{"id":"https://openalex.org/W4406049757","doi":"https://doi.org/10.1080/10618600.2024.2446357","title":"Bayesian Partial Reduced-Rank Regression","display_name":"Bayesian Partial Reduced-Rank Regression","publication_year":2025,"publication_date":"2025-01-03","ids":{"openalex":"https://openalex.org/W4406049757","doi":"https://doi.org/10.1080/10618600.2024.2446357"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2446357","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2446357","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2446357?download=true","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":"bronze","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2446357?download=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092094984","display_name":"Maria F. Pintado","orcid":null},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Maria F. Pintado","raw_affiliation_strings":["School of Mathematical Sciences, Queen Mary University of London","Queen Mary University of London, United Kingdom"],"raw_orcid":"https://orcid.org/0009-0008-3115-6792","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Queen Mary University of London","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"Queen Mary University of London, United Kingdom","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058826854","display_name":"Matteo Iacopini","orcid":"https://orcid.org/0000-0002-3551-4891"},"institutions":[{"id":"https://openalex.org/I56441308","display_name":"Libera Universit\u00e0 Internazionale degli Studi Sociali Guido Carli","ror":"https://ror.org/01q8b6q23","country_code":"IT","type":"education","lineage":["https://openalex.org/I56441308"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Matteo Iacopini","raw_affiliation_strings":["Department of Economics and Finance, LUISS University","LUISS University, Italy"],"raw_orcid":"https://orcid.org/0000-0002-3551-4891","affiliations":[{"raw_affiliation_string":"Department of Economics and Finance, LUISS University","institution_ids":["https://openalex.org/I56441308"]},{"raw_affiliation_string":"LUISS University, Italy","institution_ids":["https://openalex.org/I56441308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077185947","display_name":"Luca Rossini","orcid":"https://orcid.org/0000-0002-7302-4543"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]},{"id":"https://openalex.org/I4210128773","display_name":"Fondazione Eni Enrico Mattei","ror":"https://ror.org/03bvx5w91","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210128773"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Rossini","raw_affiliation_strings":["Department of Economics, Management and Quantitative Methods, University of Milan","Fondazione Eni Enrico Mattei","University of Milan, Italy, and Fondazione Eni Enrico Mattei, Italy"],"raw_orcid":"https://orcid.org/0000-0002-7302-4543","affiliations":[{"raw_affiliation_string":"Department of Economics, Management and Quantitative Methods, University of Milan","institution_ids":["https://openalex.org/I189158943"]},{"raw_affiliation_string":"Fondazione Eni Enrico Mattei","institution_ids":["https://openalex.org/I4210128773"]},{"raw_affiliation_string":"University of Milan, Italy, and Fondazione Eni Enrico Mattei, Italy","institution_ids":["https://openalex.org/I4210128773","https://openalex.org/I189158943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072957829","display_name":"Alexander Y. Shestopaloff","orcid":"https://orcid.org/0000-0003-2228-5708"},"institutions":[{"id":"https://openalex.org/I130438778","display_name":"Memorial University of Newfoundland","ror":"https://ror.org/04haebc03","country_code":"CA","type":"education","lineage":["https://openalex.org/I130438778"]},{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["CA","GB"],"is_corresponding":false,"raw_author_name":"Alexander Y. Shestopaloff","raw_affiliation_strings":["Department of Mathematics and Statistics, Memorial University of Newfoundland","School of Mathematical Sciences, Queen Mary University of London","Queen Mary University of London, United Kingdom, and Memorial University of Newfoundland, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Memorial University of Newfoundland","institution_ids":["https://openalex.org/I130438778"]},{"raw_affiliation_string":"School of Mathematical Sciences, Queen Mary University of London","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"Queen Mary University of London, United Kingdom, and Memorial University of Newfoundland, Canada","institution_ids":["https://openalex.org/I130438778","https://openalex.org/I166337079"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5092094984"],"corresponding_institution_ids":["https://openalex.org/I166337079"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00487433,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"4","first_page":"1344","last_page":"1355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.993399977684021,"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":0.993399977684021,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9864000082015991,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.95660001039505,"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/mathematics","display_name":"Mathematics","score":0.6605997085571289},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6394784450531006},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.619418203830719},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.553728461265564},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5275599360466003},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5254156589508057},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5189911723136902},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.45706596970558167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24150705337524414},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2104954719543457},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1476086676120758}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6605997085571289},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6394784450531006},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.619418203830719},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.553728461265564},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