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

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  • Anqi Chen
  • Cheng-Yu Sun
  • Boxin Tang

Abstract

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.

Suggested Citation

  • Anqi Chen & Cheng-Yu Sun & Boxin Tang, 2021. "Selecting baseline designs using a minimum aberration criterion when some two-factor interactions are important," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 5(2), pages 95-101, April.
    • Handle: RePEc:taf:tstfxx:v:5:y:2021:i:2:p:95-101
    DOI: 10.1080/24754269.2020.1867795
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    Cited by:

    1. Yan, Zhaohui & Zhao, Shengli, 2023. "Optimal fractions of three-level factorials under a baseline parameterization," Statistics & Probability Letters, Elsevier, vol. 202(C).

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