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Uniform design with prior information of factors under weighted wrap-around $$L_2$$ L 2 -discrepancy

Author

Listed:
  • Biao Luo

    (Jishou University)

  • Hongyi Li

    (Jishou University)

  • Yingying Wei

    (Jishou University)

  • Zujun Ou

    (Jishou University)

Abstract

Uniform design is one of the most frequently used designs of experiment, and all factors are usually regarded as equally important in the existing literature of uniform design. If some prior information of certain factors is known, the potential importance of factors should be distinguished. In this paper, by assigning different weights to factors with different importance, the weighted wrap-around $$L_2$$ L 2 -discrepancy is proposed to measure the uniformity of design when some prior information of certain factors are known. The properties of weighted wrap-around $$L_2$$ L 2 -discrepancy are explored. Accordingly, the weighted generalized wordlength pattern is proposed to describe the aberration of these kinds of designs. The relationship between the weighted wrap-around $$L_2$$ L 2 -discrepancy and weighted generalized wordlength pattern is built, and a lower bound of weighted wrap-around $$L_2$$ L 2 -discrepancy is obtained. Numerical results show that both weighted wrap-around $$L_2$$ L 2 -discrepancy and weighted generalized wordlength pattern are precisely to capture the difference of importance among the columns of design.

Suggested Citation

  • Biao Luo & Hongyi Li & Yingying Wei & Zujun Ou, 2022. "Uniform design with prior information of factors under weighted wrap-around $$L_2$$ L 2 -discrepancy," Computational Statistics, Springer, vol. 37(5), pages 2717-2739, November.
    • Handle: RePEc:spr:compst:v:37:y:2022:i:5:d:10.1007_s00180-022-01193-9
    DOI: 10.1007/s00180-022-01193-9
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    References listed on IDEAS

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    1. Liuping Hu & Kashinath Chatterjee & Jiaqi Liu & Zujun Ou, 2020. "New lower bound for Lee discrepancy of asymmetrical factorials," Statistical Papers, Springer, vol. 61(4), pages 1763-1772, August.
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    3. 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.
    4. Hong Qin & Kai-Tai Fang, 2004. "Discrete discrepancy in factorial designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 60(1), pages 59-72, July.
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