SDE based regression for random PDEs

dc.bibliographicCitation.seriesTitleWIAS Preprintseng
dc.bibliographicCitation.volume2192
dc.contributor.authorAnker, Felix
dc.contributor.authorBayer, Christian
dc.contributor.authorEigel, Martin
dc.contributor.authorLadkau, Marcel
dc.contributor.authorNeumann, Johannes
dc.contributor.authorSchoenmakers, John G.M.
dc.date.accessioned2016-12-13T10:46:54Z
dc.date.available2019-06-28T08:26:58Z
dc.date.issued2015
dc.description.abstractA simulation based method for the numerical solution of PDE with random coefficients is presented. By the Feynman-Kac formula, the solution can be represented as conditional expectation of a functional of a corresponding stochastic differential equation driven by independent noise. A time discretization of the SDE for a set of points in the domain and a subsequent Monte Carlo regression lead to an approximation of the global solution of the random PDE. We provide an initial error and complexity analysis of the proposed method along with numerical examples illustrating its behaviour.
dc.description.versionpublishedVersioneng
dc.formatapplication/pdf
dc.identifier.issn2198-5855
dc.identifier.urihttps://doi.org/10.34657/3124
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/3505
dc.language.isoengeng
dc.publisherBerlin : Weierstraß-Institut für Angewandte Analysis und Stochastik
dc.relation.issn0946-8633eng
dc.rights.licenseDieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.ger
dc.rights.licenseThis document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties.eng
dc.subject.ddc510
dc.subject.otherPartial differential equations with random coefficientseng
dc.subject.otherrandom PDEeng
dc.subject.otheruncertainty quantificationeng
dc.subject.otherFeynman-Kaceng
dc.subject.otherstochastic differential equationseng
dc.subject.otherstochastic simulationeng
dc.subject.otherstochastic regressioneng
dc.subject.otherMonte-Carloeng
dc.subject.otherEuler-Maruyamaeng
dc.titleSDE based regression for random PDEs
dc.typeReporteng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorWIASeng
wgl.subjectMathematikeng
wgl.typeReport / Forschungsbericht / Arbeitspapiereng
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