Three-stage stochastic Runge-Kutta methods for stochastic differential equations

DOI10.1016/J.CAM.2007.11.001zbMath1181.65016OpenAlexW2057638127MaRDI QIDQ955051

Peng Wang

Publication date: 18 November 2008

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2007.11.001

zbMATH Keywords

numerical resultsWiener processnumerical stabilityStratonovich stochastic differential equationstochastic Runge-Kutta methodsorder conditionprincipal error coefficient

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Stability and convergence of numerical methods for ordinary differential equations (65L20) Ordinary differential equations and systems with randomness (34F05) Multistep, Runge-Kutta and extrapolation methods for ordinary differential equations (65L06) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)

Related Items (10)

Stochastic symplectic Runge-Kutta methods for the strong approximation of Hamiltonian systems with additive noise ⋮ Stochastic multi-symplectic Runge-Kutta methods for stochastic Hamiltonian PDEs ⋮ High strong order stochastic Runge-Kutta methods for Stratonovich stochastic differential equations with scalar noise ⋮ Split-step forward methods for stochastic differential equations ⋮ Strong convergence of split-step theta methods for non-autonomous stochastic differential equations ⋮ Convergence and stability of the split-step \(\theta \)-method for stochastic differential equations ⋮ Symplectic conditions and stochastic generating functions of stochastic Runge-Kutta methods for stochastic Hamiltonian systems with multiplicative noise ⋮ Preservation of quadratic invariants of stochastic differential equations via Runge-Kutta methods ⋮ Five-stage Milstein methods for SDEs ⋮ A-stable Runge-Kutta methods for stiff stochastic differential equations with multiplicative noise

Cites Work

• Higher-order implicit strong numerical schemes for stochastic differential equations
• A bound on the maximum strong order of stochastic Runge-Kutta methods for stochastic ordinary differential equations
• Two-stage stochastic Runge-Kutta methods for stochastic differential equations
• Order Conditions of Stochastic Runge--Kutta Methods by B-Series
• An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations
• Numerical Treatment of Stochastic Differential Equations
• Diagonally Implicit Runge–Kutta Methods for Stiff O.D.E.’s
• Stability Analysis of Numerical Schemes for Stochastic Differential Equations
• High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Three-stage stochastic Runge-Kutta methods for stochastic differential equations