ghc-mcmc-types

Common types for sampling

Common types for implementing Markov Chain Monte Carlo (MCMC) algorithms. An instance of an MCMC problem can be characterized by the following: * A /target distribution/ over some parameter space * A /parameter space/ for a Markov chain to wander over * A /transition operator/ to drive the Markov chain /mcmc-types/ provides the suitably-general 'Target', 'Chain', and 'Transition' types for representing these things respectively.

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