On the construction of multi-level supersaturated designs

Kai Tai Fang, Dennis K.J. Lin, Chang Xing Ma

Research output: Contribution to journalArticlepeer-review

68 Scopus citations

Abstract

New criteria of comparing multi-level supersaturated designs are proposed and their properties are studied. A new class of multi-level supersaturated designs are obtained by collapsing a U-type uniform design to an orthogonal array. A global optimization algorithm, the threshold accepting algorithm, is then applied to search for the best supersaturated designs under any prespecified criterion. Examples show that these newly constructed supersaturated designs have good modeling properties.

Original languageEnglish (US)
Pages (from-to)239-252
Number of pages14
JournalJournal of Statistical Planning and Inference
Volume86
Issue number1
DOIs
StatePublished - Apr 15 2000

All Science Journal Classification (ASJC) codes

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

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