{"id":"https://openalex.org/W2154513807","doi":"https://doi.org/10.1145/2133390.2133394","title":"Confidence intervals for quantiles when applying variance-reduction techniques","display_name":"Confidence intervals for quantiles when applying variance-reduction techniques","publication_year":2012,"publication_date":"2012-03-01","ids":{"openalex":"https://openalex.org/W2154513807","doi":"https://doi.org/10.1145/2133390.2133394","mag":"2154513807"},"language":"en","primary_location":{"id":"doi:10.1145/2133390.2133394","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2133390.2133394","pdf_url":null,"source":{"id":"https://openalex.org/S38703467","display_name":"ACM Transactions on Modeling and Computer Simulation","issn_l":"1049-3301","issn":["1049-3301","1558-1195"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Modeling and Computer Simulation","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/A5114002932","display_name":"Fang Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Fang Chu","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ"],"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001888075","display_name":"Marvin K. Nakayama","orcid":"https://orcid.org/0000-0003-1503-373X"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marvin K. Nakayama","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ"],"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5114002932"],"corresponding_institution_ids":["https://openalex.org/I118118575"],"apc_list":null,"apc_paid":null,"fwci":7.1978,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.97158261,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"22","issue":"2","first_page":"1","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11720","display_name":"Probability and Risk Models","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11720","display_name":"Probability and Risk Models","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.993399977684021,"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/quantile","display_name":"Quantile","score":0.9260790348052979},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.809830904006958},{"id":"https://openalex.org/keywords/variance-reduction","display_name":"Variance reduction","score":0.7196230292320251},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7061842679977417},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.6377427577972412},{"id":"https://openalex.org/keywords/control-variates","display_name":"Control variates","score":0.6173887252807617},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5977500677108765},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5402836799621582},{"id":"https://openalex.org/keywords/robust-confidence-intervals","display_name":"Robust confidence intervals","score":0.5301706790924072},{"id":"https://openalex.org/keywords/delta-method","display_name":"Delta method","score":0.4890037775039673},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43507182598114014},{"id":"https://openalex.org/keywords/cdf-based-nonparametric-confidence-interval","display_name":"CDF-based nonparametric confidence interval","score":0.4214792847633362},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.36069220304489136},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.15707102417945862},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.10775676369667053}],"concepts":[{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.9260790348052979},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.809830904006958},{"id":"https://openalex.org/C62644790","wikidata":"https://www.wikidata.org/wiki/Q3454689","display_name":"Variance reduction","level":3,"score":0.7196230292320251},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7061842679977417},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.6377427577972412},{"id":"https://openalex.org/C121683094","wikidata":"https://www.wikidata.org/wiki/Q3554721","display_name":"Control variates","level":5,"score":0.6173887252807617},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5977500677108765},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5402836799621582},{"id":"https://openalex.org/C66520545","wikidata":"https://www.wikidata.org/wiki/Q7353538","display_name":"Robust confidence intervals","level":3,"score":0.5301706790924072},{"id":"https://openalex.org/C971699","wikidata":"https://www.wikidata.org/wiki/Q1132714","display_name":"Delta method","level":3,"score":0.4890037775039673},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43507182598114014},{"id":"https://openalex.org/C42468098","wikidata":"https://www.wikidata.org/wiki/Q5009921","display_name":"CDF-based