First-order weak balanced schemes for stochastic differential equations

DOI10.1007/s11009-019-09733-5zbMath1484.65017OpenAlexW2962880898MaRDI QIDQ2195961

H. A. Mardones, Carlos M. Mora

Publication date: 28 August 2020

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11009-019-09733-5

zbMATH Keywords

weak convergencestochastic differential equationsMonte Carlo methodsnumerical solution

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Stochastic stability in control theory (93E15) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)

Related Items (4)

Second-order balanced stochastic Runge-Kutta methods with multi-dimensional studies ⋮ Weak variable step-size schemes for stochastic differential equations based on controlling conditional moments ⋮ Balanced implicit methods with strong order 1.5 for solving stochastic differential equations ⋮ A Stable Numerical Scheme for Stochastic Differential Equations with Multiplicative Noise

Uses Software

• SDELab

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