{"id":"https://openalex.org/W7224012182","doi":"https://doi.org/10.48550/arxiv.2610.33665","title":"Renewable model averaging for generalized linear models","display_name":"Renewable model averaging for generalized linear models","publication_year":2026,"publication_date":"2026-10-24","ids":{"openalex":"https://openalex.org/W7224012182","doi":"https://doi.org/10.48550/arxiv.2610.33665"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.33665","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.33665","pdf_url":"https://arxiv.org/pdf/2610.33665","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.33665","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5159782385","display_name":"Yalu Ping","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping, Yalu","raw_affiliation_strings":["School of Mathematics and Statistics , Xi'an Jiaotong University , Xi'an , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics , Xi'an Jiaotong University , Xi'an , China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101709841","display_name":"Xuerong Chen","orcid":"https://orcid.org/0009-0000-8638-1630","observed_orcids":["https://orcid.org/0009-0000-8638-1630"]},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuerong, Chen","raw_affiliation_strings":["Centre of Statistical Research , Southwestern University of Finance and Economics , Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre of Statistical Research , Southwestern University of Finance and Economics , Chengdu , China","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031527123","display_name":"Dalei Yu","orcid":"https://orcid.org/0000-0002-6254-0710","observed_orcids":["https://orcid.org/0000-0002-6254-0710"]},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dalei, Yu","raw_affiliation_strings":["School of Mathematics and Statistics , Xi'an Jiaotong University , Xi'an , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics , Xi'an Jiaotong University , Xi'an , China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9560999870300293,"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":0.9560999870300293,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.026900000870227814,"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":0.001500000013038516,"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/generalized-linear-models","display_name":"generalized linear models","score":0.949999988079071},{"id":"https://openalex.org/keywords/data-streams","display_name":"data streams","score":0.9670000076293945},{"id":"https://openalex.org/keywords/real-time-forecasting","display_name":"real-time prediction","score":0.968999981880188},{"id":"https://openalex.org/keywords/second-order-approximation","display_name":"second-order approximation","score":0.8629999756813049},{"id":"https://openalex.org/keywords/quadratic-programming","display_name":"quadratic programming","score":0.7710000276565552},{"id":"https://openalex.org/keywords/asymptotic-optimality","display_name":"asymptotic optimality","score":0.8830000162124634},{"id":"https://openalex.org/keywords/airline-on-time-performance","display_name":"airline on-time performance","score":0.746999979019165}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5917999744415283},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.569100022315979},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5605999827384949},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.5257999897003174},{"id":"https://openalex.org/C41587187","wikidata":"https://www.wikidata.org/wiki/Q1501882","display_name":"Generalized linear model","level":2,"score":0.5019000172615051},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.4966999888420105},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.45719999074935913},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.424699991941452},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4097999930381775},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C187166803","wikidata":"https://www.wikidata.org/wiki/Q2835831","display_name":"Streaming algorithm","level":3,"score":0.36169999837875366},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3508000075817108},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33149999380111694},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28940001130104065},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2727000117301941},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C160824197","wikidata":"https://www.wikidata.org/wiki/Q2071054","display_name":"Linear approximation","level":3,"score":0.2676999866962433},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.33665","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.33665","pdf_url":"https://arxiv.org/pdf/2610.33665","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"doi:10.48550/arxiv.2610.33665","doi":"https://doi.org/10.48550/arxiv.2610.33665","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.33665","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.33665","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.33665","pdf_url":"https://arxiv.org/pdf/2610.33665","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224012182.pdf","grobid_xml":"https://content.openalex.org/works/W7224012182.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4407167273","https://openalex.org/W2399190701","https://openalex.org/W1996935589","https://openalex.org/W3175971538","https://openalex.org/W1632510297","https://openalex.org/W2549828435","https://openalex.org/W1517464268","https://openalex.org/W4200491655","https://openalex.org/W3130126291","https://openalex.org/W3129530230"],"abstract_inverted_index":{"Prediction":[0],"is":[1,62,137,173,204,225,232],"one":[2,178],"of":[3,18,38,44,59,70,89,162,190,223,246],"the":[4,16,36,67,85,97,130,153,167,200,210,216,220,244,247,253,256],"most":[5],"important":[6],"research":[7,29],"topics":[8],"in":[9,15,31,64,92,187,243,260],"statistics":[10],"and":[11,53,76,81,87,252],"machine":[12],"learning.":[13],"Moreover,":[14,171],"domain":[17],"streaming":[19,39,60,71,126],"data":[20,61,163],"analysis,":[21],"real-time":[22,57,90],"prediction":[23,58,91,156],"has":[24,99],"become":[25],"a":[26,110,139,144,159,183],"rapidly":[27],"growing":[28],"field":[30],"recent":[32],"years,":[33],"owing":[34],"to":[35,84,151,181,207],"abundance":[37],"data.":[40,127,170],"In":[41],"many":[42],"fields":[43],"scientific":[45],"research,":[46,50],"such":[47,73],"as":[48,74,177],"biomedical":[49],"weather":[51],"forecasting,":[52],"traffic":[54],"management,":[55],"improving":[56],"crucial":[63],"general.":[65],"However,":[66],"complicated":[68],"features":[69],"data,":[72,219],"large-scale":[75],"high-velocity,":[77],"impose":[78],"both":[79],"theoretical":[80],"computational":[82],"challenges":[83],"development":[86],"evaluation":[88],"this":[93],"field,":[94],"especially":[95],"when":[96,158],"investigator":[98],"multiple":[100],"models":[101],"at":[102],"hand.":[103],"To":[104],"overcome":[105],"these":[106],"challenges,":[107],"we":[108,196],"propose":[109],"novel":[111],"Renewable":[112],"Model":[113],"Averaging":[114],"method":[115,231,259],"through":[116],"Quadratic":[117],"approximation":[118],"(ReMAQ)":[119],"for":[120,125,134],"generalized":[121],"linear":[122],"model":[123,131,154,212],"(GLM)":[124],"By":[128],"approximating":[129],"averaging":[132,155,213],"procedure":[133],"GLMs":[135],"(which":[136],"typically":[138],"convex":[140],"optimization":[141,146],"problem)":[142],"with":[143],"quadratic":[145,184],"formulation,":[147],"ReMAQ":[148,172,202,224,242],"allows":[149],"us":[150],"update":[152],"sequentially":[157],"new":[160],"batch":[161],"arrives,":[164],"without":[165],"accessing":[166],"entire":[168],"historical":[169],"also":[174,197,233],"computationally":[175],"efficient":[176],"only":[179],"needs":[180],"consider":[182],"programming":[185],"problem":[186],"each":[188],"steps":[189],"updating.":[191],"Under":[192],"certain":[193],"regular":[194],"conditions,":[195],"show":[198],"that":[199,208],"proposed":[201,230,241],"weight":[203],"asymptotically":[205],"equivalent":[206],"by":[209,235],"oracle":[211],"based":[214],"on":[215],"inaccessible":[217],"full":[218],"asymptotic":[221],"optimality":[222],"then":[226],"established":[227],"accordingly.":[228],"The":[229],"assessed":[234],"simulation":[236],"studies.":[237],"We":[238],"apply":[239],"our":[240,258],"study":[245],"Airline":[248],"On-Time":[249],"Performance":[250],"Dataset":[251],"results":[254],"demonstrate":[255],"superiority":[257],"practical":[261],"situations.":[262]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2026-10-28T00:00:00"}
