{"id":"https://openalex.org/W4390930515","doi":"https://doi.org/10.5705/ss.202023.0009","title":"A Regularized Low Tubal-Rank Model for High-dimensional Time Series Data","display_name":"A Regularized Low Tubal-Rank Model for High-dimensional Time Series Data","publication_year":2024,"publication_date":"2024-01-16","ids":{"openalex":"https://openalex.org/W4390930515","doi":"https://doi.org/10.5705/ss.202023.0009"},"language":"en","primary_location":{"id":"doi:10.5705/ss.202023.0009","doi":"https://doi.org/10.5705/ss.202023.0009","is_oa":true,"landing_page_url":"https://doi.org/10.5705/ss.202023.0009","pdf_url":"http://dx.doi.org/10.5705/ss.202023.0009","source":{"id":"https://openalex.org/S23408671","display_name":"Statistica Sinica","issn_l":"1017-0405","issn":["1017-0405","1996-8507"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","jufo-2","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4362561675","host_organization_name":"Institute of Statistical Science","host_organization_lineage":["https://openalex.org/P4362561675"],"host_organization_lineage_names":["Institute of Statistical Science"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistica Sinica","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"http://dx.doi.org/10.5705/ss.202023.0009","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007576073","display_name":"Samrat Guha Roy","orcid":"https://orcid.org/0000-0001-7291-3747","observed_orcids":["https://orcid.org/0000-0001-7291-3747"]},"institutions":[{"id":"https://openalex.org/I150870154","display_name":"Indian Institute of Management Ahmedabad","ror":"https://ror.org/02egcpy68","country_code":"IN","type":"education","lineage":["https://openalex.org/I150870154"]},{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["IN","US"],"is_corresponding":true,"raw_author_name":"Samrat Roy","raw_affiliation_strings":["Indian Institute of Management Ahmedabad and University of Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Management Ahmedabad and University of Florida","institution_ids":["https://openalex.org/I150870154","https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017220650","display_name":"George C. Michailidis","orcid":"https://orcid.org/0000-0002-3676-1739","observed_orcids":["https://orcid.org/0000-0002-3676-1739"]},"institutions":[{"id":"https://openalex.org/I150870154","display_name":"Indian Institute of Management Ahmedabad","ror":"https://ror.org/02egcpy68","country_code":"IN","type":"education","lineage":["https://openalex.org/I150870154"]},{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"George Michailidis","raw_affiliation_strings":["Indian Institute of Management Ahmedabad and University of Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Management Ahmedabad and University of Florida","institution_ids":["https://openalex.org/I150870154","https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007576073"],"corresponding_institution_ids":["https://openalex.org/I150870154","https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0038835,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9657999873161316,"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":0.9657999873161316,"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/T10136","display_name":"Statistical Methods and Inference","score":0.024700000882148743,"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":0.006500000134110451,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/high-dimensional-time-series","display_name":"high-dimensional time series","score":0.7490000128746033},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"tensor decomposition","score":0.7540000081062317},{"id":"https://openalex.org/keywords/sparse-tensors","display_name":"sparse tensors","score":0.6140000224113464},{"id":"https://openalex.org/keywords/latent-factor-models","display_name":"latent factor models","score":0.6700000166893005},{"id":"https://openalex.org/keywords/time-dependence","display_name":"time dependence","score":0.9279999732971191},{"id":"https://openalex.org/keywords/identifiability","display_name":"identifiability","score":0.8539999723434448},{"id":"https://openalex.org/keywords/convex-regularization","display_name":"convex regularization","score":0.7409999966621399},{"id":"https://openalex.org/keywords/finite-sample-error-bounds","display_name":"finite-sample error bounds","score":0.7710000276565552},{"id":"https://openalex.org/keywords/macroeconometrics","display_name":"macroeconometrics","score":0.7710000276565552}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6504000425338745},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5891199707984924},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.45001569390296936},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.431161493062973},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.418979674577713},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38860806822776794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3801760673522949},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.11889275908470154},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07333880662918091},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5705/ss.202023.0009","doi":"https://doi.org/10.5705/ss.202023.0009","is_oa":true,"landing_page_url":"https://doi.org/10.5705/ss.202023.0009","pdf_url":"http://dx.doi.org/10.5705/ss.202023.0009","source":{"id":"https://openalex.org/S23408671","display_name":"Statistica