Temporal Aggregation Model Settings

You can change the following settings in the Options pane of the pipeline. For more information, see Options Pane.

High Frequency Settings

Sensitivity level for intermittency test

Specify an integer greater than one. This setting is used to determine whether a time seriesan aggregation of transactional data into specified time intervals and sorted according to unique combinations of the default attributes (BY variables) is intermittent. If the demand interval is equal to or greater than this number, then the series is assumed to be intermittent.

IDM method

Select one of the following models:

  • Average : requests the extended sample autocorrelation function.
  • Best : uses the single smoothing model to fit the average demand component.
  • Croston : uses the two smoothing models to fit the demand interval component and the demand size component.

Low Frequency Settings

Model Generation

For best results, make sure at least two of these models are selected. If none of the models are selected, an ESM model (ESM BEST) is used for all time series.

Include ESM models

Turn this setting on to include an exponential smoothing model (ESM) for diagnosis.

Include ARIMAX models

Turn this setting on to include an ARIMAX model for diagnosis.

Include UCM models

Turn this setting on to include a UCM model for diagnosis.

Model Selection

Number of data points used in the holdout sample

Enter a positive integer to be used as the size of the holdout samplethe number of periods of the most recent data that should be excluded from the parameter estimation. The holdout sample can be used to evaluate the forecasting performance of a candidate model.. The actual holdout sample is the minimum between this value and the Percentage of data points used in the holdout sample . The default value is zero, which means no holdout sample is used.

Percentage of data points used in the holdout sample

Enter a value between 0 and 100 to specify the percentage of the sample that is used for the holdout sample. The actual holdout sample is the minimum between this value and the Number of data points used in the holdout sample . This option is displayed only if Number of data points used in the holdout sample is greater than zero.

Model selection criterion

Choose the statistics of fit to use for selecting the best model in this modeling node. For descriptions for each option, see Descriptions of Model Selection Criteria.

Output Tables

The following tables are automatically generated when running this modeling node. The tables can be saved to another caslib by using the Save Data Node.

You can select the following optional tables. Select any tables that you want generated when this node is run. After the node is run, you can use the Save Data Node if you need to save any of these tables.

Note: The low-frequency tables are not generated if the time interval for the project is not supported. For more information, see Temporal Aggregation Model.
Last updated: March 16, 2026