Monte Carlo simulation of nonlinear diffusion processes

DOI10.1007/BF03167193zbMath0748.60051MaRDI QIDQ1185114

Shigeyoshi Ogawa

Publication date: 28 June 1992

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

zbMATH Keywords

stochastic differential equationssimulation algorithmsefficiency of the Euler scheme

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10)

Related Items (8)

An MCMC computational approach for a continuous time state-dependent regime switching diffusion process ⋮ A stochastic particle method for some one-dimensional nonlinear p.d.e ⋮ Some problems in the simulation of nonlinear diffusion processes ⋮ Basic Concepts of Numerical Analysis of Stochastic Differential Equations Explained by Balanced Implicit Theta Methods ⋮ An efficient weak Euler-Maruyama type approximation scheme of very high dimensional SDEs by orthogonal random variables ⋮ Confidence intervals of discretized Euler-Maruyama approximate solutions of SDE's ⋮ Convergence rate for the approximation of the limit law of weakly interacting particles: Application to the Burgers equation ⋮ Monte Carlo simulation of nonlinear diffusion processes. II

Cites Work

• Unnamed Item
• A survey of numerical methods for stochastic differential equations
• Second-order discretization schemes of stochastic differential systems for the computation of the invariant law
• A CLASS OF MARKOV PROCESSES ASSOCIATED WITH NONLINEAR PARABOLIC EQUATIONS

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