STAT565 DECISION THEORY AND BAYESIAN ANALYSIS
| Course Code: |
2460565 |
| METU Credit (Theoretical-Laboratory hours/week): |
3(3-0) |
| ECTS Credit: |
8.0 |
| Department: |
Statistics |
| Language of Instruction: |
English |
| Level of Study: |
Graduate |
| Course Coordinator: |
Prof.Dr. VÝLDA PURUTÇUOÐLU |
| Offered Semester: |
Fall or Spring Semesters. |
Course Content
Introduction to decision making. Subjective and frequentist probability. Bayes theorem and Bayesian decision theory. Advantages of using a Bayesian approach. Likelihood principle, prior and posterior distributions, conjugate families. Inference as a statistical decision problem. Bayesian point estimation, Tests and confidence regions, model choice, invariance, equivariant estimators, hierarchical and empirical Bayes extensions, robustness and sensitivity, utility and loss, sequential experiments, Markov Chain Monte Carlo Methods, Metropolis-Hastings Algorithm, Gibbs Sampling, The EM Algorithm.
