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\(\hat y = \beta _0 + bx' + x'Bx\)
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© 2007 Springer Science+Business Media, LLC
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(2007). Experimental Designs for Second Order Models. In: Process Optimization. International Series in Operations Research & Management Science, vol 105. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-71435-6_5
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DOI: https://doi.org/10.1007/978-0-387-71435-6_5
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-71434-9
Online ISBN: 978-0-387-71435-6
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