{"id":"https://openalex.org/W4388213009","doi":"https://doi.org/10.32614/rj-2023-033","title":"Robust\u00a0Functional\u00a0Linear\u00a0Regression\u00a0Models","display_name":"Robust\u00a0Functional\u00a0Linear\u00a0Regression\u00a0Models","publication_year":2023,"publication_date":"2023-09-07","ids":{"openalex":"https://openalex.org/W4388213009","doi":"https://doi.org/10.32614/rj-2023-033"},"language":"lt","primary_location":{"id":"doi:10.32614/rj-2023-033","is_oa":true,"landing_page_url":"http://dx.doi.org/10.32614/rj-2023-033","pdf_url":"https://journal.r-project.org/articles/RJ-2023-033/RJ-2023-033.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journal.r-project.org/articles/RJ-2023-033/RJ-2023-033.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037497633","display_name":"Ufuk Beyazta\u015f","orcid":"https://orcid.org/0000-0002-5208-4950"},"institutions":[{"id":"https://openalex.org/I74897591","display_name":"Marmara University","ror":"https://ror.org/02kswqa67","country_code":"TR","type":"education","lineage":["https://openalex.org/I74897591"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ufuk Beyaztas","raw_affiliation_strings":["Marmara University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Marmara University","institution_ids":["https://openalex.org/I74897591"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087947210","display_name":"Han Lin Shang","orcid":"https://orcid.org/0000-0003-1769-6430"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Han Lin Shang","raw_affiliation_strings":["Macquarie University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie University","institution_ids":["https://openalex.org/I99043593"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2456,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81203381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"15","issue":"1","first_page":"212","last_page":"233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.557200014591217,"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":0.557200014591217,"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/functional-data-analysis","display_name":"Functional data analysis","score":0.8198626041412354},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7885701656341553},{"id":"https://openalex.org/keywords/functional-principal-component-analysis","display_name":"Functional principal component analysis","score":0.7380161285400391},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.613226592540741},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.6084750294685364},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6019331812858582},{"id":"https://openalex.org/keywords/scalar","display_name":"Scalar (mathematics)","score":0.5669342875480652},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5247464179992676},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.51668381690979},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5107669830322266},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5013890266418457},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45207950472831726},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4506063163280487},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.4278997480869293},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4278542399406433},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.36171215772628784},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34476393461227417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32055431604385376},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31761229038238525},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2953624725341797},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.08353176712989807}],"concepts":[{"id":"https://openalex.org/C51820054","wikidata":"https://www.wikidata.org/wiki/Q5508814","display_name":"Functional data analysis","level":2,"score":0.8198626041412354},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7885701656341553},{"id":"https://openalex.org/C71176878","wikidata":"https://www.wikidata.org/wiki/Q17014987","display_name":"Functional principal component analysis","level":3,"score":0.7380161285400391},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.613226592540741},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.6084750294685364},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6019331812858582},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.5669342875480652},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5247464179992676},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.51668381690979},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5107669830322266},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5013890266418457},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45207950472831726},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4506063163280487},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.4278997480869293},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4278542399406433},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.36171215772628784},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34476393461227417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32055431604385376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31761229038238525},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2953624725341797},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.08353176712989807},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.32614/rj-2023-033","is_oa":true,"landing_page_url":"http://dx.doi.org/10.32614/rj-2023-033","pdf_url":"https://journal.r-project.org/articles/RJ-2023-033/RJ-2023-033.