{"id":"https://openalex.org/W4292183872","doi":"https://doi.org/10.1080/03610918.2022.2110595","title":"An exact bootstrap-based bandwidth selection rule for kernel quantile estimators","display_name":"An exact bootstrap-based bandwidth selection rule for kernel quantile estimators","publication_year":2022,"publication_date":"2022-08-16","ids":{"openalex":"https://openalex.org/W4292183872","doi":"https://doi.org/10.1080/03610918.2022.2110595"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2110595","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2110595","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"],"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/A5100455506","display_name":"Xiaoyu Liu","orcid":"https://orcid.org/0000-0002-5385-6676"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Liu","raw_affiliation_strings":["Institute of Statistics and Big Data, Renmin University of China","Institute of Statistics and Big Data, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Statistics and Big Data, Renmin University of China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Institute of Statistics and Big Data, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033601783","display_name":"Yan Song","orcid":"https://orcid.org/0000-0003-3240-3931"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Song","raw_affiliation_strings":["Institute of Statistics and Big Data, Renmin University of China","Institute of Statistics and Big Data, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Statistics and Big Data, Renmin University of China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Institute of Statistics and Big Data, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022021576","display_name":"Kun Zhang","orcid":"https://orcid.org/0000-0002-0898-5807"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kun Zhang","raw_affiliation_strings":["Institute of Statistics and Big Data, Renmin University of China","Institute of Statistics and Big Data, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Statistics and Big Data, Renmin University of China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Institute of Statistics and Big Data, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5022021576"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":0.9724,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76250336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"53","issue":"8","first_page":"3699","last_page":"3720"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9969000220298767,"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":0.9969000220298767,"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/T11236","display_name":"Control Systems and Identification","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7916244864463806},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.7892168760299683},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.6277729272842407},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5142948031425476},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.4998748302459717},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.48857077956199646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.48684900999069214},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4750523567199707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44218599796295166},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.4232056736946106},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.41232332587242126},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3995892405509949}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7916244864463806},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.7892168760299683},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.6277729272842407},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5142948031425476},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.4998748302459717},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.48857077956199646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.48684900999069214},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4750523567199707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44218599796295166},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.4232056736946106},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.41232332587242126},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3995892405509949},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2022.2110595","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2110595","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1970375475","https://openalex.org/W1981008951","https://openalex.org/W1981579074","https://openalex.org/W1992674605","https://openalex.org/W1993128469","https://openalex.org/W2001710797","https://openalex.org/W2005283340","https://openalex.org/W2011008826","https://openalex.org/W2020023242","https://openalex.org/W2025918145","https://openalex.org/W2033046771","https://openalex.org/W2040181733","https://openalex.org/W2041779525","https://openalex.org/W2043661225","https://openalex.org/W2044458394","https://openalex.org/W2046079480","https://openalex.org/W2047748458","https://openalex.org/W2052558588","https://openalex.org/W2055113717","https://openalex.org/W2055260494","https://openalex.org/W2059257118","https://openalex.org/W2075249830","https://openalex.org/W2077866122","https://openalex.org/W2079042375","https://openalex.org/W2094221602","https://openalex.org/W2096904991","https://openalex.org/W2112717751","https://openalex.org/W2117847142","https://openalex.org/W2122794444","https://openalex.org/W2259066093","https://openalex.org/W2320278257","https://openalex.org/W2485494180","https://openalex.org/W2496072794","https://openalex.org/W2498233082","https://openalex.org/W2504767107","https://openalex.org/W2539107629","https://openalex.org/W2598163062","https://openalex.org/W2605588234","https://openalex.org/W2621212896","https://openalex.org/W2734914701","https://openalex.org/W2786676311","https://openalex.org/W2803394595","https://openalex.org/W2952861576","https://openalex.org/W2999188005","https://openalex.org/W4205824955","https://openalex.org/W4238717354","https://openalex.org/W4245289321","https://openalex.org/W4253749611","https://openalex.org/W4300546246","https://openalex.org/W6692313766","https://openalex.org/W6844905184"],"related_works":["https://openalex.org/W1488761988","https://openalex.org/W2044551864","https://openalex.org/W2047938026","https://openalex.org/W1572557500","https://openalex.org/W4390690393","https://openalex.org/W3124946120","https://openalex.org/W2180954594","https://openalex.org/W2052515325","https://openalex.org/W1965635691","https://openalex.org/W2030885862"],"abstract_inverted_index":{"Bandwidth":[0],"selection":[1,30,39,95],"is":[2,63,87,101,149],"key":[3],"for":[4,32,49,122],"kernel":[5],"quantile":[6,155],"estimators":[7,156],"(KQEs),":[8],"which":[9],"estimate":[10],"quantiles":[11,124,191],"by":[12,73,89,145],"averaging":[13],"all":[14],"of":[15,55,83,97,105,167,174,176,196],"the":[16,35,45,50,57,67,75,93,98,113,165,168,172,194],"order":[17],"statistics":[18],"with":[19,132,141,151],"appropriate":[20],"kernel-weighting":[21],"functions.":[22],"This":[23],"paper":[24],"provides":[25],"a":[26,106,142],"new":[27],"data-driven":[28],"bandwidth":[29,38,69,94,143],"method":[31,100,115],"KQEs,":[33,56],"named":[34],"exact":[36,46],"bootstrap-based":[37],"(EBS)":[40],"rule.":[41],"By":[42],"relying":[43],"on":[44],"analytic":[47],"expressions":[48],"bootstrap":[51,61],"mean":[52,76],"and":[53,65,125,135],"variance":[54],"error":[58,78,180],"due":[59],"to":[60,103,128],"resampling":[62],"eliminated,":[64],"thus":[66],"optimal":[68],"can":[70],"be":[71],"obtained":[72],"minimizing":[74],"squared":[77],"(MSE)":[79],"estimate.":[80],"The":[81,161],"effectiveness":[82],"this":[84],"EBS":[85,99,114,147,169],"rule":[86,148],"confirmed":[88],"numerical":[90],"experiments.":[91],"First,":[92],"performance":[96],"compared":[102,150,189],"that":[104,112,182],"benchmark":[107],"approach.":[108],"Simulation":[109],"studies":[110],"show":[111],"performs":[116],"well,":[117],"especially":[118],"in":[119],"selecting":[120],"bandwidths":[121],"extreme":[123],"when":[126,184],"applied":[127],"small":[129],"sample":[130],"sizes":[131],"skewed":[133],"distributions":[134],"relatively":[136],"large":[137],"variances.":[138],"Second,":[139],"KQEs":[140],"determined":[144],"our":[146,197],"five":[152],"other":[153],"state-of-the-art":[154],"over":[157],"six":[158],"typical":[159],"distributions.":[160],"results":[162,173],"further":[163,192],"validate":[164],"efficiency":[166],"method.":[170],"Third,":[171],"simulations":[175],"controlling":[177],"actual":[178],"type-I":[179],"rates":[181],"occur":[183],"two":[185],"independent":[186],"groups":[187],"are":[188],"through":[190],"demonstrate":[193],"precision":[195],"EBS-based":[198],"KQEs.":[199]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2025-10-10T00:00:00"}