{"id":"https://openalex.org/W2013805643","doi":"https://doi.org/10.1093/biomet/92.4.937","title":"Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation","display_name":"Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation","publication_year":2005,"publication_date":"2005-11-12","ids":{"openalex":"https://openalex.org/W2013805643","doi":"https://doi.org/10.1093/biomet/92.4.937","mag":"2013805643"},"language":"en","primary_location":{"id":"doi:10.1093/biomet/92.4.937","doi":"https://doi.org/10.1093/biomet/92.4.937","is_oa":false,"landing_page_url":"https://doi.org/10.1093/biomet/92.4.937","pdf_url":null,"source":{"id":"https://openalex.org/S172180718","display_name":"Biometrika","issn_l":"0006-3444","issn":["0006-3444","1464-3510"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biometrika","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015458882","display_name":"Yuhong Yang","orcid":"https://orcid.org/0000-0003-3618-3083","observed_orcids":["https://orcid.org/0000-0003-3618-3083","https://orcid.org/0009-0003-9979-2166","https://orcid.org/0009-0001-5358-3217"]},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuhong Yang","raw_affiliation_strings":["School of Statistics, University of Minnesota, 224 Church Street S.E., Minneapolis, Minnesota 55455, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics, University of Minnesota, 224 Church Street S.E., Minneapolis, Minnesota 55455, U.S.A","institution_ids":["https://openalex.org/I130238516","https://openalex.org/I2800403580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015458882"],"corresponding_institution_ids":["https://openalex.org/I130238516","https://openalex.org/I2800403580"],"apc_list":{"value":2724,"currency":"GBP","value_usd":3592},"apc_paid":null,"fwci":12.9487,"has_fulltext":false,"cited_by_count":651,"citation_normalized_percentile":{"value":0.99195151,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"92","issue":"4","first_page":"937","last_page":"950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":1.0,"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":1.0,"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/T13141","display_name":"Statistical Methods and Applications","score":0.0,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.0,"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/akaike-information-criterion","display_name":"Akaike information criterion","score":0.8069999814033508},{"id":"https://openalex.org/keywords/bic","display_name":"BIC","score":0.9980000257492065},{"id":"https://openalex.org/keywords/model-selection","display_name":"model selection","score":0.6830000281333923},{"id":"https://openalex.org/keywords/adaptive-model-selection","display_name":"adaptive model selection","score":0.8029999732971191},{"id":"https://openalex.org/keywords/bayesian-model-averaging","display_name":"Bayesian model averaging","score":0.9520000219345093},{"id":"https://openalex.org/keywords/model-averaging","display_name":"model averaging","score":0.7070000171661377},{"id":"https://openalex.org/keywords/regression-function-estimation","display_name":"regression function estimation","score":0.7310000061988831},{"id":"https://openalex.org/keywords/minimax-rates-of-convergence","display_name":"minimax rates of convergence","score":0.9620000123977661},{"id":"https://openalex.org/keywords/consistency","display_name":"consistency","score":0.6119999885559082},{"id":"https://openalex.org/keywords/system-identification","display_name":"system identification","score":0.4860000014305115},{"id":"https://openalex.org/keywords/penalty-term","display_name":"penalty term","score":0.39100000262260437}],"concepts":[{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.7630546689033508},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.7460035085678101},{"id":"https://openalex.org/C168136583","wikidata":"https://www.wikidata.org/wiki/Q1988242","display_name":"Bayesian information criterion","level":2,"score":0.7454463243484497},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6562607884407043},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5268223285675049},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4859124720096588},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.46430686116218567},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4630816876888275},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.448103129863739},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4386877417564392},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4269920587539673},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.41848549246788025},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3740173876285553},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2914251685142517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2256614863872528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1840398609638214},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1093/biomet/92.4.937","doi":"https://doi.org/10.1093/biomet/92.4.937","is_oa":false,"landing_page_url":"https://doi.org/10.1093/biomet/92.4.937","pdf_url":null,"source":{"id":"https://openalex.org/S172180718","display_name":"Biometrika","issn_l":"0006-3444","issn":["0006-3444","1464-3510"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biometrika","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.10.2327","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.2327","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.stat.iastate.edu/preprint/articles/2003-10.