This is a compact utility package for defining diffusion processes and sampling from their laws. It is created to work in conjunction with a suite of packages in JuliaDiffusionBayes that provide tools for Bayesian inference for diffusion processes. However, it can also be used on its own to:
- define diffusion laws
- forward-sample their trajectories
- compute functionals of sampled paths
- compute gradients of functionals of sampled paths with respect to diffusion parameters or with respect to the starting point of the trajectory
Depending on your intended use of this package you might choose to start at different places:
- For a quick overview of DiffusionDefinition.jl's main functionality see Get started.
- For a systematic introduction to all functionality introduced in this package see the Manual
- For a didactic introduction to problems that can be solved using DiffusionDefinition.jl see the Tutorials
- If you have a problem that you think can be addressed with this package, then check out the How-to guides to see if the answer is already there.