Course flyer
This is an onsite live course
GLMs and GAMs with Spatial, or Spatial-Temporal Correlation using INLA
Dates and times: 9 - 13 November 2026. 09.00 - 16.00 (CET)
This course offers a practical introduction to the analysis of spatial, and spatial-temporal data using generalised linear models (GLMs) and generalised additive models (GAMs) in INLA (using inlabru).
This course offers a practical introduction to the analysis of spatial, and spatial-temporal data using generalised linear models (GLMs) and generalised additive models (GAMs) in INLA (using inlabru). We begin with how to add spatial structure to regression models using frequentist techniques, and then introduce Bayesian methods, focusing on how to implement models with spatial or spatial-temporal dependency using INLA. The course covers a range of data types and distributions, including Gaussian, Poisson, generalised Poisson, negative binomial, Bernoulli, Gamma and Tweedie.
Participants will learn how to build models that incorporate spatial correlation, and spatio-temporal structure, and how to address practical challenges such as modelling in the presence of natural barriers (e.g., coastlines, forests) that prevent spatial correlation from extending freely across space, such as marine/terrestrial boundaries or fragmented habitats. We will also cover the use of more complex spatial meshes and multivariate likelihoods to accommodate study areas with isolated groups of sites.
We will utilise the inlabru package in R
The course includes a 1-hour face-to-face video chat with the instructors.
Pre-required knowledge
Working knowledge of R, data exploration, linear regression and GLM (Poisson, negative binomial,
Bernoulli). This is a non-technical course. The course website provides preparatory materials, including on-demand videos and R scripts covering multiple linear regression, basic matrix notation, generalised linear models, model validation using DHARMa, and the explanation of variograms. If you are not familiar with these methods, please review them before the course begin
1 hour face-to-face
The course includes a 1-hour face-to-face video chat with the instructors (to be used after the course). You are invited to apply the statistical techniques discussed during the course on your own data and if you encounter any problems, you can ask questions during the 1-hour face-to-face chat.
A discussion board (access for 12 months) allows for interaction on course content between instructors and participants.
See the course flyer for course content by day: Flyer.
For terms and conditions, see: