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A note on the connection between uniformity and generalized minimum aberration

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  • Hong Qin
  • Mingyao Ai

Abstract

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Suggested Citation

  • Hong Qin & Mingyao Ai, 2007. "A note on the connection between uniformity and generalized minimum aberration," Statistical Papers, Springer, vol. 48(3), pages 491-502, September.
  • Handle: RePEc:spr:stpapr:v:48:y:2007:i:3:p:491-502
    DOI: 10.1007/s00362-006-0350-7
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    References listed on IDEAS

    as
    1. Ming-Yao Ai & Run-Chu Zhang, 2004. "Projection justification of generalized minimum aberration for asymmetrical fractional factorial designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 60(3), pages 279-285, November.
    2. Fred J. Hickernell, 2002. "Uniform designs limit aliasing," Biometrika, Biometrika Trust, vol. 89(4), pages 893-904, December.
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    Citations

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    Cited by:

    1. Chatterjee, Kashinath & Qin, Hong, 2008. "A new look at discrete discrepancy," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2988-2991, December.
    2. Hong Qin & Na Zou & Kashinath Chatterjee, 2009. "Connection between uniformity and minimum moment aberration," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 70(1), pages 79-88, June.
    3. A. M. Elsawah & Kai-Tai Fang, 2018. "New results on quaternary codes and their Gray map images for constructing uniform designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(3), pages 307-336, April.
    4. A. M. Elsawah & Hong Qin, 2017. "Optimum mechanism for breaking the confounding effects of mixed-level designs," Computational Statistics, Springer, vol. 32(2), pages 781-802, June.
    5. Yong-Dao Zhou & Kai-Tai Fang, 2013. "An efficient method for constructing uniform designs with large size," Computational Statistics, Springer, vol. 28(3), pages 1319-1331, June.
    6. Fasheng Sun & Jie Chen & Min-Qian Liu, 2011. "Connections between uniformity and aberration in general multi-level factorials," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(3), pages 305-315, May.

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