Near G-optimal Tchakaloff designs. (English) Zbl 1482.62004

Bos, Len; Piazzon, Federico; Vianello, Marco

Comput. Stat. 35, No. 2, 803-819 (2020).

Summary: 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.

MSC:

62-08	Computational methods for problems pertaining to statistics
62K05	Optimal statistical designs

Keywords:

near G-optimal designs; polynomial regression; norming sets; polynomial meshes; Dubiner distance; D-optimal designs; multiplicative algorithms; Caratheodory-Tchakaloff measure compression

Software:

dCATCH

References:

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