{"id":"https://openalex.org/W4282958563","doi":"https://doi.org/10.1007/s00180-022-01242-3","title":"Model aggregation for doubly divided data with large size and large dimension","display_name":"Model aggregation for doubly divided data with large size and large dimension","publication_year":2022,"publication_date":"2022-06-16","ids":{"openalex":"https://openalex.org/W4282958563","doi":"https://doi.org/10.1007/s00180-022-01242-3"},"language":"en","primary_location":{"id":"doi:10.1007/s00180-022-01242-3","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s00180-022-01242-3","pdf_url":null,"source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","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/A5044332523","display_name":"Baihua He","orcid":"https://orcid.org/0000-0002-9717-8053"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baihua He","raw_affiliation_strings":["School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416810","display_name":"Yanyan Liu","orcid":"https://orcid.org/0000-0002-1405-7345"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyan Liu","raw_affiliation_strings":["School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080151722","display_name":"Guosheng Yin","orcid":"https://orcid.org/0000-0003-3276-1392"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Guosheng Yin","raw_affiliation_strings":["Department of Statistics and Actuarial Science, University of Hong Kong, Pokfulam Road, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Actuarial Science, University of Hong Kong, Pokfulam Road, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032522521","display_name":"Yuanshan Wu","orcid":"https://orcid.org/0000-0002-2121-8952"},"institutions":[{"id":"https://openalex.org/I158934434","display_name":"Zhongnan University of Economics and Law","ror":"https://ror.org/04yqxxq63","country_code":"CN","type":"education","lineage":["https://openalex.org/I158934434"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuanshan Wu","raw_affiliation_strings":["School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, Hubei, 430073, China"],"raw_orcid":"https://orcid.org/0000-0002-2121-8952","affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, Hubei, 430073, China","institution_ids":["https://openalex.org/I158934434"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032522521"],"corresponding_institution_ids":["https://openalex.org/I158934434"],"apc_list":{"value":3090,"currency":"USD","value_usd":3090},"apc_paid":null,"fwci":0.232,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58654973,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"38","issue":"1","first_page":"509","last_page":"529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9965000152587891,"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"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9965000152587891,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9914000034332275,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9879000186920166,"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/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.8686710596084595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7117041349411011},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.7028994560241699},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.5782037377357483},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.557981014251709},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4701671302318573},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4430301785469055},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4099920094013214},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33789360523223877},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2732087969779968},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16277438402175903},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15698963403701782}],"concepts":[{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.8686710596084595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7117041349411011},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.7028994560241699},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.5782037377357483},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.557981014251709},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4701671302318573},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4430301785469055},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4099920094013214},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33789360523223877},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2732087969779968},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16277438402175903},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15698963403701782},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s00180-022-01242-3","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s00180-022-01242-3","pdf_url":null,"source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:compst:v:38:y:2023:i:1:d:10.1007_s00180-022-01242-3","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s00180-022-01242-3","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,"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"}],"best_oa_location":null,"sustainable_development_goals":[],"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":32,"referenced_works":["https://openalex.org/W27682692","https://openalex.org/W1603903339","https://openalex.org/W1694091468","https://openalex.org/W1800261609","https://openalex.org/W1994672023","https://openalex.org/W2009435671","https://openalex.org/W2011689122","https://openalex.org/W2025349443","https://openalex.org/W2028763699","https://openalex.org/W2052025831","https://openalex.org/W2057331441","https://openalex.org/W2062579211","https://openalex.org/W2078502317","https://openalex.org/W2108443364","https://openalex.org/W2119738171","https://openalex.org/W2122196572","https://openalex.org/W2125251038","https://openalex.org/W2129122308","https://openalex.org/W2141895117","https://openalex.org/W2142246398","https://openalex.org/W2146774335","https://openalex.org/W2151565294","https://openalex.org/W2154560360","https://openalex.org/W2166436449","https://openalex.org/W2611757366","https://openalex.org/W2801571965","https://openalex.org/W2963126228","https://openalex.org/W2964231067","https://openalex.org/W3102942031","https://openalex.org/W3103397206","https://openalex.org/W3103741939","https://openalex.org/W4233413206"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W408992594","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}