Removal of the points that do not support an E-optimal experimental design

Radoslav Harman and Samuel Rosa

Statistics & Probability Letters, 2019, vol. 147, issue C, 83-89

Abstract: We propose a method for removing design points that cannot support any E-optimalexperimental design of a linear regression model with uncorrelated observations. The proposed method can be used to reduce the size of some large E-optimal design problems such that they can be efficiently solved by semidefinite programming. This paper complements the results of Pronzato [Pronzato, L., 2013. A delimitation of the support of optimal designs for Kiefer’s ϕp-class of criteria. Statistics & Probability Letters 83, 2721–2728], who studied the same problem for analytically simpler criteria of design optimality.

Keywords: Approximate design of experiment; E-optimal design; Support point; Design algorithm (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1016/j.spl.2018.12.005

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