A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise

In this paper a family of fully implicit Milstein methods are introduced for solving stiff stochastic differential equations (SDEs). It is proved that the methods are convergent with strong order 1.0 for a class of SDEs. For a linear scalar test equation with multiplicative noise terms, mean-square...

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Main Authors: Wang, Xiaojie, Gan, Siqing, Wang, Desheng
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2013
Online Access:https://hdl.handle.net/10356/98993
http://hdl.handle.net/10220/12699
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-989932020-03-07T12:34:45Z A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise Wang, Xiaojie Gan, Siqing Wang, Desheng School of Physical and Mathematical Sciences In this paper a family of fully implicit Milstein methods are introduced for solving stiff stochastic differential equations (SDEs). It is proved that the methods are convergent with strong order 1.0 for a class of SDEs. For a linear scalar test equation with multiplicative noise terms, mean-square and almost sure asymptotic stability of the methods are also investigated. We combine analytical and numerical techniques to get insights into the stability properties. The fully implicit methods are shown to be superior to those of the corresponding semi-implicit methods in term of stability property. Finally, numerical results are reported to illustrate the convergence and stability results. 2013-08-01T01:56:54Z 2019-12-06T20:02:06Z 2013-08-01T01:56:54Z 2019-12-06T20:02:06Z 2012 2012 Journal Article Wang, X., Gan, S.,& Wang, D. (2012). A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise. BIT Numerical Mathematics, 52(3), 741-772. https://hdl.handle.net/10356/98993 http://hdl.handle.net/10220/12699 10.1007/s10543-012-0370-8 en BIT numerical mathematics
institution Nanyang Technological University
building NTU Library
country Singapore
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language English
description In this paper a family of fully implicit Milstein methods are introduced for solving stiff stochastic differential equations (SDEs). It is proved that the methods are convergent with strong order 1.0 for a class of SDEs. For a linear scalar test equation with multiplicative noise terms, mean-square and almost sure asymptotic stability of the methods are also investigated. We combine analytical and numerical techniques to get insights into the stability properties. The fully implicit methods are shown to be superior to those of the corresponding semi-implicit methods in term of stability property. Finally, numerical results are reported to illustrate the convergence and stability results.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Wang, Xiaojie
Gan, Siqing
Wang, Desheng
format Article
author Wang, Xiaojie
Gan, Siqing
Wang, Desheng
spellingShingle Wang, Xiaojie
Gan, Siqing
Wang, Desheng
A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise
author_sort Wang, Xiaojie
title A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise
title_short A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise
title_full A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise
title_fullStr A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise
title_full_unstemmed A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise
title_sort family of fully implicit milstein methods for stiff stochastic differential equations with multiplicative noise
publishDate 2013
url https://hdl.handle.net/10356/98993
http://hdl.handle.net/10220/12699
_version_ 1681044986351583232