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dc.contributor.authorRuzayqat, Hamza M.
dc.contributor.authorJasra, Ajay
dc.date.accessioned2020-05-20T08:12:12Z
dc.date.available2020-03-01T13:37:58Z
dc.date.available2020-05-20T08:12:12Z
dc.date.issued2020-05-26
dc.identifier.citationRuzayqat, H. M., & Jasra, A. (2020). Unbiased estimation of the solution to Zakai’s equation. Monte Carlo Methods and Applications, 26(2), 113–129. doi:10.1515/mcma-2020-2061
dc.identifier.issn1569-3961
dc.identifier.issn0929-9629
dc.identifier.doi10.1515/mcma-2020-2061
dc.identifier.urihttp://hdl.handle.net/10754/661826
dc.description.abstractIn the following article, we consider the non-linear filtering problem in continuous time and in particular the solution to Zakai's equation or the normalizing constant. We develop a methodology to produce finite variance, almost surely unbiased estimators of the solution to Zakai's equation. That is, given access to only a first-order discretization of solution to the Zakai equation, we present a method which can remove this discretization bias. The approach, under assumptions, is proved to have finite variance and is numerically compared to using a particular multilevel Monte Carlo method.
dc.description.sponsorshipKing Abdullah University of Science and Technology Award identifier / Grant number: BAS/1/1681-01-01 Both authors were supported by KAUST baseline funding.
dc.publisherWalter de Gruyter GmbH
dc.relation.urlhttps://www.degruyter.com/view/journals/mcma/ahead-of-print/article-10.1515-mcma-2020-2061/article-10.1515-mcma-2020-2061.xml
dc.rightsArchived with thanks to Monte Carlo Methods and Applications
dc.titleUnbiased Estimation of the Solution to Zakai's Equation
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalMonte Carlo Methods and Applications
dc.rights.embargodate2021-04-15
dc.eprint.versionPost-print
dc.identifier.arxivid2002.01270
kaust.personRuzayqat, Hamza M.
kaust.personJasra, Ajay
kaust.grant.numberBAS/1/1681-01-01
dc.identifier.eid2-s2.0-85083655983
refterms.dateFOA2020-03-01T13:38:22Z
kaust.acknowledged.supportUnitKAUST baseline fund
dc.date.published-online2020-05-26
dc.date.published-print2020-06-01
dc.date.posted2020-02-04


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