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},{"id":"pmh:oai:openaccess.marmara.edu.tr:11424/294271","is_oa":true,"landing_page_url":"https://journal.r-project.org/articles/RJ-2023-033/","pdf_url":null,"source":{"id":"https://openalex.org/S7407055305","display_name":"Marmara University Open Access System","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.32614/rj-2023-033","is_oa":true,"landing_page_url":"http://dx.doi.org/10.32614/rj-2023-033","pdf_url":"https://journal.r-project.org/articles/RJ-2023-033/RJ-2023-033.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8782586941","display_name":"Fonksiyonel Veri Analizinde Makine \u00d6\u011frenmesi Ve K\u0131smi En K\u00fc\u00e7\u00fck Kareler Tabanl\u0131 Yeni \u00d6ng\u00f6r\u00fc, Tahmin Ve S\u0131n\u0131fland\u0131rma Y\u00f6ntemleri","funder_award_id":"120F270","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"}],"funders":[{"id":"https://openalex.org/F4320322626","display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","ror":"https://ror.org/04w9kkr77"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388213009.pdf","grobid_xml":"https://content.openalex.org/works/W4388213009.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W8449462","https://openalex.org/W59540123","https://openalex.org/W163215356","https://openalex.org/W621923488","https://openalex.org/W649348608","https://openalex.org/W1597891688","https://openalex.org/W1854313250","https://openalex.org/W1964241258","https://openalex.org/W1964782536","https://openalex.org/W1969842547","https://openalex.org/W1974498411","https://openalex.org/W1978002454","https://openalex.org/W1981015491","https://openalex.org/W1981606742","https://openalex.org/W1981673657","https://openalex.org/W1991308917","https://openalex.org/W2001853007","https://openalex.org/W2002711615","https://openalex.org/W2011627547","https://openalex.org/W2013365346","https://openalex.org/W2024524669","https://openalex.org/W2027515083","https://openalex.org/W2031381243","https://openalex.org/W2038580754","https://openalex.org/W2039470961","https://openalex.org/W2058496912","https://openalex.org/W2061833611","https://openalex.org/W2067165060","https://openalex.org/W2069998832","https://openalex.org/W2079815272","https://openalex.org/W2081862629","https://openalex.org/W2094675242","https://openalex.org/W2102854765","https://openalex.org/W2134874509","https://openalex.org/W2152280271","https://openalex.org/W2152701363","https://openalex.org/W2180438109","https://openalex.org/W2191641151","https://openalex.org/W2312731870","https://openalex.org/W2602734281","https://openalex.org/W2770018807","https://openalex.org/W2798816298","https://openalex.org/W2807360184","https://openalex.org/W2810783072","https://openalex.org/W2971886787","https://openalex.org/W2999845560","https://openalex.org/W3037036111","https://openalex.org/W3046155657","https://openalex.org/W3098296952","https://openalex.org/W3098777574","https://openalex.org/W3100980645","https://openalex.org/W3103642488","https://openalex.org/W3124806422","https://openalex.org/W4221034886","https://openalex.org/W4223893183","https://openalex.org/W4239038476","https://openalex.org/W4250766106","https://openalex.org/W4251011993","https://openalex.org/W4288400169","https://openalex.org/W4292156489","https://openalex.org/W4399650373"],"related_works":["https://openalex.org/W2299080873","https://openalex.org/W273216563","https://openalex.org/W2963184067","https://openalex.org/W2605967135","https://openalex.org/W2056592727","https://openalex.org/W1925427981","https://openalex.org/W3046155657","https://openalex.org/W4288245065","https://openalex.org/W2970478921","https://openalex.org/W1981015491"],"abstract_inverted_index":{"With":[0],"advancements":[1],"in":[2,30,83,129],"technology":[3],"and":[4,26,42,58,98,122,125,140],"data":[5,11],"storage,":[6],"the":[7,50,54,87,91,115,130],"availability":[8],"of":[9,89,132],"functional":[10,36,51,59,116],"whose":[12],"sample":[13],"observations":[14],"are":[15,68,74,81,136],"recorded":[16],"over":[17],"a":[18,102],"continuum,":[19],"such":[20],"as":[21],"time,":[22],"wavelength,":[23],"space":[24],"grids,":[25],"depth,":[27],"progressively":[28],"increases":[29],"almost":[31],"all":[32],"scientific":[33],"branches.":[34],"The":[35,134],"linear":[37],"regression":[38,127],"models,":[39],"including":[40],"scalar-on-function":[41,124],"function-on-function,":[43],"have":[44],"become":[45],"popular":[46],"tools":[47],"for":[48,120],"exploring":[49],"relationships":[52],"between":[53],"scalar":[55],"response-functional":[56,60],"predictors":[57],"predictors,":[61],"respectively.":[62],"However,":[63],"most":[64],"existing":[65],"estimation":[66,97],"strategies":[67],"based":[69],"on":[70],"non-robust":[71,92],"estimators":[72],"that":[73],"seriously":[75],"hindered":[76],"by":[77],"outlying":[78],"observations,":[79],"which":[80],"common":[82],"applied":[84],"research.":[85],"In":[86],"case":[88],"outliers,":[90],"methods":[93,112,135],"lead":[94],"to":[95],"undesirable":[96],"prediction":[99],"results.":[100],"Using":[101],"readily-available":[103],"[R]{.sans-serif}":[104],"package":[105],"robflreg,":[106],"this":[107],"paper":[108],"presents":[109],"several":[110],"robust":[111],"build":[113],"upon":[114],"principal":[117],"component":[118],"analysis":[119],"modeling":[121],"predicting":[123],"function-on-function":[126],"models":[128],"presence":[131],"outliers.":[133],"demonstrated":[137],"via":[138],"simulated":[139],"empirical":[141],"datasets.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}