performs quadratic response surface regression
- RUN QUADREG( xopt, yopt, type, parms, ,
The inputs to the GPROBCNT subroutine are as follows:
- is a returned value containing
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 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.
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