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Orthogonal-column Latin hypercube designs with small samples

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  • Prescott, Philip

Abstract

Latin hypercube designs with zero pair-wise column correlations are examined for their space-filling properties. Such designs, known as orthogonal-column Latin hypercube designs, are often used in computer experiments and in screening experiments, since all coefficients in a first-order model are estimated independently of each other. This makes interpretation of the factor effects particularly simple. Complete or partial enumeration searches are carried out to investigate the space-filling properties of all orthogonal-column Latin hypercube designs, with from 5 to 9 runs, and, from 2 to 5 factors. In cases where there are several designs with similar properties, the designs with minimum mean squared distance are determined. The maximum number of factors that can be accommodated in orthogonal-column Latin hypercube designs is determined for each design size, and designs found by various algorithmic methods proposed in the literature are identified.

Suggested Citation

  • Prescott, Philip, 2009. "Orthogonal-column Latin hypercube designs with small samples," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1191-1200, February.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:4:p:1191-1200
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    References listed on IDEAS

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    1. 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.
    2. van Beers, W.C.M., 2005. "Kriging metamodeling for simulation," Other publications TiSEM bba6cefc-7b24-4ec1-836d-5, Tilburg University, School of Economics and Management.
    3. Edwin R. van Dam & Bart Husslage & Dick den Hertog & Hans Melissen, 2007. "Maximin Latin Hypercube Designs in Two Dimensions," Operations Research, INFORMS, vol. 55(1), pages 158-169, February.
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