{"id":"https://openalex.org/W3041340310","doi":"https://doi.org/10.1007/s00180-020-01013-y","title":"Dirichlet process mixtures under affine transformations of the data","display_name":"Dirichlet process mixtures under affine transformations of the data","publication_year":2020,"publication_date":"2020-07-12","ids":{"openalex":"https://openalex.org/W3041340310","doi":"https://doi.org/10.1007/s00180-020-01013-y","mag":"3041340310"},"language":"en","primary_location":{"id":"doi:10.1007/s00180-020-01013-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-020-01013-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-020-01013-y.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00180-020-01013-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Julyan Arbel","orcid":null},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210101348","display_name":"Centre Inria de l'Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/00n8d6z93","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210101348"]},{"id":"https://openalex.org/I4210149092","display_name":"Laboratoire Jean Kuntzmann","ror":"https://ror.org/04ett5b41","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210149092","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Julyan Arbel","raw_affiliation_strings":["Inria, CNRS, Grenoble INP, LJK, Universit\u00e9 Grenoble Alpes, Grenoble, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inria, CNRS, Grenoble INP, LJK, Universit\u00e9 Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I899635006","https://openalex.org/I4210149092","https://openalex.org/I4210101348","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Riccardo Corradin","orcid":null},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Riccardo Corradin","raw_affiliation_strings":["Department of Economics, Management and Statistics, University of Milano Bicocca, Milan, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Economics, Management and Statistics, University of Milano Bicocca, Milan, Italy","institution_ids":["https://openalex.org/I66752286"]}]},{"author_position":"last","author":{"id":null,"display_name":"Bernardo Nipoti","orcid":"https://orcid.org/0000-0003-1138-951X"},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Bernardo Nipoti","raw_affiliation_strings":["Department of Economics, Management and Statistics, University of Milano Bicocca, Milan, Italy"],"raw_orcid":"https://orcid.org/0000-0003-1138-951X","affiliations":[{"raw_affiliation_string":"Department of Economics, Management and Statistics, University of Milano Bicocca, Milan, Italy","institution_ids":["https://openalex.org/I66752286"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210101348","https://openalex.org/I4210149092","https://openalex.org/I899635006"],"apc_list":{"value":2490,"currency":"EUR","value_usd":3090},"apc_paid":{"value":2490,"currency":"EUR","value_usd":3090},"fwci":0.1359,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54924138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"36","issue":"1","first_page":"577","last_page":"601"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9520000219345093,"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":0.9520000219345093,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.026599999517202377,"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/T12261","display_name":"Statistical Mechanics and Entropy","score":0.0035000001080334187,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.7121999859809875},{"id":"https://openalex.org/keywords/dirichlet-process","display_name":"Dirichlet process","score":0.6280999779701233},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5479999780654907},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5468999743461609},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4999000132083893},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.38920000195503235},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.3813000023365021},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.38109999895095825}],"concepts":[{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.7121999859809875},{"id":"https://openalex.org/C2781280628","wikidata":"https://www.wikidata.org/wiki/Q5280766","display_name":"Dirichlet process","level":3,"score":0.6280999779701233},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5479999780654907},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5468999743461609},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5023999810218811},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4999000132083893},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4607999920845032},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45509999990463257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4124999940395355},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.38920000195503235},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.3813000023365021},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.38109999895095825},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C150670458","wikidata":"https://www.wikidata.org/wiki/Q4272815","display_name":"Data