This package provides methods for Approximate Bayesian Computation (ABC) (sometimes also called simulation-based inference or likelihood-free inference). The algorithms are based on simulated annealing.
Note
Can you evaluate the probability density of your posterior? Can you write your
model in Turing.jl? Then you should most
likely not be using this or any other ABC package!
Conventional MCMC algorithm will be much more efficient.
See here for documentation and examples.
Albert, C., Künsch, H. R., & Scheidegger, A. (2015). A simulated annealing approach to approximate Bayes computations. Statistics and Computing, 25(6), 1217–1232.