This book uses R and is designed to be used with R. R is free, available on almost every operating system, and there are thousands of add-on packages to do almost anything you could ever want to do. We recommend you use R with RStudio.
- Download and install R.
- Download and install RStudio.
- Run RStudio. On the “Packages” tab, click on “Install” and install the package
fpp3(make sure “install dependencies” is checked).
That’s it! You should now be ready to go.
We provide R code for most examples in shaded boxes like this:
# Load required packages library(fpp3) # Plot one time series %>% aus_retail filter(`Series ID`=="A3349640L") %>% autoplot(Turnover) # Produce some forecasts %>% aus_retail filter(`Series ID`=="A3349640L") %>% model(ETS(Turnover)) %>% forecast(h = "2 years")
These examples assume that you have the
fpp3 package loaded as shown above. This needs to be done at the start of every R session, but it won’t be included in our examples.
Sometimes we assume that the R code that appears earlier in the same chapter of the book has also been run; so it is best to work through the R code in the order provided within each chapter.
If you have never previously used R, please work through the first section (chapters 1-8) of “R for Data Science” by Garrett Grolemund and Hadley Wickham. While this does not cover time series or forecasting, it will get you used to the basics of the R language, and the
tidyverse packages. The Coursera R Programming course is also highly recommended.
You will learn how to use R for forecasting using the exercises in this book.