{"id":"https://openalex.org/W3093872600","doi":"https://doi.org/10.1080/00401706.2020.1811157","title":"Comment: Ridge Regression, Ranking Variables and Improved Principal Component Regression","display_name":"Comment: Ridge Regression, Ranking Variables and Improved Principal Component Regression","publication_year":2020,"publication_date":"2020-10-01","ids":{"openalex":"https://openalex.org/W3093872600","doi":"https://doi.org/10.1080/00401706.2020.1811157","mag":"3093872600"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.2020.1811157","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2020.1811157","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"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":"Technometrics","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/A5026555045","display_name":"Nam-Hee Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I1320320070","display_name":"United States Food and Drug Administration","ror":"https://ror.org/034xvzb47","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1320320070"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nam-Hee Choi","raw_affiliation_strings":["Food and Drug Administration, Silver Spring, MD;;"],"affiliations":[{"raw_affiliation_string":"Food and Drug Administration, Silver Spring, MD;;","institution_ids":["https://openalex.org/I1320320070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013706483","display_name":"Kerby Shedden","orcid":"https://orcid.org/0000-0001-7222-6664"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kerby Shedden","raw_affiliation_strings":["Department of Statistics, University of Michigan, Ann Arbor, MI"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Michigan, Ann Arbor, MI","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027989356","display_name":"Gongjun Xu","orcid":"https://orcid.org/0000-0003-4023-5413"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gongjun Xu","raw_affiliation_strings":["Department of Statistics, University of Michigan, Ann Arbor, MI"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Michigan, Ann Arbor, MI","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100686653","display_name":"Xuefei Zhang","orcid":"https://orcid.org/0000-0001-9187-2004"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuefei Zhang","raw_affiliation_strings":["Department of Statistics, University of Michigan, Ann Arbor, MI"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Michigan, Ann Arbor, MI","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101765550","display_name":"Ji Zhu","orcid":"https://orcid.org/0000-0002-7812-5378"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ji Zhu","raw_affiliation_strings":["Department of Statistics, University of Michigan, Ann Arbor, MI"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Michigan, Ann Arbor, MI","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101765550"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.6613,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72769734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"62","issue":"4","first_page":"451","last_page":"455"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9916999936103821,"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":0.9916999936103821,"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":0.9890999794006348,"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/T10594","display_name":"Genetic and phenotypic traits in livestock","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/principal-component-regression","display_name":"Principal component regression","score":0.7644762992858887},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.7377554774284363},{"id":"https://openalex.org/keywords/ridge","display_name":"Ridge","score":0.669732391834259},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6668436527252197},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6624118089675903},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.6007527709007263},{"id":"https://openalex.org/keywords/segmented-regression","display_name":"Segmented regression","score":0.5592343211174011},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5088984966278076},{"id":"https://openalex.org/keywords/regression-diagnostic","display_name":"Regression diagnostic","score":0.46961575746536255},{"id":"https://openalex.org/keywords/cross-sectional-regression","display_name":"Cross-sectional regression","score":0.43950724601745605},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4365687966346741},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.42071279883384705},{"id":"https://openalex.org/keywords/elastic-net-regularization","display_name":"Elastic net regularization","score":0.41252830624580383},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.39560016989707947},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3320404589176178},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.30437517166137695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2435516119003296},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1854107677936554},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.052960991859436035}],"concepts":[{"id":"https://openalex.org/C74887250","wikidata":"https://www.wikidata.org/wiki/Q3455892","display_name":"Principal component regression","level":3,"score":0.7644762992858887},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.7377554774284363},{"id":"https://openalex.org/C32277403","wikidata":"https://www.wikidata.org/wiki/Q740445","display_name":"Ridge","level":2,"score":0.669732391834259},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6668436527252197},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6624118089675903},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6007527709007263},{"id":"https://openalex.org/C35519122","wikidata":"https://www.wikidata.org/wiki/Q3775699","display_name":"Segmented regression","level":4,"score":0.5592343211174011},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5088984966278076},{"id":"https://openalex.org/C57381214","wikidata":"https://www.wikidata.org/wiki/Q55631393","display_name":"Regression diagnostic","level":4,"score":0.46961575746536255},{"id":"https://openalex.org/C90157343","wikidata":"https://www.wikidata.org/wiki/Q5188196","display_name":"Cross-sectional regression","level":4,"score":0.43950724601745605},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4365687966346741},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.42071279883384705},{"id":"https://openalex.org/C203868755","wikidata":"https://www.wikidata.org/wiki/Q5353562","display_name":"Elastic net regularization","level":3,"score":0.41252830624580383},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.39560016989707947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3320404589176178},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.30437517166137695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2435516119003296},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1854107677936554},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.052960991859436035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/00401706.2020.1811157","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2020.1811157","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"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":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2012816719","https://openalex.org/W2038923046","https://openalex.org/W2047028564","https://openalex.org/W2053834050","https://openalex.org/W2058401000","https://openalex.org/W2122825543","https://openalex.org/W2135046866","https://openalex.org/W2148981095","https://openalex.org/W3014615384","https://openalex.org/W4234698323"],"related_works":["https://openalex.org/W1523442101","https://openalex.org/W603221366","https://openalex.org/W1496469336","https://openalex.org/W4251253833","https://openalex.org/W2240678196","https://openalex.org/W816849645","https://openalex.org/W4210660526","https://openalex.org/W1579729625","https://openalex.org/W2958976359","https://openalex.org/W1488808450"],"abstract_inverted_index":{"Hoerl":[0],"and":[1,9],"Kennard\u2019s":[2],"(1970)":[3],"ridge":[4],"regression":[5],"is":[6],"an":[7],"early":[8],"influential":[10],"instance":[11],"of":[12,20],"regularization":[13],"being":[14],"used":[15,23],"to":[16],"improve":[17],"the":[18],"performance":[19],"a":[21],"widely":[22],"modeling":[24],"technique.":[25],"Roughly":[26],"30":[27],"years":[28],"later,...":[29]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-21T08:13:44.787528","created_date":"2025-10-10T00:00:00"}