{"id":"https://openalex.org/W2742322455","doi":"https://doi.org/10.1109/wsc.2017.8247924","title":"Accurate computation of the right tail of the sum of dependent log-normal variates","display_name":"Accurate computation of the right tail of the sum of dependent log-normal variates","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2742322455","doi":"https://doi.org/10.1109/wsc.2017.8247924","mag":"2742322455"},"language":"en","primary_location":{"id":"doi:10.1109/wsc.2017.8247924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2017.8247924","pdf_url":null,"source":{"id":"https://openalex.org/S4363607803","display_name":"2017 Winter Simulation Conference (WSC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/1959.4/unsworks_50522","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003450294","display_name":"Zdravko I. Botev","orcid":"https://orcid.org/0000-0001-9054-3452"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zdravko Botev","raw_affiliation_strings":["School of Mathematics and Statistics, The University of New South Wales, Sydney, NSW, Australia","School of Mathematics and statistics [Sydney] (School of Mathematics and Statistics F07 University of Sydney NSW 2006 Australia - Australia)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, The University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Mathematics and statistics [Sydney] (School of Mathematics and Statistics F07 University of Sydney NSW 2006 Australia - Australia)","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091510633","display_name":"Pierre L\u2019Ecuyer","orcid":"https://orcid.org/0000-0002-3184-0796"},"institutions":[{"id":"https://openalex.org/I4210111842","display_name":"Computer Research Institute of Montr\u00e9al","ror":"https://ror.org/0279d5115","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210111842"]},{"id":"https://openalex.org/I70931966","display_name":"Universit\u00e9 de Montr\u00e9al","ror":"https://ror.org/0161xgx34","country_code":"CA","type":"education","lineage":["https://openalex.org/I70931966"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Pierre L'Ecuyer","raw_affiliation_strings":["DIRO, Universit\u00e9 de Montreal, Montr\u00e9al, Qu\u00e9bec, Canada","DIONYSOS - Dependability Interoperability and perfOrmance aNalYsiS Of networkS (Campus de Beaulieu 35042 Rennes cedex - France)","DIRO - D\u00e9partement d'Informatique et de Recherche Op\u00e9rationnelle [Montreal] (D\u00e9partement d'Informatique et de recherche op\u00e9rationnelle Universit\u00e9 de Montr\u00e9al Pavillon Andr\u00e9-Aisenstadt CP 6128 succ Centre-Ville Montr\u00e9al QC H3C 3J7 Canada - Canada)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DIRO, Universit\u00e9 de Montreal, Montr\u00e9al, Qu\u00e9bec, Canada","institution_ids":["https://openalex.org/I70931966"]},{"raw_affiliation_string":"DIONYSOS - Dependability Interoperability and perfOrmance aNalYsiS Of networkS (Campus de Beaulieu 35042 Rennes cedex - France)","institution_ids":[]},{"raw_affiliation_string":"DIRO - D\u00e9partement d'Informatique et de Recherche Op\u00e9rationnelle [Montreal] (D\u00e9partement d'Informatique et de recherche op\u00e9rationnelle Universit\u00e9 de Montr\u00e9al Pavillon Andr\u00e9-Aisenstadt CP 6128 succ Centre-Ville Montr\u00e9al QC H3C 3J7 Canada - Canada)","institution_ids":["https://openalex.org/I4210111842","https://openalex.org/I70931966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1880","last_page":"1890"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9983999729156494,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9958000183105469,"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/T11720","display_name":"Probability and Risk Models","score":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.909275233745575},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.7703962922096252},{"id":"https://openalex.org/keywords/control-variates","display_name":"Control variates","score":0.6845171451568604},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.6595146059989929},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6385830640792847},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.48679110407829285},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4726604223251343},{"id":"https://openalex.org/keywords/efficiency","display_name":"Efficiency","score":0.464022696018219},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44185811281204224},{"id":"https://openalex.org/keywords/normal-distribution","display_name":"Normal distribution","score":0.41347116231918335},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.38588958978652954},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36813369393348694},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35778552293777466},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.34639835357666016},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.2667529582977295},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.18653804063796997}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.909275233745575},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.7703962922096252},{"id":"https://openalex.org/C121683094","wikidata":"https://www.wikidata.org/wiki/Q3554721","display_name":"Control