Abstract
This paper is devoted to studying optimal designs for estimating an extremal point of a multivariate quadratic regression model in the unit hyperball. The problem of estimating an extremal point is reduced to that of estimating certain parameters of a corresponding nonlinear (in parameters) regression model. For this reduced problem truncated locally D-optimal designs are found in an explicit form. The result is a generalization of the results of Fedorov and Müller (1997) for onedimensional quadratic regression function in the unit segment.
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Received February 2002
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Melas, V.B., Pepelyshev, A. & Cheng, R.C. Designs for estimating an extremal point of quadratic regression models in a hyperball. Metrika 58, 193–208 (2003). https://doi.org/10.1007/s001840200237
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DOI: https://doi.org/10.1007/s001840200237