A Bayesian Reading List

  1. Box, G.E.P. and Tiao, G.C. (1973). Bayesian Inference in Statistical Analysis. Reading: Addison-Wesley.
  2. Press, S.J. (1989). Bayesian Statistics. Principles, Models and Applications. New York: Wiley.
  3. Berry, D.A. (1996). Statistics: A Bayesian Perspective. Duxbury Press: Belmont.
  4. Sivia, D.S. (1996). Data Analysis: A Bayesian Tutorial. Clarendon Press: Oxford.
  5. Migon, H.S. and Gamerman, D. (1999). Statistical Inference: an Integrated Approach. London: Arnold.
  6. Bernardo, J.M. and Smith, A.F.M. (1994). Bayesian Theory. Chichester: Wiley.
  7. O'Hagan, A. (1994). Kendall's Advanced Theory of Statistics, Vol. 2b: Bayesian Inference. Cambridge: Edward Arnold.
  8. Leonard, T. and Hsu, J.S.J. (1999). Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers. Cambridge: Cambrige University Press.
  9. Gelman, A., Carlin, J.B., Stern, H.S. and Rubin, D.B. (1995). Bayesian Data Analysis. London: Chapman & Hall.
  10. Gamerman, D. (1996). Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference. London: Chapman & Hall.
  11. Gilks, W.R., Richardson, S. and Spiegelhalter, D.J. (1996). Markov Chain Monte Carlo in Practice. London: Chapman & Hall.
  12. Congdon, P. (2001). Bayesian Statistical Modelling. Chichester: Wiley.