Rotation designs: Orthogonal first-order designs with higher order projectivity

Dizza Bursztyn, David M. Steinberg*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In many factorial experiments, just a few of the experimental factors account for most of the variation in the response, a situation known as factor sparsity. Accurate modelling of the factor-response relationship may require use of higher-order terms in the active factors. In such settings, it may be desirable to use a design that is able, simultaneously, to screen out the important factors and to fit higher-order models in those factors. We derive a useful class of designs by rotating standard two-level fractional factorials. A special class of rotations is developed that has some appealing symmetry properties and can accommodate more factors than the rotation designs in Bursztyn and Steinberg (J. Stat. Plann. Inference 2001;97:399). A comparison of designs based on their projection and alias matrices shows that the new designs are better than many other alternatives.

Original languageAmerican English
Pages (from-to)197-206
Number of pages10
JournalApplied Stochastic Models in Business and Industry
Volume18
Issue number3
DOIs
StatePublished - Jul 2002
Externally publishedYes

Keywords

  • Computer experiments
  • Factor sparsity
  • Factorial designs
  • Response surface designs

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