The Rmarkdown notebooks in this directory are as follows. Each notebook also has a corresponding HTML file, which is the rendered output from running the code.

`01_dataprep.Rmd`

creates the training and test datasets`02_basic_models.Rmd`

fits a range of simple time series models to the data, including ARIMA and ETS.`02a_reg_models.Rmd`

adds independent variables as regressors to the ARIMA model.`02b_prophet_models.Rmd`

fits some simple models using the Prophet algorithm.

If you want to run the code in the notebooks interactively, you must start from `01_dataprep.Rmd`

and proceed in sequence, as the earlier notebooks will generate artifacts (datasets/model objects) that are used by later ones.

The following packages are needed to run the basic analysis notebooks in this directory:

- rmarkdown
- dplyr
- tidyr
- ggplot2
- tsibble
- fable
- feasts
- yaml
- here

Itâ€™s likely that you will already have many of these (particularly the Tidyverse packages) installed, if you use R for data science tasks. The main exceptions are the packages in the Tidyverts family, which is a modern framework for time series analysis building on the Tidyverse.

```
install.packages("tidyverse") # installs all tidyverse packages
install.packages("rmarkdown")
install.packages("here")
install.packages(c("tsibble", "fable", "feasts"))
```

The following packages are needed to run the Prophet analysis notebook:

- prophet
- fable.prophet

While prophet is available from CRAN, its frontend for the tidyverts framework, fable.prophet, is currently on GitHub only. You can install these packages with

```
install.packages("prophet")
install.packages("https://github.com/mitchelloharawild/fable.prophet/archive/master.tar.gz", repos=NULL)
```