{"id":"https://openalex.org/W3128411041","doi":"https://doi.org/10.1080/03610918.2021.1874987","title":"A simulation study of a class of nonparametric test statistics: a close look of empirical distribution function-based tests","display_name":"A simulation study of a class of nonparametric test statistics: a close look of empirical distribution function-based tests","publication_year":2021,"publication_date":"2021-02-01","ids":{"openalex":"https://openalex.org/W3128411041","doi":"https://doi.org/10.1080/03610918.2021.1874987","mag":"3128411041"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2021.1874987","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.1874987","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://figshare.com/articles/journal_contribution/A_simulation_study_of_a_class_of_nonparametric_test_statistics_a_close_look_of_empirical_distribution_function-based_tests/13685817","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049050864","display_name":"Wenjun Zheng","orcid":"https://orcid.org/0000-0002-6236-9765"},"institutions":[{"id":"https://openalex.org/I919571938","display_name":"The University of Texas Health Science Center at Houston","ror":"https://ror.org/03gds6c39","country_code":"US","type":"education","lineage":["https://openalex.org/I919571938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenjun Zheng","raw_affiliation_strings":["Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas"],"affiliations":[{"raw_affiliation_string":"Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas","institution_ids":["https://openalex.org/I919571938"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059257496","display_name":"Dejian Lai","orcid":"https://orcid.org/0000-0003-1927-8021"},"institutions":[{"id":"https://openalex.org/I919571938","display_name":"The University of Texas Health Science Center at Houston","ror":"https://ror.org/03gds6c39","country_code":"US","type":"education","lineage":["https://openalex.org/I919571938"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dejian Lai","raw_affiliation_strings":["Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas"],"affiliations":[{"raw_affiliation_string":"Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas","institution_ids":["https://openalex.org/I919571938"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089392996","display_name":"K. Lance Gould","orcid":"https://orcid.org/0000-0003-4019-5941"},"institutions":[{"id":"https://openalex.org/I4210166946","display_name":"Imaging Center","ror":"https://ror.org/05hsqsk33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210166946"]},{"id":"https://openalex.org/I919571938","display_name":"The University of Texas Health Science Center at Houston","ror":"https://ror.org/03gds6c39","country_code":"US","type":"education","lineage":["https://openalex.org/I919571938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K. Lance Gould","raw_affiliation_strings":["Weatherhead PET Imaging Center, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas"],"affiliations":[{"raw_affiliation_string":"Weatherhead PET Imaging Center, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas","institution_ids":["https://openalex.org/I919571938","https://openalex.org/I4210166946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059257496"],"corresponding_institution_ids":["https://openalex.org/I919571938"],"apc_list":null,"apc_paid":null,"fwci":0.4728,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64680169,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"52","issue":"3","first_page":"1132","last_page":"1148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9965000152587891,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9965000152587891,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.996399998664856,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9962000250816345,"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/statistics","display_name":"Statistics","score":0.7837181687355042},{"id":"https://openalex.org/keywords/kolmogorov\u2013smirnov-test","display_name":"Kolmogorov\u2013Smirnov test","score":0.7420873045921326},{"id":"https://openalex.org/keywords/empirical-distribution-function","display_name":"Empirical distribution function","score":0.7007020711898804},{"id":"https://openalex.org/keywords/anderson\u2013darling-test","display_name":"Anderson\u2013Darling