A compromise experimental design method for parametric polynomial response surface approximations

Pradeep George, Madara M. Ogot

Research output: Contribution to journalArticle


This study presents a compromise approach to augmentation of experimental designs, necessitated by the expense of performing each experiment (computational or physical), that yields higher quality parametric polynomial response surface approximations than traditional augmentation. Based on the D-optimality criterion as a measure of experimental design quality, the method simultaneously considers several polynomial models during the experimental design, resulting in good quality designs for all models under consideration, as opposed to good quality designs only for lower-order models, as in the case of traditional augmentation. Several numerical examples and an engineering example are presented to illustrate the efficacy of the approach.

Original languageEnglish (US)
Pages (from-to)1037-1050
Number of pages14
JournalJournal of Applied Statistics
Issue number10
StatePublished - Dec 1 2006



  • Response surface method
  • Surrogate models

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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