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A construction method for orthogonal Latin hypercube designs

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  • David M. Steinberg
  • Dennis K. J. Lin

Abstract

The Latin hypercube design is a popular choice of experimental design when computer simulation is used to study a physical process. These designs guarantee uniform samples for the marginal distribution of each single input. A number of methods have been proposed for extending the uniform sampling to higher dimensions.We show how to construct Latin hypercube designs in which all main effects are orthogonal. Our method can also be used to construct Latin hypercube designs with low correlation of first-order and second-order terms. Our method generates orthogonal Latin hypercube designs that can include many more factors than those proposed by Ye (1998). Copyright 2006, Oxford University Press.

Suggested Citation

  • David M. Steinberg & Dennis K. J. Lin, 2006. "A construction method for orthogonal Latin hypercube designs," Biometrika, Biometrika Trust, vol. 93(2), pages 279-288, June.
    • Handle: RePEc:oup:biomet:v:93:y:2006:i:2:p:279-288
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    File URL: http://hdl.handle.net/10.1093/biomet/93.2.279
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    Citations

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    Cited by:

    1. Song-Nan Liu & Min-Qian Liu & Jin-Yu Yang, 2023. "Construction of Column-Orthogonal Designs with Two-Dimensional Stratifications," Mathematics, MDPI, vol. 11(6), pages 1-27, March.
    2. Stelios Georgiou & Christos Koukouvinos & Min-Qian Liu, 2014. "U-type and column-orthogonal designs for computer experiments," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(8), pages 1057-1073, November.
    3. Philipp Bejol & Nicola Livingstone, 2018. "Revisiting currency swaps: hedging real estate investments in global city markets," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 36(2), pages 191-209, March.
    4. Mandal, B.N. & Dash, Sukanta & Parui, Shyamsundar & Parsad, Rajender, 2016. "Orthogonal Latin hypercube designs with special reference to four factors," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 181-185.
    5. Fasheng Sun & Boxin Tang, 2017. "A Method of Constructing Space-Filling Orthogonal Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 683-689, April.
    6. Wenlong Li & Min-Qian Liu & Jian-Feng Yang, 2022. "Construction of column-orthogonal strong orthogonal arrays," Statistical Papers, Springer, vol. 63(2), pages 515-530, April.
    7. Ru Yuan & Bing Guo & Min-Qian Liu, 2021. "Flexible sliced Latin hypercube designs with slices of different sizes," Statistical Papers, Springer, vol. 62(3), pages 1117-1134, June.
    8. Li Gu & Jian-Feng Yang, 2013. "Construction of nearly orthogonal Latin hypercube designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(6), pages 819-830, August.
    9. 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.
    10. Chen, Hao & Yang, Jinyu & Lin, Dennis K.J. & Liu, Min-Qian, 2019. "Sliced Latin hypercube designs with both branching and nested factors," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 124-131.
    11. Prescott, Philip, 2009. "Orthogonal-column Latin hypercube designs with small samples," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1191-1200, February.
    12. Ifigenia Efthimiou & Stelios Georgiou & Min-Qian Liu, 2015. "Construction of nearly orthogonal Latin hypercube designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(1), pages 45-57, January.
    13. Li, Hui & Yang, Liuqing & Liu, Min-Qian, 2022. "Construction of space-filling orthogonal Latin hypercube designs," Statistics & Probability Letters, Elsevier, vol. 180(C).

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