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  • Week 7: Bayes theory. Markov chains. Chapter 2 and 4 Gamerman & Lopes
  • Week 8: Gibbs sampling. Chapter 5 Gamerman & LopesGibbs sampler in graph . Overview/Example: Repetition)
  • Week 9: Metropolis Hastings. Chapter 6 Gamerman & Lopes. Overview/Example: Repetition)
  • Week 10-11: Exercise 2

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  • Week 12: Bootstraping.
  • Week 13: Boostrapping. (Repetition) Permutation tests. Cross-validation.
  • Week 14: Easter break (No teaching Tuesday 3 April, Friday 6 April, Tuesday 10 April.)
  • Week 15-16: (Repetition). Kernel estimation and classification.
  • Week 16-17: Exercise 3
2012-04-17, Jo Eidsvik