{"id":"https://openalex.org/W4394579166","doi":"https://doi.org/10.1007/s11222-024-10424-6","title":"Screen then select: a strategy for correlated predictors in high-dimensional quantile regression","display_name":"Screen then select: a strategy for correlated predictors in high-dimensional quantile regression","publication_year":2024,"publication_date":"2024-04-08","ids":{"openalex":"https://openalex.org/W4394579166","doi":"https://doi.org/10.1007/s11222-024-10424-6"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-024-10424-6","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s11222-024-10424-6","pdf_url":null,"source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"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":"Statistics and Computing","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/A5088187019","display_name":"Xuejun Jiang","orcid":"https://orcid.org/0000-0001-8966-8864"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuejun Jiang","raw_affiliation_strings":["Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054183212","display_name":"Yakun Liang","orcid":"https://orcid.org/0000-0002-5282-2511"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yakun Liang","raw_affiliation_strings":["Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080023492","display_name":"Haofeng Wang","orcid":"https://orcid.org/0000-0001-8175-5621"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Haofeng Wang","raw_affiliation_strings":["Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China","institution_ids":["https://openalex.org/I141568987"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080023492"],"corresponding_institution_ids":["https://openalex.org/I141568987"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":null,"fwci":2.9458,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.90236686,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"34","issue":"3","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":0.9991999864578247,"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":0.9991999864578247,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.991599977016449,"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/quantile-regression","display_name":"Quantile regression","score":0.7160204648971558},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5575717091560364},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.5269273519515991},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4957626760005951},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4957042932510376},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.47855693101882935},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4540089964866638},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44697463512420654},{"id":"https://openalex.org/keywords/high-dimensional","display_name":"High dimensional","score":0.43271875381469727},{"id":"https://openalex.org/keywords/cross-sectional-regression","display_name":"Cross-sectional regression","score":0.4221895933151245},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3793359398841858},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34227004647254944},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3304235339164734},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.19792848825454712}],"concepts":[{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.7160204648971558},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5575717091560364},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.5269273519515991},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4957626760005951},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4957042932510376},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.47855693101882935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4540089964866638},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44697463512420654},{"id":"https://openalex.org/C3019722297","wikidata":"https://www.wikidata.org/wiki/Q4440864","display_name":"High dimensional","level":2,"score":0.43271875381469727},{"id":"https://openalex.org/C90157343","wikidata":"https://www.wikidata.org/wiki/Q5188196","display_name":"Cross-sectional regression","level":4,"score":0.4221895933151245},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3793359398841858},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34227004647254944},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3304235339164734},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.19792848825454712},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11222-024-10424-6","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s11222-024-10424-6","pdf_url":null,"source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"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":"Statistics and Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G165964565","display_name":null,"funder_award_id":"12271238","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2057401296","display_name":null,"funder_award_id":"JCYJ20210324104803010","funder_id":"https://openalex.org/F4320336569","funder_display_name":"Shenzhen Science and Technology Innovation Program"},{"id":"https://openalex.org/G5552755503","display_name":null,"funder_award_id":"2017A030313012,","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320336569","display_name":"Shenzhen Science and Technology Innovation Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1580111774","https://openalex.org/W1881895402","https://openalex.org/W1965125844","https://openalex.org/W1972623885","https://openalex.org/W1979568080","https://openalex.org/W1986180958","https://openalex.org/W2003423725","https://openalex.org/W2012309718","https://openalex.org/W2020695240","https://openalex.org/W2035684306","https://openalex.org/W2043398720","https://openalex.org/W2074682976","https://openalex.org/W2078269124","https://openalex.org/W2091433838","https://openalex.org/W2118711140","https://openalex.org/W2120875981","https://openalex.org/W2122825543","https://openalex.org/W2135046866","https://openalex.org/W2136659330","https://openalex.org/W2154560360","https://openalex.org/W2163891305","https://openalex.org/W2164092415","https://openalex.org/W2317235261","https://openalex.org/W2941600398","https://openalex.org/W2949372305","https://openalex.org/W2968003962","https://openalex.org/W2994645496","https://openalex.org/W3037382667","https://openalex.org/W3039617216","https://openalex.org/W3098306969","https://openalex.org/W3101066107","https://openalex.org/W3101498811","https://openalex.org/W3101883867","https://openalex.org/W3122008423","https://openalex.org/W3212645967","https://openalex.org/W4200031895","https://openalex.org/W4234698323","https://openalex.org/W4241653265","https://openalex.org/W4247571494","https://openalex.org/W4292363360","https://openalex.org/W4295136015","https://openalex.org/W4362471705"],"related_works":["https://openalex.org/W4206511378","https://openalex.org/W4206618949","https://openalex.org/W2526321210","https://openalex.org/W3205863630","https://openalex.org/W4318833145","https://openalex.org/W2364275385","https://openalex.org/W4388704167","https://openalex.org/W2007977664","https://openalex.org/W4376874882","https://openalex.org/W2224749288"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-01-21T23:30:37.877113","created_date":"2025-10-10T00:00:00"}