The ARIMA Procedure
Functional Summary
The statements and options that control the ARIMA procedure are summarized in Table 7.3.
Table 7.3: 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 | |
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