Users of the legacy NLP procedure in SAS/OR include statisticians who use its nonlinear optimization capabilities to, for example, perform customized nonlinear regressions. In this context, PROC NLP’s output of a covariance matrix of the decision variables (or parameter estimates) is essential. Other PROC NLP users also rely on its covariance matrix output. In SAS/OR 13.2, the NLP solver, accessible from PROC OPTMODEL, adds covariance matrix output to better enable these statistical SAS/OR users to take advantage of its more modern nonlinear optimization methods.
The NLP solver provides all six types of central-difference approximations of the covariance matrix that are provided by PROC NLP, with the same calculation adjustments for problems that have minimization or least squares objective functions. The options that control the calculation of the covariance matrix correspond to the options in PROC NLP, and, for the NLP solver, they appear as suboptions in the COVEST= option in the SOLVE statement, which requests that the NLP solver produce a covariance matrix. The COVOUT= suboption enables you to specify a parameter in PROC OPTMODEL that contains the covariance matrix. You can use this parameter in a CREATE DATA statement in PROC OPTMODEL to output the covariance matrix to a SAS data set.