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The NLP Procedure 
This example shows how you can restart an optimization problem using the OUTEST=, INEST=, OUTMODEL=, and MODEL= options and how to save output into an OUT= data set. The leastsquares solution of the Rosenbrock function using the trustregion method is used.
The following code solves the problem and saves the model in the MODEL data set and the solution in the EST and in OUT1 data sets.
proc nlp tech=trureg outmodel=model outest=est out=out1; lsq y1 y2; parms x1 = 1.2 , x2 = 1.; y1 = 10. * (x2  x1 * x1); y2 = 1.  x1; proc print data=out1; run;
The final parameter estimates x^{*}=(1,1) and the values of the functions f_{1}=Y1 and f_{2}=Y2 are written into an OUT= data set. Since OUTDER=0 is the default, the OUT= data set does not contain the Jacobian matrix.
Output 5.4.1: Solution in an OUT= Data Set

proc nlp tech=none model=model inest=est out=out2 outder=1 pjac; lsq y1 y2; parms x1 x2; run; proc print data=out2; run;
Output 5.4.2 displays the Jacobian matrix,
Output 5.4.2: Jacobian Matrix Output


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