Week 4: The forecaster’s toolbox

Tutorial exercises

• Complete Exercise 2, 3, 10 from Section 3.7 of the book.
• Tutorial learning objectives.

What you will learn this week

• Four benchmark forecasting methods that we will use for comparison
• Fitted values, residuals
• Forecasting using transformations
• Forecasting with decompositions
• Evaluating forecasts

Pre-seminar activities

Read Chapter 5 of the textbook and watch all embedded videos

{r} # #| output: asis # show_slides(week) #

Lectorial activities

1. Create a tsibble with total Holiday travellers for Victoria and Queensland from the tourism data set. Plot the series. What do you see?

2. Generate 4 year ahead forecasts from all four benchmarks. Plot them using autoplot(). Comment in the resulting forecasts.

3. Plot the residuals from the most appropriate benchmark using gg_tsresiduals(). What do you see?

4. Test if the residuals are white noise. What do you conclude?

5. Plot point and interval forecasts from the most appropriate benchmark.

6. Now try a decomposition forecasting model.

7. Use accuracy() to evaluate which benchmark fits the data best.

8. Use a test set of last 3 years to check forecast accuracy.

9. Now use time series cross-validation to check forecast accuracy.

10. Exam 2024

    • Section A: Q3, Q6
    • Section B: Q3a, Q3b

Seminar code

week4.R

Assignments

• GA1 is due on Monday 23 March.
• IA2 is due on Monday 13 April.

Weekly quiz

• Week 4 quiz is due on Monday 23 March.