Lectures for STK4050 Fall 2011


Reference are to the course text book R&K (Rubinstein & Kroese) unless otherwise statet.

Lectures so far

Lecture Monday 29/8:

  • General introduction to the course
  • Sections 2.1-2.3.1 in R&K: Random number generation and inverse transform method

    Lecture Monday 5/9:

  • Sections 2.3.2-2.6 in R&K: More on random number generation
  • Section 4.2 in R&K: Monte Carlo integral

    Lecture Monday 12/9:

  • Chapter 5.1-5.3 and 5.5 i R&K
  • Here are R-scripts for the simulations presented in the lecture on MC-integrals of the exponential and sin(Qx) exp(x).

    Lecture Monday 26/9:

  • Chapter 5.3 and 5.5 in R&K
  • Here are the R-files we used: Random sum (Pr. 5.7b and c in R(K),
    Conditioning for function sin(Qx) exp(x) and
    Importance sampling for function exp(x).

    Lecture Monday 3/10:

  • Importance sampling 5.6 to 5.6.3 in R&K

    Lecture Monday 10/10:

  • Review of Markov chains 1.12.1-1.12.4 in R&K
  • Introduction to Metropolis-Hasting, Chapter 6 in R&K, pg. 168-169.

    Lecture Monday 17/10:

  • More on Metropolis-Hasting, Chapter 6.2 in R&K.
  • We did also discuss some points made in Chapter 4, pg.104.
  • Here is some R code used in the lecture.

    Lecture Monday 24/10:

  • More on MCMC: 6.4 The Gibbs sampler, 6.6 Bayesian statistics
  • Useful to read a chapter on Bayesian methods by Geir Storvik.
  • Here are a couple of R-scripts used in the lecture: Bayes on binomial data and Gibbs-sampling for Example 6.4 in R&K


    Plans for future lectures

    Lecture Monday 31/10:

  • More on MCMC: 6.3 Hit-and-run sample, 6.4 The Gibbs sampler (continued).

    Lectures November:

  • Some more stuff related to MCMC

    Ansvarlig: Sven Ove Samuelsen. Oppdatert 13.10.11