Module sampling 

Monte-Carlo sampling (PRML ch 11) — the inference engine for Bayesian methods.

• mcmc — random-walk Metropolis-Hastings over an arbitrary log-density.

Gibbs / Hamiltonian Monte-Carlo can specialise this later (build order in stats_plan.md).

Re-exports

pub use mcmc::metropolis_hastings;

pub use mcmc::McmcResult;

Modules

mcmc

Markov-Chain Monte Carlo (PRML ch 11) — random-walk Metropolis-Hastings over an arbitrary (unnormalized) log-density. This is the general inference engine the Bayesian methods lean on: give it log p(x) (up to a constant) and it returns samples from p. Kernel-class Divergent (the accept/reject branch).