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Conditional Path Sampling of SDEs and the Langevin MCMC Method

Stuart, Andrew M. and Voss, Jochen and Wilberg, Petter (2004) Conditional Path Sampling of SDEs and the Langevin MCMC Method. Communications in Mathematical Sciences, 2 (4). pp. 685-697. ISSN 1539-6746. doi:10.4310/CMS.2004.v2.n4.a7.

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We introduce a stochastic PDE based approach to sampling paths of SDEs, conditional on observations. The SPDEs are derived by generalising the Langevin MCMC method to infinite dimensions. Various applications are described, including sampling paths subject to two end-point conditions (bridges) and nonlinear filter/smoothers.

Item Type:Article
Related URLs:
URLURL TypeDescription
Voss, Jochen0000-0001-7740-8811
Additional Information:© 2004 International Press. Received: July 14, 2004; accepted (in revised version): October 7, 2004. We are grateful to Eric Vanden Eijnden for helpful suggestions. This project was partially funded by the EPSRC. Jochen Voss was additionally funded by the European Union with a Marie Curie scholarship. The computing facilities were provided by the Centre for Scientific Computing of the University of Warwick.
Funding AgencyGrant Number
Engineering and Physical Sciences Research Council (EPSRC)UNSPECIFIED
Marie Curie FellowshipUNSPECIFIED
Subject Keywords:MCMC methods, stochastic partial differential equations, path sampling, Kalman filter
Other Numbering System:
Other Numbering System NameOther Numbering System ID
Andrew StuartJ61
Issue or Number:4
Classification Code:AMS Classification number: 65C05, 65C60, 60H15
Record Number:CaltechAUTHORS:20170612-144819276
Persistent URL:
Official Citation:Stuart, Andrew M.; Voss, Jochen; Wilberg, Petter. Conditional Path Sampling of SDEs and the Langevin MCMC Method. Commun. Math. Sci. 2 (2004), no. 4, 685--697.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:78125
Deposited By: Tony Diaz
Deposited On:12 Jun 2017 21:56
Last Modified:15 Nov 2021 17:37

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