5275599360466003},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5254156589508057},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5189911723136902},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.45706596970558167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24150705337524414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2104954719543457},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1476086676120758}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1080/10618600.2024.2446357","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2446357","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2446357?download=true","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:qmro.qmul.ac.uk:123456789/103451","is_oa":true,"landing_page_url":"https://qmro.qmul.ac.uk/xmlui/handle/123456789/103451","pdf_url":"https://qmro.qmul.ac.uk/xmlui/bitstream/123456789/103451/2/BPRR_main.pdf","source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"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":null,"raw_type":"Article"},{"id":"pmh:oai:air.unimi.it:2434/1145916","is_oa":true,"landing_page_url":"https://hdl.handle.net/2434/1145916","pdf_url":null,"source":{"id":"https://openalex.org/S4306400516","display_name":"Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I189158943","host_organization_name":"University of Milan","host_organization_lineage":["https://openalex.org/I189158943"],"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":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:iris.luiss.it:11385/245858","is_oa":false,"landing_page_url":"https://hdl.handle.net/11385/245858","pdf_url":null,"source":{"id":"https://openalex.org/S4377196446","display_name":"IRIS - Institutional Research Information System (Libera Universit\u00e0 Internazionale degli Studi Sociali Guido Carli)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56441308","host_organization_name":"Libera Universit\u00e0 Internazionale degli Studi Sociali Guido Carli","host_organization_lineage":["https://openalex.org/I56441308"],"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"}],"best_oa_location":{"id":"doi:10.1080/10618600.2024.2446357","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2446357","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2446357?download=true","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"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G4119229734","display_name":null,"funder_award_id":"2021-000007-01EXTF-00090","funder_id":"https://openalex.org/F4320321739","funder_display_name":"Consejo Nacional de Ciencia y Tecnolog\u00eda"}],"funders":[{"id":"https://openalex.org/F4320313475","display_name":"Universit\u00e0 degli Studi di Milano","ror":"https://ror.org/00wjc7c48"},{"id":"https://openalex.org/F4320321739","display_name":"Consejo Nacional de Ciencia y Tecnolog\u00eda","ror":"https://ror.org/059ex5q34"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4406049757.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1560240297","https://openalex.org/W1628017834","https://openalex.org/W1989692914","https://openalex.org/W2011471859","https://openalex.org/W2017696952","https://openalex.org/W2018304737","https://openalex.org/W2023447826","https://openalex.org/W2034133761","https://openalex.org/W2054121219","https://openalex.org/W2089763487","https://openalex.org/W2099878672","https://openalex.org/W2102650396","https://openalex.org/W2122721364","https://openalex.org/W2141366416","https://openalex.org/W2492613925","https://openalex.org/W2600746470","https://openalex.org/W2901357766","https://openalex.org/W2938232807","https://openalex.org/W2943399556","https://openalex.org/W3087940778","https://openalex.org/W3182190454","https://openalex.org/W4211177544","https://openalex.org/W4292403327","https://openalex.org/W4312095692","https://openalex.org/W4313029228","https://openalex.org/W4387741411","https://openalex.org/W6723343479"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W4391160746","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"Reduced-rank":[0],"(RR)":[1],"regression":[2,22,51],"may":[3],"be":[4,93],"interpreted":[5],"as":[6,89],"a":[7,35,46,81,133,144,152],"dimensionality":[8],"reduction":[9],"technique":[10],"able":[11],"to":[12,71,92,102,165,172,184],"reveal":[13,177,185],"complex":[14],"relationships":[15],"among":[16,30],"the":[17,31,39,55,59,72,104,111,121,156,160,167,178,181,189],"data":[18,112,176],"parsimoniously.":[19],"However,":[20],"RR":[21,49],"models":[23],"typically":[24],"overlook":[25],"any":[26],"potential":[27,179],"group":[28,77,108,168],"structure":[29,37,78],"responses":[32],"by":[33],"assuming":[34],"low-rank":[36],"on":[38,118,143,151],"coefficient":[40,60],"matrix.":[41],"To":[42],"address":[43],"this":[44,119],"limitation,":[45],"Bayesian":[47,134],"Partial":[48],"(BPRR)":[50],"is":[52,84,98,113,125],"exploited,":[53],"where":[54],"response":[56],"vector":[57],"and":[58,66,79,106,115,141,159,174],"matrix":[61],"are":[62,129],"partitioned":[63],"into":[64],"low-":[65,105],"full-rank":[67,107],"sub-groups.":[68],"As":[69],"opposed":[70],"literature,":[73],"which":[74],"assumes":[75],"known":[76],"rank,":[80],"novel":[82],"strategy":[83],"introduced":[85],"that":[86],"treats":[87],"them":[88],"unknown":[90],"parameters":[91],"estimated.":[94,126],"The":[95],"main":[96],"contribution":[97],"two-fold:":[99],"an":[100],"approach":[101],"infer":[103],"memberships":[109],"from":[110],"proposed,":[114],"then,":[116],"conditionally":[117],"allocation,":[120],"corresponding":[122],"(reduced)":[123],"rank":[124],"Both":[127],"steps":[128],"carried":[130],"out":[131],"in":[132,188],"approach,":[135],"allowing":[136],"for":[137],"full":[138],"uncertainty":[139],"quantification":[140],"based":[142],"partially":[145],"collapsed":[146],"Gibbs":[147],"sampler.":[148],"It":[149],"relies":[150],"Laplace":[153],"approximation":[154],"of":[155,180],"marginal":[157],"likelihood":[158],"Metropolized":[161],"Shotgun":[162],"Stochastic":[163],"Search":[164],"estimate":[166],"allocation":[169],"efficiently.":[170],"Applications":[171],"synthetic":[173],"real-world":[175],"proposed":[182],"method":[183],"hidden":[186],"structures":[187],"data.":[190]},"counts_by_year":[],"updated_date":"2026-03-11T06:11:40.159057","created_date":"2025-10-10T00:00:00"}