Tag Archives: forecast combination

Guest post: On the robustness of bagging exponential smoothing

This is a guest blog entry by Fotios Petropoulos. A few months ago, Bergmeir, Hyndman and Benitez made available a very interesting working paper titled “Bagging exponential smoothing methods using STL decomposition and Box-Cox transformation”. In short, they successfully employed the bootstrap aggregation technique for improving the performance of exponential smoothing. The bootstrap technique is… Read More »

Ensemble size and combination operators

Combining forecasts has been shown in many cases to lead to improvements in forecasting performance, in terms of accuracy and bias. This is also common in forecasting with neural networks or other computationally intensive methods, where ensemble forecasts are considered more accurate than individual model forecasts. A useful feature of forecast combination is that it… Read More »