The decomposition of time series

Once the data has been cleaned and reformatted, one of the first steps of the analysis is to identify the structure of the series components. The decomposition of time series is a generic name for the process of separating a series into its components. This process provides insights into the structural patterns of the series. Typically, those insights utilize and identify the most appropriate approaches to handle the series, based on the aim of the analysis (for example, seasonality analysis, and forecasting). For example, if you identify in this process that the series has a strong seasonality pattern, you should select models that have the ability to handle this pattern. Although there are multiple decomposition methods, in this chapter, we will focus on the classical seasonal decomposition method, as most methods are based on a type of extension...