specifies the name of the SAS catalog entry in which forecasting models and other results are stored and from which previously stored results are loaded into the forecasting system.

specifies the name of the SAS data set containing the input data.

specifies the series variable name. It must be a numeric variable contained in the data set.

specifies the time ID variable name for the data set. If the ID= option is not specified, the system attempts to locate the variables named DATE, DATETIME, and TIME in the data set specified by the DATA= option. However, it is recommended that you specify the time ID variable whenever you are using the ENTRY= argument.

specifies the time ID interval between observations in the data set. Commonly used intervals are year, semiyear, qtr, month, semimonth, week, weekday, day, hour, minute, and second. See Chapter 4, Date Intervals, Formats, and Functions, for information about more complex interval specifications. If the INTERVAL= option is not specified, the system attempts to determine the interval based on the time ID variable. However, it is recommended that you specify the interval whenever you are using the ENTRY= argument.

specifies the name of the goodness-of-fit statistic to be used as the model selection criterion. The default is RMSE. Valid names are

sse

sum of square error

mse

mean square error

rmse

root mean square error

mae

mean absolute error

mape

mean absolute percent error

aic

Akaike information criterion

sbc

Schwarz Bayesian information criterion

rsquare

R-square

adjrsq

adjusted R-square

rwrsq

random walk R-square

arsq

Amemiya’s adjusted R-square

apc

Amemiya’s prediction criterion

specifies the level of the confidence limits to be computed for the forecast. This integer represents a percentage; for example, 925 indicates 92.5% confidence limits. The default is 95—that is, 95% confidence limits.

specifies the number of periods into the future for which forecasts are computed. The default is 12 periods. The maximum is 9999.

The name of an entry point into the system. Valid names are

main

starts the system at the Time Series Forecasting window (default).

devmod

starts the system at the Develop Models window.

viewmod

starts the system at the Model Viewer window. Specify a project that contains a forecasting model by using the PROJECT= option. If a project containing a model is not specified, the message "No forecasting model to view" appears.

viewser

starts the system at the Time Series Viewer window.

autofit

runs the system in unattended mode, fitting a forecasting model automatically and saving it in a project. If PROJECT= is not specified, the default project name SASUSER.FMSPROJ.PROJ is used.

forecast

runs the system in unattended mode to generate a forecast data set. The name of this data set is specified by the OUT= parameter. If OUT= is not specified, a window appears to prompt for the name and label of the output data set. If PROJECT= is not specified, the default project name SASUSER.FMSPROJ.PROJ is used. If the project does not exist or does not contain a forecasting model for the specified series, automatic model fitting is performed and the forecast is computed by using the automatically selected model. If the project exists and contains a forecasting model for the specified series, the forecast is computed by using this model. If the series covers a different time range than it did when the project was created, use the REFIT or REEVAL keyword to reset the time ranges.

specifies one or two-level name of a SAS data set in which forecasts are saved. Use in conjunction with ENTRY=FORECAST. If omitted, the system prompts for the name of the forecast data set.

specifies the number of models to keep in the project when automatic model fitting is performed. This corresponds to Models to Keep in the Automatic Model Selection Options window. A value greater than 9 indicates that all models are kept. The default is 1.

specifies which models to search with regard to series diagnostics. DIAG= YES causes the automatic model selection process to search only over those models that are consistent with the series diagnostics. DIAG= NO causes the automatic model selection process to search over all models in the selection list, without regard for the series diagnostics. This corresponds to Models to Fit in the Automatic Model Selection Options window. The default is YES.

(for macro usage) refits a previously saved forecasting model by using the current fit range; that is, it reestimates the model parameters. Refitting also causes the model to be reevaluated (statistics of fit recomputed), and it causes the time ranges to be reset if the data range has changed (for example, if new observations have been added to the series). This keyword has no effect if you do not use the PROJECT= argument to reference an existing project containing a forecasting model. Use the REFIT keyword if you have added new data to the input series and you want to refit the forecasting model and update the forecast by using the new time ranges. Be sure to use the same project, data set, and series names that you used previously.

(for macro usage) reevaluates a previously saved forecasting model by using the current evaluation range; that is, it recomputes the statistics of fit. Reevaluating also causes the time ranges to be reset if the data range has changed (for example, if new observations have been added to the series). It does not refit the model parameters. This keyword has no effect if you also specify REFIT, or if you do not use the PROJECT= argument to reference an existing project containing a forecasting model. Use the REEVAL keyword if you have added new data to the input series and want to update your forecast by using a previously fit forecasting model and the same project, data set, and series names that you used previously.