R for Data Science Cookbook

Decomposing time series

A seasonal time series is made up of seasonal components, deterministic trend components, and irregular components. In this recipe, we introduce how to use the decompose function to destruct a time series into these three parts.

Getting ready

Ensure you have completed the previous recipe by generating a time series object and storing it in two variables: m and m_ts.

How to do it…

Please perform the following steps to decompose a time series:

1. First, use the window function to construct a time series object, m.sub, from m:

   > m.sub = window(m, start=c(2012, 1), end=c(2014, 4)) 
   > m.sub
        Qtr1 Qtr2 Qtr3 Qtr4
   2012 1055 1281 1414 1313
   2013 1328 1559 1626 1458
   2014 1482 1830 2090 2225
   > plot(m.sub)
   

   Figure 6: A time series plot in a ...