Bayesian Computational Statistics & Modeling
Welcome to Professor Haavard Rue's research group


Courses offered

The research group will give theses courses

  • Bayesian statistics   (200-level) An introduction course to Bayesian statistics where we go through a series of examples, discussing statistical modeling, interpretation of the results and how to do Bayesian inference using MCMC/rjags, while implementing everything in R.  Will be given fall 2017.
  • Computational statistics (300-level) In this course we will discuss more advanced topics relevant for Bayesian inference, like forward-backward recursions for hidden Markov chains, Gaussian Markov random fields and computations with them using numerical methods for sparse matrices, strategies for block-updating within MCMC and auxilliary variables, Integrated nested Laplace approximations, Markov representations/approximations of Gaussian fields. Will be given winter 2019 (I think).