{"id":"https://openalex.org/W2005839292","doi":"https://doi.org/10.1080/03610910701569069","title":"On the Use of Adaptive Nearest Neighbors for Missing Value Imputation","display_name":"On the Use of Adaptive Nearest Neighbors for Missing Value Imputation","publication_year":2007,"publication_date":"2007-11-05","ids":{"openalex":"https://openalex.org/W2005839292","doi":"https://doi.org/10.1080/03610910701569069","mag":"2005839292"},"language":"en","primary_location":{"id":"doi:10.1080/03610910701569069","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910701569069","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/A5056545688","display_name":"Myoungshic Jhun","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]},{"id":"https://openalex.org/I1317225278","display_name":"Statistics Korea","ror":"https://ror.org/004g7jm05","country_code":"KR","type":"government","lineage":["https://openalex.org/I1317225278","https://openalex.org/I2801339556","https://openalex.org/I4210126005"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Myoungshic Jhun","raw_affiliation_strings":["Department of Statistics , Korea University , Seoul,  Korea","Dept. of Statistics, Korea University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Statistics , Korea University , Seoul,  Korea","institution_ids":["https://openalex.org/I197347611","https://openalex.org/I1317225278"]},{"raw_affiliation_string":"Dept. of Statistics, Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611","https://openalex.org/I1317225278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110112763","display_name":"Hyeong Chul Jeong","orcid":null},"institutions":[{"id":"https://openalex.org/I16764540","display_name":"University of Suwon","ror":"https://ror.org/03ysk5e42","country_code":"KR","type":"education","lineage":["https://openalex.org/I16764540"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyeong Chul Jeong","raw_affiliation_strings":["Department of Applied Statistics , The University of Suwon , Suwon,  Korea","Department of Applied Statistics , The University of Suwon , Suwon, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Applied Statistics , The University of Suwon , Suwon,  Korea","institution_ids":["https://openalex.org/I16764540"]},{"raw_affiliation_string":"Department of Applied Statistics , The University of Suwon , Suwon, Korea","institution_ids":["https://openalex.org/I16764540"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103221995","display_name":"Ja\u2010Yong Koo","orcid":"https://orcid.org/0000-0002-1035-6102"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]},{"id":"https://openalex.org/I1317225278","display_name":"Statistics Korea","ror":"https://ror.org/004g7jm05","country_code":"KR","type":"government","lineage":["https://openalex.org/I1317225278","https://openalex.org/I2801339556","https://openalex.org/I4210126005"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ja-Yong Koo","raw_affiliation_strings":["Department of Statistics , Korea University , Seoul,  Korea","Dept. of Statistics, Korea University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Statistics , Korea University , Seoul,  Korea","institution_ids":["https://openalex.org/I197347611","https://openalex.org/I1317225278"]},{"raw_affiliation_string":"Dept. of Statistics, Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611","https://openalex.org/I1317225278"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110112763"],"corresponding_institution_ids":["https://openalex.org/I16764540"],"apc_list":null,"apc_paid":null,"fwci":0.2679,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.57698963,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"36","issue":"6","first_page":"1275","last_page":"1286"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9936000108718872,"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/imputation","display_name":"Imputation (statistics)","score":0.909264087677002},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.8682518005371094},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6846388578414917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6299680471420288},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5421984195709229},{"id":"https://openalex.org/keywords/nearest-neighbour","display_name":"Nearest neighbour","score":0.5092081427574158},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.42672306299209595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3350745439529419},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3268962502479553},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3100179433822632},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26380860805511475},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2139447033405304}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.909264087677002},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.8682518005371094},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6846388578414917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6299680471420288},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5421984195709229},{"id":"https://openalex.org/C2983946233","wikidata":"https://www.wikidata.org/wiki/Q4088109","display_name":"Nearest neighbour","level":2,"score":0.5092081427574158},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.42672306299209595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3350745439529419},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3268962502479553},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3100179433822632},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26380860805511475},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2139447033405304}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610910701569069","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610910701569069","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1550443206","https://openalex.org/W1584512145","https://openalex.org/W1651215666","https://openalex.org/W1989076816","https://openalex.org/W1995880999","https://openalex.org/W2044758663","https://openalex.org/W2096863518","https://openalex.org/W2109205571","https://openalex.org/W2117135012","https://openalex.org/W2121159025","https://openalex.org/W2157795344","https://openalex.org/W2171118759","https://openalex.org/W2312873536","https://openalex.org/W4294107304","https://openalex.org/W4300187280"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549","https://openalex.org/W3123177881"],"abstract_inverted_index":{"A":[0],"popular":[1],"nonparametric":[2],"treatment":[3],"of":[4,18,26,30,52,61,72],"missing":[5,31,66,74],"value":[6],"imputation":[7,38,102],"uses":[8],"methods":[9],"based":[10,40,104],"on":[11,41,105],"k-nearest":[12,106],"neighbors,":[13,44],"where":[14],"the":[15,27,49,53,59,65,70,73,94,101],"number":[16,60],"k":[17],"nearest":[19,43],"neighbors":[20,62],"is":[21,78,91],"fixed":[22],"without":[23],"any":[24],"consideration":[25],"local":[28,50],"features":[29,51],"values.":[32,75],"This":[33],"article":[34],"proposes":[35],"an":[36],"alternative":[37],"method":[39,57,96,103],"adaptive":[42],"which":[45],"takes":[46],"into":[47],"account":[48],"data.":[54,89],"The":[55],"proposed":[56,95],"adapts":[58],"in":[63],"imputing":[64],"values":[67],"according":[68],"to":[69],"location":[71],"Efficiency":[76],"evaluation":[77],"then":[79],"gauged":[80],"through":[81],"simulation":[82],"studies":[83],"using":[84],"both":[85],"simulated":[86],"and":[87],"real":[88],"It":[90],"shown":[92],"that":[93],"has":[97],"distinct":[98],"advantages":[99],"over":[100],"neighbors.":[107]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-03-15T09:29:46.208133","created_date":"2025-10-10T00:00:00"}
