Strong Predictor-Corrector Methods for Stochastic Pantograph Equations

Strong Predictor-Corrector Methods for Stochastic Pantograph Equations

Year:    2016

Author:    Feiyan Xiao, Peng Wang

Journal of Computational Mathematics, Vol. 34 (2016), Iss. 1 : pp. 1–11

Abstract

The paper introduces a new class of numerical schemes for the approximate solutions of stochastic pantograph equations. As an effective technique to implement implicit stochastic methods, strong predictor-corrector methods (PCMs) are designed to handle scenario simulation of solutions of stochastic pantograph equations. It is proved that the PCMs are strong convergent with order $\frac{1}{2}$. Linear MS-stability of stochastic pantograph equations and the PCMs are researched in the paper. Sufficient conditions of MS-unstability of stochastic pantograph equations and MS-stability of the PCMs are obtained, respectively. Numerical experiments demonstrate these theoretical results.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jcm.1506-m2014-0110

Journal of Computational Mathematics, Vol. 34 (2016), Iss. 1 : pp. 1–11

Published online:    2016-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    11

Keywords:    Stochastic pantograph equation Predictor-corrector method MS-convergence MS-stability.

Author Details

Feiyan Xiao

Peng Wang