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dc.contributor.authorBayer, Christian
dc.contributor.authorHoel, Hakon
dc.contributor.authorVon Schwerin, Erik
dc.contributor.authorTempone, Raul
dc.date.accessioned2015-05-25T08:34:13Z
dc.date.available2015-05-25T08:34:13Z
dc.date.issued2014-01
dc.identifier.citationOn NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations 2014, 36 (2):A869 SIAM Journal on Scientific Computing
dc.identifier.issn1064-8275
dc.identifier.issn1095-7197
dc.identifier.doi10.1137/130911433
dc.identifier.urihttp://hdl.handle.net/10754/555670
dc.description.abstractWe consider the setting of estimating the mean of a random variable by a sequential stopping rule Monte Carlo (MC) method. The performance of a typical second moment based sequential stopping rule MC method is shown to be unreliable in such settings both by numerical examples and through analysis. By analysis and approximations, we construct a higher moment based stopping rule which is shown in numerical examples to perform more reliably and only slightly less efficiently than the second moment based stopping rule.
dc.publisherSociety for Industrial & Applied Mathematics (SIAM)
dc.relation.urlhttp://epubs.siam.org/doi/abs/10.1137/130911433
dc.rightsArchived with thanks to SIAM Journal on Scientific Computing
dc.subjectMonte Carlo methods
dc.subjectoptimal stopping
dc.subjectsequential stopping rules
dc.subjectnonasymptotic
dc.titleOn NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalSIAM Journal on Scientific Computing
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionWeierstrass Institute, Mohrenstr. 39, 10117 Berlin, Germany
dc.contributor.institutionDepartment of Numerical Analysis and Computer Science, KTH, SE-100 44, Stockholm, Sweden
kaust.personHoel, Hakon
kaust.personTempone, Raul
refterms.dateFOA2018-06-14T07:55:20Z


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