Unbiased Estimators and Multilevel Monte Carlo
Vihola, M. (2018). Unbiased Estimators and Multilevel Monte Carlo. Operations Research, 66(2), 448-462. https://doi.org/10.1287/opre.2017.1670
Published inOperations Research
© 2017 INFORMS
Multilevel Monte Carlo (MLMC) and recently proposed unbiased estimators are closely related. This connection is elaborated by presenting a new general class of unbiased estimators, which admits previous debiasing schemes as special cases. New lower variance estimators are proposed, which are stratified versions of earlier unbiased schemes. Under general conditions, essentially when MLMC admits the canonical square root Monte Carlo error rate, the proposed new schemes are shown to be asymptotically as efficient as MLMC, both in terms of variance and cost. The experiments demonstrate that the variance reduction provided by the new schemes can be substantial.
PublisherInstitute for Operations Research and the Management Sciences
Publication in research information system
MetadataShow full item record
Related funder(s)Academy of Finland
Funding program(s)Research costs of Academy Research Fellow, AoF; Research post as Academy Research Fellow, AoF
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