| Date | Topics |
|---|---|
| Week 1 (Aug.27) | Introduction, types of spatial data (Ch.1) |
| Week 2 (Sep.5) | Labor Day Classical geostatistics: exploratory data analysis + basic theory. |
| Week 3 (Sep.10) | Classical geostatistics: kriging, Gaussian processes. (Ch.2) |
| Week 4 (Sep.17) | Areal/lattice data basics: theory of Markov random field models (Ch.3) |
| Week 4 (Sep.19) | Project abstracts due Wed, Sep.19th |
| Week 5 (Sep.24) | Introduction to Bayesian inference and computation. (Ch.4) |
| Week 6 (Oct.1) | Hierarchical modeling for geostatistics (Ch.5) |
| Week 7 (Oct.8) | Bayesian areal/lattice data models (Ch.5) |
| Week 7 (Oct.8) | Revised abstracts due Monday, Oct.8th |
| Week 8 (Oct.15) | Modeling spatially misaligned data (Ch.6) |
| Week 9 (Oct.22) | Spatio-temporal modeling (Ch.8), Multivariate spatial data models (Ch.7) |
| Week 10 (Oct.29) | Spatial point processes |
| Week 11 (Nov.5) | Spatial point processes |
| Week 12 (Nov.12) | Nonstationary models |
| Break (Nov.19) | Thanksgiving |
| Week 13 (Nov.26) | Advanced topics: Spectral methods, Special computational methods |
| Week 14 (Dec.3) | Project presentations |
| Week 15 (Dec.10) | Project presentations |
| Week 15 (Dec.13) | Final project writeups (hard copy) due 12pm, Thursday Dec.13 |