Construction of Marginally Coupled Designs by Subspace Theory
| Autor: | Yuanzhen He, Fasheng Sun, C. Devon Lin |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Statistics and Probability
FOS: Computer and information sciences General method computer experiment Property (programming) lower-dimensional projection Computer experiment Methodology (stat.ME) orthogonal array Latin hypercube Latin hypercube sampling cascading Latin hypercube Hypercube Orthogonal array Algorithm Subspace topology Statistics - Methodology Mathematics |
| Zdroj: | Bernoulli 25, no. 3 (2019), 2163-2182 |
| DOI: | 10.48550/arxiv.2203.06340 |
| Popis: | Recent researches on designs for computer experiments with both qualitative and quantitative factors have advocated the use of marginally coupled designs. This paper proposes a general method of constructing such designs for which the designs for qualitative factors are multi-level orthogonal arrays and the designs for quantitative factors are Latin hypercubes with desirable space-filling properties. Two cases are introduced for which we can obtain the guaranteed low-dimensional space-filling property for quantitative factors. Theoretical results on the proposed constructions are derived. For practical use, some constructed designs for three-level qualitative factors are tabulated. |
| Databáze: | OpenAIRE |
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