Statistical Theory and Related Fields (Apr 2021)

Selecting baseline designs using a minimum aberration criterion when some two-factor interactions are important

  • Anqi Chen,
  • Cheng-Yu Sun,
  • Boxin Tang

DOI
https://doi.org/10.1080/24754269.2020.1867795
Journal volume & issue
Vol. 5, no. 2
pp. 95 – 101

Abstract

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This article considers the problem of selecting two-level designs under the baseline parameterisation when some two-factor interactions are important. We propose a minimum aberration criterion, which minimises the bias caused by the non-negligible effects. Using this criterion, a class of optimal designs can be further distinguished from one another, and we present an algorithm to find the minimum aberration designs among the D-optimal designs. Sixteen-run and twenty-run designs are summarised for practical use.

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