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Generalized foldover method for high-level designs

Author

Listed:
  • Zou, Na
  • Gou, Tingxun
  • Qin, Hong
  • Chatterjee, Kashinath

Abstract

Fractional factorial designs are popularly used in different fields of experimentations, which allow experimenters to study large number of potentially relevant factors with relatively small number of experimental units but suffer from the fact that some of the effects are aliased with some others. In order to overcome these drawbacks, the foldover technique is widely used to de-alias factor effects. This article aims at using the mirror image reflection to augment a given design, to improve its properties in terms of the uniformity criterion measured by Lee discrepancy.

Suggested Citation

  • Zou, Na & Gou, Tingxun & Qin, Hong & Chatterjee, Kashinath, 2020. "Generalized foldover method for high-level designs," Statistics & Probability Letters, Elsevier, vol. 164(C).
    • Handle: RePEc:eee:stapro:v:164:y:2020:i:c:s0167715220300985
    DOI: 10.1016/j.spl.2020.108795
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    References listed on IDEAS

    as
    1. Elsawah, A.M. & Qin, Hong, 2015. "Lee discrepancy on symmetric three-level combined designs," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 273-280.
    2. Zhou, Yong-Dao & Ning, Jian-Hui & Song, Xie-Bing, 2008. "Lee discrepancy and its applications in experimental designs," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1933-1942, September.
    3. Zujun Ou & Kashinath Chatterjee & Hong Qin, 2011. "Lower bounds of various discrepancies on combined designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 74(1), pages 109-119, July.
    Full references (including those not matched with items on IDEAS)

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