{"id":"https://openalex.org/W7127976207","doi":"https://doi.org/10.1016/j.jmva.2026.105616","title":"Statistical inference for large-dimensional tensor factor model by iterative projections","display_name":"Statistical inference for large-dimensional tensor factor model by iterative projections","publication_year":2026,"publication_date":"2026-02-05","ids":{"openalex":"https://openalex.org/W7127976207","doi":"https://doi.org/10.1016/j.jmva.2026.105616"},"language":"en","primary_location":{"id":"doi:10.1016/j.jmva.2026.105616","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jmva.2026.105616","pdf_url":null,"source":{"id":"https://openalex.org/S133905466","display_name":"Journal of Multivariate Analysis","issn_l":"0047-259X","issn":["0047-259X","1095-7243"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Multivariate Analysis","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.jmva.2026.105616","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013616417","display_name":"Matteo Barigozzi","orcid":"https://orcid.org/0000-0001-9090-5708"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Matteo Barigozzi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125100134","display_name":"Yong He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong He","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125157703","display_name":"Lingxiao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lingxiao Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5008137367","display_name":"Lorenzo Trapani","orcid":"https://orcid.org/0000-0003-3425-2786"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lorenzo Trapani","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013616417"],"corresponding_institution_ids":[],"apc_list":{"value":3060,"currency":"USD","value_usd":3060},"apc_paid":{"value":3060,"currency":"USD","value_usd":3060},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31422018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"214","issue":null,"first_page":"105616","last_page":"105616"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"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/T12303","display_name":"Tensor decomposition and applications","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"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":0.00139999995008111,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6992999911308289},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6721000075340271},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6471999883651733},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6399000287055969},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6270999908447266},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5611000061035156},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4837999939918518},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.4596000015735626},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4106000065803528}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.8134999871253967},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6992999911308289},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6721000075340271},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6471999883651733},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6399000287055969},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6270999908447266},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.5989000201225281},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5611000061035156},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4106000065803528},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3799000084400177},{"id":"https://openalex.org/C175694140","wikidata":"https://www.wikidata.org/wiki/Q980329","display_name":"Orthographic projection","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.37220001220703125},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C10879293","wikidata":"https://www.wikidata.org/wiki/Q726474","display_name":"Factor analysis","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34209999442100525},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.33469998836517334},{"id":"https://openalex.org/C118038509","wikidata":"https://www.wikidata.org/wiki/Q382970","display_name":"Projection pursuit","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C45354692","wikidata":"https://www.wikidata.org/wiki/Q2734388","display_name":"Vector projection","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C71176878","wikidata":"https://www.wikidata.org/wiki/Q17014987","display_name":"Functional principal component analysis","level":3,"score":0.30410000681877136},{"id":"https://openalex.org/C48057537","wikidata":"https://www.wikidata.org/wiki/Q3551145","display_name":"Statistical