Review Articles

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

Anqi Chen ,

Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, Canada

Cheng-Yu Sun ,

Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, Canada

Boxin Tang

Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, Canada

boxint@sfu.ca

Pages 95-101 | Received 16 Jul. 2020, Accepted 19 Dec. 2020, Published online: 31 Jan. 2020,
  • Abstract
  • Full Article
  • References
  • Citations

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.

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