{"id":"https://openalex.org/W4389381589","doi":"https://doi.org/10.1080/10618600.2023.2289545","title":"Copula Graphical Models for Heterogeneous Mixed Data","display_name":"Copula Graphical Models for Heterogeneous Mixed Data","publication_year":2023,"publication_date":"2023-12-06","ids":{"openalex":"https://openalex.org/W4389381589","doi":"https://doi.org/10.1080/10618600.2023.2289545"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2023.2289545","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2023.2289545","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://edepot.wur.nl/648722","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086148540","display_name":"Sjoerd Hermes","orcid":"https://orcid.org/0000-0002-9382-1347"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sjoerd Hermes","raw_affiliation_strings":["Mathematical and Statistical Methods, Wageningen University, Wageningen, Netherlands","Plant Production Systems, Wageningen University, Wageningen, Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-9382-1347","affiliations":[{"raw_affiliation_string":"Mathematical and Statistical Methods, Wageningen University, Wageningen, Netherlands","institution_ids":[]},{"raw_affiliation_string":"Plant Production Systems, Wageningen University, Wageningen, Netherlands","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010868049","display_name":"Joost van Heerwaarden","orcid":"https://orcid.org/0000-0002-4959-3914"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joost van Heerwaarden","raw_affiliation_strings":["Mathematical and Statistical Methods, Wageningen University, Wageningen, Netherlands","Plant Production Systems, Wageningen University, Wageningen, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mathematical and Statistical Methods, Wageningen University, Wageningen, Netherlands","institution_ids":[]},{"raw_affiliation_string":"Plant Production Systems, Wageningen University, Wageningen, Netherlands","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050316661","display_name":"Pariya Behrouzi","orcid":"https://orcid.org/0000-0001-6762-5433"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pariya Behrouzi","raw_affiliation_strings":["Mathematical and Statistical Methods, Wageningen University, Wageningen, Netherlands"],"raw_orcid":"https://orcid.org/0000-0001-6762-5433","affiliations":[{"raw_affiliation_string":"Mathematical and Statistical Methods, Wageningen University, Wageningen, Netherlands","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050316661"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9395,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.87941131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"33","issue":"3","first_page":"991","last_page":"1005"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9958999752998352,"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":0.9958999752998352,"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":0.9890000224113464,"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/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9688000082969666,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/copula","display_name":"Copula (linguistics)","score":0.7311129570007324},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.5384838581085205},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5380750298500061},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5371860265731812},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33483877778053284},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.288521945476532},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23587897419929504}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.7311129570007324},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.5384838581085205},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5380750298500061},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5371860265731812},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33483877778053284},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.288521945476532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23587897419929504}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/10618600.2023.2289545","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2023.2289545","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:oai:library.wur.nl:wurpubs/626513","is_oa":true,"landing_page_url":"https://research.wur.nl/en/publications/copula-graphical-models-for-heterogeneous-mixed-data","pdf_url":"https://edepot.wur.nl/648722","source":{"id":"https://openalex.org/S4210201231","display_name":"Socio-Environmental Systems Modeling","issn_l":"2663-3027","issn":["2663-3027"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 1061-8600","raw_type":"Article/Letter to editor"}],"best_oa_location":{"id":"pmh:oai:library.wur.nl:wurpubs/626513","is_oa":true,"landing_page_url":"https://research.wur.nl/en/publications/copula-graphical-models-for-heterogeneous-mixed-data","pdf_url":"https://edepot.wur.nl/648722","source":{"id":"https://openalex.org/S4210201231","display_name":"Socio-Environmental