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SAS Forecast Server Procedures: User's Guide
 

The HPF Procedure

Overview: HPF Procedure

The HPF procedure provides a quick and automatic way to generate forecasts for many time series or transactional data in one step. The procedure can forecast millions of series at a time, with the series organized into separate variables or across BY groups.

  • For typical time series, you can use the following smoothing models:

    • simple

    • double

    • linear

    • damped trend

    • seasonal (additive and multiplicative)

    • Winters method (additive and multiplicative)

  • Additionally, transformed versions of these models are provided:

    • log

    • square root

    • logistic

    • Box-Cox

  • For intermittent time series (series where a large number of values are zero-valued), you can use an intermittent demand model such as Croston’s method and the average demand model.

All parameters associated with the forecast model are optimized based on the data. Optionally, the HPF procedure can select the appropriate smoothing model for you by using holdout sample analysis based on one of several model selection criteria.

The HPF procedure writes the following information to output data sets:

  • time series extrapolated by the forecasts

  • series summary statistics

  • forecasts and confidence limits

  • parameter estimates

  • fit statistics

The HPF procedure optionally produces printed output for these results by using the Output Delivery System (ODS).

The HPF procedure can forecast time series data, whose observations are equally spaced by a specific time interval (for example, monthly, weekly), and also transactional data, whose observations are not spaced with respect to any particular time interval. Internet, inventory, sales, and similar data are typical examples of transactional data. For transactional data, the data are accumulated based on a specified time interval to form a time series. The HPF procedure can also perform trend and seasonal analysis on transactional data.

Also, the EXPAND procedure can be used for the frequency conversion and transformations of time series. For more information, see Chapter 15, EXPAND Procedure (SAS/ETS User's Guide).

Last updated: March 05, 2026