ABSTRACT
There is a vast literature on Bayesian statistics. Four foundational works are de Finetti (1974 and 1975), Jeffreys (1961), and Savage (1954). Good elementary introductions to the subject are Lindley (1971) and Berry (1996). Early efforts to make Bayesian methods accessible for data analysis were made by Raiffa and Schlaifer (1961), Zellner (1971), and Box and Tiao (1973). The important topic of Bayesian prediction was presented in Aitchison and Dunsmore (1975) and Geisser (1993). Bayesian decision theory and more theoretical aspects of Bayesian inference were presented in DeGroot (1970) and Berger (1993). Modern Bayesian data analysis methods based on Markov chain Monte Carlo methods are presented in Gelman et al. (2004), Carlin and Louis (2008), Congdon (2001), and Marin and Robert (2007). Recent theoretical treatments are found in Robert (2007) and Bernardo and Smith (2000). The treatment presented here owes debts to many of these works.
