# References

## Texts for Your Shelf

The following are three texts I have recommended in the past to folks who are interested in doing Bayesian data analysis. They can be seen as introduction, intermediate, and advanced respectively.

Kruschke, J. (2014) *Doing Bayesian Data Analysis*. A very introductory text, but might be good for those not too confident in statistics generally speaking. And who doesn’t like puppies? 2nd Edition.

McElreath, R. (2020). *Statistical Rethinking*. A great modeling book in general, by one who has contributed a lot to helping others learn Stan and Bayesian analysis. 2nd Edition.

Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2013). *Bayesian Data Analysis*. 3rd Edition.

## Stan Specific Resources

More resources here

## Works Cited/Used

Carpenter, Bob, Andrew Gelman, Matthew D Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Marcus Brubaker, Jiqiang Guo, Peter Li, and Allen Riddell. 2017. “Stan: A Probabilistic Programming Language.”

*Journal of Statistical Software*76 (1).
Gelman, Andrew, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin. 2013.

*Bayesian Data Analysis*. 3rd ed. http://www.stat.columbia.edu/~gelman/book/.
Gelman, Andrew, and Jennifer Hill. 2006.

*Data Analysis Using Regression and Multilevel/Hierarchical Models*. Cambridge University Press.
Gelman, Andrew, Jessica Hwang, and Aki Vehtari. 2014. “Understanding Predictive Information Criteria for Bayesian Models.”

*Statistics and Computing*24 (6): 997–1016.
Gelman, Andrew, and Iain Pardoe. 2006. “Bayesian Measures of Explained Variance and Pooling in Multilevel (Hierarchical) Models.”

*Technometrics*48 (2): 241–51.
Gill, Jeff. 2008.

*Bayesian Methods : A Social and Behavioral Sciences Approach*. Second. Boca Raton: Chapman & Hall/CRC.
Jackman, Simon. 2009.

*Bayesian Analysis for the Social Sciences*. Chichester, UK: Wiley.
Kruschke, John. 2014.

*Doing Bayesian Data Analysis: A Tutorial with r, JAGS, and Stan*. Academic Press.
Lunn, David, Chris Jackson, Nicky Best, Andrew Thomas, and David Spiegelhalter. 2012.

*The BUGS Book: A Practical Introduction to Bayesian Analysis*. Boca Raton, FL: Chapman; Hall/CRC.
Lynch, Scott M. 2007.

*Introduction to Applied Bayesian Statistics and Estimation for Social Scientists*. New York: Springer.
McElreath, Richard. 2020.

*Statistical Rethinking: A Bayesian Course with Examples in r and Stan*. Chapman; Hall/CRC.
McGrayne, Sharon Bertsch. 2012.

*The Theory That Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy*. Reprint. New Haven Conn.: Yale University Press.
Vehtari, Aki, and Andrew Gelman. 2014. “WAIC and Cross-Validation in Stan.”

Vehtari, Aki, Andrew Gelman, and Jonah Gabry. 2017. “Practical Bayesian Model Evaluation Using Leave-One-Out Cross-Validation and WAIC.”

*Statistics and Computing*27 (5): 1413–32.
Vehtari, Aki, Daniel Simpson, Andrew Gelman, Yuling Yao, and Jonah Gabry. 2015. “Pareto Smoothed Importance Sampling.”

*arXiv Preprint arXiv:1507.02646*.