Generalised Additive Mixed Models (GAMM): modelling space-time correlation structures

July 3rd, 7th, and 9th, 2026

Registration

Contact

courses@transmittingscience.com

Course Generalised Additive Mixed Models (GAMM) modeling space-time correlation structures

Registration is closed

Are you interested in this course?

Please fill in the form below, and we will let you know as soon as the next edition is announced.
You can also use this form to request this as an in-house course for your group.

Click here to express interest in this course

Course Overview

The objective of this course is to teach participants to:

Visualise and perform tests of correlation structures in time and space in their datasets
Adjust a GAM model
Adjust a GAM+M model with auto-correlation structure (temporal)
Adjust a GAM+M model with auto-correlation structure (spatial-temporal)

Places are limited to 18 participants.

Programme

Module I. Spatial and Temporal Autocorrelation

Definition of spatial and temporal autocorrelation
Tools for detection of spatial and temporal autocorrelation
GAM Models
Theory of Additive Models (AM) and Generalized Additive Models (GAM)
Simple GAM Model
Fitting and Validation of a simple GAM model (bivariate)
Multiple GAM Models (multivariable)
Fitting and Validation of a multiple GAM model
Multiple GAM for count data with an offset

Module II. Mixed Models and GAMMs

Introduction to Mixed Effects Models
Fitting GAM Model and Independence Validation
Fitting and validation of GAMM 1 Model
GAMM with temporal autocorrelation structure
Fitting and validation of GAMM 2 Model
GAMM with space-temporal structure
Resolution of specific work doubts

Assumed Background

Participants must have working knowledge of R.

Software

All participants must have a personal computer with current versions of R and RStudio.

Dates & Schedule

Online live sessions on July 3rd, 7th, and 9th, 2026.

From 15:00 to 19:00 (Madrid time zone).

Total course hours: 21 (12 hours of online live lessons, plus 9 hours of participants working on tutored exercises independently).

Format

In the live sessions we will combine online lectures with hands-on computational exercises in R.

Live sessions will be recorded. However, attendance to the live sessions is required to obtain the course certificate.

This course will be delivered in English.

Instructor

Dr. Antonio Canepa
University of Burgos
Spain

Registration Fees

Course Fee
Early bird (until May 31st 2026):
346 €
(276.80 € for Ambassador Institutions)
Regular (after May 31st 2026):
420 €
(336 € for Ambassador Institutions)
Prices include VAT.
After registration you will receive confirmation of your acceptance on the course.
Payment is not required during registration. Check discounts here.
How do I get the Ambassador Institution discount?
Registration