mcmctypes alternatives and similar packages
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README
mcmctypes
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
mcmctypes provides the suitablygeneral Target
, Chain
, and
Transition
types for usefully representing these things respectively.
Target
is a product type intended to hold a logtarget density function and potentially its gradient.The
Chain
type represents an 'annotated' parameter space. Technically all that's required is the type of the parameter space itself (held here inchainPosition
) but in practice some additional information is typically useful. ThechainTunables
field can be used to hold arbitrary data; one should avoid using it to do something nasty like, say, invalidating the Markov property.The
Transition
type permits probabilistic transitions over some state space by way of the underlyingProb
monad.
See e.g. the mightymetropolis library for example use.
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