Orthogonal column Latin hypercube designs with small samples
Orthogonal column Latin hypercube designs with small samples
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.
mean squared distance, orthogonal columns, space-filling designs, zero correlations
1191-1200
Prescott, Philip
cf0adfdd-989b-4f15-9e60-ef85eed817b2
15 February 2009
Prescott, Philip
cf0adfdd-989b-4f15-9e60-ef85eed817b2
Prescott, Philip
(2009)
Orthogonal column Latin hypercube designs with small samples.
Computational Statistics and Data Analysis, 53 (4), .
(doi:10.1016/j.csda.2008.10.026).
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.
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Submitted date: 20 May 2008
Published date: 15 February 2009
Keywords:
mean squared distance, orthogonal columns, space-filling designs, zero correlations
Organisations:
Statistics
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Local EPrints ID: 63595
URI: http://eprints.soton.ac.uk/id/eprint/63595
ISSN: 0167-9473
PURE UUID: 91fbf915-1363-4876-86aa-5d932aa08036
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Date deposited: 20 Oct 2008
Last modified: 15 Mar 2024 11:41
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