{"id":13837500,"url":"https://github.com/dschrempf/mcmc","last_synced_at":"2025-07-12T04:42:26.440Z","repository":{"id":37683724,"uuid":"261605095","full_name":"dschrempf/mcmc","owner":"dschrempf","description":"Markov chain Monte Carlo with Metropolis-Hasting algorithm","archived":false,"fork":false,"pushed_at":"2025-05-06T21:06:47.000Z","size":87115,"stargazers_count":16,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-06-15T08:03:57.221Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Haskell","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dschrempf.png","metadata":{"files":{"readme":"README.md","changelog":"ChangeLog.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2020-05-05T23:26:37.000Z","updated_at":"2025-05-06T21:06:50.000Z","dependencies_parsed_at":"2024-04-21T05:41:40.568Z","dependency_job_id":"af72f20d-1fae-4597-b807-2a6c05104151","html_url":"https://github.com/dschrempf/mcmc","commit_stats":{"total_commits":1111,"total_committers":1,"mean_commits":1111.0,"dds":0.0,"last_synced_commit":"713f415deb283028be9abb822433ffb2b9b8a27b"},"previous_names":[],"tags_count":22,"template":false,"template_full_name":null,"purl":"pkg:github/dschrempf/mcmc","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dschrempf%2Fmcmc","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dschrempf%2Fmcmc/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dschrempf%2Fmcmc/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dschrempf%2Fmcmc/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dschrempf","download_url":"https://codeload.github.com/dschrempf/mcmc/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dschrempf%2Fmcmc/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263154351,"owners_count":23422009,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-04T15:01:11.855Z","updated_at":"2025-07-02T14:08:44.550Z","avatar_url":"https://github.com/dschrempf.png","language":"Haskell","funding_links":[],"categories":["Haskell"],"sub_categories":[],"readme":"\n\n# Markov chain Monte Carlo sampler\n\n\u003cp align=\"center\"\u003e\u003cimg src=\"https://travis-ci.org/dschrempf/mcmc.svg?branch=master\"/\u003e\u003c/p\u003e\n\nSample from a posterior using Markov chain Monte Carlo (MCMC) algorithms.\n\nAt the moment, the following algorithms are available:\n\n-   Metropolis-Hastings-Green (Geyer, Charles J, 2011);\n-   Metropolis-coupled Markov chain Monte Carlo (also known as parallel\n    tempering) (Geyer, Charles J, 1991,  Altekar, Gautam and Dwarkadas, Sandhya and Huelsenbeck, John P and Ronquist, Fredrik, 2004);\n-   Hamilton Monte Carlo proposal (Neal, Radford M, 2011);\n-   No U-Turn Sampler (NUTS) (Matthew D. Hoffman and Andrew Gelman, 2014).\n\n\n## Documentation\n\nThe [source code](https://hackage.haskell.org/package/mcmc/docs/Mcmc.html) contains detailed documentation about general concepts as well\nas specific functions.\n\n\n## Examples\n\nThe Git repository also includes [example MCMC analyses](https://github.com/dschrempf/mcmc/tree/master/mcmc-examples). Build them with\n[cabal-install](https://cabal.readthedocs.io/en/latest/cabal-commands.html#) or [Stack](https://docs.haskellstack.org/en/stable/README/).\n\n    git clone https://github.com/dschrempf/mcmc.git\n    cd mcmc\n    stack build\n\nFor example, estimate the [accuracy of an archer](https://github.com/dschrempf/mcmc/blob/master/mcmc-examples/Archery/Archery.hs) with\n\n    stack exec archery\n\nFor a more involved example, have a look at a [phylogenetic dating project](https://github.com/dschrempf/mcmc-dating).\n\n\n# References\n\nAltekar, Gautam and Dwarkadas, Sandhya and Huelsenbeck, John P and Ronquist, Fredrik (2004). *Parallel metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference*.\n\nGeyer, Charles J (2011). *{Introduction to Markov Chain Monte Carlo}*, CRC press.\n\nGeyer, Charles J (1991). *Markov chain Monte Carlo maximum likelihood*.\n\nMatthew D. Hoffman and Andrew Gelman (2014). *The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo*.\n\nNeal, Radford M (2011). *{MCMC Using Hamiltonian Dynamics}*, CRC press.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdschrempf%2Fmcmc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdschrempf%2Fmcmc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdschrempf%2Fmcmc/lists"}