{"id":"https://openalex.org/W2743806717","doi":"https://doi.org/10.1080/03610918.2017.1364384","title":"Performance of the almost unbiased ridge-type principal component estimator in logistic regression model","display_name":"Performance of the almost unbiased ridge-type principal component estimator in logistic regression model","publication_year":2017,"publication_date":"2017-08-09","ids":{"openalex":"https://openalex.org/W2743806717","doi":"https://doi.org/10.1080/03610918.2017.1364384","mag":"2743806717"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2017.1364384","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2017.1364384","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","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/A5046090893","display_name":"Jibo Wu","orcid":"https://orcid.org/0000-0001-6233-6704"},"institutions":[{"id":"https://openalex.org/I4210110609","display_name":"Chongqing University of Arts and Sciences","ror":"https://ror.org/01rcvq140","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110609"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jibo Wu","raw_affiliation_strings":["School of Mathematics and Finance, Chongqing University of Arts and Sciences, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Finance, Chongqing University of Arts and Sciences, Chongqing, China","institution_ids":["https://openalex.org/I4210110609"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037137668","display_name":"Yasin Asar","orcid":"https://orcid.org/0000-0003-1109-8456"},"institutions":[{"id":"https://openalex.org/I4210107659","display_name":"Necmettin Erbakan University","ror":"https://ror.org/013s3zh21","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210107659"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Yasin Asar","raw_affiliation_strings":["Department of Mathematics-Computer Sciences, Necmettin Erbakan University, Konya, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics-Computer Sciences, Necmettin Erbakan University, Konya, Turkey","institution_ids":["https://openalex.org/I4210107659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046090893"],"corresponding_institution_ids":["https://openalex.org/I4210110609"],"apc_list":null,"apc_paid":null,"fwci":0.6995,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74114574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"47","issue":"10","first_page":"2925","last_page":"2937"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9998999834060669,"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":0.9998999834060669,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.984499990940094,"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"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9542999863624573,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multicollinearity","display_name":"Multicollinearity","score":0.9117279052734375},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.7020555138587952},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6765969395637512},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6391655206680298},{"id":"https://openalex.org/keywords/principal-component-regression","display_name":"Principal component regression","score":0.6379901170730591},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.637448787689209},{"id":"https://openalex.org/keywords/minimum-variance-unbiased-estimator","display_name":"Minimum-variance unbiased estimator","score":0.6355412602424622},{"id":"https://openalex.org/keywords/bias-of-an-estimator","display_name":"Bias of an estimator","score":0.6244666576385498},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.59110426902771},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.584670901298523},{"id":"https://openalex.org/keywords/steins-unbiased-risk-estimate","display_name":"Stein's unbiased risk estimate","score":0.4333179295063019},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3227519392967224},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.31181126832962036}],"concepts":[{"id":"https://openalex.org/C189285262","wikidata":"https://www.wikidata.org/wiki/Q1332350","display_name":"Multicollinearity","level":3,"score":0.9117279052734375},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7020555138587952},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6765969395637512},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6391655206680298},{"id":"https://openalex.org/C74887250","wikidata":"https://www.wikidata.org/wiki/Q3455892","display_name":"Principal component regression","level":3,"score":0.6379901170730591},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.637448787689209},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.6355412602424622},{"id":"https://openalex.org/C191393472","wikidata":"https://www.wikidata.org/wiki/Q15222032","display_name":"Bias of an estimator","level":4,"score":0.6244666576385498},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.59110426902771},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.584670901298523},{"id":"https://openalex.org/C134962040","wikidata":"https://www.wikidata.org/wiki/Q7606742","display_name":"Stein's unbiased risk estimate","level":5,"score":0.4333179295063019},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3227519392967224},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.31181126832962036}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2017.1364384","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2017.1364384","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"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":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5099999904632568}],"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":19,"referenced_works":["https://openalex.org/W1579589741","https://openalex.org/W1963890906","https://openalex.org/W1973948212","https://openalex.org/W1985161831","https://openalex.org/W1988934215","https://openalex.org/W1995523953","https://openalex.org/W2002214384","https://openalex.org/W2012780689","https://openalex.org/W2020364685","https://openalex.org/W2037655921","https://openalex.org/W2067239684","https://openalex.org/W2073334899","https://openalex.org/W2106393550","https://openalex.org/W2139766869","https://openalex.org/W2187681455","https://openalex.org/W2292883286","https://openalex.org/W2396892949","https://openalex.org/W2943021792","https://openalex.org/W3171229311"],"related_works":["https://openalex.org/W2349547417","https://openalex.org/W2910434125","https://openalex.org/W4239491110","https://openalex.org/W2035998077","https://openalex.org/W4237435333","https://openalex.org/W4210503132","https://openalex.org/W3092888124","https://openalex.org/W2802667153","https://openalex.org/W2905202492","https://openalex.org/W2059813665"],"abstract_inverted_index":{"This":[0],"article":[1],"considers":[2],"some":[3],"different":[4],"parameter":[5],"estimation":[6],"methods":[7],"in":[8],"logistic":[9],"regression":[10],"model.":[11],"In":[12],"order":[13],"to":[14,52],"overcome":[15],"multicollinearity,":[16],"the":[17,32,54,57],"almost":[18],"unbiased":[19],"ridge-type":[20],"principal":[21],"component":[22],"estimator":[23,34],"is":[24,35],"proposed.":[25],"The":[26],"scalar":[27],"mean":[28],"squared":[29],"error":[30],"of":[31,56],"proposed":[33,58],"derived":[36],"and":[37,46],"its":[38],"properties":[39],"are":[40,50],"investigated.":[41],"Finally,":[42],"a":[43,47],"numerical":[44],"example":[45],"simulation":[48],"study":[49],"presented":[51],"show":[53],"performance":[55],"estimator.":[59]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
