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 The STATESPACE Procedure

## OUTMODEL= Data Set

The OUTMODEL= data set contains the estimates of the F and G matrices and their standard errors, the names of the components of the state vector, and the estimates of the innovation covariance matrix. The variables contained in the OUTMODEL= data set are as follows:

• the BY variables
• STATEVEC, a character variable containing the name of the component of the state vector corresponding to the observation. The STATEVEC variable has the value STD for standard deviations observations, which contain the standard errors for the estimates given in the preceding observation.
• F_j, numeric variables containing the columns of the F matrix. The variable F_j contains the jth column of F. The number of F_j variables is equal to the value of the DIMMAX= option. If the model is of smaller dimension, the extraneous variables are set to missing.
• G_j, numeric variables containing the columns of the G matrix. The variable G_j contains the jth column of G. The number of G_j variables is equal to r, the dimension of xt given by the number of variables in the VAR statement.
• SIG_j, numeric variables containing the columns of the innovation covariance matrix. The variable SIG_j contains the jth column of .There are r variables SIG_j.

Table 18.2 shows an example of the OUTMODEL= data set, with xt = (xt,yt)', ,and DIMMAX=4. In Table 18.2, Fi,j and Gi,j are the i,jth elements of F and G respectively. Note that all elements for F_4 are missing because F is a 3 ×3 matrix.

Table 18.2: Value in the OUTMODEL= Data Set
 Obs STATEVEC F_1 F_2 F_3 F_4 G_1 G_2 SIG_1 SIG_2 1 X(T;T) 0 0 1 . 1 0 1,1 1,2 2 STD . . . . . . . . 3 Y(T;T) F2,1 F2,2 F2,3 . 0 1 2,1 2,2 4 STD std F2,1 std F2,2 std F2,3 . . . . . 5 X(T+1;T) F3,1 F3,2 F3,3 . G3,1 G3,2 . . 6 STD std F3,1 std F3,2 std F3,3 . std G3,1 std G3,2 . .

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