{"id":"https://openalex.org/W7212064610","doi":"https://doi.org/10.48550/arxiv.2609.06509","title":"Revisiting dependence in multiple testing: empirical distribution approaches for FDP control","display_name":"Revisiting dependence in multiple testing: empirical distribution approaches for FDP control","publication_year":2026,"publication_date":"2026-09-06","ids":{"openalex":"https://openalex.org/W7212064610","doi":"https://doi.org/10.48550/arxiv.2609.06509"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.06509","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.06509","pdf_url":"https://arxiv.org/pdf/2609.06509","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,"listed_in":[],"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":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.06509","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122305445","display_name":"Fangyong Zheng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zheng, Fangyong","raw_affiliation_strings":["Department of Statistics and Data Science , National University of Singapore , 117546 , Singapore","Department of Statistics and Data Science , National University of Singapore , Singapore , 117546"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science , National University of Singapore , 117546 , Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Department of Statistics and Data Science , National University of Singapore , Singapore , 117546","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5150925569","display_name":"Pengfei Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Li, Pengfei","raw_affiliation_strings":["Department of Statistics and Actuarial Sciences , University of Waterloo , N2L 3G1 , ON , Canada","Department of Statistics and Actuarial Sciences , University of Waterloo , Waterloo , ON , Canada , N2L 3G1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Actuarial Sciences , University of Waterloo , N2L 3G1 , ON , Canada","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Department of Statistics and Actuarial Sciences , University of Waterloo , Waterloo , ON , Canada , N2L 3G1","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5150963499","display_name":"Yuan Jiang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiang, Yuan","raw_affiliation_strings":["Department of Statistics , Oregon State University , Corvallis , 97331 , OR , United States","Department of Statistics , Oregon State University , Corvallis , OR , United States , 97331"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics , Oregon State University , Corvallis , 97331 , OR , United States","institution_ids":["https://openalex.org/I131249849"]},{"raw_affiliation_string":"Department of Statistics , Oregon State University , Corvallis , OR , United States , 97331","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5150986308","display_name":"Tao Yu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yu, Tao","raw_affiliation_strings":["Department of Statistics and Data Science , National University of Singapore , 117546 , Singapore","Department of Statistics and Data Science , National University of Singapore , Singapore , 117546"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science , National University of Singapore , 117546 , Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Department of Statistics and Data Science , National University of Singapore , Singapore , 117546","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.6762999892234802,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.6762999892234802,"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/T10136","display_name":"Statistical Methods and Inference","score":0.20579999685287476,"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":0.031599998474121094,"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/multiple-testing","display_name":"multiple comparisons","score":0.9100000262260437},{"id":"https://openalex.org/keywords/empirical-distribution-function","display_name":"empirical distribution function","score":0.7590000033378601},{"id":"https://openalex.org/keywords/multivariate-mixture-models","display_name":"multivariate mixture models","score":0.8579999804496765},{"id":"https://openalex.org/keywords/nonparametric-estimation","display_name":"nonparametric estimation","score":0.8629999756813049},{"id":"https://openalex.org/keywords/high-dimensional-data","display_name":"high-dimensional data","score":0.7720000147819519},{"id":"https://openalex.org/keywords/breast-cancer-gene-expression","display_name":"breast cancer gene expression","score":0.906000018119812}],"concepts":[{"id":"https://openalex.org/C203763787","wikidata":"https://www.wikidata.org/wiki/Q371029","display_name":"Null (SQL)","level":2,"score":0.6761999726295471},{"id":"https://openalex.org/C191988596","wikidata":"https://www.wikidata.org/wiki/Q628374","display_name":"Null hypothesis","level":2,"score":0.6608999967575073},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.642799973487854},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.6240000128746033},{"id":"https://openalex.org/C120639","wikidata":"https://www.wikidata.org/wiki/Q7068958","display_name":"Null distribution","level":4,"score":0.612500011920929},{"id":"https://openalex.org/C98385598","wikidata":"https://www.wikidata.org/wiki/Q1339385","display_name":"Empirical distribution function","level":2,"score":0.583299994468689},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5436000227928162},{"id":"https://openalex.org/C193244246","wikidata":"https://www.wikidata.org/wiki/Q5432696","display_name":"False discovery rate","level":3,"score":0.5304999947547913},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4855000078678131},{"id":"https://openalex.org/C183905921","wikidata":"https://www.wikidata.org/wiki/Q1038757","display_name":"Multiple comparisons problem","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4115000069141388},{"id":"https://openalex.org/C65778772","wikidata":"https://www.wikidata.org/wiki/Q12345341","display_name":"Asymptotic