StanLogDensityProblems implements the LogDensityProblems API for Stan models using BridgeStan. For easily benchmarking inference algorithms, StanLogDensityProblems also integrates with PosteriorDB.
For example, here we sample a Stan model from PosteriorDB using DynamicHMC:
julia> using DynamicHMC, PosteriorDB, Random, StanLogDensityProblems
julia> pdb = PosteriorDB.database()
PosteriorDatabase(...)
julia> post = PosteriorDB.posterior(pdb, "dogs-dogs")
Posterior: dogs-dogs
julia> prob = StanProblem(post, ".")
StanProblem: dogs_model
julia> rng = Random.default_rng();
julia> result = mcmc_with_warmup(rng, prob, 1_000; reporter=NoProgressReport());
julia> result.posterior_matrix
3×1000 Matrix{Float64}:
1.27568 1.29648 1.32405 … 1.65451 1.3875 1.76917
-0.327308 -0.305644 -0.303549 -0.273245 -0.387199 -0.333485
-0.128237 -0.166094 -0.15898 -0.223369 -0.15062 -0.236186