A state space model for exponential smoothing with group seasonality

 

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.

Cite

@techreport{GSI,
  author      = {Pim Ouwehand and Rob J Hyndman and Ton G {de Kok} and Karel H {van Donselaar}},
  institution = {Department of Econometrics \& Business Statistics, Monash University},
  number      = {07/07},
  title       = {A state space model for exponential smoothing with group seasonality},
  type        = {Working paper},
  year        = 2007
}