  This is a hands-on introduction to Generalised Additive Mixed Models (GAMMs)
in the context of linguistics with a particular focus on dynamic speech
analysis (e.g. formant contours, pitch tracks, diachronic change, etc.). The
main goal is to explain some of the main ideas underlying GAMMs, and to provide
a practical guide to frequentist significance testing using these models. The
introduction covers a range of topics including basis functions, the smoothing
penalty, random smooths, difference smooths, smooth interactions, model
comparison and autocorrelation. It is divided into two parts. The first part
looks at what GAMMs are, how they work and why/when we should use them.
Although the reader can replicate some of the example analyses in this section,
this is not essential. The second part is a tutorial introduction that
illustrates the process of fitting and evaluating GAMMs in the R statistical
software environment, and the reader is strongly encouraged to work through the
examples on their own machine.
