Stat 260/CS 294
Bayesian Modeling and Inference
Prof. Michael Jordan
Monday and Wednesday, 1:303:00, 330 Evans
Spring 2010
Announcements
 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.
Topics
 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,
neutraltotheright processes, completely random measures)
 Decision theory and frequentist perspectives (complete class
theorems, consistency, empirical Bayes)
 Experimental design
Prerequisites
 Stat 210A or Stat 241A/EECS 281A
Recommended Text
Supplemental Texts

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.
Lectures
Reading Assignments
 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, 1790.
 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, 410423.
 Mar. 29: Chap. 10 of Robert (pp. 456474)
 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, 717726.
 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):899924, 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.
Staff Office Hours and Locations