Recursive strategy
The recursive strategy is the oldest, most intuitive, and most popular technique to generate multi-step forecasts. To understand a strategy, there are two major regimes we have to understand:
- Training regime: How is the training of the models done?
- Forecasting regime: How are the trained models used to generate forecasts?
Let’s take the help of a diagram to understand the recursive strategy:
Figure 18.2: Recursive strategy for multi-step forecasting
Let’s discuss these regimes in detail.
Training regime
The recursive strategy involves training a single model to perform a one-step-ahead forecast. We can see in Figure 18.2 that we use the window function, W(Yt), to draw a window from Yt and train the model to predict Yt+1.
During training, a loss function (which measures the divergence between the output of the model, 
, and the actual value, Yt+1) is used to optimize the parameters of the model.
