Tosta II - part 2

In the last part of the course we will consider a) numerical methods for generalized linear mixed models and b) give an introduction to Markov random fields.

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

  1. Slides. Videos tosta_logistic1-4 at youtube.

  2. Slides. Note on Laplace approximation. Practical exercise on Laplace approximation.

  3. Slides. Practical exercise on importance sampling.

  4. Slides on Markov random fields I. Additional reading: Chapter on conditional auto regressions (beware, their notation differs a bit from mine).

  5. Slides on Markov random fields II. We continue with Markov random fields.

  6. 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:

  1. Computation of the likelihood function for GLMMs: deterministic quadrature
  2. Computation of the likelihood function for GLMMs: Monte Carlo methods
  3. Markov random fields: the Hammersley-Clifford theorem
  4. Markov random fields: Brooks factorization and Gaussian Markov random fields
The curriculum for the course and exam consists of the lecture slides including the exercises given in the slides.
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