# Week 6: Exponential smoothing

## What you will learn this week

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

## Pre-class activities

Read Chapter 8 of the textbook and watch all embedded videos

## Exercises (on your own or in tutorial)

Complete Exercises 1-4, 16, 17 from Section 8.8 of the book.

## Slides for seminar

## Seminar activities

Try forecasting the Chinese GDP from the

`global_economy`

data set using an ETS model.Experiment with the various options in the

`ETS()`

function to see how much the forecasts change with damped trend, or with a Box-Cox transformation. Try to develop an intuition of what each is doing to the forecasts.[Hint: use

`h=20`

when forecasting, so you can clearly see the differences between the various options when plotting the forecasts.]Find an ETS model for the Gas data from

`aus_production`

and forecast the next few years.- Why is multiplicative seasonality necessary here?
- Experiment with making the trend damped. Does it improve the forecasts?

## Assignments

- Assignment 3 is due on Sunday 14 April.