Stat 260/CS 294: Bayesian Modeling and Inference

Stat 260/CS 294
Bayesian Modeling and Inference

Prof. Michael Jordan
Monday and Wednesday, 1:30-3:00, 330 Evans
Spring 2010

4/28: Homework 5 is due on May 5th at 5pm. Hardcopies only accepted; they should be placed in the box outside my office door (427 Evans).
4/22: On problem 1 in Homework 5, you can assume that the kernel satisfies detailed balance.
4/21: The due date for the final project is May 12th (at 5pm). Please submit a hardcopy of your project writeup.
4/21: Solutions to homework 4 are now available on the course website.
4/19: Homework 5 is now available on the course website.

Priors (conjugate, noninformative, reference)
Hierarchical models, spatial models, longitudinal models, dynamic models, survival models
Testing
Model choice
Inference (importance sampling, MCMC, sequential Monte Carlo)
Nonparametric models (Dirichlet processes, Gaussian processes, neutral-to-the-right processes, completely random measures)
Decision theory and frequentist perspectives (complete class theorems, consistency, empirical Bayes)
Experimental design

Robert, C., The Bayesian Choice (2nd Edition), Springer, 2001. [Springer Link] [Amazon]

Berger, J., Statistical Decision Theory and Bayesian Analysis (2nd Edition), Springer, 1995.
Robert, C. and Casella, G., Monte Carlo Statistical Methods, Springer, 1998.
Congdon, P., Bayesian Statistical Modelling, Wiley, 2001.
Gelman, A. Carlin, J. Stern, H. and Rubin, D., Bayesian Data Analysis (2nd Edition), Chapman & Hall, 2003.

Jan. 25: Chap. 1 of Robert
Feb. 3: Chap. 3 of Robert
Feb. 17: Bernardo, J. (2005). Reference analysis, Handbook of Statistics 25, Amsterdam: Elsevier, 17--90.
Mar. 1: Chap. 5 of Robert
Mar. 10: Liang, F., Paulo, R., Molina, G., Clyde, M. and Berger, J. (2008), Mixtures of g priors for Bayesian variable selection, Journal of the American Statistical Association, 103, 410-423.
Mar. 29: Chap. 10 of Robert (pp. 456-474)
Mar. 29: Kass, R. and Steffey, D. (1989), Approximate Bayesian inference in conditionally independent hierarchical models (parametric empirical Bayes models), Journal of the American Statistical Association, 84, 717-726.
Apr. 5: Chap. 6 of Robert
Apr. 19: Cappe, O., Godsill, S., and Moulines, E. An overview of existing methods and recent advances in sequential Monte Carlo, IEEE Proceedings, 95(5):899-924, 2007.
Apr. 19: Doucet, A., Lecture notes on Importance sampling and sequential importance sampling, 2008.
Apr. 19: Doucet, A., Lecture notes on Sequential importance sampling resampling, 2008.
Apr. 21: Dirichlet processes, Chinese restaurant processes and all that. M. Jordan, 2005
Apr. 21: Hierarchical Bayesian nonparametric models with applications. Teh, Y. W. and Jordan, M. I. In N. Hjort, C. Holmes, P. Mueller, and S. Walker (Eds.), Bayesian Nonparametrics: Principles and Practice, Cambridge, UK: Cambridge University Press, to appear.