Week 9: ARIMA models

Tutorial exercises

• Complete Exercises 7, 8, 15 (a to c), 16 (a to c) from Section 9.11 of the book.
• Tutorial learning objectives.
• Week 9 Tutorial Solution.html

What you will learn this week

• Seasonal ARIMA models
• Computing forecasts for ARIMA models
• ARIMA vs ETS models

Pre-seminar activities

Read Sections 9.8-9.10 of the textbook and watch all embedded videos

Slides for seminar

Download pdf

Seminar activities

1. Identify, estimate and generate forecasts from ARIMA models for the usmelec, leisure and h02 as specified below:

   usmelec <- as_tsibble(fpp2::usmelec) |>
     rename(Month = index, Generation = value)
   
   leisure <- us_employment |>
     filter(Title == "Leisure and Hospitality", year(Month) > 2000) |>
     mutate(Employed = Employed/1000) |> select(Month, Employed)
   
   h02 <- PBS |>
     filter(ATC2 == "H02") |>
     summarise(Cost = sum(Cost))

2. Identify, estimate and generate forecasts from ARIMA and ETS models for the aus_economy and cement as specified below:

   aus_economy <- global_economy |> filter(Code == "AUS") |>
     mutate(Population = Population/1e6)
   
   cement <- aus_production |>
     select(Cement) |>
     filter_index("1988 Q1" ~ .)

3. Exam 2024

   • Section A: Q5
   • Section B: Q3 (g-h)
   • Section D: all questions

Seminar code

week9.R

Assignments

• GA3 is due on Monday 05 May.
• IA4 is due on Monday 19 May.