Highland Statistics Ltd

On demand: Introduction to GAM and GAMM using frequentist tools

Online course with on-demand video and live Zoom meetings:

Introduction to GAM and GAMM using frequentist tools

This online course consists of 5 modules representing a total of approximately 40 hours of work. Each module consists of multiple video files with short theory presentations, followed by exercises using real data sets, and video files discussing the solutions. All video files are on-demand and can be watched online, as often as you want, at any time of the day, within a 6 month period.

A discussion board allows for daily interaction between instructors and participants. The course also contains 5 2-hour live web meetings (using Zoom) in which we summarise the theory and the exercises. Attending these live web meetings is optional. We will run the web meetings in different time zones. These Zoom summary sessions will be recorded and you can watch them on the course website. You can also use a Discussion board to ask any questions on the course material. The course fee includes a 1-hour face-to-face video chat with the instructors. You can use this video chat to ask questions about your own data.

A detailed outline of the course is provided below. All exercises consist of a data set, a video describing the data and the questions, R solution code and a video discussing the R solution file.

Course content

We start with a short revision of data exploration and linear regression. We then introduce generalised additive models (GAM) to model non-linear relationships. We will execute these models in mgcv.

In Module 2, we will revise linear mixed-effects models and show how to implement a generalised additive mixed-effects model (GAMM). We also show how to include an interaction between a smoother and a categorical covariate.

In Module 3, we will revise basic GLMs and extend these towards GAMs. In Modules 4 and 5 we will discuss GAMMs for the analysis of count data, absence-presence data, proportional data and continuous data.

Keywords: Gaussian, Poisson, negative binomial, generalised Poisson, gamma, Tweedie, Bernoulli, binomial and beta GAMs and GAMMs.


A detailed outline of the course will be provided in April 2022.


Free 1-hour face-to-face video meeting: The course fee includes a 1-hour face-to-face video meeting with one or both instructors. The meeting needs to take place within 3 months after the last live zoom meeting. You can discuss your own data but we strongly suggest that the statistical topics are within the content of the course. The 1-hour needs to be used in one session and will take place on a mutually convenient day and time of the day.

Web meetings: Web meetings are hosted on zoom.us. Click here for recommended internet speed (see the text under 'Recommended bandwidth for Webinar Attendees'). We will record the meetings and make them available on the course website.

Discussion Board: You can use the Discussion Board to ask any questions related to the course material. 

Pre-required knowledge: The required knowledge for this course is fairly high. You need to have good knowledge of R, data exploration, linear regression and GLM (Poisson, negative binomial, Bernoulli). And you need to have a working knowledge of mixed-effects models. We strongly recommend that you only join this course if you either attended one of our INLA courses or are familiar with R-INLA. Short revisions are provided. This is a non-technical course.

Cancellation policy: What if you are not able to participate? Once participants are given access to course exercises with R solution codes, pdf files of certain book chapters, pdf files of PowerPoint or Prezi presentations and video solution files, all course fees are non-refundable and non-transferable to another participant.

Copyright: Sharing the access details of the course website or the pdf files of our course material is prohibited. Video files cannot be downloaded, but they can be watched in the same way as on Netflix.