Lectures: There is 1 x 2 hr lecture each week.
SGTAs: There is 1 x 1 hr SGTA class each week.
Course notes are available on iLearn, prior to the lecture. SGTA solutions are posted on iLearn.
Required and recommended resources
There is no prescribed text for this unit. The following are useful references:
- Fahrmeir, L., Kneib, T., Lang, S. and Marx, B. (2013). Regression: Models, Methods and Applications, Springer.
- Faraway, J. J. (2016). Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. CRC Press.
- De Jong, P. and Heller, G.Z. (2008). Generalized Linear Models for Insurance Data, Cambridge University Press.
- Wood, Simon N. (2017). Generalized additive models: an introduction with R, 2nd edition. CRC Press.
- Stasinopoulos M. D., Rigby R. A., Heller G. Z., Voudouris V., De Bastiani F. (2017). Flexible Regression and Smoothing: Using GAMLSS in R. CRC Press.
- Dobson, A. J. and Barnett, A. G. (2018). An Introduction to Generalized Linear Models, 4th edition, Chapman & Hall.
- Lindsey, J.K. (1997). Applying Generalized Linear Models, Springer.
- McCullagh, P. and Nelder, J.A. (1989). Generalized Linear Models, 2nd edition, Chapman & Hall.
Recommended web sites
A comprehensive list of online resources for self-learning R, is given on iLearn.
We will be using R, which is freely downloadable from the CRAN website. We recommend the use of the RStudio interface, also freely downloadable.
We will be using iLearn for posting course notes, assignments, solutions and data sets, and online discussions. You are encouraged to use the forums for discussions on the course material. Remember that if you are confused about something, the chances are that other students are also confused. Everybody benefits from the discussions, and you should not be embarrassed to admit that you do not understand a concept.
Audio recordings of lectures
Audio recordings of the lectures (Echo) will be available on the iLearn site.