{"id":"https://openalex.org/W2516623979","doi":"https://doi.org/10.1002/wics.1398","title":"A review of multivariate distributions for count data derived from the Poisson distribution","display_name":"A review of multivariate distributions for count data derived from the Poisson distribution","publication_year":2017,"publication_date":"2017-03-28","ids":{"openalex":"https://openalex.org/W2516623979","doi":"https://doi.org/10.1002/wics.1398","mag":"2516623979","pmid":"https://pubmed.ncbi.nlm.nih.gov/28983398","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/5624559"},"language":"en","primary_location":{"id":"doi:10.1002/wics.1398","doi":"https://doi.org/10.1002/wics.1398","is_oa":false,"landing_page_url":"https://doi.org/10.1002/wics.1398","pdf_url":null,"source":{"id":"https://openalex.org/S206848516","display_name":"Wiley Interdisciplinary Reviews Computational Statistics","issn_l":"1939-0068","issn":["1939-0068","1939-5108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","dongbi-d","jufo-1","norway-1","poland-100","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"WIREs Computational Statistics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://europepmc.org/pmc/articles/PMC5624559","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074209565","display_name":"David I. Inouye","orcid":"https://orcid.org/0000-0003-4493-3358","observed_orcids":["https://orcid.org/0000-0003-4493-3358"]},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David I. Inouye","raw_affiliation_strings":["Department of Computer Science The University of Texas at Austin Austin TX USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science The University of Texas at Austin Austin TX USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086698569","display_name":"Eunho Yang","orcid":"https://orcid.org/0000-0003-2188-0169","observed_orcids":["https://orcid.org/0000-0003-2188-0169"]},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eunho Yang","raw_affiliation_strings":["School of Computing , Korea Advanced Institute of Science and Technology , Daejeon , Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing , Korea Advanced Institute of Science and Technology , Daejeon , Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048412925","display_name":"Genevera I. Allen","orcid":"https://orcid.org/0000-0002-6851-4310","observed_orcids":["https://orcid.org/0000-0002-6851-4310"]},"institutions":[{"id":"https://openalex.org/I181547552","display_name":"Baylor College of Medicine","ror":"https://ror.org/02pttbw34","country_code":"US","type":"education","lineage":["https://openalex.org/I181547552","https://openalex.org/I2801539370"]},{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Genevera I. Allen","raw_affiliation_strings":["Department of Pediatrics\u2010Neurology Baylor College of Medicine Houston TX USA","Department of Statistics Rice University Houston TX USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Pediatrics\u2010Neurology Baylor College of Medicine Houston TX USA","institution_ids":["https://openalex.org/I181547552"]},{"raw_affiliation_string":"Department of Statistics Rice University Houston TX USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064427875","display_name":"Pradeep Ravikumar","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pradeep Ravikumar","raw_affiliation_strings":["School of Computer Science Carnegie Mellon University Pittsburgh PA USA","[Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science Carnegie Mellon University Pittsburgh PA USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"[Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA]","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5064427875"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":{"value":3460,"currency":"USD","value_usd":3460},"apc_paid":null,"fwci":5.7437,"has_fulltext":true,"cited_by_count":142,"citation_normalized_percentile":{"value":0.97717891,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"9","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.4878000020980835,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.4878000020980835,"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":0.40380001068115234,"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/T13500","display_name":"Probability and Statistical Research","score":0.04190000146627426,"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/multivariate-poisson-distribution","display_name":"multivariate Poisson distribution","score":0.8980000019073486},{"id":"https://openalex.org/keywords/count-data","display_name":"count data","score":0.972000002861023},{"id":"https://openalex.org/keywords/traffic-accident-data","display_name":"traffic accident data","score":0.7670000195503235},{"id":"https://openalex.org/keywords/next-generation-sequencing-data","display_name":"next-generation sequencing data","score":0.8679999709129333},{"id":"https://openalex.org/keywords/textual-data","display_name":"text data","score":0.8730000257492065},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.7519999742507935}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7511318922042847},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.7407009601593018},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.7392410039901733},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.7335670590400696},{"id":"https://openalex.org/C84181548","wikidata":"https://www.wikidata.org/wiki/Q7893853","display_name":"Univariate