Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, Canada
Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, Canada
Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, Canada
boxint@sfu.ca
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.