OUT= Data Set

The VARMAX Procedure

OUT= Data Set

The OUT= data set contains the forecast values produced by the OUTPUT statement. The following output variables can be created:

the BY variables
the ID variable
the MODEL statement endogenous (dependent) variables. These variables contain the actual values from the input data set.
FORi, numeric variables containing the forecasts. The FORi variables contain the forecasts for the ith endogenous variable in the MODEL statement list. Forecasts are 1-step-ahead predictions until the end of the data or until the observation specified by the BACK= option.
RESi, numeric variables containing the residual for the forecast of the ith endogenous variable in the MODEL statement list. For forecast observations, the actual values are missing and the RESi variables contain missing values.
STDi, numeric variables containing the standard deviation for the forecast of the ith endogenous variable in the MODEL statement list. The values of the STDi variables can be used to construct univariate confidence limits for the corresponding forecasts.
LCIi, numeric variables containing the lower confidence limits for the corresponding forecasts of the ith endogenous variable in the MODEL statement list.
UCIi, numeric variables containing the upper confidence limits for the corresponding forecasts of the ith endogenous variable in the MODEL statement list.

Table 4.2: OUT= Data Set

Obs ID variable y1 FOR1 RES1 STD1 LCI1 UCI1

1 date y₁₁ f₁₁ r₁₁ $\sigma_{11}$ l₁₁ u₁₁

2 date y₁₂ f₁₂ r₁₂ $\sigma_{11}$ l₁₂ u₁₂

Obs y2 FOR2 RES2 STD2 LCI2 UCI2

1 y₂₁ f₂₁ r₂₁ $\sigma_{22}$ l₂₁ u₂₁

2 y₂₂ f₂₂ r₂₂ $\sigma_{22}$ l₂₂ u₂₂

The OUT= data set contains the values shown in Table 4.2 for a bivariate case.

Consider the following example:

   proc varmax data=simul1 noprint;
      id date interval=year;
      model y1 y2 / p=1 noint;
      output out=out lead=5;
   run;
   proc print data=out(firstobs=98);
   run;

Obs	date	y1	FOR1	RES1	STD1	LCI1	UCI1	y2	FOR2	RES2	STD2	LCI2	UCI2
98	1997	-0.58433	-0.13500	-0.44934	1.13523	-2.36001	2.09002	0.64397	-0.34932	0.99329	1.19096	-2.68357	1.98492
99	1998	-2.07170	-1.00649	-1.06522	1.13523	-3.23150	1.21853	0.35925	-0.07132	0.43057	1.19096	-2.40557	2.26292
100	1999	-3.38342	-2.58612	-0.79730	1.13523	-4.81113	-0.36111	-0.64999	-0.99354	0.34355	1.19096	-3.32779	1.34070
101	2000	.	-3.59212	.	1.13523	-5.81713	-1.36711	.	-2.09873	.	1.19096	-4.43298	0.23551
102	2001	.	-3.09448	.	1.70915	-6.44435	0.25539	.	-2.77050	.	1.47666	-5.66469	0.12369
103	2002	.	-2.17433	.	2.14472	-6.37792	2.02925	.	-2.75724	.	1.74212	-6.17173	0.65725
104	2003	.	-1.11395	.	2.43166	-5.87992	3.65203	.	-2.24943	.	2.01925	-6.20709	1.70823
105	2004	.	-0.14342	.	2.58740	-5.21463	4.92779	.	-1.47460	.	2.25169	-5.88782	2.93863

Figure 4.47: OUT= Data Set

The output in Figure 4.39 shows part of the results of the OUT= data set.

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Obs	ID variable	y1	FOR1	RES1	STD1	LCI1	UCI1
1	date	y₁₁	f₁₁	r₁₁	$\sigma_{11}$	l₁₁	u₁₁
2	date	y₁₂	f₁₂	r₁₂	$\sigma_{11}$	l₁₂	u₁₂