# Enable universe(s) by inlabru-org
options(repos = c(
inlabruorg = "https://inlabru-org.r-universe.dev",
INLA = "https://inla.r-inla-download.org/R/testing",
CRAN = "https://cloud.r-project.org"
))
# Install some packages
install.packages("inlabru")inlabru Workshop
ICES 2025, Copenhagen
Welcome to the course!
- Welcome to the
inlabruworkshop! - The aim of this workshop is to introduce you to a range of statistical modelling approaches, in particular the temporal, spatial and spatio-temporal modelling as implemented in the
inlabrupackage. - Workshop materials are available in the github repository inlabru-workshop
Feedback
We would be very glad if you could fill in this form and share your feedback about the course.
The form can also be accessed using the QR code below

Learning Objectives for the workshop
At the end of the workshop, participants will have an understanding of:
- the motivation for and the challenges of analysing and modelling spatial data
- statistical models used to analyse spatial and spatio-temporal data
- the implementation of these models in the
inlabrupackage - how to independently analyse spatial data with
inlabru
Intended audience
The workshop aims to cater for participants with a range of different backgrounds, who is interested in analysing data with modern spatial and spatio-temporal statistical modelling approaches.
Prerequisites
Participants should be familiar with the R environment, and general statistical approaches for modelling such as regression, analysis of (co)variance, and generalized linear models.
No knowledge of R-INLA or inlabru is required.
Schedule
| Time | Topic |
|---|---|
| 10:00 - 10:30 | ICES information session |
| 10:30 - 11:30 | Session 1: Introduction to inlabru |
| 11:30 - 13:00 | Practical Session 1 |
| 13:00 - 14:30 | Lunch break 🍽️ |
| 14:30 - 15:30 | Session 2: Latent Gaussian Models and INLA |
| 15:30 - 15:45 | Coffee Break ☕ |
| 15:45 - 16:45 | Practical Session 2 |
| 16:45 - 17:00 | wrap-up and outlook |
| Time | Topic |
|---|---|
| 9:00 - 10:00 | Session 3: Temporal modelling and smoothing part 1 |
| 10:00 - 10:30 | Snack 🥙 |
| 10:30 - 11:30 | Temporal modelling and smoothing part 2 |
| 11:30 - 13:00 | Practical Session 3 |
| 13:00 - 14:30 | Lunch break 🍽️ |
| 14:30 - 15:30 | Session 5: Introduction to Spatial Statistics |
| 15:35 - 15:45 | Coffee Break ☕ |
| 15:45 - 16:45 | Practical Session 4 |
| 16:45 - 17:00 | wrap-up and outlook |
| Time | Topic |
|---|---|
| 9:00 - 10:00 | Session 6: Areal Processes |
| 10:00 - 10:30 | Snack 🥙 |
| 10:30 - 11:30 | Session 7: Geostatistics |
| 11:30 - 13:00 | Practical Session 5 |
| 13:00 - 14:30 | Lunch break 🍽️ |
| 14:30 - 15:30 | Session 8: Spatial Point processes |
| 15:35 - 15:45 | Coffee Break ☕ |
| 15:45 - 16:45 | Practical Session 5 continued |
| 16:45 - 17:00 | wrap-up and outlook |
| Time | Topic |
|---|---|
| 9:00 - 10:00 | Session 9: Spatiotemporal models |
| 10:00 - 10:30 | Snack 🥙 |
| 10:30 - 11:30 | Session 10: Model comparison and evaluation |
| 11:30 - 13:00 | Practical Session 6 |
| 13:00 - 14:30 | Lunch break 🍽️ |
| 14:30 - 15:30 | Session 11: Multi-likelihood/joint likelihood models |
| 15:35 - 15:45 | Coffee Break ☕ |
| 15:45 - 16:45 | Practical Session 7 |
| 16:45 - 17:00 | wrap-up and outlook |
| Time | Topic |
|---|---|
| 9:00 - 10:00 | Session 12: Zero inflated models |
| 10:00 - 10:30 | Snack 🥙 |
| 10:30 - 11:30 | Session 13: Complex observational processes: Distance Sampling |
| 11:30 - 13:00 | Practical Session 8: Zero Inflated models - Distance sampling |
| 13:00 - 13:15 | Coffee Break ☕ |
| 13:15 - 14:00 | Closing session |
In preparation for the workshop
Participants are required to follow the below steps ahead of the first day of the workshop:
Check your
Rversion, it should be at least 4.3….Install R-INLA
Install
inlabru(available from CRAN)
- Make sure you have the latest
R-INLA,inlabruandRversions installed. - Install the following libraries:
install.packages(c(
"CARBayesdata",
"DAAG",
"dplyr",
"FSAdata",
"ggplot2",
"gt",
"lubridate",
"magrittr",
"mapview",
"patchwork",
"scico",
"sdmTMB",
"sf",
"spatstat",
"spdep",
"terra",
"tidyr",
"tidyterra",
"tidyverse"
))