Near G-optimal Tchakaloff designs

Len Bos, Federico Piazzon and Marco Vianello ()
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Len Bos: University of Verona
Federico Piazzon: University of Padova
Marco Vianello: University of Padova

Computational Statistics, 2020, vol. 35, issue 2, No 17, 803-819

Abstract: Abstract We show that the notion of polynomial mesh (norming set), used to provide discretizations of a compact set nearly optimal for certain approximation theoretic purposes, can also be used to obtain finitely supported near G-optimal designs for polynomial regression. We approximate such designs by a standard multiplicative algorithm, followed by measure concentration via Caratheodory-Tchakaloff compression.

Keywords: Near G-optimal designs; Polynomial regression; Norming sets; Polynomial meshes; Dubiner distance; D-optimal designs; Multiplicative algorithms; Caratheodory-Tchakaloff measure compression (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s00180-019-00933-8

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