FORECAST variable-list / <options>;
The FORECAST statement lists the numeric variables in the DATA= data set whose accumulated values represent time series to be modeled and forecast. The options specify which forecast model is to be used.
A data set variable can be specified in only one FORECAST statement. Any number of FORECAST statements can be used. You can specify the following options:
specifies how the data set observations are accumulated within each time period for the variables listed in the FORECAST statement. If the ACCUMULATE= option is not specified in the FORECAST statement, accumulation is determined by the ACCUMULATE= option in the ID statement. Use the ACCUMULATE= option with multiple FORECAST statements when you want different accumulation specifications for different variables. For more information, see the ACCUMULATE= option in the ID statement.
specifies the significance level to use in computing the confidence limits of the forecast. The ALPHA= value must be between 0 and 1. By default, ALPHA=0.05, which produces 95% confidence intervals.
specifies that the median forecast values are to be estimated. Forecasts can be based on the mean or median. By default, the mean value is provided. If no transformation is applied to the time series by using the TRANSFORM= option, the mean and median forecast values are identical.
specifies the forecasting model to be used to forecast the time series. You can specify the following forecasting model-names:
produces no forecast, but the time series is appended with missing values in the OUT= data set. This option is useful when the results stored in the OUT= data set are used in a subsequent analysis where forecasts of the independent variables are needed to forecast the dependent variable.
performs simple (single) exponential smoothing.
performs double (Brown) exponential smoothing.
performs linear (Holt) exponential smoothing.
performs damped trend exponential smoothing.
performs additive seasonal exponential smoothing.
performs multiplicative seasonal exponential smoothing.
uses the Winters multiplicative method.
uses the Winters additive method.
By default, MODEL=SIMPLE.
specifies the number of observations used to initialize the backcast states. The default is the entire series.
replaces actual values that are excluded by the BACK= option with one-step-ahead forecasts in the OUT= data set.
replaces embedded missing values with one-step-ahead forecasts in the OUT= data set.
specifies how missing values (either input or accumulated) are assigned in the accumulated time series for variables listed in the FORECAST statement. If the SETMISSING= option is not specified in the FORECAST statement, missing values are set based on the SETMISSING= option of the ID statement. For more information, see the SETMISSING= option in the ID statement.
specifies the time series transformation to be applied to the input or accumulated time series. The following transformations are provided:
no transformation.
logarithmic transformation
square-root transformation
logistic transformation
Box-Cox transformation with parameter number where number is between –5 and 5
By default, TRANSFORM=NONE.
When the TRANSFORM= option is specified, the time series must be strictly positive. After the time series is transformed, the model parameters are estimated by using the transformed series. The forecasts of the transformed series are then computed, and finally the transformed series forecasts are inverse transformed. The inverse transform produces either mean or median forecasts depending on whether the MEDIAN option is specified. For more information, see the sections Transformations and Inverse Transformations.
specifies which forecast values are appended to the actual values in the OUT= and OUTSUM= data sets. You can specify the following options:
appends the predicted values to the actual values.
appends the lower confidence limit values to the actual values.
appends the upper confidence limit values to the actual values.
By default, USE=PREDICT.
Thus, the USE= option enables the OUT= and OUTSUM= data sets to be used for worst-case, best-case, average-case, and median-case decisions.
specifies how beginning or ending zero values (either input or accumulated) are interpreted in the accumulated time series for variables listed in the FORECAST statement. If the ZEROMISS= option is not specified in the FORECAST statement, beginning or ending zero values are set to missing values based on the ZEROMISS= option in the ID statement. For more information, see the ZEROMISS= option in the ID statement.