How to choose a multi-step forecasting strategy

Let’s summarize all the different strategies that we have learned in a table:

Figure 18.9: Multi-step forecasting strategies—a summary

Here, the following apply:

• S.O: Single output
• M.O: Multi-output
• T_SO and I_SO: Training and inferencing the time of a single-output model
• T_mO and I_mO: Training and inferencing the time of a multi-output model (practically, T_mO is larger than T_SO mostly because multi-output models are typically DL models, and their training time is higher than standard ML models)
• H: The horizon
• L = H/R, where R is the number of blocks in the IBD strategy
• is some positive real number

The table helps us understand and decide which strategy is better from multiple perspectives:

• Engineering complexity: Recursive, Joint, RecJoint << IBD << Direct, and DirRec << Rectify
• Training time: Recursive << Joint...