# Questions tagged [stochastic-ode]

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### Easily understandable argument that normal Runge–Kutta methods cannot be generalised to SDEs?

A naïve approach to solving stochastic differential equations (SDEs) would be: take a regular multi-step Runge–Kutta method, use a sufficiently fine discretisation of the underlying Wiener process, ...
195 views

### What’s so great about derivative-free solvers for SDEs?

I am trying to familiarise myself with SDEs and have been reading a few review papers on the topic. They leave the impression that a great deal of work has been put into solvers that are derivative-...
75 views

### Probability approximation: monte carlo VS sde

I have a probability measure $\mu$ (say, in $\mathbb{R}^{d}$, with density) and I want to approximate it numerically. Today I noticed that my measure is ergotic for a certain Stochastic Differential ...
168 views

### Solving an SDE with time-dependent parameter in R

I am trying to solve a system of SDEs in R using the Diffeqr package. Let's reduce the system to a simple ODE: ...
50 views

### Testing Wiener process splitting in adaptive-step SDE integrators

I am investigating various methods for adaptive-step integration of stochastic differential equations and trying to implement them. All of the papers that I've seen (e.g. H. Lamba, J. Comp. App. Math. ...
43 views

### Time independent Runge Kutta integration of SDE

I am trying to compare the result of numerical integration of time independent Runge_Kutta, github page for stochastic differential equations with the analytical solution. True answer match the ...
112 views

### Jump-Diffusion process: practical solver beyond Euler method?

A jump-diffusion process is a stochastic process where both continuous noise (in my case complex Wiener noise $dZ,dZ^*$ such that $dZ^2=dZ^{*2}=0,|dZ|^2=dt$) and discrete Jumps (in my case Poissonian \$...