{"id":"https://openalex.org/W4293169039","doi":"https://doi.org/10.3390/sym14081617","title":"Robust Sparse Reduced-Rank Regression with Response Dependency","display_name":"Robust Sparse Reduced-Rank Regression with Response Dependency","publication_year":2022,"publication_date":"2022-08-06","ids":{"openalex":"https://openalex.org/W4293169039","doi":"https://doi.org/10.3390/sym14081617"},"language":"en","primary_location":{"id":"doi:10.3390/sym14081617","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14081617","pdf_url":"https://www.mdpi.com/2073-8994/14/8/1617/pdf?version=1661314300","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/14/8/1617/pdf?version=1661314300","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021231831","display_name":"Wenchen Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I146613903","display_name":"Shanghai Lixin University of Accounting and Finance","ror":"https://ror.org/02g81yf77","country_code":"CN","type":"education","lineage":["https://openalex.org/I146613903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenchen Liu","raw_affiliation_strings":["School of Statistics and Mathematics, Interdisciplinary Research Institute of Data Science, Shanghai Lixin University of Accounting and Finance, Shanghai 201209, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Interdisciplinary Research Institute of Data Science, Shanghai Lixin University of Accounting and Finance, Shanghai 201209, China","institution_ids":["https://openalex.org/I146613903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047190244","display_name":"Guanfu Liu","orcid":"https://orcid.org/0000-0003-1939-9405"},"institutions":[{"id":"https://openalex.org/I905225518","display_name":"Shanghai University of International Business and Economics","ror":"https://ror.org/031t68441","country_code":"CN","type":"education","lineage":["https://openalex.org/I905225518"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guanfu Liu","raw_affiliation_strings":["School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai 201620, China","institution_ids":["https://openalex.org/I905225518"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063966491","display_name":"Yincai Tang","orcid":"https://orcid.org/0000-0001-6756-6461"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yincai Tang","raw_affiliation_strings":["KLATASDS-MOE, School of Statistics, East China Normal University, Shanghai 200241, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KLATASDS-MOE, School of Statistics, East China Normal University, Shanghai 200241, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047190244"],"corresponding_institution_ids":["https://openalex.org/I905225518"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.2452,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58035154,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"14","issue":"8","first_page":"1617","last_page":"1617"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9983000159263611,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9983000159263611,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9944999814033508,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9883000254631042,"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/outlier","display_name":"Outlier","score":0.6773466467857361},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6277647018432617},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6007376909255981},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5792874693870544},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.5570735931396484},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.53253173828125},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.49667221307754517},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.47582319378852844},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.44877398014068604},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.44629722833633423},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3715841472148895},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3609178960323334}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6773466467857361},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6277647018432617},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6007376909255981},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5792874693870544},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.5570735931396484},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.53253173828125},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.49667221307754517},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.47582319378852844},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.44877398014068604},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.44629722833633423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3715841472148895},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3609178960323334},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym14081617","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14081617","pdf_url":"https://www.mdpi.com/2073-8994/14/8/1617/pdf?version=1661314300","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5103b48ba9fe46809f31b90ade4c79b3","is_oa":true,"landing_page_url":"https://doaj.org/article/5103b48ba9fe46809f31b90ade4c79b3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 14, Iss 8, p 1617 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/14/8/1617/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym14081617","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym14081617","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14081617","pdf_url":"https://www.mdpi.com/2073-8994/14/8/1617/pdf?version=1661314300","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4293169039.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1966315074","https://openalex.org/W1968480053","https://openalex.org/W1969515697","https://openalex.org/W2034133761","https://openalex.org/W2045022844","https://openalex.org/W2054121219","https://openalex.org/W2058381303","https://openalex.org/W2081531193","https://openalex.org/W2081746825","https://openalex.org/W2105760337","https://openalex.org/W2112895071","https://openalex.org/W2125536150","https://openalex.org/W2131230871","https://openalex.org/W2132555912","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2141366416","https://openalex.org/W2586353914","https://openalex.org/W2589471818","https://openalex.org/W2770877241","https://openalex.org/W2954296989","https://openalex.org/W2963826549","https://openalex.org/W2986432779","https://openalex.org/W2989166075","https://openalex.org/W3005194147","https://openalex.org/W3098453412","https://openalex.org/W3102567422","https://openalex.org/W3103211861","https://openalex.org/W3211265568","https://openalex.org/W4251038355","https://openalex.org/W6733614249"],"related_works":["https://openalex.org/W3121734683","https://openalex.org/W4210813465","https://openalex.org/W2085680114","https://openalex.org/W1600426151","https://openalex.org/W2921280830","https://openalex.org/W2126916073","https://openalex.org/W2887132723","https://openalex.org/W1833314573","https://openalex.org/W2886934452","https://openalex.org/W2024369332"],"abstract_inverted_index":{"In":[0],"multiple":[1,37],"response":[2,28,38],"regression,":[3,39],"the":[4,15,27,32,36,43,84,97,102,131],"reduced":[5,46,134,144],"rank":[6,47,135,145],"regression":[7,48,146],"model":[8,18,72],"is":[9,52,79,127],"an":[10],"effective":[11],"method":[12,41,126,140,157],"to":[13,113,129],"reduce":[14],"number":[16,98],"of":[17,24,35,70,99,117],"parameters":[19],"and":[20,62,83,106,152,165],"it":[21],"takes":[22],"advantage":[23],"interrelation":[25],"among":[26],"variables.":[29],"To":[30],"improve":[31],"prediction":[33,163],"performance":[34,160],"a":[40,74,80,92,123,149],"for":[42],"sparse":[44,133],"robust":[45,132],"with":[49,122,141],"covariance":[50,63,85,124],"estimation(Cov-SR4)":[51],"proposed,":[53],"which":[54,78],"can":[55,110],"carry":[56],"out":[57],"variable":[58,166],"selection,":[59],"outlier":[60],"detection,":[61],"estimation":[64,125],"simultaneously.":[65],"The":[66],"random":[67],"error":[68,164],"term":[69],"this":[71],"follows":[73],"multivariate":[75],"normal":[76],"distribution":[77,82],"symmetric":[81,93],"matrix":[86,89,94],"or":[87],"precision":[88],"must":[90],"be":[91,111],"that":[95],"reduces":[96],"parameters.":[100],"Both":[101],"element-wise":[103],"penalty":[104,108],"function":[105,109],"row-wise":[107],"used":[112],"handle":[114],"different":[115],"types":[116],"outliers.":[118],"A":[119],"numerical":[120],"algorithm":[121],"proposed":[128],"solve":[130],"regression.":[136],"We":[137],"compare":[138],"our":[139],"three":[142],"recent":[143],"methods":[147],"in":[148,162],"simulation":[150],"study":[151],"real":[153],"data":[154],"analysis.":[155],"Our":[156],"exhibits":[158],"competitive":[159],"both":[161],"selection":[167],"accuracy.":[168]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}
