Automatic forecasting with exponential smoothing

The namesake function for finding errors, trend, and seasonality (ETS) provides a completely automatic way of producing forecasts for a wide range of time series.

You will now test it on two series, austa and hyndsight, that you have previously looked at in this chapter. Both have been pre-loaded into your workspace.

Using ets(), fit an ETS model to austa and save this to fitaus.
Using the appropriate function, check the residuals from this model.
Plot forecasts from this model by using forecast() and autoplot() together.
Repeat these three steps for the hyndsight data and save this model to fiths.
Which model(s) fails the Ljung-Box test? Assign fitausfail and fithsfail to either TRUE (if the test fails) or FALSE (if the test passes).

Exercise

Automatic forecasting with exponential smoothing

Instructions