Abstract
This paper studies the optimal experimental design for the evaluation of an extremum point of a quadratic regression function of one or several variables. Experimental designs which are locally optimal for arbitrary dimension k among all approximate designs are constructed (although for k > 1 an explicit form proves to be available only under a restriction on the location of the extremum point). The result obtained can be considered as an improvement of the last step of the well-known Box-Wilson procedure
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© 2001 Springer Science+Business Media Dordrecht
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Cheng, R.C.H., Melas, V.B., Pepelyshev, A.N. (2001). Optimal Designs for the Evaluation of an Extremum Point. In: Atkinson, A., Bogacka, B., Zhigljavsky, A. (eds) Optimum Design 2000. Nonconvex Optimization and Its Applications, vol 51. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3419-5_2
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DOI: https://doi.org/10.1007/978-1-4757-3419-5_2
Publisher Name: Springer, Boston, MA
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Online ISBN: 978-1-4757-3419-5
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