Subjects I'm teaching in 2018
ETC3550: Applied Forecasting for Business and Economics
Reliable forecasts of business and economic variables must often be obtained against a backdrop of structural change in markets and the economy. This unit introduces methods suitable for forecasting in these circumstances including the decomposition of time series, exponential smoothing methods, ARIMA modelling, and regression with auto-correlated disturbances. Students can expect to enhance their computer skills with exercises using R.
- Handbook entry
- Textbook: Forecasting: Principles and Practice, Hyndman & Athanasopoulos (2nd ed., 2018)
- 1. Getting started
- 2. Time series graphics
- 3. The forecasters toolbox
- 5. Time series regression
- 6. Time series decomposition
- 7. Exponential smoothing
- 8. ARIMA models
- 9. Dynamic regression models
- 11. Advanced forecasting methods
- 12. Some practical forecasting issues
ETC3580: Advanced statistical modelling
This unit introduces extensions of linear regression models for handling a wide variety of data analysis problems. Three extensions will be considered: generalised linear models for handling counts and binary data; mixed-effect models for handling data with a grouped or hierarchical structure; and non-parametric regression for handling non-linear relationships. All computing will be conducted using R.
I also teach an online course about forecasting on Datacamp.