Orthogonal column Latin hypercube designs with small samples.
Computational Statistics & Data Analysis, 53, (4), . (doi:10.1016/j.csda.2008.10.026).
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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.
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