Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality

Forecasting groups of time series is of increasing practical importance, e.g. forecasting the demand for multiple products offered by a retailer or server loads within a data center. The local approach to this problem considers each time series separately and fits a function or model to each series. The global approach fits a single function to all series. For groups of similar time series, global methods outperform the more established local methods.<img src=“http://feeds.feedburner.com/~r/ProfessorRobJHyndman/~4/rY19iBiI0wQ" height=“1” width=“1” …