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Experimental Designs for Second Order Models

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 105)

Response Surface Methods suggest to estimate a second order polynomial when there is evidence that the response is curved in the current region of interest, or when lack of fit tests point to an inadequacy of the a first order model. The decision for when to change from using first order designs and models to second order designs and models is therefore based on the single degree of freedom test for curvature and the lack of fit (LOF) tests explained earlier. In this chapter we provide a description of designed experiments with which we can fit the second order model\(\hat y = \beta _0 + bx' + x'Bx\)

Keywords

Order Model Central Composite Design Orthogonal Design Prediction Variance Rotatable Central Composite Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

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