{"id":"https://openalex.org/W4403828337","doi":"https://doi.org/10.1080/10618600.2024.2414113","title":"Heterogeneous Functional Regression for Subgroup Analysis","display_name":"Heterogeneous Functional Regression for Subgroup Analysis","publication_year":2024,"publication_date":"2024-10-28","ids":{"openalex":"https://openalex.org/W4403828337","doi":"https://doi.org/10.1080/10618600.2024.2414113","pmid":"https://pubmed.ncbi.nlm.nih.gov/40786560"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2414113","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2414113","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2414113?download=true","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","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2414113?download=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076541944","display_name":"Yeqing Zhou","orcid":"https://orcid.org/0000-0002-5386-3411"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yeqing Zhou","raw_affiliation_strings":["School of Mathematical Sciences, School of Economics and Management, and Key Laboratory of Intelligent Computing and Applications, Tongji University","School of Mathematical Sciences, School of Economics and Management, and Key Laboratory of Intelligent Computing and Applications, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, School of Economics and Management, and Key Laboratory of Intelligent Computing and Applications, Tongji University","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"School of Mathematical Sciences, School of Economics and Management, and Key Laboratory of Intelligent Computing and Applications, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101990775","display_name":"Fei Jiang","orcid":"https://orcid.org/0000-0002-1880-3704"},"institutions":[{"id":"https://openalex.org/I180670191","display_name":"University of California, San Francisco","ror":"https://ror.org/043mz5j54","country_code":"US","type":"education","lineage":["https://openalex.org/I180670191"]},{"id":"https://openalex.org/I2803209242","display_name":"University of California System","ror":"https://ror.org/00pjdza24","country_code":"US","type":"education","lineage":["https://openalex.org/I2803209242"]},{"id":"https://openalex.org/I4210101190","display_name":"Cancer Research And Biostatistics","ror":"https://ror.org/01575p865","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210101190"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Fei Jiang","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, The University of California","Department of Epidemiology and Biostatistics, The University of California, San Francisco, CA","Department of Epidemiology and Biostatistics, the University of California, San Francisco"],"affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, The University of California","institution_ids":["https://openalex.org/I4210101190"]},{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, The University of California, San Francisco, CA","institution_ids":["https://openalex.org/I180670191","https://openalex.org/I2803209242"]},{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, the University of California, San Francisco","institution_ids":["https://openalex.org/I180670191"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101990775"],"corresponding_institution_ids":["https://openalex.org/I180670191","https://openalex.org/I2803209242","https://openalex.org/I4210101190"],"apc_list":null,"apc_paid":null,"fwci":0.3345,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67311582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"34","issue":"3","first_page":"872","last_page":"883"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9811999797821045,"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"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9811999797821045,"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":0.9739999771118164,"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/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9534000158309937,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.48354244232177734},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.47578656673431396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43342354893684387},{"id":"https://openalex.org/keywords/subgroup-analysis","display_name":"Subgroup analysis","score":0.42083317041397095},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38901621103286743},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38396787643432617}],"concepts":[{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.48354244232177734},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.47578656673431396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43342354893684387},{"id":"https://openalex.org/C187960798","wikidata":"https://www.wikidata.org/wiki/Q7631152","display_name":"Subgroup analysis","level":3,"score":0.42083317041397095},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38901621103286743},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38396787643432617},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/10618600.2024.2414113","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2414113","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2414113?download=true","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"},{"id":"pmid:40786560","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40786560","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:12330897","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12330897","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12330897/pdf/nihms-2032539.