{"id":"https://openalex.org/W4404738208","doi":"https://doi.org/10.1080/10618600.2024.2433672","title":"Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model","display_name":"Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model","publication_year":2024,"publication_date":"2024-11-26","ids":{"openalex":"https://openalex.org/W4404738208","doi":"https://doi.org/10.1080/10618600.2024.2433672"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2433672","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2433672","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","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/A5100785194","display_name":"Rui Li","orcid":"https://orcid.org/0000-0001-8905-3544"},"institutions":[{"id":"https://openalex.org/I905225518","display_name":"Shanghai University of International Business and Economics","ror":"https://ror.org/031t68441","country_code":"CN","type":"education","lineage":["https://openalex.org/I905225518"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Li","raw_affiliation_strings":["School of Statistics and Information, Shanghai University of International Business and Economics","School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Information, Shanghai University of International Business and Economics","institution_ids":["https://openalex.org/I905225518"]},{"raw_affiliation_string":"School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China","institution_ids":["https://openalex.org/I905225518"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440816","display_name":"Tao Li","orcid":"https://orcid.org/0000-0002-7261-3952"},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Li","raw_affiliation_strings":["School of Statistics and Data Science, Shanghai University of Finance and Economics","School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-7261-3952","affiliations":[{"raw_affiliation_string":"School of Statistics and Data Science, Shanghai University of Finance and Economics","institution_ids":["https://openalex.org/I181679659"]},{"raw_affiliation_string":"School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China","institution_ids":["https://openalex.org/I181679659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113179275","display_name":"Huacheng Su","orcid":null},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huacheng Su","raw_affiliation_strings":["School of Statistics and Data Science, Shanghai University of Finance and Economics","School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Data Science, Shanghai University of Finance and Economics","institution_ids":["https://openalex.org/I181679659"]},{"raw_affiliation_string":"School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China","institution_ids":["https://openalex.org/I181679659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101601770","display_name":"Jinhong You","orcid":"https://orcid.org/0000-0002-9420-2097"},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinhong You","raw_affiliation_strings":["School of Statistics and Data Science, Shanghai University of Finance and Economics","School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Data Science, Shanghai University of Finance and Economics","institution_ids":["https://openalex.org/I181679659"]},{"raw_affiliation_string":"School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China","institution_ids":["https://openalex.org/I181679659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101601770"],"corresponding_institution_ids":["https://openalex.org/I181679659"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20805857,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"3","first_page":"1169","last_page":"1187"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9984999895095825,"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":0.9984999895095825,"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/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9763000011444092,"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/quantile-regression","display_name":"Quantile regression","score":0.7116624712944031},{"id":"https://openalex.org/keywords/homogeneity","display_name":"Homogeneity (statistics)","score":0.6984617710113525},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.6815446615219116},{"id":"https://openalex.org/keywords/semiparametric-model","display_name":"Semiparametric model","score":0.6258425712585449},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.5974884033203125},{"id":"https://openalex.org/keywords/semiparametric-regression","display_name":"Semiparametric regression","score":0.5792906880378723},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4821126461029053},{"id":"https://openalex.org/keywords/panel-data","display_name":"Panel data","score":0.4810921847820282},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4361780285835266},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4322557747364044},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.418989896774292},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35806936025619507},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.15924781560897827}],"concepts":[{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.7116624712944031},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.6984617710113525},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6815446615219116},{"id":"https://openalex.org/C78297888","wikidata":"https://www.wikidata.org/wiki/Q7449607","display_name":"Semiparametric