Systems Modeling","issn_l":"2663-3027","issn":["2663-3027"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 1061-8600","raw_type":"Article/Letter to editor"},"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4389381589.pdf"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W15387904","https://openalex.org/W1495663238","https://openalex.org/W1726806267","https://openalex.org/W1925749693","https://openalex.org/W1983772910","https://openalex.org/W1984407408","https://openalex.org/W1992535794","https://openalex.org/W1994427494","https://openalex.org/W2003030192","https://openalex.org/W2010406326","https://openalex.org/W2011263800","https://openalex.org/W2021556180","https://openalex.org/W2022677568","https://openalex.org/W2038816913","https://openalex.org/W2041769197","https://openalex.org/W2070609300","https://openalex.org/W2120699115","https://openalex.org/W2125156589","https://openalex.org/W2130561717","https://openalex.org/W2132555912","https://openalex.org/W2150002853","https://openalex.org/W2156489193","https://openalex.org/W2159585030","https://openalex.org/W2163702333","https://openalex.org/W2163707651","https://openalex.org/W2165009258","https://openalex.org/W2168175751","https://openalex.org/W2181222843","https://openalex.org/W2188491534","https://openalex.org/W2262834670","https://openalex.org/W2281440802","https://openalex.org/W2312839476","https://openalex.org/W2321874741","https://openalex.org/W2596585349","https://openalex.org/W2763592460","https://openalex.org/W2942708618","https://openalex.org/W2962898193","https://openalex.org/W2990084829","https://openalex.org/W3002437691","https://openalex.org/W3011726037","https://openalex.org/W3020160740","https://openalex.org/W3024958715","https://openalex.org/W3087200347","https://openalex.org/W3100089080","https://openalex.org/W3138063426","https://openalex.org/W3157804849","https://openalex.org/W4232023503","https://openalex.org/W4237438296","https://openalex.org/W4312512934","https://openalex.org/W4320341267","https://openalex.org/W4385472437","https://openalex.org/W4388323202","https://openalex.org/W4399579486","https://openalex.org/W6679405635"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4254184784","https://openalex.org/W1502836838","https://openalex.org/W2351412012","https://openalex.org/W4385681970","https://openalex.org/W3141866558","https://openalex.org/W2066826592","https://openalex.org/W1967916041","https://openalex.org/W2109986081","https://openalex.org/W1000855058"],"abstract_inverted_index":{"This":[0],"article":[1,198],"proposes":[2],"a":[3,15,53,62,115,154],"graphical":[4,55,92],"model":[5,16,56,98,145,160],"that":[6,64,88],"handles":[7],"mixed-type,":[8],"multi-group":[9],"data.":[10],"The":[11,143],"motivation":[12],"for":[13,118,196],"such":[14],"originates":[17],"from":[18],"real-world":[19,75],"observational":[20,76],"data,":[21,141,168],"which":[22,94],"often":[23],"contain":[24],"groups":[25],"of":[26,80,91,173],"samples":[27],"obtained":[28],"under":[29],"heterogeneous":[30],"conditions":[31],"in":[32,38,40,61,153,177],"space":[33],"and":[34,51,131],"time,":[35],"potentially":[36],"resulting":[37],"differences":[39],"network":[41,63],"structure":[42],"among":[43],"groups.":[44],"Therefore,":[45],"the":[46,69,85,97,104,122,134,158,170,174,186],"iid":[47],"assumption":[48,87],"is":[49,78,89,161],"unrealistic,":[50],"fitting":[52,114],"single":[54],"on":[57,149,163,192],"all":[58],"data":[59,77,136],"results":[60],"does":[65],"not":[66],"accurately":[67],"represent":[68],"between":[70],"group":[71,124],"differences.":[72],"In":[73],"addition,":[74],"typically":[79],"mixed":[81],"discrete-and-continuous":[82],"type,":[83],"violating":[84],"Gaussian":[86,140],"typical":[90],"models,":[93],"leads":[95],"to":[96,101,126],"being":[99],"unable":[100],"adequately":[102],"recover":[103],"underlying":[105],"graph":[106,117],"structure.":[107],"Both":[108],"these":[109],"problems":[110],"are":[111,199],"solved":[112],"by":[113,132],"different":[116],"each":[119],"group,":[120],"applying":[121],"fused":[123],"penalty":[125],"fuse":[127],"similar":[128],"graphs":[129],"together":[130],"treating":[133],"observed":[135],"as":[137],"transformed":[138],"latent":[139],"respectively.":[142],"proposed":[144,159,175,187],"outperforms":[146],"related":[147],"models":[148],"learning":[150],"partial":[151],"correlations":[152],"simulation":[155],"study.":[156],"Finally,":[157],"applied":[162],"real":[164],"on-farm":[165],"maize":[166],"yield":[167],"showcasing":[169],"added":[171],"value":[172],"method":[176],"generating":[178],"new":[179],"production-ecological":[180],"hypotheses.":[181],"An":[182],"R":[183],"package":[184],"containing":[185],"methodology":[188],"can":[189],"be":[190],"found":[191],"https://CRAN.R-project.org/package=heteromixgm.":[193],"Supplementary":[194],"materials":[195],"this":[197],"available":[200],"online.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
