{"id":"https://openalex.org/W4214576475","doi":"https://doi.org/10.1007/s11634-021-00488-x","title":"Gaussian mixture model with an extended ultrametric covariance structure","display_name":"Gaussian mixture model with an extended ultrametric covariance structure","publication_year":2022,"publication_date":"2022-02-25","ids":{"openalex":"https://openalex.org/W4214576475","doi":"https://doi.org/10.1007/s11634-021-00488-x"},"language":"en","primary_location":{"id":"doi:10.1007/s11634-021-00488-x","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s11634-021-00488-x","pdf_url":null,"source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Data Analysis and Classification","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pure.eur.nl/en/publications/c49ef322-21b4-4cf3-8244-c08daa6b63ab","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015179218","display_name":"Carlo Cavicchia","orcid":"https://orcid.org/0000-0003-1816-3521"},"institutions":[{"id":"https://openalex.org/I913958620","display_name":"Erasmus University Rotterdam","ror":"https://ror.org/057w15z03","country_code":"NL","type":"education","lineage":["https://openalex.org/I913958620"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Carlo Cavicchia","raw_affiliation_strings":["Econometric Institute, Erasmus University Rotterdam, Rotterdam, Netherlands"],"raw_orcid":"https://orcid.org/0000-0003-1816-3521","affiliations":[{"raw_affiliation_string":"Econometric Institute, Erasmus University Rotterdam, Rotterdam, Netherlands","institution_ids":["https://openalex.org/I913958620"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027243034","display_name":"Maurizio Vichi","orcid":"https://orcid.org/0000-0002-3876-444X"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Maurizio Vichi","raw_affiliation_strings":["Department of Statistical Sciences, University of Rome La Sapienza, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-3876-444X","affiliations":[{"raw_affiliation_string":"Department of Statistical Sciences, University of Rome La Sapienza, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086164987","display_name":"Giorgia Zaccaria","orcid":"https://orcid.org/0000-0001-9119-9104"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Giorgia Zaccaria","raw_affiliation_strings":["Department of Statistical Sciences, University of Rome La Sapienza, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0001-9119-9104","affiliations":[{"raw_affiliation_string":"Department of Statistical Sciences, University of Rome La Sapienza, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015179218","https://openalex.org/A5027243034","https://openalex.org/A5086164987"],"corresponding_institution_ids":["https://openalex.org/I861853513","https://openalex.org/I913958620"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":null,"fwci":1.572,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.85134082,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"16","issue":"2","first_page":"399","last_page":"427"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9995999932289124,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9957000017166138,"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/T11106","display_name":"Data Management and Algorithms","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ultrametric-space","display_name":"Ultrametric space","score":0.8104063868522644},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.7975815534591675},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.7531846761703491},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.6794464588165283},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5789383053779602},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.5770708918571472},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5770054459571838},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5544052124023438},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.47868090867996216},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.4771706163883209},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37523776292800903},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3494685888290405},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.318331778049469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2982184886932373},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.20591384172439575}],"concepts":[{"id":"https://openalex.org/C61067352","wikidata":"https://www.wikidata.org/wiki/Q1897429","display_name":"Ultrametric space","level":3,"score":0.8104063868522644},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.7975815534591675},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7531846761703491},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.6794464588165283},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5789383053779602},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.5770708918571472},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5770054459571838},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5544052124023438},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.47868090867996216},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.4771706163883209},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37523776292800903},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3494685888290405},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.318331778049469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2982184886932373},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.20591384172439575},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1007/s11634-021-00488-x","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s11634-021-00488-x","pdf_url":null,"source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Data Analysis and