distribution","level":3,"score":0.5686258673667908},{"id":"https://openalex.org/C88721176","wikidata":"https://www.wikidata.org/wiki/Q966010","display_name":"Zero-inflated model","level":4,"score":0.5668108463287354},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5007607936859131},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46988773345947266},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.43345868587493896},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.4239156246185303},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4221286475658417},{"id":"https://openalex.org/C73269764","wikidata":"https://www.wikidata.org/wiki/Q954529","display_name":"Poisson regression","level":3,"score":0.4042598307132721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19207823276519775},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.07597193121910095},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1002/wics.1398","doi":"https://doi.org/10.1002/wics.1398","is_oa":false,"landing_page_url":"https://doi.org/10.1002/wics.1398","pdf_url":null,"source":{"id":"https://openalex.org/S206848516","display_name":"Wiley Interdisciplinary Reviews Computational Statistics","issn_l":"1939-0068","issn":["1939-0068","1939-5108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","dongbi-d","jufo-1","norway-1","poland-100","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"WIREs Computational Statistics","raw_type":"journal-article"},{"id":"pmid:28983398","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28983398","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Wiley interdisciplinary reviews. Computational statistics","raw_type":"Journal Article"},{"id":"pmh:oai:europepmc.org:4846838","doi":null,"is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC5624559","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:5624559","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5624559","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Wiley Interdiscip Rev Comput Stat","raw_type":"Text"},{"id":"pmh:oai:arXiv.org:1609.00066","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1609.00066","pdf_url":"https://arxiv.org/pdf/1609.00066","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,"listed_in":[],"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":"mag:2516623979","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1609.00066","pdf_url":null,"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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1609.00066","doi":"https://doi.org/10.48550/arxiv.1609.00066","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1609.00066","pdf_url":null,"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,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:europepmc.org:4846838","doi":null,"is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC5624559","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1882923911","display_name":"Collaborative Research:  Statistical Methods for Integrated Analysis of High-Throughput Biomedical Data","funder_award_id":"1264033","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G234936229","display_name":null,"funder_award_id":"W911NF-12-1-0390","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3103054859","display_name":null,"funder_award_id":"1554821","funder_id":"https://openalex.org/F4320337380","funder_display_name":"Division of Mathematical Sciences"},{"id":"https://openalex.org/G3146162964","display_name":null,"funder_award_id":"DMS-1554821","funder_id":"https://openalex.org/F4320337380","funder_display_name":"Division of Mathematical Sciences"},{"id":"https://openalex.org/G4319621678","display_name":"BIGDATA: F: DKA: Collaborative Research: High-Dimensional Statistical Machine Learning for Spatio-Temporal Climate Data","funder_award_id":"1447574","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4865686992","display_name":"CAREER: A New Neat Framework for Statistical Machine Learning","funder_award_id":"1149803","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6713332814","display_name":"Collaborative Research:  Statistical Methods for Integrated Analysis of High-Throughput Biomedical Data","funder_award_id":"1264058","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6806883083","display_name":"CAREER: New Techniques for Statistical Learning and Multivariate Analysis","funder_award_id":"1554821","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G7631466","display_name":"Mathematical Chemical Imaging with Uncertainty Quantification  ","funder_award_id":"R01GM117594","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G8170182421","display_name":null,"funder_award_id":"W911NF-12-1-0390","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G844935001","display_name":null,"funder_award_id":"W911NF-12-1- 0390","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8667631518","display_name":null,"funder_award_id":"1264058","funder_id":"https://openalex.org/F4320337380","funder_display_name":"Division of Mathematical Sciences"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"},{"id":"https://openalex.org/F4320337380","display_name":"Division of Mathematical