A time-series is a sequence of data points ordered in time, often used in economics or, for example, in social sciences. The great advantage of collecting data over a long period of time compared to cross-sectional observations is that we can analyze the collected values of the exact same object over time instead of comparing different observations.
This special characteristic of the data requires new methods and data structures for time-series analysis. We will cover these in this chapter:
First, we learn how to load or transform observations into time-series objects
Then we visualize them and try to improve the plots by smoothing and filtering the observations
Besides seasonal decomposition, we introduce forecasting methods based on time-series models, and we also cover methods to identify outliers, extreme values, and anomalies in time-series