{"id":"https://openalex.org/W3178283125","doi":"https://doi.org/10.3390/sym13071212","title":"On the Admissibility of Simultaneous Bootstrap Confidence Intervals","display_name":"On the Admissibility of Simultaneous Bootstrap Confidence Intervals","publication_year":2021,"publication_date":"2021-07-06","ids":{"openalex":"https://openalex.org/W3178283125","doi":"https://doi.org/10.3390/sym13071212","mag":"3178283125"},"language":"en","primary_location":{"id":"doi:10.3390/sym13071212","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13071212","pdf_url":"https://www.mdpi.com/2073-8994/13/7/1212/pdf?version=1625571006","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/13/7/1212/pdf?version=1625571006","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004008569","display_name":"Xin Gao","orcid":"https://orcid.org/0000-0001-8057-5100"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Xin Gao","raw_affiliation_strings":["Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada"],"raw_orcid":"https://orcid.org/0000-0001-8057-5100","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004526564","display_name":"Frank Konietschke","orcid":"https://orcid.org/0000-0002-5674-2076"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]},{"id":"https://openalex.org/I4210139777","display_name":"Berlin Institute of Health at Charit\u00e9 - Universit\u00e4tsmedizin Berlin","ror":"https://ror.org/0493xsw21","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210139777","https://openalex.org/I7877124"]},{"id":"https://openalex.org/I75951250","display_name":"Freie Universit\u00e4t Berlin","ror":"https://ror.org/046ak2485","country_code":"DE","type":"education","lineage":["https://openalex.org/I75951250"]},{"id":"https://openalex.org/I7877124","display_name":"Charit\u00e9 - Universit\u00e4tsmedizin Berlin","ror":"https://ror.org/001w7jn25","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I7877124"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Frank Konietschke","raw_affiliation_strings":["Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Stra\u00dfe 2, 10178 Berlin, Germany","Berlin Institute of Health, Institute of Biometry and Clinical Epidemiology Berlin and Charit\u00e9-Universit\u00e4tsmedizin Berlin, Corporate Member of Freie Universit\u00e4t Berlin, Humboldt-Universit\u00e4t zu Berlin, 10117 Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5674-2076","affiliations":[{"raw_affiliation_string":"Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Stra\u00dfe 2, 10178 Berlin, Germany","institution_ids":["https://openalex.org/I4210139777"]},{"raw_affiliation_string":"Berlin Institute of Health, Institute of Biometry and Clinical Epidemiology Berlin and Charit\u00e9-Universit\u00e4tsmedizin Berlin, Corporate Member of Freie Universit\u00e4t Berlin, Humboldt-Universit\u00e4t zu Berlin, 10117 Berlin, Germany","institution_ids":["https://openalex.org/I7877124","https://openalex.org/I39343248","https://openalex.org/I75951250"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100358442","display_name":"Qiong Li","orcid":"https://orcid.org/0000-0002-8627-4066"},"institutions":[{"id":"https://openalex.org/I12615008","display_name":"Beijing Normal-Hong Kong Baptist University","ror":"https://ror.org/04snvc712","country_code":"CN","type":"education","lineage":["https://openalex.org/I12615008"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiong Li","raw_affiliation_strings":["BNU-HKBU United International College, Zhuhai 519087, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BNU-HKBU United International College, Zhuhai 519087, China","institution_ids":["https://openalex.org/I12615008"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004008569"],"corresponding_institution_ids":["https://openalex.org/I192455969"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.2337,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.58150652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"13","issue":"7","first_page":"1212","last_page":"1212"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9986000061035156,"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":0.9986000061035156,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9930999875068665,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9922000169754028,"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/confidence-distribution","display_name":"Confidence distribution","score":0.8769116401672363},{"id":"https://openalex.org/keywords/cdf-based-nonparametric-confidence-interval","display_name":"CDF-based nonparametric confidence interval","score":0.8604344725608826},{"id":"https://openalex.org/keywords/robust-confidence-intervals","display_name":"Robust confidence intervals","score":0.8367536067962646},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.8248342275619507},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.7660030126571655},{"id":"https://openalex.org/keywords/coverage-probability","display_name":"Coverage probability","score":0.661361575126648},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6552879810333252},{"id":"https://openalex.org/keywords/percentile","display_name":"Percentile","score":0.5676896572113037},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.559032142162323},{"id":"https://openalex.org/keywords/confidence-and-prediction-bands","display_name":"Confidence and prediction