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Bibliografía Recomendada

  1. Box, G.E.P. y 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. y Gamerman, D. (1999). Statistical Inference: an Integrated Approach. London: Arnold.

  6. Bernardo, J.M. y 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. y Hsu, J.S.J. (1999). Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers. Cambridge: Cambrige University Press.

  9. Robert, C.P. (2007). The Bayesian Choice. (2a. ed.) New York: Springer.

  10. Gelman, A., Carlin, J.B., Stern, H.S. y Rubin, D.B. (1995). Bayesian Data Analysis. London: Chapman & Hall.

  11. Congdon, P. (2003). Applied Bayesian Modelling Chichester: Wiley.

  12. Congdon, P. (2006). Bayesian Statistical Modelling. (2a. ed.) Chichester: Wiley.

  13. Congdon, P. (2005). Bayesian Models for Categorical Data.

  14. Gamerman, D. y Lopes H.F. (2006). Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference. London: Chapman & Hall.

  15. Gilks, W.R., Richardson, S. y Spiegelhalter, D.J. (1996). Markov Chain Monte Carlo in Practice. London: Chapman & Hall.

  16. Robert, C.P. y Casella, G. (2004). Monte Carlo Statistical Methods. (2a. ed.) New York: Springer.

  17. Marin J.M. y Robert, C.P. (2007). Bayesian Core. New York: Springer.