Exploring time series forecasting with forecast()
The most logical next step after understanding a time series' features and trends is trying to forecast its future development.
As one would imagine, R provides optimal tools to perform this task.
In this recipe, we will leverage the extremely popular
forecast package by Professor Rob J Hyndman. The package provides an always increasing number of tools for performing univariate time series forecasting.
You can find out more on the package on Prof. Hyndman's personal site at http://robjhyndman.com/software/forecast/.
As stated earlier, the only package needed to perform this recipe is the
forecast package. We therefore need to install it and load it:
install.packages("forecast") library(forecast) ...