Majorization framework for balanced lattice designs

Aijun Zhang*, Kai-Tai Fang, Runze Li, Agus Sudjianto

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

39 Citations (Scopus)


This paper aims to generalize and unify classical criteria for comparisons of balanced lattice designs, including fractional factorial designs, supersaturated designs and uniform designs. We present a general majorization framework for assessing designs, which includes a stringent criterion of majorization via pairwise coincidences and flexible surrogates via convex functions. Classical orthogonality, aberration and uniformity criteria are unified by choosing combinatorial and exponential kernels. A construction method is also sketched out.

Original languageEnglish
Pages (from-to)2837-2853
Number of pages17
JournalAnnals of Statistics
Issue number6
Publication statusPublished - Dec 2005

Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • Admissible
  • Discrepancy
  • Fractional factorial design
  • Majorization
  • Minimum aberration
  • Separable convex
  • Supersaturated design
  • Uniform design


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