 Construction of space-filling orthogonal Latin hypercube designsHui Li, Liuqing Yang and Min-Qian Liu Statistics & Probability Letters, 2022, vol. 180, issue C Abstract: Latin hypercube designs (LHDs) play an important role in computer experiments, because they can achieve the maximum stratification when projected onto any one dimension. The orthogonal LHD (OLHD), as a special kind of LHDs, has been widely studied and used. OLHDs ensure that the estimates of main effects in linear models are uncorrelated. Also, it is crucial to use a design with good stratifications in order to explore the experimental region efficiently and build a high-quality metamodel. This paper first proposes a method to construct OLHDs with sd runs and d⌊(sd−1)/(d(s−1))⌋/2 factors, which achieve a stratification on an s2×s or s×s2 grid when projected onto any two dimensions. Moreover, most column pairs achieve stratifications on s2×s2 grids. Another method is further provided to construct OLHDs with more factors, which achieve the aforementioned stratifications in each sub-design. The resulting OLHDs are more space-filling than existing OLHDs. Keywords: Orthogonal array; Orthogonality; Rotation; Stratification (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:180:y:2022:i:c:s0167715221002078 Ordering information: This journal article can be ordered from DOI: 10.1016/j.spl.2021.109245 Access Statistics for this article Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul More articles in Statistics & Probability Letters from Elsevier |
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