Special methods and models

Having learned the basics of specifying, fitting, evaluating, and comparing Bayesian models, we are now well equipped to tackle real-world data analysis. In this chapter, we outline the Bayesian treatment of several special methods and models useful in practice. We make no claim of comprehensive coverage; indeed, each of this chapter’s sections could be expanded into a book of its own! Rather, our goal is to highlight the key differences between the Bayesian and classical approaches in these important areas, and provide links to more complete investigations. As general Bayesian modeling references, we list the recent books by O’Hagan and Forster (2004) and Gelman, Carlin, Stern, and Rubin (2004).