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A general construction for nested Latin hypercube designs

Author

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  • Xu, Jin
  • Duan, Xiaojun
  • Wang, Zhengming
  • Yan, Liang

Abstract

We propose a new construction for nested designs, called General Nested Latin Hypercube designs (GNLHs). Such designs contain nested Latin hypercube designs as special cases. Besides achieving maximum uniformity in one dimension, each layer of GNLHs is flexible in run sizes. Moreover, theoretical results and numerical simulations show that GNLHs perform well on the sampling variance.

Suggested Citation

  • Xu, Jin & Duan, Xiaojun & Wang, Zhengming & Yan, Liang, 2018. "A general construction for nested Latin hypercube designs," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 134-140.
    • Handle: RePEc:eee:stapro:v:134:y:2018:i:c:p:134-140
    DOI: 10.1016/j.spl.2017.10.022
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    References listed on IDEAS

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    1. Marc C. Kennedy & Anthony O'Hagan, 2001. "Bayesian calibration of computer models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(3), pages 425-464.
    2. Jin Xu & Jiajie Chen & Peter Z. G. Qian, 2015. "Sequentially Refined Latin Hypercube Designs: Reusing Every Point," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1696-1706, December.
    3. Xu He & Peter Z. G. Qian, 2011. "Nested orthogonal array-based Latin hypercube designs," Biometrika, Biometrika Trust, vol. 98(3), pages 721-731.
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    Cited by:

    1. Weiyan Mu & Chengxin Liu & Shifeng Xiong, 2023. "Nested Maximum Entropy Designs for Computer Experiments," Mathematics, MDPI, vol. 11(16), pages 1-12, August.
    2. Hao Chen & Yan Zhang & Xue Yang, 2021. "Uniform projection nested Latin hypercube designs," Statistical Papers, Springer, vol. 62(4), pages 2031-2045, August.

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