Programme of the course

Course is every day from 9.00am until 16.00pm except for Friday (finish at 12.45pm)


  • General introduction.
  • Theory presentation on options and limitations of adding dependency to a regression model using frequentist techniques: Temporal correlation, spatial correlation, mixed effects models.
  • Short introduction to mixed effects models.
  • Various exercises.
  • Short introduction to Bayesian analysis.
  • Conjugate priors.
  • Diffuse versus informative priors.

Tuesday and Wednesday:

  • Theory presentation on INLA.
  • Fitting linear regression, mixed effects models and GLMs in R-INLA.
  • Theory presentation on adding spatial correlation to regression models in R-INLA.
  • Various exercises showing how to add spatial correlation to linear regression models, Poisson, negative binomial and Bernoulli GLMs. Solution files for applying gamma and binomial GLMs in R-INLA are provided.

Thursday - Friday:

  • Theory presentation on temporal correlation in R-INLA.
  • Various exercises.
  • Theory presentation on adding spatial-temporal correlation in R-INLA.
  • Various exercises showing how to add spatial-temporal correlation to GLM and GLMMs.