The ARIMA Procedure
- Overview
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Getting Started
The Three Stages of ARIMA Modeling Identification Stage Estimation and Diagnostic Checking Stage Forecasting Stage Using ARIMA Procedure Statements General Notation for ARIMA Models Stationarity Differencing Subset, Seasonal, and Factored ARMA Models Input Variables and Regression with ARMA Errors Intervention Models and Interrupted Time Series Rational Transfer Functions and Distributed Lag Models Forecasting with Input Variables Data Requirements -
Syntax
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Details
The Inverse Autocorrelation Function The Partial Autocorrelation Function The Cross-Correlation Function The ESACF Method The MINIC Method The SCAN Method Stationarity Tests Prewhitening Identifying Transfer Function Models Missing Values and Autocorrelations Estimation Details Specifying Inputs and Transfer Functions Initial Values Stationarity and Invertibility Naming of Model Parameters Missing Values and Estimation and Forecasting Forecasting Details Forecasting Log Transformed Data Specifying Series Periodicity Detecting Outliers OUT= Data Set OUTCOV= Data Set OUTEST= Data Set OUTMODEL= SAS Data Set OUTSTAT= Data Set Printed Output ODS Table Names Statistical Graphics
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Examples
- References
| Functional Summary |
The statements and options that control the ARIMA procedure are summarized in Table 7.3.
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 |
|