theory","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.26649999618530273}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.jmva.2026.105616","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jmva.2026.105616","pdf_url":null,"source":{"id":"https://openalex.org/S133905466","display_name":"Journal of Multivariate Analysis","issn_l":"0047-259X","issn":["0047-259X","1095-7243"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Multivariate Analysis","raw_type":"journal-article"},{"id":"pmh:oai:cris.unibo.it:11585/1042532","is_oa":true,"landing_page_url":"https://hdl.handle.net/11585/1042532","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"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"}],"best_oa_location":{"id":"doi:10.1016/j.jmva.2026.105616","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jmva.2026.105616","pdf_url":null,"source":{"id":"https://openalex.org/S133905466","display_name":"Journal of Multivariate Analysis","issn_l":"0047-259X","issn":["0047-259X","1095-7243"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Multivariate Analysis","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4160459637641907,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G7488678027","display_name":null,"funder_award_id":"2023YFA1008701","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1593060747","https://openalex.org/W1814521481","https://openalex.org/W1970377488","https://openalex.org/W1982253419","https://openalex.org/W1991135386","https://openalex.org/W2000215628","https://openalex.org/W2014165366","https://openalex.org/W2024165284","https://openalex.org/W2030677701","https://openalex.org/W2040373108","https://openalex.org/W2079563517","https://openalex.org/W2088911135","https://openalex.org/W2103958279","https://openalex.org/W2111885075","https://openalex.org/W2136002544","https://openalex.org/W2141280932","https://openalex.org/W2146661536","https://openalex.org/W2633758049","https://openalex.org/W2766386494","https://openalex.org/W2950126918","https://openalex.org/W2964255370","https://openalex.org/W3045618615","https://openalex.org/W3080360029","https://openalex.org/W3080660600","https://openalex.org/W3101998287","https://openalex.org/W3124106041","https://openalex.org/W3125051887","https://openalex.org/W3129086483","https://openalex.org/W3136847322","https://openalex.org/W3157910549","https://openalex.org/W3159581759","https://openalex.org/W3194853173","https://openalex.org/W3197930437","https://openalex.org/W3209323023","https://openalex.org/W4244083731","https://openalex.org/W4318334914","https://openalex.org/W4324134806","https://openalex.org/W4327587455","https://openalex.org/W4392591491","https://openalex.org/W4394951162","https://openalex.org/W4403142257","https://openalex.org/W4405603129","https://openalex.org/W4408337937"],"related_works":[],"abstract_inverted_index":{"Tensor":[0],"Factor":[1],"Models":[2],"(TFM)":[3],"are":[4,106,117,154],"appealing":[5],"dimension":[6],"reduction":[7],"tools":[8],"for":[9,33,55],"high-order":[10],"large-dimensional":[11],"tensor":[12,104],"time":[13],"series,":[14],"and":[15,22,38,71,100,131],"have":[16],"wide":[17],"applications":[18],"in":[19],"economics,":[20],"finance":[21],"medical":[23],"imaging.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28],"propose":[29],"a":[30,90,137],"projection":[31,61,95,164],"estimator":[32,96],"the":[34,46,50,56,65,68,72,75,85,94,98,101,111,124,143,148,158,162,168],"Tucker-decomposition":[35],"based":[36,141],"TFM,":[37],"provide":[39,136],"its":[40],"least-square":[41,47],"interpretation":[42,48],"which":[43,105,122],"parallels":[44],"to":[45,81,127,146,156,167],"of":[49,67,74,84,93,97,110,161],"Principal":[51],"Component":[52],"Analysis":[53],"(PCA)":[54],"vector":[57],"factor":[58,103,149],"model.":[59],"The":[60],"technique":[62],"simultaneously":[63],"reduces":[64],"dimensionality":[66],"signal":[69],"component":[70,77],"magnitudes":[73],"idiosyncratic":[76,125],"tensor,":[78],"thus":[79],"leading":[80],"an":[82],"increase":[83],"signal-to-noise":[86],"ratio.":[87],"We":[88,134],"derive":[89],"convergence":[91],"rate":[92],"loadings":[99],"common":[102],"faster":[107],"than":[108],"that":[109],"naive":[112],"PCA-based":[113],"estimator.":[114],"Our":[115],"results":[116],"obtained":[118],"under":[119],"mild":[120],"conditions":[121],"allow":[123],"components":[126],"be":[128],"weakly":[129],"cross-":[130],"auto-":[132],"correlated.":[133],"also":[135],"novel":[138],"iterative":[139],"procedure":[140],"on":[142],"eigenvalue-ratio":[144],"principle":[145],"determine":[147],"numbers.":[150],"Extensive":[151],"numerical":[152],"studies":[153],"conducted":[155],"investigate":[157],"empirical":[159],"performance":[160],"proposed":[163],"estimators":[165],"relative":[166],"state-of-the-art":[169],"ones.":[170]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-02-07T00:00:00"}