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Journal Articles Journal of Statistical Planning and Inference Year : 2021

Removing inessential points in c-and A-optimal design

Abstract

A design point is inessential when it does not contribute to an optimal design, and can therefore be safely discarded from the design space. We derive three inequalities for the detection of such inessential points in c-optimal design: the first two are direct consequences of the equivalence theorem for c-optimality; the third one is derived from a second-order cone programming formulation of c-optimal design. Elimination rules for A-optimal design are obtained as a byproduct. When implemented within an optimization algorithm, each inequality gives a screening test that may provide a substantial acceleration by reducing the size of the problem online. Several examples are presented with a multiplicative algorithm to illustrate the effectiveness of the approach.
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Dates and versions

hal-02868664 , version 1 (15-06-2020)

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Luc Pronzato, Guillaume Sagnol. Removing inessential points in c-and A-optimal design. Journal of Statistical Planning and Inference, 2021, 213, pp.233-252. ⟨10.1016/j.jspi.2020.11.011⟩. ⟨hal-02868664⟩
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