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