A suite of Julia packages providing efficient and intuitive tools for performing Bayesian inference for diffusion processes.
JuliaDiffusionBayes currently comprises of five main packages:
- DiffusionDefinition.jl: makes it possible to define diffusion processes and sample from their laws
- ObservationSchemes.jl: provides a systematic way of encoding discrete-time observations for stochastic processes
- GuidedProposals.jl: is responsible for defining and sampling conditioned diffusion processes
- ExtensibleMCMC.jl: a modular implementation of the Markov chain Monte Carlo (MCMC) algorithms
- DiffusionMCMC.jl: Markov chain Monte Carlo (MCMC) algorithms for doing inference for diffusion processes
It is a work in progress and I will update this page as the progress is made.