Sinica","issn_l":"1017-0405","issn":["1017-0405","1996-8507"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","jufo-2","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4362561675","host_organization_name":"Institute of Statistical Science","host_organization_lineage":["https://openalex.org/P4362561675"],"host_organization_lineage_names":["Institute of Statistical Science"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistica Sinica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.5705/ss.202023.0009","doi":"https://doi.org/10.5705/ss.202023.0009","is_oa":true,"landing_page_url":"https://doi.org/10.5705/ss.202023.0009","pdf_url":"http://dx.doi.org/10.5705/ss.202023.0009","source":{"id":"https://openalex.org/S23408671","display_name":"Statistica Sinica","issn_l":"1017-0405","issn":["1017-0405","1996-8507"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","jufo-2","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4362561675","host_organization_name":"Institute of Statistical Science","host_organization_lineage":["https://openalex.org/P4362561675"],"host_organization_lineage_names":["Institute of Statistical Science"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistica Sinica","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390930515.pdf","grobid_xml":"https://content.openalex.org/works/W4390930515.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1754431113","https://openalex.org/W1819151015","https://openalex.org/W1925915230","https://openalex.org/W1992426838","https://openalex.org/W2014165366","https://openalex.org/W2020245429","https://openalex.org/W2024165284","https://openalex.org/W2043571470","https://openalex.org/W2083577057","https://openalex.org/W2087535060","https://openalex.org/W2099210013","https://openalex.org/W2103358330","https://openalex.org/W2133073622","https://openalex.org/W2134689741","https://openalex.org/W2136321181","https://openalex.org/W2138180087","https://openalex.org/W2145962650","https://openalex.org/W2154514661","https://openalex.org/W2241027494","https://openalex.org/W2364072717","https://openalex.org/W2516878419","https://openalex.org/W2787360447","https://openalex.org/W2799651819","https://openalex.org/W2945670879","https://openalex.org/W2950836853","https://openalex.org/W2963107235","https://openalex.org/W2963328634","https://openalex.org/W2964214749","https://openalex.org/W2964255370","https://openalex.org/W2996534391","https://openalex.org/W3011197231","https://openalex.org/W3121553976","https://openalex.org/W3121573968","https://openalex.org/W3121890438","https://openalex.org/W3123507112","https://openalex.org/W3194853173","https://openalex.org/W3198813250","https://openalex.org/W4221115534","https://openalex.org/W4285703539","https://openalex.org/W4388357039"],"related_works":["https://openalex.org/W7204527604","https://openalex.org/W7135077575","https://openalex.org/W4414958187","https://openalex.org/W4226464447","https://openalex.org/W4388357039","https://openalex.org/W4408601718","https://openalex.org/W2973043157","https://openalex.org/W3101998287","https://openalex.org/W7162994037","https://openalex.org/W4417123814"],"abstract_inverted_index":{"High":[0],"dimensional":[1,142],"time":[2,58,77],"series":[3,59],"analysis":[4],"has":[5],"diverse":[6],"applications":[7],"in":[8,67,101,112],"macroeconometrics":[9],"and":[10,32,54,70,93,115],"finance.Recent":[11],"factor-type":[12],"models":[13],"employing":[14],"tensor-based":[15],"decompositions":[16],"prove":[17],"to":[18,23,124],"be":[19],"computationally":[20],"involved":[21],"due":[22],"the":[24,28,38,43,49,64,68,72,76,90,98,102,105,126,133,145],"non-convex":[25],"nature":[26],"of":[27,42,51,107,109],"underlying":[29,39],"optimization":[30,129],"problem":[31,130],"also":[33],"they":[34],"do":[35],"not":[36],"capture":[37],"temporal":[40,65],"dependence":[41,66],"latent":[44],"factor":[45],"structure.This":[46],"work":[47],"leverages":[48],"concept":[50],"tubal":[52,86],"rank":[53,87],"develops":[55],"a":[56,84,94,118],"matrix-valued":[57],"model,":[60],"which":[61],"first":[62],"captures":[63],"data,":[69],"then":[71],"remainder":[73],"signals":[74],"across":[75],"points":[78],"are":[79],"decomposed":[80],"into":[81],"two":[82],"components:":[83],"low":[85],"tensor":[88,96],"representing":[89],"baseline":[91],"signals,":[92],"sparse":[95],"capturing":[97],"additional":[99],"idiosyncrasies":[100],"signal.We":[103],"address":[104],"issue":[106],"identifiability":[108],"various":[110],"components":[111],"our":[113],"model":[114,146],"subsequently":[116],"develop":[117],"scalable":[119],"Alternating":[120],"Block":[121],"Minimization":[122],"algorithm":[123],"solve":[125],"convex":[127],"regularized":[128],"for":[131,144],"estimating":[132],"parameters.We":[134],"provide":[135],"finite":[136],"sample":[137],"error":[138],"bounds":[139],"under":[140],"high":[141],"scaling":[143],"parameters.":[147]},"counts_by_year":[],"updated_date":"2026-11-01T11:40:01.658920","created_date":"2024-01-17T00:00:00"}