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Orthogonal arrays robust to nonnegligible two-factor interactions

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  • Boxin Tang

Abstract

Regular fractional factorial designs with clear two-factor interactions provide a useful class of designs that are robust to nonnegligible two-factor interactions. In this paper, the concept of clear two-factor interactions is generalised to orthogonal arrays. The new concept leads to a much wider class of designs robust to nonnegligible two-factor interactions. We study the existence and construction of such designs. The designs we construct have a structure that render themselves particularly attractive in the robust parameter design setting. We also discuss an interesting connection between designs with clear two-factor interactions and mixed orthogonal arrays. Copyright 2006, Oxford University Press.

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  • Boxin Tang, 2006. "Orthogonal arrays robust to nonnegligible two-factor interactions," Biometrika, Biometrika Trust, vol. 93(1), pages 137-146, March.
    • Handle: RePEc:oup:biomet:v:93:y:2006:i:1:p:137-146
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    File URL: http://hdl.handle.net/10.1093/biomet/93.1.137
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    Cited by:

    1. Jin-Guan Lin & Xue-Ping Chen & Jian-Feng Yang & Xing-Fang Huang & Ying-Shan Zhang, 2015. "Generalized variable resolution designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(7), pages 873-884, October.
    2. Boxin Tang & Julie Zhou, 2013. "D-optimal two-level orthogonal arrays for estimating main effects and some specified two-factor interactions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(3), pages 325-337, April.
    3. Chen, Xue-Ping & Lin, Jin-Guan & Wang, Hong-Xia & Huang, Xing-Fang, 2017. "Designs containing partially clear main effects," Statistics & Probability Letters, Elsevier, vol. 121(C), pages 12-17.

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