{"id":"https://openalex.org/W2795530222","doi":"https://doi.org/10.1109/tsp.2018.2821628","title":"A Model Selection Criterion for High-Dimensional Linear Regression","display_name":"A Model Selection Criterion for High-Dimensional Linear Regression","publication_year":2018,"publication_date":"2018-04-02","ids":{"openalex":"https://openalex.org/W2795530222","doi":"https://doi.org/10.1109/tsp.2018.2821628","mag":"2795530222"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2018.2821628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2018.2821628","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231694","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090549596","display_name":"Arash Owrang","orcid":"https://orcid.org/0000-0002-1276-2577"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Arash Owrang","raw_affiliation_strings":["Department of Information Science and Engineering and the ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-1276-2577","affiliations":[{"raw_affiliation_string":"Department of Information Science and Engineering and the ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019386542","display_name":"Magnus Jansson","orcid":"https://orcid.org/0000-0002-6855-5868"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Magnus Jansson","raw_affiliation_strings":["Department of Information Science and Engineering and the ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-6855-5868","affiliations":[{"raw_affiliation_string":"Department of Information Science and Engineering and the ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":{"value":193,"currency":"EUR","value_usd":208},"fwci":1.2064,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.8045839,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"66","issue":"13","first_page":"3436","last_page":"3446"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9998000264167786,"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":0.9998000264167786,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9984999895095825,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9934999942779541,"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/model-selection","display_name":"Model selection","score":0.6922229528427124},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6340169906616211},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6224209666252136},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6002883315086365},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5865235328674316},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.506496787071228},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.47300368547439575},{"id":"https://openalex.org/keywords/bayesian-information-criterion","display_name":"Bayesian information criterion","score":0.4714803695678711},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.47047358751296997},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.46164268255233765},{"id":"https://openalex.org/keywords/fisher-information","display_name":"Fisher information","score":0.4433761239051819},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4405137002468109},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.43899986147880554},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3542884290218353},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.26719504594802856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20309314131736755}],"concepts":[{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.6922229528427124},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6340169906616211},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6224209666252136},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6002883315086365},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5865235328674316},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.506496787071228},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47300368547439575},{"id":"https://openalex.org/C168136583","wikidata":"https://www.wikidata.org/wiki/Q1988242","display_name":"Bayesian information criterion","level":2,"score":0.4714803695678711},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.47047358751296997},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.46164268255233765},{"id":"https://openalex.org/C29406490","wikidata":"https://www.wikidata.org/wiki/Q1420659","display_name":"Fisher information","level":2,"score":0.4433761239051819},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4405137002468109},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.43899986147880554},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3542884290218353},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26719504594802856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20309314131736755},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tsp.2018.2821628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2018.2821628","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:DiVA.org:kth-231694","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231694","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article in journal"},{"id":"pmh:oai:zenodo.org:3502715","is_oa":true,"landing_page_url":"https://zenodo.org/record/3502715","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:kth-231694","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231694","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article in journal"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.44999998807907104,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G4654529413","display_name":"Actively Enhanced Cognition based Framework for Design of Complex Systems","funder_award_id":"742648","funder_id":"https://openalex.org/F4320338335","funder_display_name":"H2020 European Research Council"},{"id":"https://openalex.org/G7038735060","display_name":null,"funder_award_id":"2015-05484","funder_id":"https://openalex.org/F4320322581","funder_display_name":"Vetenskapsr\u00e5det"}],"funders":[{"id":"https://openalex.org/F4320322581","display_name":"Vetenskapsr\u00e5det","ror":"https://ror.org/03zttf063"},{"id":"https://openalex.org/F4320338335","display_name":"H2020 European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W143004564","https://openalex.org/W1498464051","https://openalex.org/W1501760102","https://openalex.org/W1965268603","https://openalex.org/W1965392255","https://openalex.org/W1981903823","https://openalex.org/W1996068192","https://openalex.org/W2008414513","https://openalex.org/W2034260606","https://openalex.org/W2037491422","https://openalex.org/W2050834445","https://openalex.org/W2053061982","https://openalex.org/W2054658115","https://openalex.org/W2057682568","https://openalex.org/W2060161465","https://openalex.org/W2063978378","https://openalex.org/W2086403511","https://openalex.org/W2108076619","https://openalex.org/W2109246257","https://openalex.org/W2109842006","https://openalex.org/W2114147096","https://openalex.org/W2115447612","https://openalex.org/W2129131372","https://openalex.org/W2135046866","https://openalex.org/W2142635246","https://openalex.org/W2150940164","https://openalex.org/W2165186963","https://openalex.org/W2168175751","https://openalex.org/W2329095262","https://openalex.org/W2591874138","https://openalex.org/W2997644599","https://openalex.org/W3101762025","https://openalex.org/W3105120000","https://openalex.org/W3105340263","https://openalex.org/W3106266785","https://openalex.org/W3121832289","https://openalex.org/W6682241100"],"related_works":["https://openalex.org/W3122388856","https://openalex.org/W2509820422","https://openalex.org/W2783425804","https://openalex.org/W2114625140","https://openalex.org/W2963415778","https://openalex.org/W2033907215","https://openalex.org/W1502087262","https://openalex.org/W2176075850","https://openalex.org/W2963176572","https://openalex.org/W4389544250"],"abstract_inverted_index":{"Statistical":[0],"model":[1,28,45,60,110,125],"selection":[2,29,35,46,56,126],"is":[3,13],"a":[4,43,58,112,119,135],"great":[5],"challenge":[6],"when":[7,91],"the":[8,17,20,25,31,49,55,63,75,81,92,108,128,142,147,154],"number":[9,82],"of":[10,19,27,33,57,71,77,83],"accessible":[11],"measurements":[12,84],"much":[14],"smaller":[15],"than":[16],"dimension":[18],"parameter":[21,145],"space.":[22],"We":[23,73],"study":[24],"problem":[26],"in":[30,131],"context":[32],"subset":[34],"for":[36,146],"high-dimensional":[37],"linear":[38],"regressions.":[39],"Accordingly,":[40],"we":[41,101,117],"propose":[42],"new":[44],"criterion":[47,79,106,130],"with":[48,111,127],"Fisher":[50],"information":[51],"that":[52,103,151],"leads":[53],"to":[54,67,86,96,123,162],"parsimonious":[59],"from":[61],"all":[62],"combinatorial":[64],"models":[65],"up":[66],"some":[68],"maximum":[69],"level":[70],"sparsity.":[72],"analyze":[74],"performance":[76],"our":[78,104,138,164],"as":[80,88,90,134],"grows":[85],"infinity,":[87],"well":[89],"noise":[93],"variance":[94],"tends":[95],"zero.":[97],"In":[98],"each":[99],"case,":[100],"prove":[102],"proposed":[105,129],"gives":[107],"true":[109,155],"probability":[113],"approaching":[114],"one.":[115],"Additionally,":[116],"devise":[118],"computationally":[120],"affordable":[121],"algorithm":[122,139],"conduct":[124],"practice.":[132],"Interestingly,":[133],"side":[136],"product,":[137],"can":[140],"provide":[141],"ideal":[143],"regularization":[144],"Lasso":[148,152],"estimator":[149],"such":[150],"selects":[153],"variables.":[156],"Finally,":[157],"numerical":[158],"simulations":[159],"are":[160],"included":[161],"support":[163],"theoretical":[165],"findings.":[166]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}