model","level":3,"score":0.6258425712585449},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.5974884033203125},{"id":"https://openalex.org/C19539793","wikidata":"https://www.wikidata.org/wiki/Q7449609","display_name":"Semiparametric regression","level":3,"score":0.5792906880378723},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4821126461029053},{"id":"https://openalex.org/C6422946","wikidata":"https://www.wikidata.org/wiki/Q857354","display_name":"Panel data","level":2,"score":0.4810921847820282},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4361780285835266},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4322557747364044},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.418989896774292},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35806936025619507},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.15924781560897827},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/10618600.2024.2433672","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2433672","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"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":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7148681469","display_name":null,"funder_award_id":"11971291","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1554555365","https://openalex.org/W1590868158","https://openalex.org/W1851612831","https://openalex.org/W1973429805","https://openalex.org/W1974971448","https://openalex.org/W1988809278","https://openalex.org/W2008472950","https://openalex.org/W2012653948","https://openalex.org/W2047287351","https://openalex.org/W2074682976","https://openalex.org/W2080363285","https://openalex.org/W2090520128","https://openalex.org/W2093049247","https://openalex.org/W2145561165","https://openalex.org/W2416478502","https://openalex.org/W2489216403","https://openalex.org/W2555225900","https://openalex.org/W2779756914","https://openalex.org/W2904877501","https://openalex.org/W2948540663","https://openalex.org/W2962983230","https://openalex.org/W2973125071","https://openalex.org/W2978979574","https://openalex.org/W3018068258","https://openalex.org/W3037696054","https://openalex.org/W3048917248","https://openalex.org/W3095983171","https://openalex.org/W3098561233","https://openalex.org/W3121739575","https://openalex.org/W3123093362","https://openalex.org/W3173550393","https://openalex.org/W3183522126","https://openalex.org/W4200532526","https://openalex.org/W4229444725","https://openalex.org/W4248244593","https://openalex.org/W4255889554","https://openalex.org/W4283586619","https://openalex.org/W4318755913"],"related_works":["https://openalex.org/W4206511378","https://openalex.org/W4206618949","https://openalex.org/W2526321210","https://openalex.org/W3205863630","https://openalex.org/W4318833145","https://openalex.org/W2364275385","https://openalex.org/W4388704167","https://openalex.org/W2007977664","https://openalex.org/W4376874882","https://openalex.org/W2224749288"],"abstract_inverted_index":{"In":[0],"this":[1,78],"article,":[2],"we":[3,33,66,80,100,115,138,161],"delve":[4],"into":[5],"the":[6,37,48,91,94,108,122,128,145,149,153],"quantile":[7],"regression":[8],"and":[9,25,42,45,52,124,143,165,177],"homogeneity":[10,73,83,98],"detection":[11],"of":[12,93,131,148,157],"a":[13,59,82,102,117,170],"varying":[14],"index":[15,43],"coefficient":[16],"panel":[17],"data":[18],"model,":[19],"which":[20],"incorporates":[21],"fixed":[22],"individual":[23],"effects":[24],"exhibits":[26],"nonlinear":[27],"time":[28],"trends.":[29,76],"Utilizing":[30],"spline":[31],"approximation,":[32],"obtain":[34],"estimators":[35],"for":[36],"trend":[38,64],"functions,":[39,41,65],"link":[40],"parameters,":[44],"subsequently":[46],"establish":[47],"corresponding":[49],"convergence":[50],"rates":[51],"asymptotic":[53,146],"normality.":[54],"Observing":[55],"that":[56],"subjects":[57],"within":[58,127],"group":[60],"may":[61],"share":[62],"identical":[63],"are":[67],"motivated":[68],"to":[69,120,169],"further":[70],"explore":[71],"potential":[72],"in":[74,97,111],"these":[75],"To":[77,151],"end,":[79],"propose":[81,101],"identification":[84],"algorithm":[85],"based":[86],"on":[87],"binary":[88],"segmentation.":[89],"For":[90],"determination":[92],"thresholding":[95],"parameter":[96],"identification,":[99],"generalized":[103],"Bayesian":[104],"information":[105],"criterion,":[106],"following":[107],"approach":[109],"outlined":[110],"Chen":[112],"(2019).":[113],"Furthermore,":[114],"introduce":[116],"penalized":[118],"method":[119],"discern":[121],"constant":[123],"linear":[125],"structures":[126],"nonparametric":[129],"functions":[130],"our":[132,158,167],"model.":[133],"By":[134],"leveraging":[135],"grouped":[136],"observations,":[137],"achieve":[139],"more":[140],"efficient":[141],"estimation":[142],"improve":[144],"properties":[147],"estimators.":[150],"demonstrate":[152],"finite":[154],"sample":[155],"performance":[156],"proposed":[159],"approach,":[160],"conduct":[162],"simulation":[163],"studies":[164],"apply":[166],"methodology":[168],"real-world":[171],"dataset":[172],"comprising":[173],"Air":[174],"Pollution":[175],"Data":[176,180],"Integrated":[178],"Surface":[179],"(APD&ISD).":[181]},"counts_by_year":[],"updated_date":"2026-06-14T06:11:07.267592","created_date":"2025-10-10T00:00:00"}
