A general construction method for mixed-level supersaturated design

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

doi:10.1016/j.csda.2004.07.018

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 journal › Article › peer-review

7 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 language	English
Pages (from-to)	254-265
Number of pages	12
Journal	Computational Statistics and Data Analysis
Volume	50
Issue number	1 SPEC. ISS.
DOIs	https://doi.org/10.1016/j.csda.2004.07.018
Publication status	Published - 2006 Jan 10
Externally published	Yes

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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10.1016/j.csda.2004.07.018

Cite this

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title = "A general construction method for mixed-level supersaturated design",

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.",

keywords = "Algorithmic approach, Non-orthogonality, χ value",

author = "Shu Yamada and Michiyo Matsui and Tomomi Matsui and Lin, {Dennis K.J.} and Takenori Takahashi",

note = "Funding Information: Dennis Lin's research was partially supported by National Security Agency, via Grant MDA904-02-1-0054 and by Smeal College of Business Administration, Penn State University. ",

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T1 - A general construction method for mixed-level supersaturated design

AU - Yamada, Shu

AU - Matsui, Michiyo

AU - Matsui, Tomomi

AU - Lin, Dennis K.J.

AU - Takahashi, Takenori

N1 - Funding Information: Dennis Lin's research was partially supported by National Security Agency, via Grant MDA904-02-1-0054 and by Smeal College of Business Administration, Penn State University.

PY - 2006/1/10

Y1 - 2006/1/10

N2 - 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.

AB - 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.

KW - Algorithmic approach

KW - Non-orthogonality

KW - χ value

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JO - Computational Statistics and Data Analysis

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A general construction method for mixed-level supersaturated design

Abstract

Keywords

ASJC Scopus subject areas

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