The ARIMA Procedure 
Statistical Graphics 
This section provides information about the basic ODS statistical graphics produced by the ARIMA procedure. To request graphics with PROC ARIMA, you must first enable ODS Graphics by specifying the ODS GRAPHICS ON; statement. See Chapter 21, Statistical Graphics Using ODS (SAS/STAT 9.22 User's Guide), for more information. The main types of plots available are as follows:
plots useful in the trend and correlation analysis of the dependent and input series
plots useful for the residual analysis of an estimated model
forecast plots
You can obtain most plots relevant to the specified model by default if ODS Graphics is enabled. For finer control of the graphics, you can use the PLOTS= option in the PROC ARIMA statement. The following example is a simple illustration of how to use the PLOTS= option.
The series in this example, the monthly airline passenger series, is also discussed later, in Example 7.2.
The following statements specify an ARIMA(0,1,1)(0,1,1) model without a mean term to the logarithms of the airline passengers series, xlog. Notice the use of the global plot option ONLY in the PLOTS= option of the PROC ARIMA statement. It suppresses the production of default graphics and produces only the plots specified by the subsequent RESIDUAL and FORECAST plot options. The RESIDUAL(SMOOTH) plot specification produces a time series plot of residuals that has an overlaid loess fit; see Figure 7.21. The FORECAST(FORECAST) option produces a plot that shows the onestepahead forecasts, as well as the multistepahead forecasts; see Figure 7.22.
ods graphics on; proc arima data=seriesg plots(only)=(residual(smooth) forecast(forecasts)); identify var=xlog(1,12); estimate q=(1)(12) noint method=ml; forecast id=date interval=month; run;
PROC ARIMA assigns a name to each graph it creates by using ODS. You can use these names to reference the graphs when you use ODS. The names are listed in Table 7.13.
ODS Graph Name 
Plot Description 
Option 

SeriesPlot 
Time series plot of the dependent series 

SeriesACFPlot 
Autocorrelation plot of the dependent series 

SeriesPACFPlot 
Partialautocorrelation plot of the dependent series 

SeriesIACFPlot 
Inverseautocorrelation plot of the dependent series 

SeriesCorrPanel 
Series trend and correlation analysis panel 
Default 
CrossCorrPanel 
Crosscorrelation plots, either individual or paneled. They are numbered 1, 2, and so on as needed. 
Default 
ResidualACFPlot 
Residualautocorrelation plot 

ResidualPACFPlot 
Residualpartialautocorrelation plot 

ResidualIACFPlot 
Residualinverseautocorrelation plot 

ResidualWNPlot 
Residualwhitenoiseprobability plot 

ResidualHistogram 
Residual histogram 

ResidualQQPlot 
Residual normal QQ Plot 

ResidualPlot 
Time series plot of residuals with a superimposed smoother 
PLOTS=RESIDUAL(SMOOTH) 
ForecastsOnlyPlot 
Time series plot of multistep forecasts 
Default 
ForecastsPlot 
Time series plot of onestepahead as well as multistep forecasts 
PLOTS=FORECAST(FORCAST) 
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