Stochastic Taylor Methods for Stochastic Delay Differential Equations

Stochastic Taylor Methods for Stochastic Delay Differential Equations

This paper demonstrates a systematic derivation of high order numerical methods from stochastic Taylor expansion for solving stochastic delay differential equations (SDDEs) with a constant time lag, r > 0 . The stochastic Taylor expansion of SDDEs is truncated at certain terms to achieve the orde...

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Main Authors: Norhayati, Rosli, Arifah, Bahar, Hoe, Yeak Su, Haliza, Abdul Rahman
Format: Article
Language:English
Published: Universiti Teknologi Malaysia 2013
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/13514/
http://umpir.ump.edu.my/id/eprint/13514/
http://umpir.ump.edu.my/id/eprint/13514/
http://umpir.ump.edu.my/id/eprint/13514/1/29.1c.241-251.pdf
id ump-13514
recordtype eprints
spelling ump-135142016-12-28T08:38:49Z http://umpir.ump.edu.my/id/eprint/13514/ Stochastic Taylor Methods for Stochastic Delay Differential Equations Norhayati, Rosli Arifah, Bahar Hoe, Yeak Su Haliza, Abdul Rahman QA Mathematics This paper demonstrates a systematic derivation of high order numerical methods from stochastic Taylor expansion for solving stochastic delay differential equations (SDDEs) with a constant time lag, r > 0 . The stochastic Taylor expansion of SDDEs is truncated at certain terms to achieve the order of convergence of numerical methods for SDDEs. Three different numerical schemes of Euler method, Milstein scheme and stochastic Taylor method of order 1.5 have been derived. The performance of Euler method, Milstein scheme and stochastic Taylor method of order 1.5 are investigated in a simulation study. Universiti Teknologi Malaysia 2013-06 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/13514/1/29.1c.241-251.pdf Norhayati, Rosli and Arifah, Bahar and Hoe, Yeak Su and Haliza, Abdul Rahman (2013) Stochastic Taylor Methods for Stochastic Delay Differential Equations. MATEMATIKA, 29 (1c). pp. 241-251. ISSN 0127-8274 http://dx.doi.org/10.11113/matematika.v29.n.597 10.11113/matematika.v29.n.597
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA Mathematics
spellingShingle QA Mathematics
Norhayati, Rosli
Arifah, Bahar
Hoe, Yeak Su
Haliza, Abdul Rahman
Stochastic Taylor Methods for Stochastic Delay Differential Equations
description This paper demonstrates a systematic derivation of high order numerical methods from stochastic Taylor expansion for solving stochastic delay differential equations (SDDEs) with a constant time lag, r > 0 . The stochastic Taylor expansion of SDDEs is truncated at certain terms to achieve the order of convergence of numerical methods for SDDEs. Three different numerical schemes of Euler method, Milstein scheme and stochastic Taylor method of order 1.5 have been derived. The performance of Euler method, Milstein scheme and stochastic Taylor method of order 1.5 are investigated in a simulation study.
format Article
author Norhayati, Rosli
Arifah, Bahar
Hoe, Yeak Su
Haliza, Abdul Rahman
author_facet Norhayati, Rosli
Arifah, Bahar
Hoe, Yeak Su
Haliza, Abdul Rahman
author_sort Norhayati, Rosli
title Stochastic Taylor Methods for Stochastic Delay Differential Equations
title_short Stochastic Taylor Methods for Stochastic Delay Differential Equations
title_full Stochastic Taylor Methods for Stochastic Delay Differential Equations
title_fullStr Stochastic Taylor Methods for Stochastic Delay Differential Equations
title_full_unstemmed Stochastic Taylor Methods for Stochastic Delay Differential Equations
title_sort stochastic taylor methods for stochastic delay differential equations
publisher Universiti Teknologi Malaysia
publishDate 2013
url http://umpir.ump.edu.my/id/eprint/13514/
http://umpir.ump.edu.my/id/eprint/13514/
http://umpir.ump.edu.my/id/eprint/13514/
http://umpir.ump.edu.my/id/eprint/13514/1/29.1c.241-251.pdf
first_indexed 2023-09-18T22:16:14Z
last_indexed 2023-09-18T22:16:14Z
_version_ 1777415356327919616

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