{"id":19179173,"url":"https://github.com/melling/probabilistic_programming","last_synced_at":"2026-03-15T16:17:24.363Z","repository":{"id":136800023,"uuid":"313686770","full_name":"melling/Probabilistic_Programming","owner":"melling","description":null,"archived":false,"fork":false,"pushed_at":"2021-04-14T19:44:13.000Z","size":3700,"stargazers_count":14,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-05-07T21:45:49.528Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/melling.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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}},"created_at":"2020-11-17T17:02:24.000Z","updated_at":"2021-05-09T19:56:55.000Z","dependencies_parsed_at":null,"dependency_job_id":"98754ae6-903a-4f78-abb3-7e7709652872","html_url":"https://github.com/melling/Probabilistic_Programming","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/melling%2FProbabilistic_Programming","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/melling%2FProbabilistic_Programming/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/melling%2FProbabilistic_Programming/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/melling%2FProbabilistic_Programming/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/melling","download_url":"https://codeload.github.com/melling/Probabilistic_Programming/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252961858,"owners_count":21832192,"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":"2024-11-09T10:42:22.373Z","updated_at":"2025-10-27T13:02:50.147Z","avatar_url":"https://github.com/melling.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Probabilistic Programming\n\nA collection of examples to learn Probabilistic Programming\n\n## Resources\n\n- https://benlambertdotcom.files.wordpress.com/2019/03/bayesianbook_problemsanswers_including_errata.pdf\n- http://www.stat.columbia.edu/~gelman/book/\n    - https://github.com/avehtari/BDA_R_demos\n    - [Datasets in BDA3](http://www.stat.columbia.edu/~gelman/book/data/)\n    - https://avehtari.github.io/BDA_course_Aalto/\n    \n## RStan\n\n- [Coin Flip Example](rstan/coin_flip_r/README.md)\n- [8 Schools Example](rstan/school_example_r/README.md)\n- [Rats Example](rstan/rats_r/README.md)\n- [Titanic Kaggle with Stan](rstan/titanic_kaggle)\n\n### References\n\n- http://faculty.ucr.edu/~jflegal/203/STAN_tutorial.pdf\n- [A Student’s Guide to Bayesian Statistics by Ben Lambert](https://github.com/alexandrahotti/Solutions-to-A-Students-Guide-to-Bayesian-Statistics-by-Ben-Lambert)\n\n## PyStan\n\n- [8 Schools Example PyStan](pystan/school_example_py/README.md)\n- [Coin Flip Example](pystan/coin_flip_py/README.md)\n\n\n## Julia Stan\n\n- https://astrostatistics.psu.edu/su14/lectures/BayesComp2014LabMCMCv1.pdf\n- https://mc-stan.org/users/interfaces/julia-stan\n- http://stanjulia.github.io/Stan.jl/stable/INTRO.html\n\n\n## PyMC3\n\n\n\n### References\n\n- https://github.com/pymc-devs/pymc3\n- https://people.duke.edu/~ccc14/sta-663/PyMC3.html\n- https://medium.com/airy-science/bayesian-inference-with-probabilistic-programming-using-pymc3-a00702ccd9e0\n\n## Time Series\n\n- https://www.unofficialgoogledatascience.com/2017/07/fitting-bayesian-structural-time-series.html?m=1\n- https://multithreaded.stitchfix.com/blog/2016/04/21/forget-arima/\n\n## Multi-Level Models\n\n- https://www.rensvandeschoot.com/tutorials/brms-started/\n- https://www.rensvandeschoot.com/tutorials/lme4/\n\n## brms \n\n- https://vuorre.netlify.app/post/2017/01/02/how-to-compare-two-groups-with-robust-bayesian-estimation-using-r-stan-and-brms/\n- https://www.fionamseaton.com/tutorial/misc/brms-examples/\n\n## rstanarm\n\n- [Introduction to Bayesian Computation Using the rstanarm R Package](https://youtu.be/z7zOzL9Rrzs)\n\n## Misc\n\n- https://mathvault.ca/statistical-significance/\n- https://betanalpha.github.io/assets/case_studies/principled_bayesian_workflow.html\n- https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers\n- https://blog.floydhub.com/naive-bayes-for-machine-learning/\n- https://ryxcommar.com/2019/09/06/some-things-you-maybe-didnt-know-about-linear-regression/\n- https://towardsdatascience.com/an-introduction-to-bayesian-inference-in-pystan-c27078e58d53\n- https://chi-feng.github.io/mcmc-demo/\n- https://github.com/fonnesbeck/statistical-analysis-python-tutorial\n- https://towardsdatascience.com/how-bayes-theorem-helped-win-the-second-world-war-7f3be5f4676c\n- https://stackoverflow.com/questions/54853017/why-is-my-python-implementation-of-metropolis-algorithm-mcmc-so-slow\n- https://jakevdp.github.io/blog/2014/06/14/frequentism-and-bayesianism-4-bayesian-in-python/\n- https://www.evanmiller.org/statistical-formulas-for-programmers.html\n- https://srcd.onlinelibrary.wiley.com/doi/full/10.1111/cdev.12169\n- https://bookdown.org/content/3686/stan.html\n- http://dm13450.github.io/2020/11/03/BayesPointProcess.html\n- https://www.tweag.io/blog/2019-10-25-mcmc-intro1/\n- https://towardsdatascience.com/importance-sampling-introduction-e76b2c32e744\n- https://www.r-bloggers.com/2014/09/in-depth-introduction-to-machine-learning-in-15-hours-of-expert-videos/\n- http://elevanth.org/blog/2017/11/28/build-a-better-markov-chain/\n- https://github.com/chi-feng/mcmc-demo\n- https://towardsdatascience.com/explaining-probability-plots-9e5c5d304703\n- https://philippmuens.com/linear-and-multiple-regression-from-scratch/\n- https://www.r-bloggers.com/2019/05/bayesian-modeling-using-stan-a-case-study/\n- https://philippmuens.com/logistic-regression-from-scratch/\n- https://github.com/asadoughi/stat-learning\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmelling%2Fprobabilistic_programming","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmelling%2Fprobabilistic_programming","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmelling%2Fprobabilistic_programming/lists"}