[73],"simulations":[74],"to":[75],"see":[76],"performance":[78],"of":[79],"developed":[81],"methods.":[82],"Finally,":[83],"proposed":[85],"method":[86],"is":[87],"illustrated":[88],"by":[89],"real":[91],"dataset.":[92]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
