{"id":"https://openalex.org/W4402745802","doi":"https://doi.org/10.1080/00401706.2024.2407310","title":"A Subsampling Strategy for AIC-based Model Averaging with Generalized Linear Models","display_name":"A Subsampling Strategy for AIC-based Model Averaging with Generalized Linear Models","publication_year":2024,"publication_date":"2024-09-23","ids":{"openalex":"https://openalex.org/W4402745802","doi":"https://doi.org/10.1080/00401706.2024.2407310"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.2024.2407310","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2024.2407310","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"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":"Technometrics","raw_type":"journal-article"},"type":"article","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/A5019853998","display_name":"Jun Yu","orcid":"https://orcid.org/0000-0001-6068-8415"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Yu","raw_affiliation_strings":["School of Mathematics and Statistics, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100379056","display_name":"HaiYing Wang","orcid":"https://orcid.org/0000-0001-7729-0243"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"HaiYing Wang","raw_affiliation_strings":["Department of Statistics, University of Connecticut"],"raw_orcid":"https://orcid.org/0000-0001-7729-0243","affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Connecticut","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083167231","display_name":"Mingyao Ai","orcid":"https://orcid.org/0000-0002-0421-0051"},"institutions":[{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Mingyao Ai","raw_affiliation_strings":["LMAM, School of Mathematical Sciences and Center for Statistical Science, Peking University"],"raw_orcid":"https://orcid.org/0000-0002-0421-0051","affiliations":[{"raw_affiliation_string":"LMAM, School of Mathematical Sciences and Center for Statistical Science, Peking University","institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100379056"],"corresponding_institution_ids":["https://openalex.org/I140172145"],"apc_list":null,"apc_paid":null,"fwci":3.2581,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.92943559,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"67","issue":"1","first_page":"122","last_page":"132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9927999973297119,"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":0.9927999973297119,"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/T11236","display_name":"Control Systems and Identification","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9732000231742859,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generalized-linear-model","display_name":"Generalized linear model","score":0.5792063474655151},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5030671954154968},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4919564425945282},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4233863353729248},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.42037534713745117},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3967565894126892},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3682193160057068}],"concepts":[{"id":"https://openalex.org/C41587187","wikidata":"https://www.wikidata.org/wiki/Q1501882","display_name":"Generalized linear model","level":2,"score":0.5792063474655151},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5030671954154968},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4919564425945282},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4233863353729248},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.42037534713745117},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3967565894126892},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3682193160057068}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/00401706.2024.2407310","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2024.2407310","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"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":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2805320715","display_name":null,"funder_award_id":"2020YFE0204200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G440961750","display_name":null,"funder_award_id":"1232019","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G7215518276","display_name":null,"funder_award_id":"12471244","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320323110","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74"},{"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":53,"referenced_works":["https://openalex.org/W1501760102","https://openalex.org/W1517600448","https://openalex.org/W1994672023","https://openalex.org/W2006571972","https://openalex.org/W2006722592","https://openalex.org/W2020144485","https://openalex.org/W2021136548","https://openalex.org/W2022587791","https://openalex.org/W2028763699","https://openalex.org/W2052025831","https://openalex.org/W2058815839","https://openalex.org/W2078502317","https://openalex.org/W2087913441","https://openalex.org/W2094509095","https://openalex.org/W2104103536","https://openalex.org/W2122196572","https://openalex.org/W2125251038","https://openalex.org/W2125621954","https://openalex.org/W2144164089","https://openalex.org/W2290516599","https://openalex.org/W2396477770","https://openalex.org/W2596535828","https://openalex.org/W2611757366","https://openalex.org/W2754880706","https://openalex.org/W2766451779","https://openalex.org/W2787894218","https://openalex.org/W2921430350","https://openalex.org/W2955312852","https://openalex.org/W2963468210","https://openalex.org/W2975245449","https://openalex.org/W3007063426","https://openalex.org/W3028903392","https://openalex.org/W3037232215","https://openalex.org/W3043437699","https://openalex.org/W3044420422","https://openalex.org/W3097162844","https://openalex.org/W3098488568","https://openalex.org/W3099924168","https://openalex.org/W3105049881","https://openalex.org/W3118133300","https://openalex.org/W3119971523","https://openalex.org/W3156809662","https://openalex.org/W3158480457","https://openalex.org/W3210246363","https://openalex.org/W4206341000","https://openalex.org/W4246784033","https://openalex.org/W4288077079","https://openalex.org/W4320491312","https://openalex.org/W4385191393","https://openalex.org/W4386435107","https://openalex.org/W4387743165","https://openalex.org/W6677280552","https://openalex.org/W6907522769"],"related_works":["https://openalex.org/W3081465059","https://openalex.org/W1510072949","https://openalex.org/W1969243170","https://openalex.org/W4242077822","https://openalex.org/W4386783521","https://openalex.org/W1556631438","https://openalex.org/W2081875724","https://openalex.org/W2550180129","https://openalex.org/W2900631639","https://openalex.org/W2290516599"],"abstract_inverted_index":{"Subsampling":[0],"is":[1,111,116],"an":[2],"effective":[3],"approach":[4],"to":[5,41,66],"address":[6],"computational":[7],"challenges":[8],"associated":[9],"with":[10],"massive":[11],"datasets.":[12,126],"However,":[13],"existing":[14],"subsampling":[15,28,39,86],"methods":[16],"do":[17],"not":[18],"consider":[19],"model":[20],"uncertainty.":[21],"In":[22],"this":[23],"article,":[24],"we":[25,71],"investigate":[26],"the":[27,31,38,42,48,56,60,68,73,76,80,89,96,101,104],"technique":[29],"for":[30,88],"Akaike":[32],"information":[33],"criterion":[34],"(AIC)":[35],"and":[36,94,103,113,124],"extend":[37],"method":[40],"smoothed":[43,90],"AIC":[44,77,91],"model-averaging":[45,92],"framework":[46],"in":[47],"context":[49],"of":[50,59,75,100],"generalized":[51],"linear":[52],"models.":[53],"By":[54],"correcting":[55],"asymptotic":[57,98],"bias":[58],"maximized":[61],"subsample":[62],"objective":[63],"function":[64],"used":[65],"approximate":[67],"Kullback\u2013Leibler":[69],"divergence,":[70],"derive":[72],"form":[74],"based":[78],"on":[79,121],"subsample.":[81],"We":[82],"then":[83],"provide":[84],"a":[85],"strategy":[87],"estimator":[93],"study":[95],"corresponding":[97],"properties":[99],"loss":[102],"resulting":[105],"estimator.":[106],"A":[107],"practically":[108],"implementable":[109],"algorithm":[110],"developed,":[112],"its":[114],"performance":[115],"evaluated":[117],"through":[118],"numerical":[119],"experiments":[120],"both":[122],"real":[123],"simulated":[125]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2025-10-10T00:00:00"}