test","score":0.6948096752166748},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6682382225990295},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.54158616065979},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.5389744639396667},{"id":"https://openalex.org/keywords/test-statistic","display_name":"Test statistic","score":0.5369804501533508},{"id":"https://openalex.org/keywords/z-test","display_name":"Z-test","score":0.52001953125},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.49355852603912354},{"id":"https://openalex.org/keywords/pearsons-chi-squared-test","display_name":"Pearson's chi-squared test","score":0.48769888281822205},{"id":"https://openalex.org/keywords/goldfeld\u2013quandt-test","display_name":"Goldfeld\u2013Quandt test","score":0.4752925634384155},{"id":"https://openalex.org/keywords/normality-test","display_name":"Normality test","score":0.4750675857067108},{"id":"https://openalex.org/keywords/sampling-distribution","display_name":"Sampling distribution","score":0.4706399142742157},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.4451406002044678},{"id":"https://openalex.org/keywords/infimum-and-supremum","display_name":"Infimum and supremum","score":0.44486624002456665},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.42521756887435913},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4206305146217346},{"id":"https://openalex.org/keywords/cumulative-distribution-function","display_name":"Cumulative distribution function","score":0.41897016763687134},{"id":"https://openalex.org/keywords/chi-square-test","display_name":"Chi-square test","score":0.41494351625442505},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.3026883006095886}],"concepts":[{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.7837181687355042},{"id":"https://openalex.org/C82581908","wikidata":"https://www.wikidata.org/wiki/Q575766","display_name":"Kolmogorov\u2013Smirnov test","level":3,"score":0.7420873045921326},{"id":"https://openalex.org/C98385598","wikidata":"https://www.wikidata.org/wiki/Q1339385","display_name":"Empirical distribution function","level":2,"score":0.7007020711898804},{"id":"https://openalex.org/C187758679","wikidata":"https://www.wikidata.org/wiki/Q491401","display_name":"Anderson\u2013Darling test","level":4,"score":0.6948096752166748},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6682382225990295},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.54158616065979},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5389744639396667},{"id":"https://openalex.org/C169857963","wikidata":"https://www.wikidata.org/wiki/Q1461038","display_name":"Test statistic","level":3,"score":0.5369804501533508},{"id":"https://openalex.org/C117661179","wikidata":"https://www.wikidata.org/wiki/Q897827","display_name":"Z-test","level":4,"score":0.52001953125},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.49355852603912354},{"id":"https://openalex.org/C66924754","wikidata":"https://www.wikidata.org/wiki/Q2336256","display_name":"Pearson's chi-squared test","level":4,"score":0.48769888281822205},{"id":"https://openalex.org/C122379554","wikidata":"https://www.wikidata.org/wiki/Q3519047","display_name":"Goldfeld\u2013Quandt test","level":5,"score":0.4752925634384155},{"id":"https://openalex.org/C85031952","wikidata":"https://www.wikidata.org/wiki/Q3026029","display_name":"Normality test","level":3,"score":0.4750675857067108},{"id":"https://openalex.org/C167723999","wikidata":"https://www.wikidata.org/wiki/Q3773214","display_name":"Sampling distribution","level":2,"score":0.4706399142742157},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.4451406002044678},{"id":"https://openalex.org/C95611797","wikidata":"https://www.wikidata.org/wiki/Q17502105","display_name":"Infimum and supremum","level":2,"score":0.44486624002456665},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.42521756887435913},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4206305146217346},{"id":"https://openalex.org/C103784038","wikidata":"https://www.wikidata.org/wiki/Q386228","display_name":"Cumulative distribution function","level":3,"score":0.41897016763687134},{"id":"https://openalex.org/C32809988","wikidata":"https://www.wikidata.org/wiki/Q1071004","display_name":"Chi-square test","level":2,"score":0.41494351625442505},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.3026883006095886},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/03610918.2021.1874987","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.1874987","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":"pmh:oai:figshare.com:article/13685817","is_oa":true,"landing_page_url":null,"pdf_url":"https://figshare.com/articles/journal_contribution/A_simulation_study_of_a_class_of_nonparametric_test_statistics_a_close_look_of_empirical_distribution_function-based_tests/13685817","source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.6084/m9.figshare.13685817.