Models for non-stationary time series
In the previous section, we discussed ARMA models for stationary time series data. In this section, we will look at non-stationary time series data and extend our model to work with non-stationary data. Let us start by taking a look at some sample data (shown in Figure 11.17). There are two series: US GDP (left) and airline passenger volume (right).
Figure 11.17 – US GDP (left) and airline passenger (right) time series
The US GDP series appears to exhibit an upward trend with some variations in the series. The airline passenger volume series also exhibits an upward trend, but there also appears to be a repeated pattern in the series. The repeated pattern in the airline series is called seasonality. Both series are non-stationary because of the apparent trend. Additionally, the airline passenger volume series appears to exhibit non-constant variance. We will model the GDP series with ARIMA, and we will model...
