Random walk numerical scheme for the steady-state of stochastic differential equations

DOI10.1016/j.cnsns.2023.107200OpenAlexW4322772081MaRDI QIDQ2698368

Jian Zu

Publication date: 21 April 2023

Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cnsns.2023.107200

zbMATH Keywords

stochastic differential equationsteady statecontinuous-time random walkinvariant distribution

Mathematics Subject Classification ID

Numerical analysis (65-XX) Probability theory and stochastic processes (60-XX)

Cites Work

• Unnamed Item
• Strong convergence of an explicit numerical method for SDEs with nonglobally Lipschitz continuous coefficients
• The truncated Euler-Maruyama method for stochastic differential equations
• Higher-order implicit strong numerical schemes for stochastic differential equations
• Convergence rate and stability of the truncated Euler-Maruyama method for stochastic differential equations
• A data-driven method for the steady state of randomly perturbed dynamics
• Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise.
• Continuous Markov processes and stochastic equations
• Approximate Integration of Stochastic Differential Equations
• Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations
• Continuous-time Random Walks for the Numerical Solution of Stochastic Differential Equations

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