| CW2: 12.01 (10:15-12:00), Zoom | L1 | Introduction and Part 1: Markov chain Monte Carlo (MCMC) | Assumed background knowledge, getting to know each other and the plans ahead, starting introducing Markov chain Monte Carlo | Slides |
| CW3: 19.01 (10:15-12:00), Zoom | L2 | Part 1: MCMC: Metropolis-Hastings | Different proposal distributions (independent, random walk, Langevin), Gibbs sampling | Slides, Metropolis algorithm illustration, Ipad notes for lecture 1 and 2, Link to MCMC gallery app: MCMC-demo |
| CW4: 26.01 (10:15-12:00), 734 Sentralbygg II | L3 | Part 1: MCMC: Hamiltonian | Convergence and diagnostic checks, MCMC using auxiliary variables, Hamiltonian MCMC | we continue with the material from last time |
| CW4: 26.01 (14:00-15:00), 734 Sentralbygg II | Paper discussion | Part 1 | Dunson and Johndrow (2020), The Hastings algorithm at fifty | |
| CW5: 02.02 (10:15-12:00), F4 Gamle Fysikk | L4 | Part 1: MCMC: Stan | Introduction to Stan and RStan http://mc-stan.org | Slides, Stan example in R: R-part, Stan-part |
| CW5: 02.02 (14:00-15:00), R4 Realfagbygget | Paper discussion | Part 1 | Betancourt (2017), A conceptual introduction to Hamiltonian Monte Carlo | |
| CW6: 09.02 (10:15-12:00), 734 Sentralbygg II | L5 | Part 1: Project work | | |
| CW7: 16.02 (10:15-12:00), 734 Sentralbygg II | L6 | Part 2: Gaussian processes | Repetition of properties of multivariate normal, definition and simulation from GPs | Slides, simGP.R |
| CW8: 23.02 (10:15-12:00), F4 Gamle Fysikk | L7 | Part 2: Gaussian processes | Gaussian process regression, parameter estimation, predictions, proper scoring rules | Slides |
| CW8: 23.02 (14:00-15:00), R4 Realfagbygget | Paper discussion | Part 2 | Heaton (2018), A case study competition among methods for analyzing large spatial data | |
| CW9: 02.03 (10:15-12:00), 734 Sentralbygg II | L8 Geir-Arne Fuglstad | Part 2 | Modern Spatial Statistics | Slides |
| CW10: 09.03 (10:15-12:00), 734 Sentralbygg II | L9 | Part 2: INLA | | Slides |
| CW10: 09.03 (14:00-15:00), R4 Realfagbygget | Paper discussion | Part 2 | Martino and Riebler (2014), Integrated nested Laplace approximations (INLA) | |
| CW11: 16.03 (10:15-12:00), F4 (Gamle Fysikk) | L10 | Part 2 | Prior distributions | Slides |
| CW12 | | Part 2: project work | | |
| CW13: 28.03 (14:15-16:00), F4 Gamle Fysikk | L12: Henning Omre | Part 3 | | Slides |
| CW13: 30.03 (10:15-12:00), F4 Gamle Fysikk | L13: Henning Omre | Part 3 | | |
| CW14: 06.04 (10:15-12:00), F4 Gamle Fysikk | L14: Henning Omre | Part 3 | | Slides |
| CW14: 07.04 (10:15-12:00), 734 Sentralbygg II | L15: Henning Omre | Part 3 | | |
| CW15: | EASTER HOLIDAY | | | |
| CW16: 20.04 (10:00-12:00), F4 (Gamle Fysikk) | 2 paper discussions | Part 3 | * Speekenbrink, M. (2016). A tutorial on particle filters, * Katzfuss, M., Stroud, J. R., & Wikle, C. K. (2016). Understanding the ensemble Kalman filter | |
| CW17: 27.04 (10:15-12:00), 734 Sentralbygg II | | Part 3: Project work | | |