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The Stan modeling language manual contains a guide to programming in Stan with an extensive collection of modeling techniques and accompanying example models. Additionally, the manual serves as reference manual for the language itself, and a reference guide to the built-in special functions and probability functions. Stan’s modeling language is portable across all interfaces.
Modeling Language User's Guide and Reference Manual, Version 2.16.0
(GitHub pdf, CC-BY 4.0 license)
The Stan Wiki is largely focused on development documentation but it also includes a few pages with helpful information for users.
Stan Wiki (GitHub)
Two particularly recommended pages are
The Stan development team and many users have contributed tutorials aimed at introducing users to various aspects of statistical modeling with Stan, both in written and visual formats. These tutorials can be found at
Case Studies and Notebooks
Case studies provide longer, more-detailed discussion of various applications, models, and methodologies. Each case study is written in knitr or Jupyter notebooks so that the discussion is accompanied with working code. Case studies written or validated by the Stan development team can be found at
The proceedings of each Stan Conference also take the form of self-contained notebooks. Contributions for each conference can be found in their corresponding GibHub repository:
StanCon 2017 Case Studies (GitHub, with video links)
The Stan Forums
The most up to date discussion of modeling techniques and computational issues if often found in the Stan Forums before it ends up in a case study or a paper.
Stan Forums (Discourse)
Discussions prior to June 2017 are achived and public on the now deprecated Stan Users Google Group.
The quick start guides for each interface contain example models for demonstrating how to run Stan.
The Stan modeling language manual contains many other model examples to illustrate various modeling and coding techniques in Stan.
A larger set of example models translating the BUGS examples (Volumes 1 through 3) and the models from several Bayesian textbooks are also available on GibHub,
Example Models (GitHub)
Specialized Field Guides
Tutorials, case studies, software packages, and publications related to specific fields.
Education research using Stan (GitHub)
Finally, there are many works that elaborate on aspects of Stan from algorithms to applications. Some of the more relevant references can be found at