You’re welcome to browse the resources below. Filter by clicking on type, difficulty level, or tags.
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Beginner Bayesian Analysis Reporting Guidelines
Kruschke (2021), Nature Human Behaviour.
Beginner brms: Bayesian regression models using Stan
An R package for multilevel models using R's formula syntax, compiled to Stan.
Beginner
Regression and Other Stories
Beginner Statistical Rethinking
Richard McElreath's book and accompanying video lectures.
Advanced A Tutorial on Hidden Markov Models using Stan
Tutorial written by Luis Damiano (2017).
Advanced Bayesian Workflow
Gelman et al. (2020), arXiv.
Advanced Martin Modrák's blog
My favorite post is Thank you: Statistics as a journey.
Advanced Mattias Villani's resources
A book-in-progress and interactive widgets (see the bottom of the website for links).
Advanced Prior Knowledge Elicitation: The Past, Present, and Future
Mikkola et al. (2024), Bayesian Analysis.
Advanced PyMC
A probabilistic programming language in Python
Advanced Statistical Thinking
Frank Harrell's blog about statistics.
Advanced The Stan language
Learn about the most established probabilistic programming language nowadays.
Advanced Turing.jl
Probably the most established way to write probabilistic models in Julia.
Expert Michael Betancourt's resources
In-depth writing about statistical modelling in Stan.
Expert Pattern Recognition and Machine Learning
An in-depth textbook discussing many advanced Bayesian algorithms.
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