A general construction method for mixed-level supersaturated design

Shu Yamada, Michiyo Matsui, Tomomi Matsui, Dennis K.J. Lin, Takenori Takahashi

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

When the number of the experimental variables is large, the first and most critical step is to identify the (few) active factors among those (many) candidate factors. Supersaturated design is shown to be helpful for such a critical first step. A general construction method for mixed-level supersaturated design is proposed. The newly constructed design has several advantages, including the flexibility for the number of runs and the assurance of upper bound of the (pairwise) dependency among all design columns. Specific applications to the construction of two-level and three-level mixed-level designs are discussed in detail.

Original languageEnglish
Pages (from-to)254-265
Number of pages12
JournalComputational Statistics and Data Analysis
Volume50
Issue number1 SPEC. ISS.
DOIs
Publication statusPublished - 2006 Jan 10

Keywords

  • Algorithmic approach
  • Non-orthogonality
  • χ value

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

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