learn to use Stan

Tutorial Papers About Stan

• Thomas P. Harte and R. Michael Weylandt (2016) Modern Bayesian Tools for Time Series Analysis. 2016. R in Finance Conference, Chicago, IL.

• Jim Savage (2016) A quick-start introduction to Stan for economists. A QuantEcon Notebook.

• Michael Clark (2015) Bayesian Basics (including Stan, BUGS, and JAGS) Center for Statistical Consultation and Research, University of Michigan.

• Tanner Sorensen and Shravan Vasishth (2015) A tutorial on fitting Bayesian linear mixed models using Stan. 2015. University of Postdam. Earlier draft, arXiv: 1506.06201.

• Aki Vehtari, Andrew Gelman, and Jonah Gabry (2015) Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. In Statistics and Computing, Online first doi:10.1007/s11222-016-9696-4. arXiv: 1507.04544.

• Andrew Gelman, Daniel Lee, and Jiqiang Guo (2015) Stan: A probabilistic programming language for Bayesian inference and optimization. In press, Journal of Educational and Behavior Science.

Tutorial Papers About HMC

• Michael Betancourt (2017) A Conceptual Introduction to Hamiltonian Monte Carlo. arXiv.

• Cole C. Monnahan, James T. Thorson, and Trevor A. Branch (2016) Faster estimation of Bayesian models in ecology using Hamiltonian Monte Carlo. Methods in Ecology and Evolution.

Tutorial Videos

Courses

• Statistical Rethinking 2022 (YouTube)
  Richard McElreath.

• Bayesian Statistics for the Social Sciences 2018 (YouTube)
  Ben Goodrich.

• Bayes Days 2015 Stan/RStan Tutorials (5 hours) (YouTube)
  Mike Lawrence (2015)

• Bayesian Inference for Psychologists using R & Stan (Full graduate-level course) (YouTube)
  Mike Lawrence (2017)

Lectures

• Principled Bayesian Workflow—Practicing Safe Bayes (YouTube)
  Keith O’Rourke (2019)

• How to Use (R)Stan to Estimate Models in External R Packages (useR2017 Conference)
  Ben Goodrich (2017)

• Combining the Power of R with Stan to Extend Analysis Functionality (60 minutes) (Southern New England UseR Meetup via YouTube)
  Ben Goodrich (2017)

• Scalable Bayesian Inference with Hamiltonian Monte Carlo (40 minutes) (ICERM Video Archive)
  Michael Betancourt (2016)

• Some Bayesian Modeling Techniques in Stan (100 minutes) (YouTube)
  Michael Betancourt (2016)

• Scalable Bayesian Inference with Hamiltonian Monte Carlo (60 minutes) (YouTube)
  Michael Betancourt (2016)

• ADVI — 10 Minute Presentation (YouTube)
  Alp Kucukelbir (2015)

• Probabilistic Modeling and Inference Made Easy (60 minutes) (Vimeo).
  Bob Carpenter (2015)

• Bayesian Inference and MCMC (3 hours) (YouTube).
  Bob Carpenter (2015)

• Stan for the beginners [Bayesian inference] in 6 mins (close captioned) (YouTube)
  Ehsan Karim (2015)

• Efficient Bayesian inference with Hamiltonian Monte Carlo (YouTube)
  Michael Betancourt (2014) Machine Learning Summer School, Reykjavik

• The Stan modeling language (YouTube)
  Michael Betancourt (2014) Machine Learning Summer School, Reykjavik

Textbooks Employing Stan

• Joseph M. Hilbe, Rafeal S. de Souza, and Emile E. O. Ishida. 2017. Bayesian Models for Astrophysical Data Using R, JAGS, Python, and Stan. Cambridge University Press.

• Kentarou Matsuura (2016) Bayesian Statistical Modeling Using Stan and R. Kyoritsu Shuppan Co., Ltd.

• Julian J. Faraway (2016) Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition. Chapman & Hall/CRC Press.

• Richard McElreath (2020) Statistical Rethinking A Bayesian Course with Examples in R and Stan, Second Edition . Chapman & Hall/CRC Press.
  free online: Chapters 1 and 2; code examples; video tutorials (follow title link above)

• Fränzi Korner-Nievergelt, Tobias Roth, Stefanie von Felten, Jérôme Guélat, Bettina Almasi, Pius Korner-Nievergelt (2015) Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Academic Press.

• John Kruschke (2015) Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan. Academic Press.

• Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin (2013) Bayesian Data Analysis, Third Edition. Chapman & Hall/CRC Press.
  free online: Appendix C: Computation in R and Stan