Show simple item record

dc.contributor.authorVihola, Matti
dc.date.accessioned2018-10-03T10:15:33Z
dc.date.available2018-10-03T10:15:33Z
dc.date.issued2018
dc.identifier.citationVihola, M. (2018). Unbiased Estimators and Multilevel Monte Carlo. <i>Operations Research</i>, <i>66</i>(2), 448-462. <a href="https://doi.org/10.1287/opre.2017.1670" target="_blank">https://doi.org/10.1287/opre.2017.1670</a>
dc.identifier.otherCONVID_27812908
dc.identifier.otherTUTKAID_76334
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/59752
dc.description.abstractMultilevel 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.fi
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherInstitute for Operations Research and the Management Sciences
dc.relation.ispartofseriesOperations Research
dc.rightsIn Copyright
dc.subject.otherefficiency
dc.subject.othermultilevel Monte Carlo
dc.subject.otherstochastic differential equation
dc.subject.otherunbiased estimators
dc.titleUnbiased Estimators and Multilevel Monte Carlo
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201810034330
dc.contributor.laitosMatematiikan ja tilastotieteen laitosfi
dc.contributor.laitosDepartment of Mathematics and Statisticsen
dc.contributor.oppiaineTilastotiedefi
dc.contributor.oppiaineStatisticsen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2018-10-03T09:15:41Z
dc.description.reviewstatuspeerReviewed
dc.format.pagerange448-462
dc.relation.issn0030-364X
dc.relation.numberinseries2
dc.relation.volume66
dc.type.versionacceptedVersion
dc.rights.copyright© 2017 INFORMS
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber284513
dc.relation.grantnumber274740
dc.subject.ysoMonte Carlo -menetelmät
dc.subject.ysodifferentiaaliyhtälöt
dc.subject.ysostokastiset prosessit
dc.subject.ysokerrostuneisuus
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p6361
jyx.subject.urihttp://www.yso.fi/onto/yso/p3552
jyx.subject.urihttp://www.yso.fi/onto/yso/p11400
jyx.subject.urihttp://www.yso.fi/onto/yso/p12358
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1287/opre.2017.1670
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
dc.relation.funderAcademy of Finlanden
dc.relation.funderAcademy of Finlanden
jyx.fundingprogramAkatemiatutkijan tutkimuskulut, SAfi
jyx.fundingprogramAkatemiatutkijan tehtävä, SAfi
jyx.fundingprogramResearch costs of Academy Research Fellow, AoFen
jyx.fundingprogramResearch post as Academy Research Fellow, AoFen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

In Copyright
Except where otherwise noted, this item's license is described as In Copyright