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Finite Difference Approximation for Linear Stochastic Partial Differential Equations with Method of Lines

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  • McDonald, Stuart

Abstract

A stochastic partial differential equation, or SPDE, describes the dynamics of a stochastic process defined on a space-time continuum. This paper provides a new method for solving SPDEs based on the method of lines (MOL). MOL is a technique that has largely been used for numerically solving deterministic partial differential equations (PDEs). MOL works by transforming the PDE into a system of ordinary differential equations (ODEs) by discretizing the spatial dimension of the PDE. The resulting system of ODEs is then solved by application of either a finite difference or a finite element method. This paper provides a proof that the MOL can be used to provide a finite difference approximation of the boundary value solutions for two broad classes of linear SPDEs, the linear elliptic and parabolic SPDEs.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 3983.

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Date of creation: 10 Oct 2006
Date of revision: 30 May 2007
Handle: RePEc:pra:mprapa:3983

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Keywords: Finite difference approximation; linear stochastic partial differential equations (SPDEs); the method of lines (MOL);

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  1. Ma, Jin & Yong, Jiongmin, 1997. "Adapted solution of a degenerate backward spde, with applications," Stochastic Processes and their Applications, Elsevier, Elsevier, vol. 70(1), pages 59-84, October.
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