Week 6: Exponential smoothing

Tutorial exercises

• Complete Exercises 1-5 from Section 8.8.
• Tutorial learning objectives.
• Week 6 Tutorial Solution.html

What you will learn this week

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

Pre-seminar activities

Read Sections 8.4-8.7 of the textbook and watch all embedded videos.

Slides for seminar

Download pdf

Seminar activities

1. Use the tsibble created from tourism for holiday travel in Victoria and Queensland. Plot the series to remind yourself what these look like.

2. Use the ETS() function to fit models with additive and multiplicative errors to both series. Also let ETS() auto select models. Explore the fitted models and their residuals.

3. Generate forecasts from the fitted models. Why is the multiplicative model needed for Victoria?

4. Generate the h02 series from the PBS tsibble using the code below. Plot the data and study it’s features. What ETS model would be appropriate for forecasting this data?

   h02 <- PBS |>
   filter(ATC2 == "H02") |>
   summarise(Cost = sum(Cost))

5. Find an ETS model and study it.

6. Generate forecasts for the next few years.

7. Combine STL decomposition with ETS to forecast the h02 series.

8. Exam 2024

   • Section A: Q1, Q2
   • Section B: Q3d, Q3e, Q3f
   • Section C: all questions

Seminar code

week6.R

Assignments

• IA2 is due on Monday 07 April.
• GA2 is due on Monday 14 April.
• IA3 is due on Monday 28 April.