SDE based regression for random PDEs

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.ispartofseriesPreprint / Weierstraß-Institut für Angewandte Analysis und Stochastik , Volume 2192, ISSN 2198-5855eng
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.subjectPartial differential equations with random coefficients
dc.subjectrandom PDE
dc.subjectuncertainty quantification
dc.subjectFeynman-Kac
dc.subjectstochastic differential equations
dc.subjectstochastic simulation
dc.subjectstochastic regression
dc.subjectMonte-Carlo
dc.subjectEuler-Maruyama
dc.subject.ddc510
dc.titleSDE based regression for random PDEs
dc.typereporteng
dc.typeTexteng
dcterms.bibliographicCitation.journalTitlePreprint / Weierstraß-Institut für Angewandte Analysis und Stochastikeng
tib.accessRightsopenAccesseng
wgl.contributorWIASeng
wgl.subjectMathematikeng
wgl.typeReport / Forschungsbericht / Arbeitspapiereng
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