{"id":"https://openalex.org/W7117105337","doi":"https://doi.org/10.1007/s00180-025-01687-2","title":"Bayesian variable selection and estimation based on asymmetric squared loss in high dimensions","display_name":"Bayesian variable selection and estimation based on asymmetric squared loss in high dimensions","publication_year":2025,"publication_date":"2025-12-24","ids":{"openalex":"https://openalex.org/W7117105337","doi":"https://doi.org/10.1007/s00180-025-01687-2"},"language":"en","primary_location":{"id":"doi:10.1007/s00180-025-01687-2","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s00180-025-01687-2","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/A5121145401","display_name":"Xiangyu Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyu Shi","raw_affiliation_strings":["School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, 100124, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, 100124, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121212376","display_name":"Xiangyang Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyang Xu","raw_affiliation_strings":["School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, 100124, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, 100124, China","institution_ids":["https://openalex.org/I37796252","https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111231723","display_name":"Ruiyuan Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiyuan Cao","raw_affiliation_strings":["School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, 100124, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, 100124, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121190485","display_name":"Tianfa Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianfa Xie","raw_affiliation_strings":["School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, 100124, China"],"raw_orcid":"https://orcid.org/0000-0001-5817-0836","affiliations":[{"raw_affiliation_string":"School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, 100124, China","institution_ids":["https://openalex.org/I37796252","https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5121190485"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":{"value":2490,"currency":"EUR","value_usd":3090},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.6866941,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"41","issue":"1","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":0.9279999732971191,"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":0.9279999732971191,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.02160000056028366,"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":0.00800000037997961,"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/heteroscedasticity","display_name":"Heteroscedasticity","score":0.8790000081062317},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.650600016117096},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6031000018119812},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4894999861717224},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4715000092983246},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4311000108718872},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.41609999537467957},{"id":"https://openalex.org/keywords/homogeneity","display_name":"Homogeneity (statistics)","score":0.41429999470710754}],"concepts":[{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.8790000081062317},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.650600016117096},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6031000018119812},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5652999877929688},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5020999908447266},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4894999861717224},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4311000108718872},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.41609999537467957},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.41429999470710754},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4032000005245209},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.382999986410141},{"id":"https://openalex.org/C203868755","wikidata":"https://www.wikidata.org/wiki/Q5353562","display_name":"Elastic net regularization","level":3,"score":0.3815000057220459},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.37400001287460327},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3707999885082245},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.36719998717308044},{"id":"https://openalex.org/C37903108","wikidata":"https://www.wikidata.org/wiki/Q4874474","display_name":"Bayesian linear regression","level":4,"score":0.3521000146865845},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.35179999470710754},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.322299987077713},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.26829999685287476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s00180-025-01687-2","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s00180-025-01687-2","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1711911837","https://openalex.org/W1965125844","https://openalex.org/W1966411627","https://openalex.org/W1975083447","https://openalex.org/W1982652137","https://openalex.org/W1990885553","https://openalex.org/W1999974018","https://openalex.org/W2007069447","https://openalex.org/W2010441486","https://openalex.org/W2020925091","https://openalex.org/W2031817855","https://openalex.org/W2042590947","https://openalex.org/W2054100651","https://openalex.org/W2067558949","https://openalex.org/W2074682976","https://openalex.org/W2099413686","https://openalex.org/W2114169935","https://openalex.org/W2119444931","https://openalex.org/W2120875981","https://openalex.org/W2135046866","https://openalex.org/W2137620021","https://openalex.org/W2566065221","https://openalex.org/W2788365376","https://openalex.org/W2884758310","https://openalex.org/W3186659415","https://openalex.org/W4221033146","https://openalex.org/W4241653265","https://openalex.org/W4366222321","https://openalex.org/W4386847600","https://openalex.org/W4388320111","https://openalex.org/W4394912635"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-01-21T23:30:37.877113","created_date":"2025-12-24T00:00:00"}