Sciences","ror":"https://ror.org/051fftw81"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2516623979.pdf","grobid_xml":"https://content.openalex.org/works/W2516623979.grobid-xml"},"referenced_works_count":89,"referenced_works":["https://openalex.org/W114565888","https://openalex.org/W156493003","https://openalex.org/W1197916086","https://openalex.org/W1513873506","https://openalex.org/W1590120741","https://openalex.org/W1857611597","https://openalex.org/W1891298814","https://openalex.org/W1966296137","https://openalex.org/W1978812719","https://openalex.org/W1980049607","https://openalex.org/W1980345828","https://openalex.org/W1984262781","https://openalex.org/W1985435398","https://openalex.org/W1991856328","https://openalex.org/W1992105816","https://openalex.org/W1993332813","https://openalex.org/W1994403842","https://openalex.org/W1995671377","https://openalex.org/W2001249527","https://openalex.org/W2001534132","https://openalex.org/W2002870907","https://openalex.org/W2003602339","https://openalex.org/W2004081230","https://openalex.org/W2008909284","https://openalex.org/W2010824638","https://openalex.org/W2016332760","https://openalex.org/W2020708932","https://openalex.org/W2026924877","https://openalex.org/W2027254536","https://openalex.org/W2027467831","https://openalex.org/W2028233321","https://openalex.org/W2033612661","https://openalex.org/W2046129503","https://openalex.org/W2046299501","https://openalex.org/W2054818806","https://openalex.org/W2055354074","https://openalex.org/W2056367065","https://openalex.org/W2062630838","https://openalex.org/W2071498445","https://openalex.org/W2074130726","https://openalex.org/W2076053335","https://openalex.org/W2087067179","https://openalex.org/W2087811140","https://openalex.org/W2090499758","https://openalex.org/W2100398996","https://openalex.org/W2114220616","https://openalex.org/W2119755537","https://openalex.org/W2120340025","https://openalex.org/W2122066903","https://openalex.org/W2124953793","https://openalex.org/W2127083809","https://openalex.org/W2127958806","https://openalex.org/W2128576231","https://openalex.org/W2128990575","https://openalex.org/W2129795780","https://openalex.org/W2130561717","https://openalex.org/W2131242330","https://openalex.org/W2150002853","https://openalex.org/W2151738960","https://openalex.org/W2154290889","https://openalex.org/W2154496417","https://openalex.org/W2156952342","https://openalex.org/W2157894547","https://openalex.org/W2158636039","https://openalex.org/W2169082384","https://openalex.org/W2170290763","https://openalex.org/W2183926210","https://openalex.org/W2196807682","https://openalex.org/W2211637485","https://openalex.org/W2212660284","https://openalex.org/W2245213139","https://openalex.org/W2289278205","https://openalex.org/W2296146392","https://openalex.org/W2329116892","https://openalex.org/W2396000217","https://openalex.org/W2409064471","https://openalex.org/W2417187449","https://openalex.org/W2423602597","https://openalex.org/W2529593327","https://openalex.org/W2530516905","https://openalex.org/W2789167075","https://openalex.org/W2907233437","https://openalex.org/W2950724390","https://openalex.org/W2952350108","https://openalex.org/W3042188089","https://openalex.org/W4205256993","https://openalex.org/W4285719527","https://openalex.org/W4293052541","https://openalex.org/W4388323202"],"related_works":["https://openalex.org/W4251506318","https://openalex.org/W1155720097","https://openalex.org/W4408704162","https://openalex.org/W4322722354","https://openalex.org/W4244359126","https://openalex.org/W7020956284","https://openalex.org/W2055354074","https://openalex.org/W2042035600","https://openalex.org/W2007593879","https://openalex.org/W4399846060"],"abstract_inverted_index":{"The":[0],"Poisson":[1,18,94],"distribution":[2,19,87,176],"has":[3],"been":[4,25],"widely":[5],"studied":[6],"and":[7,39,47,96,117,125,157,169],"used":[8],"for":[9,42,51],"modeling":[10],"univariate":[11,67],"count-valued":[12,32],"data.":[13,59,159],"Multivariate":[14],"generalizations":[15],"of":[16,91,111,114,123,171,174],"the":[17,49,66,78,85,99,105,109,119,166,181,192],"that":[20,54,140,177],"permit":[21],"dependencies,":[22,46],"however,":[23],"have":[24,141],"far":[26],"less":[27],"popular.":[28],"Yet,":[29],"real-world":[30,138],"high-dimensional":[31],"data":[33,143],"found":[34],"in":[35,121,191],"word":[36],"counts,":[37],"genomics,":[38],"crime":[40],"statistics,":[41],"example,":[43],"exhibit":[44],"rich":[45],"motivate":[48],"need":[50],"multivariate":[52,62,93,175],"distributions":[53,63,80,101],"can":[55],"appropriately":[56],"model":[57],"this":[58],"We":[60,107],"review":[61],"derived":[64,103,179],"from":[65,104,133,145,180],"Poisson,":[68,82],"categorizing":[69],"these":[70,115],"models":[71,120,132],"into":[72],"three":[73,137],"main":[74],"classes:":[75],"1)":[76],"where":[77,84,98],"marginal":[79],"are":[81,102],"2)":[83],"joint":[86],"is":[88],"a":[89],"mixture":[90],"independent":[92],"distributions,":[95],"3)":[97],"node-conditional":[100],"Poisson.":[106,182],"discuss":[108],"development":[110],"multiple":[112,131],"instances":[113],"classes":[116],"compare":[118,130],"terms":[122],"interpretability":[124],"theory.":[126],"Then,":[127],"we":[128,184],"empirically":[129],"each":[134,172],"class":[135,173],"on":[136],"datasets":[139],"varying":[142],"characteristics":[144],"different":[146],"domains,":[147],"namely":[148],"traffic":[149],"accident":[150],"data,":[151,156],"biological":[152],"next":[153],"generation":[154],"sequencing":[155],"text":[158],"These":[160],"empirical":[161],"experiments":[162],"develop":[163],"intuition":[164],"about":[165],"comparative":[167],"advantages":[168],"disadvantages":[170],"was":[178],"Finally,":[183],"suggest":[185],"new":[186],"research":[187],"directions":[188],"as":[189],"explored":[190],"subsequent":[193],"discussion":[194],"section.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":16},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":9}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2016-09-16T00:00:00"}