Numerical simulation of stochastic ordinary differential equations in biomathematical modelling

Authors:
M. Carletti;K. Burrage;P. M. Burrage
Affiliations:
Istituto di Biomatematica, Universitá di Urbino, Localita' Crocicchia, Urbino (Pu) 61029, Italy;University of Queensland, Brisbane, Australia;University of Queensland, Brisbane, Australia
Venue:
Mathematics and Computers in Simulation
Year:
2004

Citing 1
Cited 4

High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations

Applied Numerical Mathematics - Special issue celebrating the centenary of Runge-Kutta methods

Numerical solution of stochastic differential problems in the biosciences

Journal of Computational and Applied Mathematics - Special issue: International workshop on the technological aspects of mathematics
Numerical solution of stochastic differential problems in the biosciences

Journal of Computational and Applied Mathematics - Special issue: International workshop on the technological aspects of mathematics
Qualitative analysis of a stochastic ratio-dependent predator-prey system

Journal of Computational and Applied Mathematics
Brief paper: Dynamics of a multigroup SIR epidemic model with stochastic perturbation

Automatica (Journal of IFAC)

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Abstract

In this work we discuss the effects of white and coloured noise perturbations on the parameters of a mathematical model of bacteriophage infection introduced by Beretta and Kuang in [Math. Biosc. 149 (1998) 57]. We numerically simulate the strong solutions of the resulting systems of stochastic ordinary differential equations (SDEs), with respect to the global error, by means of numerical methods of both Euler-Taylor expansion and stochastic Runge-Kutta type.