{"id":"https://openalex.org/W4387182665","doi":"https://doi.org/10.1080/03610918.2023.2259637","title":"Distributed estimation for linear regression with covariates missing at random","display_name":"Distributed estimation for linear regression with covariates missing at random","publication_year":2023,"publication_date":"2023-09-28","ids":{"openalex":"https://openalex.org/W4387182665","doi":"https://doi.org/10.1080/03610918.2023.2259637"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2023.2259637","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2259637","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","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/A5084788149","display_name":"Yingli Pan","orcid":"https://orcid.org/0000-0002-5033-7301"},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingli Pan","raw_affiliation_strings":["Faculty of Mathematics and Statistics, Hubei University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Statistics, Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427174","display_name":"Haoyu Wang","orcid":"https://orcid.org/0000-0001-9575-7345"},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Wang","raw_affiliation_strings":["Faculty of Mathematics and Statistics, Hubei University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Statistics, Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101368845","display_name":"Kaidong Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaidong Xu","raw_affiliation_strings":["Faculty of Mathematics and Statistics, Hubei University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Statistics, Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043941427","display_name":"He Huang","orcid":"https://orcid.org/0000-0003-3236-7539"},"institutions":[{"id":"https://openalex.org/I4210107865","display_name":"Wuzhou University","ror":"https://ror.org/01vv37n49","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210107865"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"He Huang","raw_affiliation_strings":["Faculty of Management, Wuzhou University, Wuzhou, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Management, Wuzhou University, Wuzhou, China","institution_ids":["https://openalex.org/I4210107865"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043941427"],"corresponding_institution_ids":["https://openalex.org/I4210107865"],"apc_list":null,"apc_paid":null,"fwci":0.3419,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64141335,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"54","issue":"2","first_page":"583","last_page":"601"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.998199999332428,"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":0.998199999332428,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9932000041007996,"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/estimator","display_name":"Estimator","score":0.7245603799819946},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.6709690093994141},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.603678822517395},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.4715335965156555},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.47061875462532043},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4546440541744232},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.43945109844207764},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42551130056381226},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.378143310546875},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3756418228149414},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3642043173313141},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2878159284591675},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.23038789629936218},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.193148672580719},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11940181255340576}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7245603799819946},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.6709690093994141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.603678822517395},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.4715335965156555},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.47061875462532043},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4546440541744232},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.43945109844207764},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42551130056381226},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.378143310546875},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3756418228149414},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3642043173313141},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2878159284591675},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.23038789629936218},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.193148672580719},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11940181255340576},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2023.2259637","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2023.2259637","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.6000000238418579,"display_name":"Life in Land"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1569625389","https://openalex.org/W1994463864","https://openalex.org/W2395344476","https://openalex.org/W2726134516","https://openalex.org/W2766140019","https://openalex.org/W2779146491","https://openalex.org/W2962853966","https://openalex.org/W2963050660","https://openalex.org/W2964231067","https://openalex.org/W3035663991","https://openalex.org/W3197494818","https://openalex.org/W4233471163","https://openalex.org/W4282958563","https://openalex.org/W4292363360"],"related_works":["https://openalex.org/W2015747722","https://openalex.org/W2362050182","https://openalex.org/W2382418233","https://openalex.org/W2369897927","https://openalex.org/W3031731056","https://openalex.org/W4293167957","https://openalex.org/W2361035307","https://openalex.org/W2380455807","https://openalex.org/W3032945164","https://openalex.org/W2057612738"],"abstract_inverted_index":{"AbstractIn":[0],"this":[1],"article,":[2],"we":[3,28,83],"propose":[4],"a":[5,30,67,113],"distributed":[6,24,68],"optimization":[7],"approach":[8],"to":[9,96],"analyzing":[10],"distributed-stored":[11],"data":[12],"based":[13,42],"on":[14,43],"linear":[15],"regression":[16],"with":[17,60],"covariates":[18],"missing":[19],"at":[20],"random.":[21],"To":[22],"solve":[23],"statistical":[25],"learning":[26],"problems,":[27],"construct":[29],"communication-efficient":[31,47],"surrogate":[32,48,56],"weighted":[33,39,57],"loss":[34,40,49,58],"function":[35,41,59],"for":[36,72],"the":[37,52,55,73,85,89,98,107,134,141,151],"global":[38],"inverse":[44],"probability-weighted":[45],"and":[46,162,171],"method.":[50,103],"Combining":[51],"advantages":[53,108],"of":[54,64,75,88,101,109,129,146,155,158,166,175,178],"alternating":[61],"direction":[62],"method":[63,111],"multipliers":[65],"algorithm,":[66],"algorithm":[69],"is":[70,138],"developed":[71],"calculation":[74],"our":[76,102,110],"proposed":[77,90],"estimator.":[78,91],"Under":[79],"some":[80],"mild":[81],"assumptions,":[82],"establish":[84],"asymptotic":[86],"properties":[87],"Simulation":[92],"studies":[93],"are":[94],"performed":[95],"access":[97],"finite-sample":[99],"performance":[100],"We":[104],"further":[105],"illustrate":[106],"by":[112,133,140],"real-world":[114],"dataset":[115],"from":[116],"Beijing":[117],"Municipal":[118],"Environmental":[119],"Monitoring":[120],"Center.Keywords:":[121],"ADMM":[122],"algorithmCSLDistributed":[123],"optimizationIPWMAR":[124],"Disclosure":[125],"statementNo":[126],"potential":[127],"conflict":[128],"interest":[130],"was":[131],"reported":[132],"authors.Additional":[135],"informationFundingThis":[136],"work":[137],"supported":[139],"National":[142],"Natural":[143,152],"Science":[144,153,170],"Foundation":[145,154],"China":[147,159],"(NSFC)":[148],"(No.":[149,160,180],"12361059),":[150],"Henan":[156],"Province":[157],"222300420126)":[161],"Hubei":[163],"Key":[164],"Laboratory":[165],"Big":[167],"Data":[168],"in":[169],"Technology":[172],"(Wuhan":[173],"Library":[174],"Chinese":[176],"Academy":[177],"Science)":[179],"E3KF291001).":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}
