Intermediate Bayesian Statistical Modeling
Calendar and Notes
| Week | DATES | TOPIC | NOTES |
| Week 1 | 03/31 - 04/02 | Introduction. Description of the syllabus. Background material | slides1.pdf |
| background.pdf | |||
| Week 2 | 04/07 - 04/09 | Large sample inference Chp. 4, Chp. 10, 13.3 |
slides2.pdf |
| The multinomial and the multivariate normal models. 3.5,3.6 |
slides3.pdf | ||
| Week 3 | 04/14 - 04/16 | Hierarchical models and meta-analysis. 5.1-5.6 |
|
| Model Checking. 6.1-6.5 |
slides6.pdf slides7.pdf |
||
| Week 4 | 04/21 - 04/23 | Model comparison. 7.1-7.4 Quiz 1 (30%) |
slides7a.pdf |
| Accounting for data collection schemes. 8.1-8.5 |
slides8.pdf | ||
| Week 5 | 04/28 - 04/30 | Observational studies. Censoring and truncation. 8.6-8.8 |
slides9.pdf |
| Auxiliary variables for Monte Carlo methods. 12.1 |
slides10.pdf | ||
| Week 6 | 05/05 - 05/07 | Regression models. 14.1-14.8 |
slides11.pdf |
| Regression models. 14.1-14.8 |
slides12.pdf | ||
| Week 7 | 05/12 - 05/14 | Midterm (40%) | |
| G-priors. Regularization. Robust Inference. 17.1-17.5 |
slides13.pdf slides14.pdf |
||
| Week 8 | 05/19 - 05/21 | Mixture models. 22.1-22.5 |
slides15.pdf |
| Mixture models. 22.1-22.5 |
|||
| Week 9 | 05/26 - 05/28 | Posterior Modes. EM algorithm. 13.1-13.4 |
slides16.pdf |
| Efficient Gibbs and Metropolis samplers. 12.1-12.3 |
slides17.pdf | ||
| Week 10 | 06/02 - 06/04 | Approximations 13.7 |
|
| Gaussian process models 21.1-21.5 Quiz 1 (30%) |
slides18.pdf |
| Attachment | Size |
|---|---|
 slide7.pdf | 65.14 KB |