bands","score":0.5342627763748169},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.5223346948623657},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.47297847270965576},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4692860543727875},{"id":"https://openalex.org/keywords/confidence-region","display_name":"Confidence region","score":0.44841235876083374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2502252459526062},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.10918232798576355}],"concepts":[{"id":"https://openalex.org/C13662513","wikidata":"https://www.wikidata.org/wiki/Q5160087","display_name":"Confidence distribution","level":3,"score":0.8769116401672363},{"id":"https://openalex.org/C42468098","wikidata":"https://www.wikidata.org/wiki/Q5009921","display_name":"CDF-based nonparametric confidence interval","level":3,"score":0.8604344725608826},{"id":"https://openalex.org/C66520545","wikidata":"https://www.wikidata.org/wiki/Q7353538","display_name":"Robust confidence intervals","level":3,"score":0.8367536067962646},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.8248342275619507},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.7660030126571655},{"id":"https://openalex.org/C2776292839","wikidata":"https://www.wikidata.org/wiki/Q5179217","display_name":"Coverage probability","level":3,"score":0.661361575126648},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6552879810333252},{"id":"https://openalex.org/C122048520","wikidata":"https://www.wikidata.org/wiki/Q2913954","display_name":"Percentile","level":2,"score":0.5676896572113037},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.559032142162323},{"id":"https://openalex.org/C140529851","wikidata":"https://www.wikidata.org/wiki/Q5160083","display_name":"Confidence and prediction bands","level":3,"score":0.5342627763748169},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.5223346948623657},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.47297847270965576},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4692860543727875},{"id":"https://openalex.org/C143380155","wikidata":"https://www.wikidata.org/wiki/Q5160088","display_name":"Confidence region","level":3,"score":0.44841235876083374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2502252459526062},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10918232798576355},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym13071212","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13071212","pdf_url":"https://www.mdpi.com/2073-8994/13/7/1212/pdf?version=1625571006","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d51ece4c267b4c8191f5677a3ad6983b","is_oa":true,"landing_page_url":"https://doaj.org/article/d51ece4c267b4c8191f5677a3ad6983b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 13, Iss 7, p 1212 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/13/7/1212/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym13071212","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym13071212","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13071212","pdf_url":"https://www.mdpi.com/2073-8994/13/7/1212/pdf?version=1625571006","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3178283125.pdf"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W2012224392","https://openalex.org/W2044113250","https://openalex.org/W2054714441","https://openalex.org/W2069057356","https://openalex.org/W2093043381","https://openalex.org/W2117897510","https://openalex.org/W2135046866","https://openalex.org/W2188723048","https://openalex.org/W2460320198","https://openalex.org/W3047071853","https://openalex.org/W4212883601","https://openalex.org/W4230173782","https://openalex.org/W4298872162","https://openalex.org/W6687352254"],"related_works":["https://openalex.org/W2032077494","https://openalex.org/W229248166","https://openalex.org/W3006095576","https://openalex.org/W913292429","https://openalex.org/W2223145623","https://openalex.org/W199440744","https://openalex.org/W2109861989","https://openalex.org/W2016092528","https://openalex.org/W2099093790","https://openalex.org/W2102222239"],"abstract_inverted_index":{"Simultaneous":[0],"confidence":[1,31,44,67,95,104],"intervals":[2,45,57,68,105],"are":[3,99],"commonly":[4],"used":[5],"in":[6],"joint":[7,15],"inference":[8],"of":[9,17,54],"multiple":[10],"parameters.":[11],"When":[12],"the":[13,18,48,55,65,70],"underlying":[14],"distribution":[16],"estimates":[19],"is":[20,58],"unknown,":[21],"nonparametric":[22,42,88,93],"methods":[23,98],"can":[24],"be":[25],"applied":[26,100],"to":[27,91,101],"provide":[28],"distribution-free":[29],"simultaneous":[30,43,94,103],"intervals.":[32,96],"In":[33],"this":[34],"note,":[35],"we":[36,84],"propose":[37],"new":[38],"one-sided":[39],"and":[40,77],"two-sided":[41],"based":[46],"on":[47],"percentile":[49],"bootstrap":[50,82],"approach.":[51],"The":[52,60,97],"admissibility":[53],"proposed":[56,66],"established.":[59],"numerical":[61],"results":[62],"demonstrate":[63],"that":[64],"maintain":[69],"correct":[71],"coverage":[72],"probability":[73],"for":[74,106],"both":[75],"normal":[76],"non-normal":[78],"distributions.":[79],"For":[80],"smoothed":[81],"estimates,":[83],"extend":[85],"Efron\u2019s":[86],"(2014)":[87],"delta":[89],"method":[90],"construct":[92,102],"LASSO":[107],"regression":[108],"estimates.":[109]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}