Some of the terms that we used in this chapter are:
- ARIMA: The ARIMA model was analyzed by looking at various aspects of the model. We gained an understanding of the auto-regressive and moving average component of ARIMA. We also looked at the p, d, and q elements of the model. We developed an understanding of how the process helps to deal with autocorrelation, in comparison to regression. We forecasted values from the model using the historical data from the variable of interest only.
- Dependent: The variable that we are trying to forecast or gain a better understanding of is the dependent. We can use a series of independent variables to try and forecast a dependent variable.
- Differencing: This is the transformation of the data that we have used to derive a new variable, based on the change of the series from one data point to another.
- Independent: The variables...