Performing time series decomposition using the stl() function

Nearly every phenomenon can be represented as a time series.

It is therefore not surprising that time series analysis is one of most popular topics within data-science communities.

As is often the case, R provides a great tool for time-series decomposition, starting with the stl() function provided within base R itself. This function will be the base of our recipe.

Getting ready

This recipe will mainly use the stl() function, which implements the Loess() method for time-series decomposition.

Using this method, we are able to separate a time series into three different parts:

  • Trend component: This highlights the core trend of the phenomenon if perturbations and external influence were not ...

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