MIT licensed by Jared Tobin
Maintained by jared@jtobin.ca
This version can be pinned in stack with:mcmc-types-1.0.2@sha256:6ebf389a0b6799cd609a30533b05c638fdaf36a6afeff9c58f674eebd68e3565,1177

Module documentation for 1.0.2

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.