{"id":"https://openalex.org/W2793586077","doi":"https://doi.org/10.1080/03610918.2018.1433840","title":"A multiple-case deletion approach for detecting influential points in high-dimensional regression","display_name":"A multiple-case deletion approach for detecting influential points in high-dimensional regression","publication_year":2018,"publication_date":"2018-02-25","ids":{"openalex":"https://openalex.org/W2793586077","doi":"https://doi.org/10.1080/03610918.2018.1433840","mag":"2793586077"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2018.1433840","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2018.1433840","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/A5100453553","display_name":"Tao Wang","orcid":"https://orcid.org/0000-0002-5728-6463"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]},{"id":"https://openalex.org/I4210147117","display_name":"Huaiyin Normal University","ror":"https://ror.org/03xvggv44","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147117"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wang","raw_affiliation_strings":["Institute of Statistics and LPMC, Nankai University, Tianjin City, P. R. China","School of Mathematical Sciences, Huaiyin Normal University, Huaian City, P. R. China"],"affiliations":[{"raw_affiliation_string":"Institute of Statistics and LPMC, Nankai University, Tianjin City, P. R. China","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"School of Mathematical Sciences, Huaiyin Normal University, Huaian City, P. R. China","institution_ids":["https://openalex.org/I4210147117"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091715452","display_name":"Qun Li","orcid":"https://orcid.org/0000-0002-5501-8262"},"institutions":[{"id":"https://openalex.org/I227486990","display_name":"University of Szeged","ror":"https://ror.org/01pnej532","country_code":"HU","type":"education","lineage":["https://openalex.org/I227486990"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Qun Li","raw_affiliation_strings":["Department of Physiology, University of Szeged, Szeged, Hungary"],"affiliations":[{"raw_affiliation_string":"Department of Physiology, University of Szeged, Szeged, Hungary","institution_ids":["https://openalex.org/I227486990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045217211","display_name":"Qing-pei Zang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210147117","display_name":"Huaiyin Normal University","ror":"https://ror.org/03xvggv44","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147117"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingpei Zang","raw_affiliation_strings":["School of Mathematical Sciences, Huaiyin Normal University, Huaian City, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Huaiyin Normal University, Huaian City, P. R. China","institution_ids":["https://openalex.org/I4210147117"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100398093","display_name":"Zhonghua Li","orcid":"https://orcid.org/0000-0002-0927-226X"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhonghua Li","raw_affiliation_strings":["Institute of Statistics and LPMC, Nankai University, Tianjin City, P. R. China"],"affiliations":[{"raw_affiliation_string":"Institute of Statistics and LPMC, Nankai University, Tianjin City, P. R. China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100398093"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":1.2208,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.80529344,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"48","issue":"7","first_page":"2065","last_page":"2082"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.993399977684021,"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":0.993399977684021,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9814000129699707,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6230180859565735},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6051924228668213},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5763470530509949},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5710432529449463},{"id":"https://openalex.org/keywords/prime","display_name":"Prime (order theory)","score":0.48579835891723633},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4815242886543274},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4223785400390625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36384135484695435},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3472439646720886},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32284700870513916},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29319220781326294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27404147386550903}],"concepts":[{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6230180859565735},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6051924228668213},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5763470530509949},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5710432529449463},{"id":"https://openalex.org/C184992742","wikidata":"https://www.wikidata.org/wiki/Q7243229","display_name":"Prime (order theory)","level":2,"score":0.48579835891723633},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4815242886543274},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4223785400390625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36384135484695435},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3472439646720886},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32284700870513916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29319220781326294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27404147386550903},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2018.1433840","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2018.1433840","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":[],"awards":[{"id":"https://openalex.org/G6147173942","display_name":null,"funder_award_id":"11571191","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7912291713","display_name":null,"funder_award_id":"11431006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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":0,"referenced_works":[],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"In":[0,60],"high-dimensional":[1,82],"regression,":[2],"the":[3,34,49,76,103,116,121,134,138],"presence":[4,50,77],"of":[5,33,51,78,102,109,137],"influential":[6,53,73,110],"observations":[7,54,74],"may":[8,45],"lead":[9],"to":[10,23,48],"inaccurate":[11],"analysis":[12,132],"results":[13],"so":[14],"that":[15,55,105],"it":[16],"is":[17,68,106],"a":[18,92,129],"prime":[19],"and":[20,43,96,128],"important":[21],"issue":[22],"detect":[24],"these":[25],"unusual":[26],"points":[27],"before":[28],"statistical":[29],"regression":[30],"analysis.":[31],"Most":[32],"traditional":[35],"approaches":[36],"are,":[37],"however,":[38],"based":[39],"on":[40],"single-case":[41],"diagnostics,":[42],"they":[44],"fail":[46],"due":[47],"multiple":[52,72],"suffer":[56],"from":[57],"masking":[58,79],"effects.":[59],"this":[61],"paper,":[62],"an":[63,98],"adaptive":[64],"multiple-case":[65,93],"deletion":[66,94],"approach":[67],"proposed":[69,139],"for":[70],"detecting":[71],"in":[75,81,115],"effects":[80],"regression.":[83],"The":[84],"procedure":[85],"contains":[86],"two":[87],"stages.":[88],"Firstly,":[89],"we":[90,119],"propose":[91],"technique,":[95],"obtain":[97],"approximate":[99],"clean":[100],"subset":[101],"data":[104,131],"presumably":[107],"free":[108],"observations.":[111],"To":[112],"enhance":[113],"efficiency,":[114],"second":[117],"stage,":[118],"refine":[120],"detection":[122],"rule.":[123],"Monte":[124],"Carlo":[125],"simulation":[126],"studies":[127],"real-life":[130],"investigate":[133],"effective":[135],"performance":[136],"procedure.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