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.831.2406","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.831.2406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://lib.dr.iastate.edu/cgi/viewcontent.cgi?article%3D1118%26context%3Dstat_las_preprints","raw_type":"text"},{"id":"pmh:oai:dr.lib.iastate.edu:20.500.12876/90275","doi":null,"is_oa":false,"landing_page_url":"https://dr.lib.iastate.edu/handle/20.500.12876/90275","pdf_url":null,"source":{"id":"https://openalex.org/S4377196104","display_name":"Iowa State University Digital Repository (Iowa State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I173911158","host_organization_name":"Iowa State University","host_organization_lineage":["https://openalex.org/I173911158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"archive/lib.dr.iastate.edu/stat_las_preprints/116/2003_YangY_CanStrengthsAIC.pdf|||Fri Jan 14 18:53:53 UTC 2022","raw_type":"Text"},{"id":"pmh:oai:lib.dr.iastate.edu:stat_las_preprints-1118","doi":null,"is_oa":false,"landing_page_url":"https://dr.lib.iastate.edu/bitstreams/18dd70f5-b86f-4f6a-b518-04039ba9eef4/download","pdf_url":null,"source":{"id":"https://openalex.org/S4377196104","display_name":"Iowa State University Digital Repository (Iowa State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I173911158","host_organization_name":"Iowa State University","host_organization_lineage":["https://openalex.org/I173911158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Statistics Preprints","raw_type":"text"},{"id":"pmh:oai:RePEc:oup:biomet:v:92:y:2005:i:4:p:937-950","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1093/biomet/92.4.937","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,"listed_in":[],"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":"mag:1749166525","doi":null,"is_oa":false,"landing_page_url":"http://users.stat.umn.edu/~yangx374/papers/Pre-Print_2003-10_Biometrika.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1506069954","https://openalex.org/W1511586053","https://openalex.org/W1521975636","https://openalex.org/W1524622012","https://openalex.org/W1965873257","https://openalex.org/W1972568734","https://openalex.org/W1973217014","https://openalex.org/W1978034330","https://openalex.org/W1983351268","https://openalex.org/W1986783130","https://openalex.org/W1995771589","https://openalex.org/W1996268356","https://openalex.org/W2004060143","https://openalex.org/W2013122042","https://openalex.org/W2022943305","https://openalex.org/W2033149996","https://openalex.org/W2033484654","https://openalex.org/W2041902797","https://openalex.org/W2050297026","https://openalex.org/W2054658115","https://openalex.org/W2056481711","https://openalex.org/W2058815839","https://openalex.org/W2069437695","https://openalex.org/W2073640547","https://openalex.org/W2084089095","https://openalex.org/W2131967549","https://openalex.org/W2146855196"],"related_works":["https://openalex.org/W1749166525","https://openalex.org/W7045182170","https://openalex.org/W4392868178","https://openalex.org/W1612700042","https://openalex.org/W2117240603","https://openalex.org/W1984035697","https://openalex.org/W2117570546","https://openalex.org/W2019448438","https://openalex.org/W2788259770","https://openalex.org/W2112153068"],"abstract_inverted_index":{"A":[0,70],"traditional":[1],"approach":[2],"to":[3,7,40,82,133,159,172],"statistical":[4],"inference":[5,25],"is":[6,48,53,62,74,89,107],"identify":[8],"the":[9,21,27,32,35,57,67,86,116,135,147,157,165,181],"true":[10,36,58],"or":[11,17,124],"best":[12],"model":[13,28,37,45,76,103,136,141,169,193],"first":[14],"with":[15],"little":[16],"no":[18],"consideration":[19],"of":[20,24,34,101,118,186,189],"specific":[22],"goal":[23],"in":[26,55,78,80,99,150,164,184],"identification":[29],"stage.":[30],"Can":[31,139],"pursuit":[33],"also":[38],"lead":[39],"optimal":[41,64,144,198],"regression":[42,68,148,182,200],"estimation?":[43],"In":[44],"selection,":[46,77,104],"it":[47,106,112,175],"well":[49],"known":[50],"that":[51,156],"BIC":[52],"consistent":[54],"selecting":[56],"model,":[59],"and":[60,84,93,120,191],"AIC":[61,83,119],"minimax-rate":[63,197],"for":[65,145,167,179,199],"estimating":[66,146,180],"function.":[69],"recent":[71],"promising":[72],"direction":[73],"adaptive":[75,102],"which,":[79],"contrast":[81],"BIC,":[85],"penalty":[87],"term":[88],"data-dependent.":[90],"Some":[91],"theoretical":[92],"empirical":[94],"results":[95],"have":[96],"been":[97],"obtained":[98],"support":[100],"but":[105],"still":[108],"not":[109],"clear":[110],"if":[111],"can":[113],"really":[114],"share":[115],"strengths":[117],"BIC.":[121],"Model":[122],"combining":[123],"averaging":[125,142,194],"has":[126],"attracted":[127],"increasing":[128],"attention":[129],"as":[130],"a":[131,151],"means":[132],"overcome":[134],"selection":[137,170],"uncertainty.":[138],"Bayesian":[140,192],"be":[143,173,196],"function":[149,183],"minimax":[152,187],"sense?":[153],"We":[154],"show":[155],"answers":[158],"these":[160],"questions":[161],"are":[162],"basically":[163],"negative:":[166],"any":[168],"criterion":[171],"consistent,":[174],"must":[176],"behave":[177],"suboptimally":[178],"terms":[185],"rate":[188],"covergence;":[190],"cannot":[195],"estimation.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":30},{"year":2025,"cited_by_count":39},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":23},{"year":2022,"cited_by_count":32},{"year":2021,"cited_by_count":41},{"year":2020,"cited_by_count":40},{"year":2019,"cited_by_count":45},{"year":2018,"cited_by_count":45},{"year":2017,"cited_by_count":38},{"year":2016,"cited_by_count":37},{"year":2015,"cited_by_count":45},{"year":2014,"cited_by_count":38},{"year":2013,"cited_by_count":35},{"year":2012,"cited_by_count":36}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2016-06-24T00:00:00"}