On Construction of Mappable Nearly Orthogonal Arrays with Column-Orthogonality

Haiyan Liu , Fasheng Sun , Dennis K. J. Lin , Min-Qian Liu

Communications in Mathematics and Statistics ›› 2023, Vol. 13 ›› Issue (2) : 455 -480.

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Communications in Mathematics and Statistics ›› 2023, Vol. 13 ›› Issue (2) : 455 -480. DOI: 10.1007/s40304-023-00333-x
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On Construction of Mappable Nearly Orthogonal Arrays with Column-Orthogonality

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Abstract

For designs of computer experiments, two important and desirable properties are projection uniformity and column-orthogonality. However, it is always a challenging task to construct designs with both properties. This paper constructs a series of designs which possess both (near) column-orthogonality and projection uniformity, called (nearly) column-orthogonal mappable nearly orthogonal arrays (MNOAs). Furthermore, we enhance the MNOAs’ projection uniformity on any one dimension by using the constructed (nearly) column-orthogonal MNOAs and rotation matrices. Compared with the existing results (such as Sun and Tang in J Am Stat Assoc 112:683–689, 2017), the newly constructed designs are able to accommodate more design columns and have a much better projection uniformity, for the same run sizes.

Keywords

Column-orthogonality / Combinatorial-orthogonality / Projection uniformity / Resolvable design / Space-filling design

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Haiyan Liu, Fasheng Sun, Dennis K. J. Lin, Min-Qian Liu. On Construction of Mappable Nearly Orthogonal Arrays with Column-Orthogonality. Communications in Mathematics and Statistics, 2023, 13(2): 455-480 DOI:10.1007/s40304-023-00333-x

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Funding

National Natural Science Foundation of China(12131001)

National Science Foundation(DMS-18102925)

National Key Research and Development Program of China(2020YFA0714102)

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School of Mathematical Sciences, University of Science and Technology of China and Springer-Verlag GmbH Germany, part of Springer Nature

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