RODE Solvers
Packages
The solvers on this page are distributed across the packages below. Add the package(s) you need to your environment.
| Package | Methods | Good for |
|---|---|---|
StochasticDiffEqRODE | RandomEM, RandomTamedEM, RandomHeun | Random ODEs (RODEs); time-dependent random forcing. |
Recommended Methods
Currently, the only implemented method is the RandomEM method in StochasticDiffEq.jl. It is strong order alpha for an alpha-Holder continuous noise process.
Full List of Methods
StochasticDiffEq.jl
Each of the StochasticDiffEq.jl solvers come with a linear interpolation.
StochasticDiffEqRODE.RandomEM- The Euler-Maruyama method for RODEs. Strong order matching Holder continuity.
Example usage:
using StochasticDiffEq # RODEProblem, RandomEM
sol = solve(prob, RandomEM(), dt = 1 / 100)