performs quadratic response surface regression
- RUN QUADREG( xopt, yopt, type, parms, x,
The inputs to the GPROBCNT subroutine are as follows:
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 saddlepoint) by computing
the eigenvalues of the estimated parameters.
- is a returned value containing
m ×1 critical factor values.
- is a returned value containing the critical response value.
- is a returned character string containing
the solution type (maximum or minimum).
- is a returned value containing the
parameter estimates for the quadratic model.
- is an n ×m factor matrix, where m is the number
of factor variables and n is the number of data points.
- is an n ×1 response vector.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.