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Comput Graph Stat","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1080/10618600.2024.2414113","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2414113","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/10618600.2024.2414113?download=true","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"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1492706270","display_name":null,"funder_award_id":"02402","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G183415983","display_name":null,"funder_award_id":"R01NS132766","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3179451784","display_name":null,"funder_award_id":"12024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3374169922","display_name":null,"funder_award_id":"12001405","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4434262648","display_name":null,"funder_award_id":"12471263","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5161677271","display_name":null,"funder_award_id":"12471","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6021694018","display_name":null,"funder_award_id":"23ZR1469000","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"},{"id":"https://openalex.org/G7357800112","display_name":null,"funder_award_id":"22120240274","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8368922551","display_name":null,"funder_award_id":"K25AG071840","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G8701829084","display_name":null,"funder_award_id":"07184","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403828337.pdf","grobid_xml":"https://content.openalex.org/works/W4403828337.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1607848239","https://openalex.org/W1823045978","https://openalex.org/W1898034894","https://openalex.org/W1903133717","https://openalex.org/W1965125844","https://openalex.org/W2003336670","https://openalex.org/W2006255103","https://openalex.org/W2007741247","https://openalex.org/W2011832962","https://openalex.org/W2039414656","https://openalex.org/W2048682879","https://openalex.org/W2051243106","https://openalex.org/W2054489122","https://openalex.org/W2058765104","https://openalex.org/W2071949631","https://openalex.org/W2074682976","https://openalex.org/W2077964948","https://openalex.org/W2086205459","https://openalex.org/W2093328522","https://openalex.org/W2127300249","https://openalex.org/W2131172946","https://openalex.org/W2137911812","https://openalex.org/W2138019504","https://openalex.org/W2153646525","https://openalex.org/W2158967769","https://openalex.org/W2162870748","https://openalex.org/W2327088741","https://openalex.org/W2582881933","https://openalex.org/W2593563251","https://openalex.org/W2596151329","https://openalex.org/W2616050959","https://openalex.org/W2785880534","https://openalex.org/W2791214532","https://openalex.org/W2794050431","https://openalex.org/W2801683790","https://openalex.org/W2810307337","https://openalex.org/W2894357926","https://openalex.org/W2935786837","https://openalex.org/W2950317621","https://openalex.org/W2954205261","https://openalex.org/W2964346891","https://openalex.org/W2973125071","https://openalex.org/W2997278068","https://openalex.org/W3005379438","https://openalex.org/W3009077291","https://openalex.org/W3098306969","https://openalex.org/W3101329868","https://openalex.org/W3127592970","https://openalex.org/W3140138476","https://openalex.org/W4210580677","https://openalex.org/W4248244593","https://openalex.org/W4311757692"],"related_works":["https://openalex.org/W4381136829","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"],"abstract_inverted_index":{"With":[0],"ever":[1],"increasing":[2],"number":[3],"of":[4,6,82,111,114,127],"features":[5],"modern":[7],"datasets,":[8],"data":[9],"heterogeneity":[10],"is":[11,76],"gradually":[12],"becoming":[13],"the":[14,18,26,37,60,106,115,121,128],"norm":[15],"rather":[16],"than":[17],"exception.":[19],"Whereas":[20],"classical":[21],"regressions":[22],"usually":[23],"assume":[24],"all":[25],"samples":[27],"follow":[28],"a":[29,48,63,66,88,99,138],"common":[30],"model,":[31],"it":[32],"becomes":[33],"imperative":[34],"to":[35,51],"identify":[36],"heterogeneous":[38,53],"relationship":[39,69],"in":[40,109],"different":[41],"subsamples.":[42],"In":[43],"this":[44,149],"article,":[45],"we":[46],"propose":[47],"new":[49,139],"approach":[50],"model":[52],"functional":[54,81],"regression":[55],"relations.":[56],"We":[57,86,104,118,130],"target":[58],"at":[59],"association":[61],"between":[62],"response":[64],"and":[65,75,95,124,135],"predictor,":[67],"whose":[68],"can":[70],"vary":[71],"across":[72],"underlying":[73],"subgroups":[74],"modeled":[77],"as":[78],"an":[79,83,142],"unknown":[80],"auxiliary":[84],"predictor.":[85],"introduce":[87],"procedure":[89],"which":[90],"performs":[91],"simultaneous":[92],"parameter":[93,116],"estimation":[94],"subgroup":[96],"identification":[97],"through":[98],"fusion":[100],"type":[101],"group-wise":[102],"penalization.":[103],"establish":[105,120],"statistical":[107],"guarantees":[108],"terms":[110],"non-asymptotic":[112],"convergence":[113],"estimation.":[117],"also":[119],"oracle":[122],"property":[123],"asymptotic":[125],"normality":[126],"estimators.":[129],"carry":[131],"out":[132],"intensive":[133],"simulations,":[134],"illustrate":[136],"with":[137],"dataset":[140],"from":[141],"Alzheimer's":[143],"disease":[144],"study.":[145],"Supplementary":[146],"materials":[147],"for":[148],"article":[150],"are":[151],"available":[152],"online.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
