The linear Steklov method for SDEs with non-globally Lipschitz coefficients: strong convergence and simulation

DOI10.1016/j.cam.2016.04.011zbMath1468.65007OpenAlexW2346607720MaRDI QIDQ313640

Silvia Jerez, Saúl Díaz-Infante

Publication date: 12 September 2016

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.2016.04.011

zbMATH Keywords

strong convergencestochastic differential equationsexplicit methodsSteklov average

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Ordinary differential equations and systems with randomness (34F05) Numerical solutions to stochastic differential and integral equations (65C30)

Related Items (5)

A stochastic model for the evolution of bone metastasis: persistence and recovery ⋮ Fluctuating periodic solutions and moment boundedness of a stochastic model for the bone remodeling process ⋮ Analytical and numerical investigation of stochastic differential equations with applications using an exponential Euler-Maruyama approach ⋮ Editorial: Mathematical modeling and computational methods ⋮ A stochastic Gronwall inequality and applications to moments, strong completeness, strong local Lipschitz continuity, and perturbations

Cites Work

• Unnamed Item
• Unnamed Item
• Euler approximations with varying coefficients: the case of superlinearly growing diffusion coefficients
• Divergence of the multilevel Monte Carlo Euler method for nonlinear stochastic differential equations
• Strong convergence of an explicit numerical method for SDEs with nonglobally Lipschitz continuous coefficients
• Convergence and asymptotic stability of the explicit Steklov method for stochastic differential equations
• The truncated Euler-Maruyama method for stochastic differential equations
• Review on the Brownian dynamics simulation of bead-rod-spring models encountered in computational rheology
• Convergence and stability of the semi-tamed Euler scheme for stochastic differential equations with non-Lipschitz continuous coefficients
• Strong convergence of the stopped Euler-Maruyama method for nonlinear stochastic differential equations
• Higher-order implicit strong numerical schemes for stochastic differential equations
• Stochastic Hopf bifurcation: An example
• Asymptotic behaviour of the stochastic Lotka-Volterra model.
• Strong convergence and stability of implicit numerical methods for stochastic differential equations with non-globally Lipschitz continuous coefficients
• Environmental Brownian noise suppresses explosions in population dynamics.
• A stochastic model for internal HIV dynamics
• Numerical approximations of stochastic differential equations with non-globally Lipschitz continuous coefficients
• Strong and weak divergence in finite time of Euler's method for stochastic differential equations with non-globally Lipschitz continuous coefficients
• Multilevel Monte Carlo Path Simulation
• Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations
• The tamed Milstein method for commutative stochastic differential equations with non-globally Lipschitz continuous coefficients
• A Fundamental Mean-Square Convergence Theorem for SDEs with Locally Lipschitz Coefficients and Its Applications
• Indeterminate forms for multi-place functions

This page was built for publication: The linear Steklov method for SDEs with non-globally Lipschitz coefficients: strong convergence and simulation