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Generalized good lattice point sets

Author

Listed:
  • Zong-Feng Qi

    (State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System)

  • Xue-Ru Zhang

    (Sichuan University)

  • Yong-Dao Zhou

    (Sichuan University)

Abstract

Good lattice point (GLP) sets are frequently used in quasi-Monte Carlo method and computer experiments. However, the space-filling property of GLP sets needs to be improved especially when the number of factors is large. This paper shows that the generalized GLP (GGLP) sets, constructed simply and fast by the linear level permutation of the GLP sets, have better space-filling property than the GLP sets and the orthogonal Latin hypercube designs (OLHD) in the sense of maximin distance criterion and uniformity criterion, especially for high dimensional cases. Unlike the OLHD, the number of runs of the GGLP sets can be chosen as any integer. It is also shown that the GLP sets are better than Latin hypercube designs as the starting design for linear and nonlinear level permutation. The GGLP sets are recommended for the designs with large number of factors and/or large number of runs.

Suggested Citation

  • Zong-Feng Qi & Xue-Ru Zhang & Yong-Dao Zhou, 2018. "Generalized good lattice point sets," Computational Statistics, Springer, vol. 33(2), pages 887-901, June.
    • Handle: RePEc:spr:compst:v:33:y:2018:i:2:d:10.1007_s00180-017-0737-z
    DOI: 10.1007/s00180-017-0737-z
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    References listed on IDEAS

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    6. Yong-Dao Zhou & Hongquan Xu, 2014. "Space-Filling Fractional Factorial Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1134-1144, September.
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