Chapter 12 Resources

This workshop is intended as a brief introduction to basic concepts, and popular packages to help you estimate, evaluate, and visualise GAMs in R, but there is so much more to GAMs!

We have a few resources to suggest if you would like to delve deeper into the subject of GAMs and how to implement them in R. Many of these resources inspired and contributed to the contents of this workshop. This is not meant to be an exhaustive list, but provides some very helpful next steps.

The book Generalized Additive Models: An Introduction with R by Simon Wood (the author of the mgcv package) is probably the most thorough resource you can find about GAMs.
Gavin Simpson’s blog, From the bottom of the heap, covers a lot of different aspects of GAMs and how to implement them in R.
Gavin Simpson’s package gratia is a useful reimplementation of GAM visualisation tools in ggplot2.
Generalized Additive Models: An Introduction with R by Noam Ross is well-designed, interactive, and free course that covers GAMs in greater detail.
Overview GAMM analysis of time series data by Jacolien van Rij is a helpful in-depth tutorial about GAMMs that greatly inspired the GAMM section of this workshop.
Simon Wood also catalogues talks and notes about GAMs on his website (maths.ed.ac.uk/~swood34/).
Hierarchical generalized additive models in ecology: an introduction with mgcv by Pedersen et al. (2019) is a great introduction to hierarchical GAMs, how to design them, and how they can be implemented in R.

Finally, the help pages, available through ?gam in R, are always an excellent resource.