The RSREG procedure uses the method of least squares to fit quadratic response surface regression models. Response surface models are a kind of general linear model in which attention focuses on characteristics of the fit response function and in particular, where optimum estimated response values occur.
In addition to fitting a quadratic function, you can use the RSREG procedure to do the following:
test for lack of fit
test for the significance of individual factors
analyze the canonical structure of the estimated response surface
compute the ridge of optimum response
predict new values of the response
The RSREG procedure uses ODS Graphics to display the response surfaces, residuals, fit diagnostics, and ridges of optimum response. For general information about ODS Graphics, see ChapterĀ 21: Statistical Graphics Using ODS.