{"id":"https://openalex.org/W3106505499","doi":"https://doi.org/10.3233/faia200695","title":"Comparison of Two Estimators of the Regression Coefficient Vector Under Pitman\u2019s Closeness Criterion","display_name":"Comparison of Two Estimators of the Regression Coefficient Vector Under Pitman\u2019s Closeness Criterion","publication_year":2020,"publication_date":"2020-11-09","ids":{"openalex":"https://openalex.org/W3106505499","doi":"https://doi.org/10.3233/faia200695","mag":"3106505499"},"language":"en","primary_location":{"id":"doi:10.3233/faia200695","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia200695","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200695","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200695","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":["Chongqing Key Laboratory of Complex Data Analysis & Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing","Chongqing Key Laboratory of Complex Data Analysis & Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing 402160, China"],"affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Complex Data Analysis & Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing","institution_ids":["https://openalex.org/I4210110609"]},{"raw_affiliation_string":"Chongqing Key Laboratory of Complex Data Analysis & Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing 402160, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5046090893"],"corresponding_institution_ids":["https://openalex.org/I4210110609"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24953236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.994700014591217,"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":0.994700014591217,"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":0.9828000068664551,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9677000045776367,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/estimator","display_name":"Estimator","score":0.7831050157546997},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7702246904373169},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.7341956496238708},{"id":"https://openalex.org/keywords/ordinary-least-squares","display_name":"Ordinary least squares","score":0.7055734395980835},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6605560779571533},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5798929929733276},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4365465044975281},{"id":"https://openalex.org/keywords/generalized-least-squares","display_name":"Generalized least squares","score":0.4316272437572479},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.41905859112739563},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.04471546411514282}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7831050157546997},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7702246904373169},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.7341956496238708},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.7055734395980835},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6605560779571533},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5798929929733276},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4365465044975281},{"id":"https://openalex.org/C188649462","wikidata":"https://www.wikidata.org/wiki/Q2246261","display_name":"Generalized least squares","level":3,"score":0.4316272437572479},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.41905859112739563},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.04471546411514282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia200695","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia200695","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200695","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia200695","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia200695","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA200695","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1268546416","display_name":null,"funder_award_id":"KJQN2019013","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G1285799110","display_name":null,"funder_award_id":"cstc2019jcyj","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"},{"id":"https://openalex.org/G1848540877","display_name":null,"funder_award_id":"KJQN201901347","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G1963275062","display_name":null,"funder_award_id":"N201901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2120360867","display_name":null,"funder_award_id":"2019013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G30305142","display_name":null,"funder_award_id":"cstc2019jcyj-msxmX0379","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3214160367","display_name":null,"funder_award_id":"No. 11","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3239092656","display_name":null,"funder_award_id":"cstc20","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"},{"id":"https://openalex.org/G4196900772","display_name":null,"funder_award_id":"KJQN201901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5047028600","display_name":null,"funder_award_id":"KJQN201901","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G5167091242","display_name":null,"funder_award_id":"No. 1","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5169721444","display_name":null,"funder_award_id":"201901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5830261330","display_name":null,"funder_award_id":"jcyj-","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"},{"id":"https://openalex.org/G7198121513","display_name":null,"funder_award_id":"cstc2019jcyj-msxmX0379","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G7370511736","display_name":null,"funder_award_id":"11501072","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8318578667","display_name":null,"funder_award_id":"KJQN201901347","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G985501918","display_name":null,"funder_award_id":"cstc2019jcyj-msxmX0379","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324805","display_name":"Chongqing Municipal Education Commission","ror":"https://ror.org/031nm5713"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3106505499.pdf","grobid_xml":"https://content.openalex.org/works/W3106505499.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1985771424","https://openalex.org/W1987061334","https://openalex.org/W2001424819","https://openalex.org/W2008545906","https://openalex.org/W2020364685","https://openalex.org/W2060387858","https://openalex.org/W2973877048","https://openalex.org/W4231873503","https://openalex.org/W4250639140","https://openalex.org/W4255607367","https://openalex.org/W4256094775","https://openalex.org/W6600457431","https://openalex.org/W6601033504","https://openalex.org/W6601065604","https://openalex.org/W6602780416","https://openalex.org/W6819101108"],"related_works":["https://openalex.org/W1913529549","https://openalex.org/W2784244297","https://openalex.org/W2980575667","https://openalex.org/W2167126078","https://openalex.org/W4250719734","https://openalex.org/W1984191672","https://openalex.org/W2890271766","https://openalex.org/W2109595325","https://openalex.org/W4251541326","https://openalex.org/W1997130844"],"abstract_inverted_index":{"Schaffrin":[0],"and":[1,14,19,70,95],"Toutenburg":[2],"[1]":[3],"proposed":[4],"a":[5],"weighted":[6,25,67,92],"mixed":[7,26,68,93],"estimation":[8],"based":[9],"on":[10],"the":[11,15,24,31,37,49,52,56,63,66,71,77,88,91,96,102],"sample":[12],"information":[13],"stochastic":[16],"prior":[17],"information,":[18],"they":[20],"also":[21],"show":[22],"that":[23],"estimator":[27,35,69,75,94,100],"is":[28,84],"superior":[29],"to":[30,47,86],"ordinary":[32,72,97],"least":[33,73,98],"squares":[34,74,99],"under":[36,55,101],"mean":[38],"squared":[39],"error":[40],"criterion.":[41,59,80,105],"However,":[42],"there":[43],"has":[44],"no":[45],"paper":[46,61],"discuss":[48],"performance":[50,89],"of":[51,65,90],"two":[53],"estimators":[54],"Pitman\u2019s":[57,78,103],"closeness":[58,79,104],"This":[60],"presents":[62],"comparison":[64],"using":[76],"A":[81],"simulation":[82],"study":[83],"performed":[85],"illustrate":[87]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
