A new characterization of Elfving's method for high dimensional computation |
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Authors: | Jay Bartroff |
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Institution: | Department of Mathematics, University of Southern California, Los Angeles, California, USA |
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Abstract: | We give a new characterization of Elfving's (1952) method for computing c-optimal designs in k dimensions which gives explicit formulae for the k unknown optimal weights and k unknown signs in Elfving's characterization. This eliminates the need to search over these parameters to compute c-optimal designs, and thus reduces the computational burden from solving a family of optimization problems to solving a single optimization problem for the optimal finite support set. We give two illustrative examples: a high dimensional polynomial regression model and a logistic regression model, the latter showing that the method can be used for locally optimal designs in nonlinear models as well. |
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Keywords: | c-Optimal design Polynomial regression Logistic regression |
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