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Minimum Aberration Split-Plot Designs Focusing on the Whole Plot Factors

Author

Listed:
  • Minyang Hu

    (School of Statistics and Data Science, Qufu Normal University, Qufu 273165, China
    These authors contributed equally to this work.)

  • Shengli Zhao

    (School of Statistics and Data Science, Qufu Normal University, Qufu 273165, China
    These authors contributed equally to this work.)

Abstract

In some experiments, the levels of some factors are difficult to change; then fractional factorial split-plot (FFSP) designs are suitable for selection. In an FFSP design, the factors are divided into two classes—the whole plot (WP) and subplot (SP) factors. In some experiments, the selection of the levels of the WP factors can affect that of the SP factors, which attracts much attention to the WP factors. Paying more attention to the WP factors, a new optimality criterion for selecting such FFSP designs is proposed. The robustness of the proposed method is discussed. The construction method of the optimal designs under the new criterion is studied.

Suggested Citation

  • Minyang Hu & Shengli Zhao, 2022. "Minimum Aberration Split-Plot Designs Focusing on the Whole Plot Factors," Mathematics, MDPI, vol. 10(5), pages 1-12, February.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:5:p:700-:d:756713
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    References listed on IDEAS

    as
    1. C.‐S. Cheng & D. M. Steinberg & D. X. Sun, 1999. "Minimum aberration and model robustness for two‐level fractional factorial designs," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 85-93.
    2. D. R. Bingham & E. D. Schoen & R. R. Sitter, 2004. "Designing fractional factorial split‐plot experiments with few whole‐plot factors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(2), pages 325-339, April.
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