D-optimal minimax fractional factorial designs

Dennis K.J. Lin, Julie Zhou

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

The D-optimal minimax criterion is proposed to construct fractional factorial designs. The resulting designs are very efficient, and robust against misspecification of the effects in the linear model. The criterion was first proposed by Wilmut & Zhou (2011); their work is limited to two-level factorial designs, however. In this paper we extend this criterion to designs with factors having any levels (including mixed levels) and explore several important properties of this criterion. Theoretical results are obtained for construction of fractional factorial designs in general. This minimax criterion is not only scale invariant, but also invariant under level permutations. Moreover, it can be applied to any run size. This is an advantage over some other existing criteria.

Original languageEnglish (US)
Pages (from-to)325-340
Number of pages16
JournalCanadian Journal of Statistics
Volume41
Issue number2
DOIs
StatePublished - Jun 1 2013

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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