A state space model for exponential smoothing with group seasonality
Pim Ouwehand, Rob J. Hyndman, Ton G. de Kok and Karel H. van Donselaar
We present an approach to improve forecast accuracy by simultaneously forecasting a group of products that exhibit similar seasonal demand patterns. Better seasonality estimates can be made by using information on all products in a group, and using these improved estimates when forecasting at the individual product level. This approach is called the group seasonal indices (GSI) approach, and is a generalization of the classical Holt-Winters procedure. This article describes an underlying state space model for this method and presents simulation results that show when it yields more accurate forecasts than Holt-Winters.
Keywords: Common seasonality; demand forecasting; exponential smoothing; Holt-Winters; state space model.
