Minimum aberration majorization in non-isomorphic saturated designs

Kai Tai Fang*, Aijun Zhang

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

7 Citations (Scopus)

Abstract

In this paper we propose a new criterion, minimum aberration majorization, for comparing non-isomorphic saturated designs. This criterion is based on the generalized word-length pattern proposed by Ma and Fang (Metrika 53 (2001) 85) and Xu and Wu (Ann. Statist. 29 (2001) 1066) and majorization theory. The criterion has been successfully applied to check non-isomorphism and rank order saturated designs. Examples are given through five non-isomorphic L16(215) designs and two L27(313) designs.

Original languageEnglish
Pages (from-to)337-346
Number of pages10
JournalJournal of Statistical Planning and Inference
Volume126
Issue number1
DOIs
Publication statusPublished - 1 Nov 2004

Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

User-Defined Keywords

  • Aberration
  • Isomorphism
  • Majorization
  • Saturated design

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