The ARIMA Procedure
Functional Summary
The statements and options that control the ARIMA procedure are summarized in Table 3.
Table 3: Functional Summary
| Description | Statement | Option |
|---|---|---|
| Data Set Options | ||
| Specify the input data set | PROC ARIMA | DATA= |
| IDENTIFY | DATA= | |
| Specify the output data set | PROC ARIMA | OUT= |
| FORECAST | OUT= | |
| Include only forecasts in the output data set | FORECAST | NOOUTALL |
| Write autocovariances to output data set | IDENTIFY | OUTCOV= |
| Write parameter estimates to an output data set | ESTIMATE | OUTEST= |
| Write correlation of parameter estimates | ESTIMATE | OUTCORR |
| Write covariance of parameter estimates | ESTIMATE | OUTCOV |
| Write estimated model to an output data set | ESTIMATE | OUTMODEL= |
| Write statistics of fit to an output data set | ESTIMATE | OUTSTAT= |
| Options for Identifying the Series | ||
| Difference time series and plot autocorrelations | IDENTIFY | |
| Specify response series and differencing | IDENTIFY | VAR= |
| Specify and cross-correlate input series | IDENTIFY | CROSSCORR= |
| Center data by subtracting the mean | IDENTIFY | CENTER |
| Exclude missing values | IDENTIFY | NOMISS |
| Delete previous models and start | IDENTIFY | CLEAR |
| Specify the significance level for tests | IDENTIFY | ALPHA= |
| Perform tentative ARMA order identification by using the ESACF method | IDENTIFY | ESACF |
| Perform tentative ARMA order identification by using the MINIC method | IDENTIFY | MINIC |
| Perform tentative ARMA order identification by using the SCAN method | IDENTIFY | SCAN |
| Specify the range of autoregressive model orders for estimating the error series for the MINIC method | IDENTIFY | PERROR= |
| Determine the AR dimension of the SCAN, ESACF, and MINIC tables | IDENTIFY | P= |
| Determine the MA dimension of the SCAN, ESACF, and MINIC tables | IDENTIFY | Q= |
| Perform stationarity tests | IDENTIFY | STATIONARITY= |
| Selection of white noise test statistic in the presence of missing values | IDENTIFY | WHITENOISE= |
| Options for Defining and Estimating the Model | ||
| Specify and estimate ARIMA models | ESTIMATE | |
| Specify autoregressive part of model | ESTIMATE | P= |
| Specify moving-average part of model | ESTIMATE | Q= |
| Specify input variables and transfer functions | ESTIMATE | INPUT= |
| Drop mean term from the model | ESTIMATE | NOINT |
| Specify the estimation method | ESTIMATE | METHOD= |
| Use alternative form for transfer functions | ESTIMATE | ALTPARM |
| Suppress degrees-of-freedom correction in variance estimates | ESTIMATE | NODF |
| Selection of white noise test statistic in the presence of missing values | ESTIMATE | WHITENOISE= |
| Options for Outlier Detection | ||
| Specify the significance level for tests | OUTLIER | ALPHA= |
| Identify detected outliers with variable | OUTLIER | ID= |
| Limit the number of outliers | OUTLIER | MAXNUM= |
| Limit the number of outliers to a percentage of the series | OUTLIER | MAXPCT= |
| Specify the variance estimator used for testing | OUTLIER | SIGMA= |
| Specify the type of level shifts | OUTLIER | TYPE= |
| Printing Control Options | ||
| Limit number of lags shown in correlation plots | IDENTIFY | NLAG= |
| Suppress printed output for identification | IDENTIFY | NOPRINT |
| Plot autocorrelation functions of the residuals | ESTIMATE | PLOT |
| Print log likelihood around the estimates | ESTIMATE | GRID |
| Control spacing for GRID option | ESTIMATE | GRIDVAL= |
| Print details of the iterative estimation process | ESTIMATE | PRINTALL |
| Suppress printed output for estimation | ESTIMATE | NOPRINT |
| Suppress printing of the forecast values | FORECAST | NOPRINT |
| Print the one-step forecasts and residuals | FORECAST | PRINTALL |
| Plotting Control Options | ||
| Request plots associated with model identification, residual analysis, and forecasting | PROC ARIMA | PLOTS= |
| Options to Specify Parameter Values | ||
| Specify autoregressive starting values | ESTIMATE | AR= |
| Specify moving-average starting values | ESTIMATE | MA= |
| Specify a starting value for the mean parameter | ESTIMATE | MU= |
| Specify starting values for transfer functions | ESTIMATE | INITVAL= |
| Options to Control the Iterative Estimation Process | ||
| Specify convergence criterion | ESTIMATE | CONVERGE= |
| Specify the maximum number of iterations | ESTIMATE | MAXITER= |
| Specify criterion for checking for singularity | ESTIMATE | SINGULAR= |
| Suppress the iterative estimation process | ESTIMATE | NOEST |
| Omit initial observations from objective | ESTIMATE | BACKLIM= |
| Specify perturbation for numerical derivatives | ESTIMATE | DELTA= |
| Omit stationarity and invertibility checks | ESTIMATE | NOSTABLE |
| Use preliminary estimates as starting values for ML and ULS | ESTIMATE | NOLS |
| Options for Forecasting | ||
| Forecast the response series | FORECAST | |
| Specify how many periods to forecast | FORECAST | LEAD= |
| Specify the ID variable | FORECAST | ID= |
| Specify the periodicity of the series | FORECAST | INTERVAL= |
| Specify size of forecast confidence limits | FORECAST | ALPHA= |
| Start forecasting before end of the input data | FORECAST | BACK= |
| Specify the variance term used to compute forecast standard errors and confidence limits | FORECAST | SIGSQ= |
| Control the alignment of SAS date values | FORECAST | ALIGN= |
| BY Groups | ||
| Specify BY-group processing | BY | |
Last updated: December 20, 2021