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Estimates of the coverage of parameter space by Latin Hypercube and Orthogonal Array-based sampling

机译:拉丁超立方体和基于正交数组的采样对参数空间覆盖率的估计

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摘要

In this paper we use counting arguments to prove that the expected percentage coverage of addimensional parameter space of sizenwhen performingktrials with either Latin Hypercube sampling or Orthogonal Array-based Latin Hypercube sampling is the same. We then extend these results to an experimental design setting by projecting onto at < ddimensional subspace. These results are confirmed by simulations. The theory presented has both theoretical and practical significance in modelling and simulation science when sampling over high dimensional spaces.
机译:在本文中,我们使用计数参数来证明在使用拉丁超立方采样或基于正交数组的拉丁超立方采样执行ktrials时,尺寸n的维参数空间的预期百分比覆盖率是相同的。然后,我们通过投影到at 维子空间上,将这些结果扩展到实验设计环境。这些结果通过仿真得到证实。当在高维空间上采样时,提出的理论在建模和仿真科学中具有理论和实践意义。

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