# 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 spaceA

*parameter space*for a Markov chain to wander overA

*transition operator*to drive the Markov chain

*mcmc-types* provides the suitably-general `Target`

, `Chain`

, and
`Transition`

types for representing these things respectively.

Versions [faq] | 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 |

Maintainer | jared@jtobin.ca |

Category | Numeric, Math |

Home page | http://github.com/jtobin/mcmc-types |

Source repo | head: git clone http://github.com/jtobin/mcmc-types.git |

Uploaded | by JaredTobin at 2016-12-04T09:19:48Z |

Distributions | LTSHaskell:1.0.3, NixOS:1.0.3, Stackage:1.0.3 |

Downloads | 3140 total (5 in the last 30 days) |

Rating | 1.75 (votes: 2) [estimated by Bayesian average] |

Your Rating | |

Status | Docs available [build log] Last success reported on 2016-12-08 [all 1 reports] |

## Downloads

- mcmc-types-1.0.3.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)