| The HPF Procedure |
| PROC HPF Statement |
The following options can be used in the PROC HPF statement.
specifies the number of observations before the end of the data where the multistep forecasts are to begin. The default is BACK=0.
names the SAS data set that contain the input data for the procedure to forecast. If the DATA= option is not specified, the most recently created SAS data set is used.
specifies the number of periods ahead to forecast (forecast lead or horizon). The default is LEAD=12.
The LEAD= value is relative to the last observation in the input data set and not to the last nonmissing observation of a particular series. Thus if a series has missing values at the end, the actual number of forecasts computed for that series will be greater than the LEAD= value.
limits the number of warning and error messages produced during the execution of the procedure to the specified value. The default is MAXERROR=50. This option is particularly useful in BY-group processing where it can be used to suppress the recurring messages.
specifies that only forecasts are written to the OUT= and OUTFOR= data sets. The NOOUTALL option includes only the final forecast observations in the output data sets, not the one-step forecasts for the data before the forecast period.
The OUT= and OUTFOR= data set will contain only the forecast results that start at the next period that follows the last observation and go to the forecast horizon specified by the LEAD= option.
names the output data set to contain the forecasts of the variables that are specified in the subsequent FORECAST statements. If an ID variable is specified, it will also be included in the OUT= data set. The values are accumulated based on the ACCUMULATE= option, and forecasts are appended to these values based on the FORECAST statement USE= option. The OUT= data set is particularly useful in extending the independent variables when forecasting dependent series associated with regression and autoregression models. If the OUT= option is not specified, a default output data set DATAn is created. If you do not want the OUT= data set created, then use OUT=_NULL_.
names the output data set to contain the model parameter estimates and the associated test statistics and probability values. The OUTEST= data set is particularly useful for evaluating the significance of the model parameters and understanding the model dynamics.
names the output data set to contain the forecast time series components (actual, predicted, lower confidence limit, upper confidence limit, prediction error, and prediction standard error). The OUTFOR= data set is particularly useful for displaying the forecasts in tabular or graphical form.
names the output data set to contain information in the SAS log, specifically the number of notes, errors, and warnings and the number of series processed, forecasts requested, and forecasts failed.
names the output data set to contain the seasonal statistics. The statistics are computed for each season as specified by the ID statement INTERVAL= option or the SEASONALITY= option. The OUTSEASON= data set is particularly useful when analyzing transactional data for seasonal variations.
names the output data set to contain the statistics of fit (or goodness-of-fit statistics). The OUTSTAT= data set is particularly useful for evaluating how well the model fits the series. The statistics of fit are based on the entire range of the time series regardless of whether the HOLDOUT= option is specified.
names the output data set to contain the summary statistics and the forecast summation. The summary statistics are based on the accumulated time series when the ACCUMULATE= or SETMISSING= options are specified. The forecast summations are based on the LEAD=, STARTSUM=, and USE= options. The OUTSUM= data set is particularly useful when forecasting large numbers of series and a summary of the results is needed.
names the output data set to contain the trend statistics. The statistics are computed for each time period as specified by the ID statement INTERVAL= option. The OUTTREND= data set is particularly useful when analyzing transactional data for trends.
specifies the graphical output desired. By default, the HPF procedure produces no graphical output. The following printing options are available:
plots prediction error time series graphics.
plots prediction error autocorrelation function graphics.
plots prediction error partial autocorrelation function graphics.
plots prediction error inverse autocorrelation function graphics.
plots white noise graphics.
plots model graphics.
plots forecast graphics.
plots forecast graphics with confidence limits in the data range.
plots the forecast in the forecast horzion only.
plots smoothed level component graphics.
plots smoothed seasonal component graphics.
plots smoothed trend (slope) component graphics.
is the same as specifying all of the preceding PLOT= options.
For example, PLOT=FORECASTS plots the forecasts for each series.
specifies the printed output desired. By default, the HPF procedure produces no printed output. The following printing options are available:
prints the results of parameter estimation (OUTEST= data set).
prints the forecasts (OUTFOR= data set).
prints the performance statistics for each forecast.
prints the performance summary for each BY group.
prints the performance summary for all of the BY groups.
prints the seasonal statistics (OUTSEASON= data set).
prints the statistics of fit (OUTSTAT= data set).
prints the backcast, initial, and final states.
prints the summary statistics for the accumulated time series (OUTSUM= data set).
prints the trend statistics (OUTTREND= data set).
is the same as PRINT=(ESTIMATES FORECASTS STATISTICS SUMMARY). PRINT=(ALL TRENDS SEASONS) prints all of the options in the preceding list.
For example, PRINT=FORECASTS prints the forecasts, PRINT=(ESTIMATES FORECASTS) prints the parameter estimates and the forecasts, and PRINT=ALL prints all of the preceding output.
The PRINT= option produces printed output for these results with the Output Delivery System (ODS). The PRINT= option produces results similar to the data sets listed in parenthesis for some of the options in the preceding list.
specifies that output requested with the PRINT= option be printed in greater detail.
specifies the length of the seasonal cycle. For example, SEASONALITY=3 means that every group of three observations forms a seasonal cycle. The SEASONALITY= option is applicable only for seasonal forecasting models. By default, the length of the seasonal cycle is one (no seasonality) or the length implied by the INTERVAL= option specified in the ID statement. For example, INTERVAL=MONTH implies that the length of the seasonal cycle is 12.
specifies that the variables specified in the FORECAST statements be processed in sorted order.
specifies the starting forecast lead (or horizon) for which to begin summation of the forecasts specified by the LEAD= option. The STARTSUM= value must be less than the LEAD= value. The default is STARTSUM=1—that is, the sum from the one-step-ahead forecast to the multistep forecast specified by the LEAD= option.
The prediction standard errors of the summation of forecasts take into account the correlation between the multistep forecasts. The section Details: HPF Procedure describes the STARTSUM= option in more detail.
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