Onsite course: Generalised Additive Models for the analysis of spatial and spatial-temporal data. Trondheim, Norway. 4 - 7 September 2023.
Course flyer: Flyer2023_09_Trondheim.pdf
We will start with a non-technical introduction to generalised additive models (GAM). Using a series of exercises, we show how GAMs can be used to allow for non-linear covariate effects. Once we are familiar with GAM, we will apply them to various spatial, and spatial-temporal data sets.
During the course, GAMs are applied to count data, absence-presence data, proportional data, and continuous data using the Gaussian, Poisson, negative binomial, Bernoulli, beta, gamma and Tweedie distributions.
We will apply GAMs with 2-dimensional smoothers to analyse spatial data. To allow for natural barriers (e.g. an island in the sea), soap-film smoothers are used. On the 4th day of the course, spatial-temporal data sets are analysed.
The course contains a short revision of generalised linear models (GLM). During the course, we will explain the beta, Gamma, and Tweedie distributions. Preparation material on data exploration and linear regression with on-demand video is supplied.
Throughout the course we will use the mgcv package in R. This is a non-technical, and easy-to-follow course.
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). A discussion board (access for 12 months) allows for interaction on course content between instructors and parti-cipants. You are invited to apply the statistical techniques discussed dur-ing the course on your own data and if you encounter any problems, you can ask questions during the 1-hour face-to-face chat.