5.2 Time-series models

  • A time-series is a sequence of evenly spaced events (numerical data observed at regular intervals of time)

  • Time-series forecasts predict the future based solely of the past values of the variable

  • Other variables are ignored

  • Common time-series models are:

  1. Moving averages
  2. Exponential smoothing
  3. Trend projections
  4. Decomposition

  • Regression models (simple and multiple) are used in trend projections and one type of decomposition model

  • Regular time-series are annually, quarterly, daily, hourly data, etc.

  • Time-series data are usually visualized using two-dimensional line plot

  • The vertical axis measures the variable of interest, while the horizontal axis corresponds to the time periods

Monthly, quarterly and annual time-series of retail trade (except of motor vehicles and motorcycles)

FIGURE 5.3: Monthly, quarterly and annual time-series of retail trade (except of motor vehicles and motorcycles)