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On nonasymptotic optimal stopping criteria in monte carlo simulations
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Numerical Analysis, NA.
2014 (English)In: SIAM Journal on Scientific Computing, ISSN 1064-8275, E-ISSN 1095-7197, Vol. 36, no 2, A869-A885 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2014. Vol. 36, no 2, A869-A885 p.
Keyword [en]
Monte Carlo methods, optimal stopping, sequential stopping rules, nonasymptotic
National Category
Computational Mathematics
URN: urn:nbn:se:kth:diva-147082DOI: 10.1137/130911433ISI: 000335817600024ScopusID: 2-s2.0-84899660875OAI: diva2:727977
Swedish Research Council

QC 20140623

Available from: 2014-06-23 Created: 2014-06-23 Last updated: 2014-06-23Bibliographically approved

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Hoel, Håkon
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Numerical Analysis, NA
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