{"id":"https://openalex.org/W4289836959","doi":"https://doi.org/10.1080/03610918.2022.2107221","title":"Generating and estimating dependency between binary variables","display_name":"Generating and estimating dependency between binary variables","publication_year":2022,"publication_date":"2022-08-04","ids":{"openalex":"https://openalex.org/W4289836959","doi":"https://doi.org/10.1080/03610918.2022.2107221"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2107221","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2107221","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/A5081816038","display_name":"Igor Ferreira do Nascimento","orcid":"https://orcid.org/0000-0003-1084-7849"},"institutions":[{"id":"https://openalex.org/I3121799822","display_name":"Universidade Federal do Piau\u00ed","ror":"https://ror.org/00kwnx126","country_code":"BR","type":"education","lineage":["https://openalex.org/I3121799822"]},{"id":"https://openalex.org/I4210127128","display_name":"Instituto Federal do Piau\u00ed","ror":"https://ror.org/033qmpy33","country_code":"BR","type":"education","lineage":["https://openalex.org/I4210127128"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Igor Ferreira do Nascimento","raw_affiliation_strings":["Department of Mathematics, Federal Institute of Piau\u00ed","Department of Mathematics, Federal Institute of Piau\u00ed, Piau\u00ed, Brazil"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Federal Institute of Piau\u00ed","institution_ids":["https://openalex.org/I4210127128","https://openalex.org/I3121799822"]},{"raw_affiliation_string":"Department of Mathematics, Federal Institute of Piau\u00ed, Piau\u00ed, Brazil","institution_ids":["https://openalex.org/I4210127128"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5081816038"],"corresponding_institution_ids":["https://openalex.org/I3121799822","https://openalex.org/I4210127128"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08675333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"53","issue":"7","first_page":"3531","last_page":"3540"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9739999771118164,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9739999771118164,"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9580000042915344,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.939300000667572,"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/dependency","display_name":"Dependency (UML)","score":0.7505571842193604},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5028631091117859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4264107048511505},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3947456479072571},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.37604498863220215},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30631768703460693},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.1561698317527771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12990346550941467}],"concepts":[{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.7505571842193604},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5028631091117859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4264107048511505},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3947456479072571},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37604498863220215},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30631768703460693},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.1561698317527771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12990346550941467}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2022.2107221","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2107221","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/W37728405","https://openalex.org/W807756941","https://openalex.org/W1513873506","https://openalex.org/W1551098300","https://openalex.org/W1906261441","https://openalex.org/W1973606738","https://openalex.org/W1980316423","https://openalex.org/W1982951617","https://openalex.org/W2005272715","https://openalex.org/W2008640468","https://openalex.org/W2031467205","https://openalex.org/W2064124628","https://openalex.org/W2082542916","https://openalex.org/W2086947844","https://openalex.org/W2103912194","https://openalex.org/W2116552163","https://openalex.org/W2121960347","https://openalex.org/W2221087461","https://openalex.org/W2292183648","https://openalex.org/W2297405967","https://openalex.org/W2312732917","https://openalex.org/W2332774781","https://openalex.org/W2435079844","https://openalex.org/W2562861616","https://openalex.org/W2878311976","https://openalex.org/W2952492922","https://openalex.org/W3082165296","https://openalex.org/W3104191735","https://openalex.org/W3127710799","https://openalex.org/W3140153594","https://openalex.org/W4248536918"],"related_works":["https://openalex.org/W63071447","https://openalex.org/W1529400504","https://openalex.org/W2888625260","https://openalex.org/W2383067397","https://openalex.org/W65617392","https://openalex.org/W2313772788","https://openalex.org/W2811279793","https://openalex.org/W2114668360","https://openalex.org/W2366986860","https://openalex.org/W2524698037"],"abstract_inverted_index":{"The":[0,44,69,84],"assumption":[1],"that":[2,22],"binary":[3,30,85],"variables":[4,31],"are":[5],"independent,":[6],"homogeneously":[7],"distributed":[8],"and":[9,42,62],"exchangeable":[10],"may":[11],"not":[12],"reflect":[13],"reality.":[14],"Therefore,":[15],"the":[16,51,92,100,105,111],"present":[17],"work":[18],"proposes":[19],"a":[20,24,33,58],"method":[21],"transforms":[23],"multivariate":[25],"simulation":[26,86],"problem":[27],"dependent":[28],"of":[29,53,94,107,114],"into":[32],"hierarchical":[34],"dependency":[35,45],"model,":[36],"which":[37],"allows":[38],"for":[39],"easier":[40],"estimation":[41,46,71],"simulation.":[43],"via":[47,72,81],"Bayesian":[48,73],"Inference":[49],"outperforms":[50],"Method":[52],"Moments,":[54],"since":[55],"it":[56],"presents":[57],"lower":[59],"error":[60],"measure":[61],"guarantees":[63],"non-negative":[64],"estimates":[65],"bounded":[66],"by":[67,77],"1.":[68],"complexity":[70],"approach":[74],"was":[75,88],"overcome":[76],"important":[78],"resampling":[79],"methods":[80],"Monte":[82],"Carlo.":[83],"proposal":[87],"applied":[89],"to":[90],"model":[91],"probability":[93,112],"death":[95,106],"in":[96],"family":[97],"groups,":[98],"considering":[99],"broken":[101],"heart":[102],"syndrome,":[103],"when":[104],"one":[108],"member":[109],"affects":[110],"distribution":[113],"another":[115],"one.":[116]},"counts_by_year":[],"updated_date":"2026-02-08T09:19:03.324500","created_date":"2025-10-10T00:00:00"}