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.13685817.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/13685817","is_oa":true,"landing_page_url":null,"pdf_url":"https://figshare.com/articles/journal_contribution/A_simulation_study_of_a_class_of_nonparametric_test_statistics_a_close_look_of_empirical_distribution_function-based_tests/13685817","source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3128411041.pdf","grobid_xml":"https://content.openalex.org/works/W3128411041.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1498801991","https://openalex.org/W1973429805","https://openalex.org/W1976553079","https://openalex.org/W1985409483","https://openalex.org/W2009687691","https://openalex.org/W2015459095","https://openalex.org/W2029590433","https://openalex.org/W2036747551","https://openalex.org/W2073064848","https://openalex.org/W2074375212","https://openalex.org/W2078582099","https://openalex.org/W2094153371","https://openalex.org/W2122093723","https://openalex.org/W2148555051","https://openalex.org/W2165112171","https://openalex.org/W2287232709","https://openalex.org/W2487069889","https://openalex.org/W2507039649","https://openalex.org/W3131845830","https://openalex.org/W4239953570","https://openalex.org/W4250405314"],"related_works":["https://openalex.org/W2329115989","https://openalex.org/W2168716636","https://openalex.org/W3176175210","https://openalex.org/W2183667932","https://openalex.org/W2996853055","https://openalex.org/W2739245009","https://openalex.org/W2586453511","https://openalex.org/W1984768317","https://openalex.org/W4226383725","https://openalex.org/W3128038183"],"abstract_inverted_index":{"Kolmogorov\u2013Smirnov":[0],"(KS)":[1],"statistic":[2,6],"is":[3,165,194],"a":[4,29,87],"non-parametric":[5],"based":[7],"on":[8,189],"the":[9,14,19,40,43,58,78,91,98,101,104,108,140,156,160,175,190],"empirical":[10,24],"distribution":[11,25,32,158],"function.":[12],"For":[13,35],"one-sample":[15],"case,":[16,37],"it":[17,38],"uses":[18],"supremum":[20],"distance":[21,44],"between":[22,45,185],"an":[23],"function":[26,33],"(EDF)":[27],"and":[28,62,76,95,107,117,121,125,159,167,196],"pre-specified":[30],"cumulative":[31],"(CDF).":[34],"two-sample":[36],"measures":[39],"maximum":[41],"of":[42,80,97,162],"two":[46,118,163],"EDFs.":[47],"KS":[48,99],"test,":[49,66,100,103,106],"as":[50,52,57,150],"well":[51],"other":[53],"EDF-based":[54,143],"tests":[55,120,144],"such":[56],"Anderson-Darling":[59],"(AD)":[60],"test":[61,82,177],"Cramer-von":[63],"Mises":[64],"(CvM)":[65],"has":[67],"been":[68],"widely":[69],"used":[70],"in":[71,172],"statistical":[72],"analysis.":[73],"To":[74],"address":[75],"compare":[77],"performance":[79],"these":[81],"statistics,":[83],"we":[84,133,151,168],"have":[85,136,152],"conducted":[86],"simulation":[88],"study":[89,112,129],"comparing":[90],"type":[92],"I":[93],"error":[94],"power":[96],"CvM":[102],"AD":[105],"Chi-squared":[109,176],"test.":[110],"Our":[111,128],"includes":[113],"both":[114,123],"one":[115],"sample":[116,119,192],"for":[122],"independent":[124],"correlated":[126],"samples.":[127],"showed":[130],"that":[131],"if":[132],"do":[134],"not":[135],"prior":[137,153],"information":[138,154],"about":[139,155],"tested":[141,157,186],"distributions,":[142],"are":[145,169],"better.":[146],"However,":[147],"so":[148],"long":[149],"density":[161],"distributions":[164],"bell-shaped":[166],"expecting":[170],"differences":[171],"variance/sparseness,":[173],"then":[174],"may":[178],"be":[179],"more":[180],"preferable.":[181],"When":[182],"correlation":[183],"exists":[184],"samples,":[187],"adjustment":[188],"informative":[191],"size":[193],"important":[195],"required.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-05T09:29:38.588285","created_date":"2025-10-10T00:00:00"}