5.4 Measures of Forecast Accuracy We discuss several different forecasting models in this chapter. To see how well one model works, or to compare that model with other models, the forecast values are compared with the actual or observed values. The forecast error (or deviation) is defined as follows: Forecast error = Actual value − Forecast value Forecast error = Actual value − Forecast value One measure of accuracy is the mean absolute deviation (MAD). This is computed by taking the sum of the absolute values of the individual forecast errors and dividing by the numbers of errors (n):
MAD = Σ | forecast error |
n