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 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.
Downloads
- mcmc-types-1.0.3.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
Maintainer's Corner
For package maintainers and hackage trustees
Candidates
- No Candidates
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 |
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 |
Reverse Dependencies | 5 direct, 1 indirect [details] |
Downloads | 3925 total (15 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] |