Tidy time series and forecasting in R
Introduction
Day 1
Day 2
On this page
Lab sessions
Lab Session 11
Lab Session 12
Lab Session 13
Introduction to forecasting
09:00-10:30
Date
18 September 2023
Lab sessions
Lab Session 11
Produce forecasts using an appropriate benchmark method for household wealth (
hh_budget
). Plot the results using
autoplot()
.
Produce forecasts using an appropriate benchmark method for Australian takeaway food turnover (
aus_retail
). Plot the results using
autoplot()
.
Lab Session 12
Compute seasonal naïve forecasts for quarterly Australian beer production from 1992.
Test if the residuals are white noise. What do you conclude?
Lab Session 13
Create a training set for household wealth (
hh_budget
) by withholding the last four years as a test set.
Fit all the appropriate benchmark methods to the training set and forecast the periods covered by the test set.
Compute the accuracy of your forecasts. Which method does best?
Repeat the exercise using the Australian takeaway food turnover data (
aus_retail
) with a test set of four years.