distribution","level":3,"score":0.40630000829696655},{"id":"https://openalex.org/C120577422","wikidata":"https://www.wikidata.org/wiki/Q843558","display_name":"Alternative hypothesis","level":3,"score":0.39480000734329224},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C169857963","wikidata":"https://www.wikidata.org/wiki/Q1461038","display_name":"Test statistic","level":3,"score":0.3571000099182129},{"id":"https://openalex.org/C194531419","wikidata":"https://www.wikidata.org/wiki/Q17104825","display_name":"Nuisance parameter","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32510000467300415},{"id":"https://openalex.org/C119047807","wikidata":"https://www.wikidata.org/wiki/Q752718","display_name":"Asymptotic analysis","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C44036329","wikidata":"https://www.wikidata.org/wiki/Q253255","display_name":"p-value","level":3,"score":0.31700000166893005},{"id":"https://openalex.org/C103784038","wikidata":"https://www.wikidata.org/wiki/Q386228","display_name":"Cumulative distribution function","level":3,"score":0.3163999915122986},{"id":"https://openalex.org/C2781117939","wikidata":"https://www.wikidata.org/wiki/Q5374245","display_name":"Empirical likelihood","level":3,"score":0.31630000472068787},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3102000057697296},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C36382193","wikidata":"https://www.wikidata.org/wiki/Q7068966","display_name":"Null model","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C154606282","wikidata":"https://www.wikidata.org/wiki/Q7048579","display_name":"Nominal level","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.2542000114917755}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.06509","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.06509","pdf_url":"https://arxiv.org/pdf/2609.06509","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,"listed_in":[],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.06509","doi":"https://doi.org/10.48550/arxiv.2609.06509","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.06509","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.06509","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.06509","pdf_url":"https://arxiv.org/pdf/2609.06509","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,"listed_in":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2271590008","display_name":null,"funder_award_id":"RGPIN 2020","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G2980201894","display_name":null,"funder_award_id":"Tier 1","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G5851588998","display_name":"Novel statistical methods for biased sampling problems","funder_award_id":"rgpin-2020-04964","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G6676354404","display_name":"Flexible and Scalable Cluster Analysis of Longitudinal Microbiome Data to Define Functional Groups","funder_award_id":"2515805","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320322676","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7212064610.pdf","grobid_xml":"https://content.openalex.org/works/W7212064610.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W1511750995","https://openalex.org/W2081769927","https://openalex.org/W2146273335","https://openalex.org/W2949892641","https://openalex.org/W3174206601","https://openalex.org/W7128436461"],"related_works":["https://openalex.org/W2142892963","https://openalex.org/W2112659545","https://openalex.org/W2003639837","https://openalex.org/W1596515083","https://openalex.org/W2115382896","https://openalex.org/W2337364438","https://openalex.org/W2116319049","https://openalex.org/W1919370433","https://openalex.org/W1486595349","https://openalex.org/W7006534872"],"abstract_inverted_index":{"Large-scale":[0],"multiple":[1],"hypothesis":[2],"testing":[3],"is":[4,16,97],"central":[5],"to":[6],"the":[7,41,57,60,72,86,90,107,145],"analysis":[8,184],"of":[9,44,59,66,89,106,114,185],"high-throughput":[10],"data,":[11],"where":[12,85],"controlling":[13,71],"false":[14,73],"discoveries":[15],"critical.":[17],"Classical":[18],"procedures":[19],"typically":[20],"rely":[21],"on":[22,120],"theoretical":[23,49],"null":[24,45,67,95],"distributions":[25],"and":[26,139,152,173,183],"often":[27],"adjust":[28],"for":[29,93,144],"dependence":[30,108,115],"among":[31],"test":[32,68,91],"statistics,":[33],"but":[34],"these":[35],"approaches":[36],"may":[37,116],"be":[38,102,117],"misleading":[39],"when":[40],"empirical":[42,61,87,126,146],"distribution":[43,63],"statistics":[46,69,92],"deviates":[47],"from":[48],"assumptions.":[50],"Motivated":[51],"by":[52],"this":[53,121],"observation,":[54],"we":[55,123],"investigate":[56],"role":[58],"cumulative":[62],"function":[64],"(c.d.f.)":[65],"in":[70],"discovery":[74],"proportion":[75],"(FDP).":[76],"We":[77],"first":[78],"show":[79],"that,":[80],"under":[81,180],"an":[82,125,154],"oracle":[83],"scenario":[84],"c.d.f.":[88],"all":[94],"hypotheses":[96],"known,":[98],"FDP":[99,128,155,161,171],"control":[100,129,156,172],"can":[101],"achieved":[103],"optimally":[104],"regardless":[105],"structure,":[109],"highlighting":[110],"that":[111,158,166],"explicit":[112],"modeling":[113],"unnecessary.":[118],"Building":[119],"insight,":[122],"propose":[124],"c.d.f.-based":[127],"(eFDP)":[130],"method,":[131],"implemented":[132],"via":[133],"a":[134,140,186],"multivariate":[135],"mixture":[136],"model":[137],"framework":[138],"nonparametric":[141],"estimation":[142],"procedure":[143,157],"c.d.f.s,":[147],"establish":[148],"its":[149,194],"asymptotic":[150,160],"convergence,":[151],"construct":[153],"achieves":[159],"control.":[162],"Extensive":[163],"simulations":[164],"demonstrate":[165],"eFDP":[167],"attains":[168],"more":[169],"accurate":[170],"higher":[174],"power":[175],"than":[176],"existing":[177],"approaches,":[178],"particularly":[179],"strong":[181],"dependence,":[182],"high-dimensional":[187],"breast":[188],"cancer":[189],"gene":[190],"expression":[191],"dataset":[192],"confirms":[193],"practical":[195],"utility.":[196]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-10T00:00:00"}