Module Library |
QUADREG Call |
performs quadratic response surface regression
The inputs to the GPROBCNT subroutine are as follows:
Is a returned value that contains critical factor values.
is a returned value that contains the critical response value.
is a returned character string that contains the solution type (maximum or minimum).
is a returned value that contains the parameter estimates for the quadratic model.
is an factor matrix, where is the number of factor variables and is the number of data points.
is an response vector.
The QUADREG module fits a regression model with a complete quadratic set of regressions across several factors. The estimated model parameters are divided into a vector of linear coefficients and a matrix of quadratic coefficients to obtain critical factor values that optimize the response. It further determines the type of the optima (maximum, minimum, or saddle point) by computing the eigenvalues of the estimated parameters.
Copyright © SAS Institute, Inc. All Rights Reserved.