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Semiparametric Exact Optimal Run Orders

Summary: [This abstract is based on the authors' abstract.]

Observed responses during an experiment are often influenced by a temporal trend that is possibly due to factors like the aging of material, learning effects, equipment wear-out, and warm-up effects. The construction of run orders that are optimally balanced for time trend effects typically rely on the incorporation of a parametric representation of the time dependence. A parametric approach works well as long as the unknown time dependence is properly specified or overspecified. For complicated temporal trends of unknown periodicity, however, or when the design size is small compared to the complexity of the response model, a parametric approach may lead to underspecification of the true time trend. Contrary to a fully parametric approach with an underfitted time trend, modeling the time trend nonparametrically is an attractive option in terms of both bias and precision of the parameter estimators.

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  • Topics:
  • Keywords: Run order,Experiments,Optimal design,Bias,Algorithm,Parametric models
  • Author: Tack, Lieven; Vandebroek, Martina
  • Journal: Journal of Quality Technology