variates","level":5,"score":0.6845171451568604},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6595146059989929},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6385830640792847},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.48679110407829285},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4726604223251343},{"id":"https://openalex.org/C17648541","wikidata":"https://www.wikidata.org/wiki/Q2265984","display_name":"Efficiency","level":3,"score":0.464022696018219},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44185811281204224},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.41347116231918335},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38588958978652954},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36813369393348694},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35778552293777466},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34639835357666016},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.2667529582977295},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.18653804063796997},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/wsc.2017.8247924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2017.8247924","pdf_url":null,"source":{"id":"https://openalex.org/S4363607803","display_name":"2017 Winter Simulation Conference (WSC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"},{"id":"pmh:oai:unsworks.library.unsw.edu.au:1959.4/unsworks_50522","is_oa":true,"landing_page_url":"http://hdl.handle.net/1959.4/unsworks_50522","pdf_url":null,"source":{"id":"https://openalex.org/S4306401737","display_name":"UNSWorks (University of New South Wales, Sydney, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40053085","host_organization_name":"Australian Defence Force Academy","host_organization_lineage":["https://openalex.org/I40053085"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2017 Winter Simulation Conference (WSC), Las Vegas, NV, USA, 2017-12-03 - 2017-12-06","raw_type":"http://purl.org/coar/resource_type/c_5794"}],"best_oa_location":{"id":"pmh:oai:unsworks.library.unsw.edu.au:1959.4/unsworks_50522","is_oa":true,"landing_page_url":"http://hdl.handle.net/1959.4/unsworks_50522","pdf_url":null,"source":{"id":"https://openalex.org/S4306401737","display_name":"UNSWorks (University of New South Wales, Sydney, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40053085","host_organization_name":"Australian Defence Force Academy","host_organization_lineage":["https://openalex.org/I40053085"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2017 Winter Simulation Conference (WSC), Las Vegas, NV, USA, 2017-12-03 - 2017-12-06","raw_type":"http://purl.org/coar/resource_type/c_5794"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W5385147","https://openalex.org/W1973034347","https://openalex.org/W2000471346","https://openalex.org/W2008586314","https://openalex.org/W2039551178","https://openalex.org/W2045269787","https://openalex.org/W2071157273","https://openalex.org/W2072285612","https://openalex.org/W2075531413","https://openalex.org/W2120137405","https://openalex.org/W2141287793","https://openalex.org/W2147810214","https://openalex.org/W2154700532","https://openalex.org/W2156080814","https://openalex.org/W2171557682","https://openalex.org/W2253849346","https://openalex.org/W2261416239","https://openalex.org/W2264709743","https://openalex.org/W2266488332","https://openalex.org/W2276496321","https://openalex.org/W2782885838","https://openalex.org/W2801768210","https://openalex.org/W2963132183","https://openalex.org/W2963732797","https://openalex.org/W2964110409","https://openalex.org/W3100441015","https://openalex.org/W3124859313","https://openalex.org/W3149611468","https://openalex.org/W6681005254","https://openalex.org/W6747656786"],"related_works":["https://openalex.org/W4232943939","https://openalex.org/W2151761082","https://openalex.org/W1997242758","https://openalex.org/W1977112355","https://openalex.org/W2169816622","https://openalex.org/W2298254442","https://openalex.org/W2900543860","https://openalex.org/W2169367269","https://openalex.org/W1605568201","https://openalex.org/W1591943079"],"abstract_inverted_index":{"We":[0,94],"study":[1],"the":[2,5,10,14,17,62],"problem":[3],"of":[4,9,13,16,19,27,66,116],"Monte":[6,74],"Carlo":[7,75],"estimation":[8],"right":[11],"tail":[12],"distribution":[15],"sum":[18],"correlated":[20],"log-normal":[21],"random":[22],"variables.":[23],"While":[24],"a":[25,38,81,88],"number":[26],"theoretically":[28,103],"efficient":[29],"estimators":[30,68,76],"have":[31],"been":[32],"proposed":[33],"for":[34,91],"this":[35,84,92],"setting,":[36],"using":[37],"few":[39],"numerical":[40],"examples":[41],"we":[42,59,86],"illustrate":[43],"that":[44,61,115],"these":[45,67],"published":[46],"proposals":[47],"may":[48],"not":[49,70,97],"always":[50],"be":[51],"useful":[52],"in":[53],"practical":[54,109],"simulations.":[55],"In":[56],"other":[57],"words,":[58],"show":[60],"established":[63],"theoretical":[64],"efficiency":[65],"does":[69],"necessarily":[71],"convert":[72],"into":[73],"with":[77],"low":[78],"variance.":[79],"As":[80],"remedy":[82],"to":[83],"defect,":[85],"propose":[87],"new":[89],"estimator":[90,102],"setting.":[93],"demonstrate":[95],"that,":[96],"only":[98],"is":[99,111],"our":[100],"novel":[101],"efficient,":[104],"but,":[105],"more":[106],"importantly,":[107],"its":[108,117],"performance":[110],"significantly":[112],"better":[113],"than":[114],"competitors.":[118]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}
