{"id":"https://openalex.org/W2174672576","doi":"https://doi.org/10.1080/03610918.2019.1610442","title":"Robust mixture regression modeling based on the generalized M (GM)-estimation method","display_name":"Robust mixture regression modeling based on the generalized M (GM)-estimation method","publication_year":2019,"publication_date":"2019-05-12","ids":{"openalex":"https://openalex.org/W2174672576","doi":"https://doi.org/10.1080/03610918.2019.1610442","mag":"2174672576"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1610442","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1610442","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","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1511.07384.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032738070","display_name":"Fatma Zehra Do\u011fru","orcid":"https://orcid.org/0000-0001-8220-2375"},"institutions":[{"id":"https://openalex.org/I148202161","display_name":"Giresun University","ror":"https://ror.org/05szaq822","country_code":"TR","type":"education","lineage":["https://openalex.org/I148202161"]},{"id":"https://openalex.org/I149218525","display_name":"Ankara University","ror":"https://ror.org/01wntqw50","country_code":"TR","type":"education","lineage":["https://openalex.org/I149218525"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Fatma Zehra Do\u011fru","raw_affiliation_strings":["Faculty of Arts and Science Department of Statistics, Giresun University, Giresun, Turkey","Ankara University"],"raw_orcid":"https://orcid.org/0000-0001-8220-2375","affiliations":[{"raw_affiliation_string":"Faculty of Arts and Science Department of Statistics, Giresun University, Giresun, Turkey","institution_ids":["https://openalex.org/I148202161"]},{"raw_affiliation_string":"Ankara University","institution_ids":["https://openalex.org/I149218525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030549839","display_name":"Ol\u00e7ay Arslan","orcid":"https://orcid.org/0000-0002-7067-4997"},"institutions":[{"id":"https://openalex.org/I149218525","display_name":"Ankara University","ror":"https://ror.org/01wntqw50","country_code":"TR","type":"education","lineage":["https://openalex.org/I149218525"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Olcay Arslan","raw_affiliation_strings":["Faculty of Science Department of Statistics, Ankara University, Ankara, Turkey","Ankara University"],"raw_orcid":"https://orcid.org/0000-0002-7067-4997","affiliations":[{"raw_affiliation_string":"Faculty of Science Department of Statistics, Ankara University, Ankara, Turkey","institution_ids":["https://openalex.org/I149218525"]},{"raw_affiliation_string":"Ankara University","institution_ids":["https://openalex.org/I149218525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032738070"],"corresponding_institution_ids":["https://openalex.org/I148202161","https://openalex.org/I149218525"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00230774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":"9","first_page":"2643","last_page":"2665"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9980000257492065,"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":0.9980000257492065,"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":0.9825999736785889,"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/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9273999929428101,"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/outlier","display_name":"Outlier","score":0.8708024024963379},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.8227494955062866},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7766628265380859},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.6109969615936279},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5825847387313843},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5505266785621643},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5310542583465576},{"id":"https://openalex.org/keywords/robust-statistics","display_name":"Robust statistics","score":0.508366048336029},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.48963695764541626},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4744321405887604},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.46943095326423645},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4249807596206665},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3623843789100647}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8708024024963379},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.8227494955062866},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7766628265380859},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6109969615936279},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5825847387313843},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5505266785621643},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5310542583465576},{"id":"https://openalex.org/C67226441","wikidata":"https://www.wikidata.org/wiki/Q1665389","display_name":"Robust statistics","level":3,"score":0.508366048336029},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.48963695764541626},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4744321405887604},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.46943095326423645},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4249807596206665},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3623843789100647},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/03610918.2019.1610442","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1610442","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"},{"id":"mag:2174672576","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1511.07384.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1511.07384","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1511.07384","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"mag:2174672576","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1511.07384.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W36711357","https://openalex.org/W149129625","https://openalex.org/W168241150","https://openalex.org/W311864731","https://openalex.org/W656292915","https://openalex.org/W1545074870","https://openalex.org/W1963925817","https://openalex.org/W1967484865","https://openalex.org/W1967969088","https://openalex.org/W1978900605","https://openalex.org/W1980262437","https://openalex.org/W1980503918","https://openalex.org/W1982182504","https://openalex.org/W1982914322","https://openalex.org/W1994296756","https://openalex.org/W1994888851","https://openalex.org/W2011627547","https://openalex.org/W2012532348","https://openalex.org/W2012712694","https://openalex.org/W2025691140","https://openalex.org/W2035753170","https://openalex.org/W2048298626","https://openalex.org/W2049419088","https://openalex.org/W2049633694","https://openalex.org/W2065209684","https://openalex.org/W2065432682","https://openalex.org/W2065742895","https://openalex.org/W2069519120","https://openalex.org/W2090268867","https://openalex.org/W2109785413","https://openalex.org/W2109820980","https://openalex.org/W2112905646","https://openalex.org/W2137354923","https://openalex.org/W2152922857","https://openalex.org/W2181759474","https://openalex.org/W2255476066","https://openalex.org/W2308181013","https://openalex.org/W2334370562","https://openalex.org/W2488678869","https://openalex.org/W2489822048","https://openalex.org/W2498631646","https://openalex.org/W2547713311","https://openalex.org/W2553186019","https://openalex.org/W3100686658","https://openalex.org/W3106889297","https://openalex.org/W3121736584","https://openalex.org/W4205806204","https://openalex.org/W4243563432","https://openalex.org/W4255230573"],"related_works":["https://openalex.org/W2566526665","https://openalex.org/W2025691140","https://openalex.org/W3147869675","https://openalex.org/W2889969537","https://openalex.org/W2953577636","https://openalex.org/W2975693586","https://openalex.org/W1981088744","https://openalex.org/W2277412672","https://openalex.org/W2063650929","https://openalex.org/W2607201789","https://openalex.org/W3103547578","https://openalex.org/W2953271812","https://openalex.org/W2260905210","https://openalex.org/W1816222873","https://openalex.org/W2805157711","https://openalex.org/W2029489153","https://openalex.org/W1779073390","https://openalex.org/W3033262879","https://openalex.org/W2347517878","https://openalex.org/W2080588939"],"abstract_inverted_index":{"A":[0],"robust":[1,23,38,53],"mixture":[2,32,54,68],"regression":[3,8,33,55,69,76],"based":[4,72],"on":[5,73],"the":[6,19,25,30,40,59,62,74,88,104,108,112,115],"M":[7],"estimation":[9,77],"method":[10,110],"has":[11],"already":[12],"been":[13],"proposed":[14,67,109],"in":[15,27,42],"literature.":[16],"However,":[17],"since":[18],"M-estimators":[20],"are":[21],"only":[22],"against":[24,39,111],"outliers":[26,41,60,113],"response":[28],"variables,":[29],"resulting":[31],"methods":[34],"will":[35],"not":[36],"be":[37],"explanatory":[43],"variables":[44],"(leverage":[45],"points).":[46],"In":[47],"this":[48],"paper,":[49],"we":[50],"propose":[51],"a":[52,94,98],"procedure":[56,70],"to":[57,84,102],"handle":[58],"and":[61,97,114],"leverage":[63,116],"points,":[64],"simultaneously.":[65],"Our":[66],"is":[71],"GM":[75],"method.":[78],"We":[79,92],"give":[80],"an":[81],"EM-type":[82],"algorithm":[83],"compute":[85],"estimates":[86],"for":[87],"parameters":[89],"of":[90,107],"interest.":[91],"provide":[93],"simulation":[95],"study":[96],"real":[99],"data":[100],"example":[101],"assess":[103],"robustness":[105],"performance":[106],"points.":[117]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
