On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations

Handle URI:
http://hdl.handle.net/10754/555670
Title:
On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations
Authors:
Bayer, Christian; Hoel, Hakon; von Schwerin, Erik; Tempone, Raul ( 0000-0003-1967-4446 )
Abstract:
We 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations 2014, 36 (2):A869 SIAM Journal on Scientific Computing
Journal:
SIAM Journal on Scientific Computing
Issue Date:
Jan-2014
DOI:
10.1137/130911433
Type:
Article
ISSN:
1064-8275; 1095-7197
Additional Links:
http://epubs.siam.org/doi/abs/10.1137/130911433
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorBayer, Christianen
dc.contributor.authorHoel, Hakonen
dc.contributor.authorvon Schwerin, Eriken
dc.contributor.authorTempone, Raulen
dc.date.accessioned2015-05-25T08:34:13Zen
dc.date.available2015-05-25T08:34:13Zen
dc.date.issued2014-01en
dc.identifier.citationOn NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations 2014, 36 (2):A869 SIAM Journal on Scientific Computingen
dc.identifier.issn1064-8275en
dc.identifier.issn1095-7197en
dc.identifier.doi10.1137/130911433en
dc.identifier.urihttp://hdl.handle.net/10754/555670en
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.en
dc.relation.urlhttp://epubs.siam.org/doi/abs/10.1137/130911433en
dc.rightsArchived with thanks to SIAM Journal on Scientific Computingen
dc.subjectMonte Carlo methodsen
dc.subjectoptimal stoppingen
dc.subjectsequential stopping rulesen
dc.subjectnonasymptoticen
dc.titleOn NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulationsen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalSIAM Journal on Scientific Computingen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionWeierstrass Institute, Mohrenstr. 39, 10117 Berlin, Germanyen
dc.contributor.institutionDepartment of Numerical Analysis and Computer Science, KTH, SE-100 44, Stockholm, Swedenen
kaust.authorHoel, Hakonen
kaust.authorTempone, Raulen
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