Deterministic construction methods for uniform designs

Space-filling designs are useful for exploring the relationship between the response and factors, especially when the true model is unknown. The wrap-around L2-discrepancy is an important measure of the uniformity, and has often been used as a type of space-filling criterion. However, most obtained...

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Published inJournal of statistical planning and inference Vol. 226; pp. 30 - 38
Main Authors Qi, Liangwei, Liu, Ze, Zhou, Yongdao
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.09.2023
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ISSN0378-3758
1873-1171
DOI10.1016/j.jspi.2023.02.001

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Abstract Space-filling designs are useful for exploring the relationship between the response and factors, especially when the true model is unknown. The wrap-around L2-discrepancy is an important measure of the uniformity, and has often been used as a type of space-filling criterion. However, most obtained designs are generated through stochastic optimization algorithms, and cannot achieve the lower bound of the discrepancies and are only nearly uniform. Then deterministic construction methods for uniform designs are desired. This paper constructs uniform designs under the wrap-around L2-discrepancy by generator matrices of linear codes. Several requirements on the generator matrices, such as a necessary and sufficient condition for generating uniform designs, are derived. Based on these, two simple deterministic constructions for uniform designs are given. Some examples illustrate the effectiveness of them. Moreover, the resulting designs can be regarded as a generalization of good lattice point sets, and also enjoy good orthogonality. •The deterministic construction methods for uniform designs under the wrap-around L2-discrepancy are given.•A necessary and sufficient condition for generating uniform designs are derived.•The resulting designs can be regarded as a generalization of good lattice point sets, and also enjoy good orthogonality.
AbstractList Space-filling designs are useful for exploring the relationship between the response and factors, especially when the true model is unknown. The wrap-around L2-discrepancy is an important measure of the uniformity, and has often been used as a type of space-filling criterion. However, most obtained designs are generated through stochastic optimization algorithms, and cannot achieve the lower bound of the discrepancies and are only nearly uniform. Then deterministic construction methods for uniform designs are desired. This paper constructs uniform designs under the wrap-around L2-discrepancy by generator matrices of linear codes. Several requirements on the generator matrices, such as a necessary and sufficient condition for generating uniform designs, are derived. Based on these, two simple deterministic constructions for uniform designs are given. Some examples illustrate the effectiveness of them. Moreover, the resulting designs can be regarded as a generalization of good lattice point sets, and also enjoy good orthogonality. •The deterministic construction methods for uniform designs under the wrap-around L2-discrepancy are given.•A necessary and sufficient condition for generating uniform designs are derived.•The resulting designs can be regarded as a generalization of good lattice point sets, and also enjoy good orthogonality.
Author Liu, Ze
Qi, Liangwei
Zhou, Yongdao
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Keywords Good lattice point set
Regular design
Wrap-around L2-discrepancy
Language English
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Snippet Space-filling designs are useful for exploring the relationship between the response and factors, especially when the true model is unknown. The wrap-around...
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SubjectTerms Good lattice point set
Regular design
Wrap-around [formula omitted]-discrepancy
Title Deterministic construction methods for uniform designs
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