Some data sets and R-code used in the course.

- Slides. Videos tosta_logistic1-4 at youtube.
- Slides. Note
on Laplace
approximation. Practical
exercise on Laplace approximation.
- Slides. Practical exercise on importance sampling.
- Slides on Markov
random fields I. Additional reading: Chapter on conditional auto regressions (beware, their notation differs a bit from mine).
- Slides on Markov
random fields II. We continue with Markov random fields.
- Selfstudy on Markov random fields and Bayesian image analysis.

Additional reading material: page 1-23 in "Markov random fields and their applications" by Kindermann and Snell.

**Eksamensspørgsmål:**

- Computation of the likelihood function for GLMMs: deterministic quadrature
- Computation of the likelihood function for GLMMs: Monte Carlo methods
- Markov random fields: the Hammersley-Clifford theorem
- Markov random fields: Brooks factorization and Gaussian Markov random fields

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