Classification","raw_type":"journal-article"},{"id":"pmh:oai:pure.eur.nl:openaire/c49ef322-21b4-4cf3-8244-c08daa6b63ab","is_oa":true,"landing_page_url":"https://pure.eur.nl/en/publications/c49ef322-21b4-4cf3-8244-c08daa6b63ab","pdf_url":null,"source":{"id":"https://openalex.org/S4306401266","display_name":"EUR Research Repository (Erasmus University Rotterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I913958620","host_organization_name":"Erasmus University Rotterdam","host_organization_lineage":["https://openalex.org/I913958620"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cavicchia, C, Vichi, M & Zaccaria, G 2022, 'Gaussian mixture model with an extended ultrametric covariance structure', Advances in Data Analysis and Classification, vol. 16, no. 2, pp. 399-427. https://doi.org/10.1007/s11634-021-00488-x","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:RePEc:spr:advdac:v:16:y:2022:i:2:d:10.1007_s11634-021-00488-x","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s11634-021-00488-x","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"},{"id":"pmh:oai:boa.unimib.it:10281/394314","is_oa":false,"landing_page_url":"http://hdl.handle.net/10281/394314","pdf_url":null,"source":{"id":"https://openalex.org/S4306401259","display_name":"BOA (University of Milano-Bicocca)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66752286","host_organization_name":"University of Milano-Bicocca","host_organization_lineage":["https://openalex.org/I66752286"],"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":"info:eu-repo/semantics/article"},{"id":"pmh:oai:iris.uniroma1.it:11573/1615269.2","is_oa":false,"landing_page_url":"http://hdl.handle.net/11573/1615269","pdf_url":null,"source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:pure.eur.nl:publications/c49ef322-21b4-4cf3-8244-c08daa6b63ab","is_oa":true,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85125274026&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306401266","display_name":"EUR Research Repository (Erasmus University Rotterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I913958620","host_organization_name":"Erasmus University Rotterdam","host_organization_lineage":["https://openalex.org/I913958620"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cavicchia , C , Vichi , M & Zaccaria , G 2022 , ' Gaussian mixture model with an extended ultrametric covariance structure ' , Advances in Data Analysis and Classification , vol. 16 , no. 2 , pp. 399-427 . https://doi.org/10.1007/s11634-021-00488-x","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:pure.eur.nl:openaire/c49ef322-21b4-4cf3-8244-c08daa6b63ab","is_oa":true,"landing_page_url":"https://pure.eur.nl/en/publications/c49ef322-21b4-4cf3-8244-c08daa6b63ab","pdf_url":null,"source":{"id":"https://openalex.org/S4306401266","display_name":"EUR Research Repository (Erasmus University Rotterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I913958620","host_organization_name":"Erasmus University Rotterdam","host_organization_lineage":["https://openalex.org/I913958620"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cavicchia, C, Vichi, M & Zaccaria, G 2022, 'Gaussian mixture model with an extended ultrametric covariance structure', Advances in Data Analysis and Classification, vol. 16, no. 2, pp. 399-427. https://doi.org/10.1007/s11634-021-00488-x","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W134695378","https://openalex.org/W195598234","https://openalex.org/W616310803","https://openalex.org/W1572240091","https://openalex.org/W1974164873","https://openalex.org/W1975120776","https://openalex.org/W1978305832","https://openalex.org/W1981367467","https://openalex.org/W1981472895","https://openalex.org/W1991278573","https://openalex.org/W2001814254","https://openalex.org/W2002053479","https://openalex.org/W2002475445","https://openalex.org/W2004833679","https://openalex.org/W2007752888","https://openalex.org/W2011832962","https://openalex.org/W2016728733","https://openalex.org/W2021137021","https://openalex.org/W2035392043","https://openalex.org/W2038269730","https://openalex.org/W2040898759","https://openalex.org/W2047555270","https://openalex.org/W2049633694","https://openalex.org/W2055764977","https://openalex.org/W2065985521","https://openalex.org/W2067713126","https://openalex.org/W2069721249","https://openalex.org/W2075092851","https://openalex.org/W2081975242","https://openalex.org/W2082398846","https://openalex.org/W2082503527","https://openalex.org/W2094595856","https://openalex.org/W2095373758","https://openalex.org/W2099465598","https://openalex.org/W2109639789","https://openalex.org/W2109820980","https://openalex.org/W2125027820","https://openalex.org/W2133487567","https://openalex.org/W2134507164","https://openalex.org/W2146610201","https://openalex.org/W2152904625","https://openalex.org/W2153988305","https://openalex.org/W2168175751","https://openalex.org/W2168980979","https://openalex.org/W2169694221","https://openalex.org/W2173611154","https://openalex.org/W2313795362","https://openalex.org/W2488678869","https://openalex.org/W2496585406","https://openalex.org/W2498094064","https://openalex.org/W2519132385","https://openalex.org/W2524681876","https://openalex.org/W2726396617","https://openalex.org/W2756395418","https://openalex.org/W2794549094","https://openalex.org/W2802627035","https://openalex.org/W2977466517","https://openalex.org/W3016393877","https://openalex.org/W3032586657","https://openalex.org/W3102266858","https://openalex.org/W3194566720","https://openalex.org/W4235169531","https://openalex.org/W4293235520","https://openalex.org/W6776396770"],"related_works":["https://openalex.org/W4287598215","https://openalex.org/W2121462994","https://openalex.org/W3099216502","https://openalex.org/W3019466575","https://openalex.org/W1580978445","https://openalex.org/W3134381438","https://openalex.org/W2801379595","https://openalex.org/W2064347530","https://openalex.org/W1555936174","https://openalex.org/W2001630616"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}