# References

## Texts for Your Shelf

The following are three texts I recommend in my consulting to folks who are interested in doing Bayesian data analyis. 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? Second edition has Stan examples.

McElreath, R. (2015). *Statistical Rethinking*. A good modeling book in general, by one who has contributed a lot to helping others learn Stan. Comes with its own R package too.

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

## Stan Specific Resources

More resources here

## Other

Statisticat, LLC. *Bayesian Inference*. A quick overview from the original author of the LaplacesDemon package.

## Works Cited/Used

Gelman, Andrew, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin. 2013. *Bayesian Data Analysis*. 3rd ed.

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). Springer: 997–1016.

Gelman, Andrew, and Iain Pardoe. 2006. “Bayesian Measures of Explained Variance and Pooling in Multilevel (Hierarchical) Models.” *Technometrics* 48 (2). Taylor & Francis: 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. 2010. *Doing Bayesian Data Analysis: A Tutorial Introduction with R*. 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. 2016. *Statistical Rethinking: A Bayesian Course with Examples in R and Stan*. Vol. 122. CRC Press.

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.”