| Instructor: | Dr. Michael Baron | |
| Office: | ECSN 3.912 | |
| Phone: | 972-UTD-6874 | |
| Text: | James O. Berger. Statistical Decision Theory and Bayesian Analysis, | |
| 2nd edition, New York: Springer-Verlag, 1985, | ||
| or 3rd edition (corrected), 1993. |
| |
| Week | Topics | Chapters |
| 1 | Introduction and philosophy. Loss function and risk. | 1; 2; 4.1 |
| 2 | Bayes rule, minimax rule, admissibility. | |
| 3 | Prior and posterior. Conjugate families. | 3; 4.1, 4.2 |
| Generalized Bayes rules. | ||
| 4-5 | Bayesian estimation and hypothesis testing. | 4.3, 4.4 |
| 6 | Empirical Bayes rules | 4.5 |
| MIDTERM EXAM | 1-4.4 | |
| 7 | Hierarchical Bayes analysis. Bayesian robustness. | 4.6, 4.7 |
| 8 | Admissibility of Bayes rules. Bayesian calculation. | 4.8, 4.9 |
| 9 | Game theory and the minimax theorem. | 5 |
| 10 | Sequential decision rules and other topics | 7 |
| 11 | FINAL EXAM on July 31 | 4-7 |
Prerequisites: STAT 5351-5352 (Probability and Mathematical Statistics) is required, STAT 6331 (Statistical Inference) is strongly recommended.