The first category of models that we are going to use to try and forecast our time series are called auto-regressive (AR) models. As already mentioned, we try to model a data point in our time series based on one or more previous points in the series. We are, thus, modeling the time series using the time series itself. This use of the series itself is what distinguishes AR methods from the more general regression methods discussed in Chapter 4, Regression.
Auto-regressive models for forecasting
Auto-regressive model overview
You will often see AR models referred to as AR(1), AR(2), and so on. These numbers correspond to the order of the AR model or process you are using to model the time series, and it is this order that you...
