mcmc-types: Common types for sampling.

[ library, math, mit, numeric ] [ Propose Tags ]

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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Versions [RSS] 1.0.0, 1.0.1, 1.0.2, 1.0.3
Dependencies base (>=4 && <6), containers (>=0.5 && <6), mwc-probability (>=1.0.1), transformers (>=0.5 && <1.0) [details]
License MIT
Author Jared Tobin
Category Numeric, Math
Home page
Source repo head: git clone
Uploaded by JaredTobin at 2016-12-04T09:19:48Z
Distributions LTSHaskell:1.0.3, NixOS:1.0.3, Stackage:1.0.3
Reverse Dependencies 5 direct, 1 indirect [details]
Downloads 3754 total (17 in the last 30 days)
Rating 1.75 (votes: 2) [estimated by Bayesian average]
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Status Docs available [build log]
Last success reported on 2016-12-08 [all 1 reports]