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A model for optimizing experimental designs for estimating response surfaces

✍ Scribed by John Conlisk; Harold Watts

Publisher
Elsevier Science
Year
1979
Tongue
English
Weight
1022 KB
Volume
11
Category
Article
ISSN
0304-4076

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## Abstract Within the realm of average mean squared error (AMSE), generalized estimation (GE; Kupper and Meydrech 1,2) is an attractive alternative to estimate the response surface. GE is based on the criterion that minimizes the variance of the fitted response $(\hat Y({\bf x}))$ by weighting the