transformation","level":3,"score":0.32440000772476196},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.29280000925064087},{"id":"https://openalex.org/C207221997","wikidata":"https://www.wikidata.org/wiki/Q938614","display_name":"Affine combination","level":3,"score":0.29269999265670776},{"id":"https://openalex.org/C17231256","wikidata":"https://www.wikidata.org/wiki/Q5156540","display_name":"Completeness (order theory)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28220000863075256},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2800999879837036},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C141318989","wikidata":"https://www.wikidata.org/wiki/Q5753066","display_name":"Hierarchical Dirichlet process","level":4,"score":0.2648000121116638},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2574000060558319}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/s00180-020-01013-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-020-01013-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-020-01013-y.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1809.02463","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.02463","pdf_url":"https://arxiv.org/pdf/1809.02463","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"pmh:oai:HAL:hal-01950652v2","is_oa":true,"landing_page_url":"https://hal.science/hal-01950652","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"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":"http://link.springer.com/article/10.1007/s00180-020-01013-y","raw_type":"Journal articles"},{"id":"pmh:oai:RePEc:spr:compst:v:36:y:2021:i:1:d:10.1007_s00180-020-01013-y","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s00180-020-01013-y","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:10281/295898","is_oa":true,"landing_page_url":"http://hdl.handle.net/10281/295898","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s00180-020-01013-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-020-01013-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-020-01013-y.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3041340310.pdf","grobid_xml":"https://content.openalex.org/works/W3041340310.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1778178912","https://openalex.org/W2033828039","https://openalex.org/W2039628234","https://openalex.org/W2050079540","https://openalex.org/W2057457426","https://openalex.org/W2065392216","https://openalex.org/W2069429561","https://openalex.org/W2078783892","https://openalex.org/W2081331602","https://openalex.org/W2091797506","https://openalex.org/W2110612578","https://openalex.org/W2110965572","https://openalex.org/W2124044492","https://openalex.org/W2125474556","https://openalex.org/W2136999619","https://openalex.org/W2150473224","https://openalex.org/W2151383118","https://openalex.org/W2161740145","https://openalex.org/W2169107869","https://openalex.org/W2414843940","https://openalex.org/W2475792925","https://openalex.org/W2552872240","https://openalex.org/W2893855365","https://openalex.org/W2949624507","https://openalex.org/W2964016406","https://openalex.org/W3047091944","https://openalex.org/W4254499902","https://openalex.org/W4308951891"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Location-scale":[1],"Dirichlet":[2],"process":[3,104],"mixtures":[4],"of":[5,24,38,44,67,80,88,130,135,138,143],"Gaussians":[6],"(DPM-G)":[7],"have":[8],"proved":[9],"extremely":[10],"useful":[11],"in":[12,20,31,140],"dealing":[13],"with":[14,75],"density":[15,56],"estimation":[16,57],"and":[17,58,94,125],"clustering":[18],"problems":[19],"a":[21,47,63,114],"wide":[22],"range":[23],"domains.":[25],"Motivated":[26],"by":[27,120,127],"an":[28,121,131],"astronomical":[29,132],"application,":[30],"this":[32],"work":[33],"we":[34,61,84],"address":[35],"the":[36,45,68,81,86,100,128,141,144],"robustness":[37,90],"DPM-G":[39,110],"models":[40,111],"to":[41,77,107],"affine":[42,78],"transformations":[43,79],"data,":[46],"natural":[48],"requirement":[49],"for":[50,55],"any":[51],"sensible":[52],"statistical":[53],"method":[54],"clustering.":[59],"First,":[60],"devise":[62],"coherent":[64],"prior":[65],"specification":[66],"model":[69],"which":[70],"makes":[71],"posterior":[72],"inference":[73],"invariant":[74],"respect":[76],"data.":[82],"Second,":[83],"formalise":[85],"notion":[87],"asymptotic":[89],"under":[91],"data":[92,102],"transformation":[93],"show":[95],"that":[96,109],"mild":[97],"assumptions":[98],"on":[99],"true":[101],"generating":[103],"are":[105],"sufficient":[106],"ensure":[108],"feature":[112],"such":[113],"property.":[115],"Our":[116],"investigation":[117],"is":[118],"supported":[119],"extensive":[122],"simulation":[123],"study":[124],"illustrated":[126],"analysis":[129],"dataset":[133],"consisting":[134],"physical":[136],"measurements":[137],"stars":[139],"field":[142],"globular":[145],"cluster":[146],"NGC":[147],"2419.":[148]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-07-16T00:00:00"}