Schedule of readings
- Week 1
- Day 1: Welcome
- Day 2: Hypothesis testing (reading, figures are not included)
- Week 2
- Week 3
- Week 4
- Day 1: Interweaving (reading (through sec 2))
- Day 2: Hamiltonian Monte Carlo (reading (sec 3-4))
- Week 5 - Dynamic linear models in R (book webpage)
- Day 1: DLMs 1 (reading (through 2.8), code)
- Day 2: DLMs 2 (reading (through 3.2 but not 3.1.2 or 3.2.5), code)
- Week 6 -
- Day 1: DLMs 3 (reading (through 4.5))
- Day 2: DLMs 4 (reading)
- Week 7 -
- Day 1: Particle MCMC (reading (through 3.1))
- Day 2: Particle learning (reading (through 3)
- Week 8 - Hierarchical Modeling and Analysis for Spatial Data
- Day 1: Gaussian Processes (Ch. 21 of BDA)
- Day 2: Conditionally Autoregressive Models
- Week 9
- Day 1: Slice sampling
- Week 10
- Week 11
- Day 1: Bayesian nonparametrics, you may want to read the discussions
- Day 2: Finite mixtures - Ch 22 of Bayesian Data Analysis (2rd ed) (Ch 18 of 2nd ed)
- Week 12
- Day 1: Dirichlet process - Ch. 23 of BDA
- Week 13
- Day 1
- Day 2: Ch. 20 of BDA