Statistical Forecasting - Forecasting Accuracy

Forecasting Accuracy

The forecast error is the difference between the actual value and the forecast value for the corresponding period.

where E is the forecast error at period t, Y is the actual value at period t, and F is the forecast for period t.

Measures of aggregate error:

Mean absolute error (MAE)
Mean Absolute Percentage Error (MAPE)
Mean Absolute Deviation (MAD)
Percent Mean Absolute Deviation (PMAD)
Mean squared error (MSE) or Mean squared prediction error (MSPE)
Root Mean squared error (RMSE)
Forecast skill (SS)
Average of Errors (E)

Business forecasters and practitioners sometimes use different terminology in the industry. They refer to the PMAD as the MAPE, although they compute this as a volume weighted MAPE. For more information see Calculating demand forecast accuracy.

See also

  • Calculating demand forecast accuracy
  • Consensus forecasts
  • Forecast error
  • Predictability
  • Prediction intervals, similar to confidence intervals
  • Reference class forecasting

Read more about this topic:  Statistical Forecasting

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