MIT licensed by Jared Tobin
Maintained by jared@jtobin.ca

Module documentation for 1.0.3

This version can be pinned in stack with:mcmc-types-1.0.3@sha256:ab64e4874cdd5eb4611e0616ab1299f64af067bc00329b93a3d931a2ec8acebd,1196

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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