1 Paper SAS1754-2015 Count Series Forecasting

Many organizations need to forecast large numbers of time series that are discretely valued. These series, called count series, fall approximately between continuously valued time series, for which there are many forecasting techniques (ARIMA, UCM, ESM, and others), and intermittent time series, for which there are few forecasting techniques (Croston’s method and others). This paper proposes a technique for large-scale automatic count series forecasting and uses SAS ® Forecast Server and SAS/ETS ® software to demonstrate this technique