Holdout Forecasting

Holdout forecasting:

  1. Removes the last few data points of the historical data.

  2. Calculates the fit and forecast points using the remaining historical data.

  3. Compares the error between the forecasted points and their corresponding, excluded, historical data points.

  4. Changes the parameters to minimize the error between the forecasted points and the excluded points.

Predictor determines the optimal forecast parameters using only the non-holdout set of data.

Note that if you have a small amount of data and want to use seasonal forecasting methods, using the holdout technique might restrict you to non-seasonal methods.

For more information on the holdout technique and when to use it effectively, see the Makridakis, Wheelwright, and Hyndman reference in Bibliography.