Week 6: Exponential smoothing

What you will learn this week

  • Exponential smoothing methods with trend and seasonality
  • ETS models
  • Automatic model selection using the AICc

Pre-class activities

Read Chapter 8 of the textbook and watch all embedded videos

Exercises (on your own or in tutorial)

Complete Exercises 1-4, 16, 17 from Section 8.8 of the book.

Solutions to Exercises

Slides for seminar

Download pdf

Seminar activities

  1. Try forecasting the Chinese GDP from the global_economy data set using an ETS model.

    Experiment with the various options in the ETS() function to see how much the forecasts change with damped trend, or with a Box-Cox transformation. Try to develop an intuition of what each is doing to the forecasts.

    [Hint: use h=20 when forecasting, so you can clearly see the differences between the various options when plotting the forecasts.]

  2. Find an ETS model for the Gas data from aus_production and forecast the next few years.

    • Why is multiplicative seasonality necessary here?
    • Experiment with making the trend damped. Does it improve the forecasts?

R code used in seminar