SDE Solvers

Recommended Methods

For most problems where a good amount of accuracy is required and stiffness may be an issue, the SRIW1Optimized algorithm should do well. If the problem has additive noise, then SRA1Optimized will be the optimal algorithm. If you simply need to quickly compute a large ensamble and don't need accuracy (and don't have stiffness problems), then EM can do well.

Special Keyword Arguments

• discard_length - Size at which to discard future information in adaptive. Default is 1e-15.

• tableau: The tableau for an :SRA or :SRI algorithm. Defaults to SRIW1 or SRA1.

• adaptivealg: The adaptive timestepping algorithm. Default is :RSwm3.

Implemented Solvers

StochasticDiffEq.jl

• EM- The Euler-Maruyama method.

• RKMil - An explicit Runge-Kutta discretization of the strong Order 1.0 Milstein method.

• SRA - The strong Order 2.0 methods for additive SDEs due to Rossler. Not yet implemented. Default tableau is for SRA1.

• SRI - The strong Order 1.5 methods for diagonal/scalar SDEs due to Rossler. Default tableau is for SRIW1.

• SRIW1 - An optimized version of SRIW1. Strong Order 1.5.

• SRA1 - An optimized version of SRIA1. Strong Order 2.0.