nonparametric confidence interval","level":3,"score":0.4214792847633362},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.36069220304489136},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.15707102417945862},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.10775676369667053},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2133390.2133394","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2133390.2133394","pdf_url":null,"source":{"id":"https://openalex.org/S38703467","display_name":"ACM Transactions on Modeling and Computer Simulation","issn_l":"1049-3301","issn":["1049-3301","1558-1195"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Modeling and Computer Simulation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3118585887","display_name":null,"funder_award_id":"CMMI-0926949","funder_id":"https://openalex.org/F4320337391","funder_display_name":"Division of Civil, Mechanical and Manufacturing Innovation"}],"funders":[{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W164158064","https://openalex.org/W193906582","https://openalex.org/W616377252","https://openalex.org/W1602773783","https://openalex.org/W1910603762","https://openalex.org/W1964894347","https://openalex.org/W1979348268","https://openalex.org/W1985734023","https://openalex.org/W2007494410","https://openalex.org/W2016907754","https://openalex.org/W2025898485","https://openalex.org/W2031455838","https://openalex.org/W2032148197","https://openalex.org/W2034107358","https://openalex.org/W2035619074","https://openalex.org/W2038564767","https://openalex.org/W2056099894","https://openalex.org/W2064565482","https://openalex.org/W2065490365","https://openalex.org/W2087018957","https://openalex.org/W2092868272","https://openalex.org/W2098730109","https://openalex.org/W2099220105","https://openalex.org/W2125131981","https://openalex.org/W2148451394","https://openalex.org/W2150665263","https://openalex.org/W2162476997","https://openalex.org/W2170206178","https://openalex.org/W2478937241","https://openalex.org/W2482577837","https://openalex.org/W2504767107","https://openalex.org/W2520117518","https://openalex.org/W2595897327","https://openalex.org/W2797333853","https://openalex.org/W2802739963","https://openalex.org/W4231742901","https://openalex.org/W4238717354","https://openalex.org/W4285719527","https://openalex.org/W4299533062","https://openalex.org/W4301516493","https://openalex.org/W4302040658","https://openalex.org/W4302114916","https://openalex.org/W6635962571","https://openalex.org/W6829118146","https://openalex.org/W6844477269"],"related_works":["https://openalex.org/W4287392940","https://openalex.org/W3121013341","https://openalex.org/W2808706851","https://openalex.org/W65440759","https://openalex.org/W1988863536","https://openalex.org/W2905302290","https://openalex.org/W4233299515","https://openalex.org/W4362599072","https://openalex.org/W2151025666","https://openalex.org/W2980045726"],"abstract_inverted_index":{"Quantiles,":[0],"which":[1,43,111],"are":[2],"also":[3],"known":[4],"as":[5,13],"values-at-risk":[6],"in":[7,11,108],"finance,":[8],"frequently":[9],"arise":[10],"practice":[12],"measures":[14],"of":[15,128],"risk.":[16],"This":[17],"article":[18],"develops":[19],"asymptotically":[20],"valid":[21],"confidence":[22,117],"intervals":[23],"for":[24,41,58,103,123,126],"quantiles":[25],"estimated":[26],"via":[27,71],"simulation":[28],"using":[29],"variance-reduction":[30],"techniques":[31],"(VRTs).":[32],"We":[33,81,119],"establish":[34],"our":[35,75],"results":[36],"within":[37,74],"a":[38,67,72,78,92,100,116],"general":[39],"framework":[40,76],"VRTs,":[42],"we":[44],"show":[45,86],"includes":[46],"importance":[47],"sampling,":[48,50],"stratified":[49],"antithetic":[51],"variates,":[52],"and":[53,97],"control":[54],"variates.":[55],"Our":[56],"method":[57],"verifying":[59],"asymptotic":[60],"validity":[61],"is":[62],"to":[63,85,98,114],"first":[64],"demonstrate":[65],"that":[66,87],"quantile":[68,89],"estimator":[69,90,102],"obtained":[70],"VRT":[73],"satisfies":[77],"Bahadur-Ghosh":[79],"representation.":[80],"then":[82],"exploit":[83],"this":[84],"the":[88,104,109,124,129],"obeys":[91],"central":[93],"limit":[94],"theorem":[95],"(CLT)":[96],"develop":[99],"consistent":[101],"variance":[105],"constant":[106],"appearing":[107],"CLT,":[110],"enables":[112],"us":[113],"construct":[115],"interval.":[118],"provide":[120],"explicit":[121],"formulae":[122],"estimators":[125],"each":[127],"VRTs":[130],"considered.":[131]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}