Orthogonal-column Latin hypercube designs with small samples

Philip Prescott

Computational Statistics & Data Analysis, 2009, vol. 53, issue 4, 1191-1200

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.

Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00494-5
Full text for ScienceDirect subscribers only.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:53:y:2009:i:4:p:1191-1200

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().