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https://github.com/dschrempf/mcmc
Markov chain Monte Carlo with Metropolis-Hasting algorithm
https://github.com/dschrempf/mcmc
Last synced: 3 months ago
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Markov chain Monte Carlo with Metropolis-Hasting algorithm
- Host: GitHub
- URL: https://github.com/dschrempf/mcmc
- Owner: dschrempf
- License: gpl-3.0
- Created: 2020-05-05T23:26:37.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-04-21T04:54:01.000Z (7 months ago)
- Last Synced: 2024-05-21T07:04:29.896Z (6 months ago)
- Language: Haskell
- Size: 83 MB
- Stars: 14
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: ChangeLog.md
- License: LICENSE
Awesome Lists containing this project
README
# Markov chain Monte Carlo sampler
Sample from a posterior using Markov chain Monte Carlo (MCMC) algorithms.
At the moment, the following algorithms are available:
- Metropolis-Hastings-Green (Geyer, Charles J, 2011);
- Metropolis-coupled Markov chain Monte Carlo (also known as parallel
tempering) (Geyer, Charles J, 1991, Altekar, Gautam and Dwarkadas, Sandhya and Huelsenbeck, John P and Ronquist, Fredrik, 2004);
- Hamilton Monte Carlo proposal (Neal, Radford M, 2011);
- No U-Turn Sampler (NUTS) (Matthew D. Hoffman and Andrew Gelman, 2014).## Documentation
The [source code](https://hackage.haskell.org/package/mcmc/docs/Mcmc.html) contains detailed documentation about general concepts as well
as specific functions.## Examples
The Git repository also includes [example MCMC analyses](https://github.com/dschrempf/mcmc/tree/master/mcmc-examples). Build them with
[cabal-install](https://cabal.readthedocs.io/en/latest/cabal-commands.html#) or [Stack](https://docs.haskellstack.org/en/stable/README/).git clone https://github.com/dschrempf/mcmc.git
cd mcmc
stack buildFor example, estimate the [accuracy of an archer](https://github.com/dschrempf/mcmc/blob/master/mcmc-examples/Archery/Archery.hs) with
stack exec archery
For a more involved example, have a look at a [phylogenetic dating project](https://github.com/dschrempf/mcmc-dating).
# References
Altekar, Gautam and Dwarkadas, Sandhya and Huelsenbeck, John P and Ronquist, Fredrik (2004). *Parallel metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference*.
Geyer, Charles J (2011). *{Introduction to Markov Chain Monte Carlo}*, CRC press.
Geyer, Charles J (1991). *Markov chain Monte Carlo maximum likelihood*.
Matthew D. Hoffman and Andrew Gelman (2014). *The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo*.
Neal, Radford M (2011). *{MCMC Using Hamiltonian Dynamics}*, CRC press.