Abstract
Space-filling designs are widely used in both computer and physical experiments. Column-orthogonality, maximin distance, and projection uniformity are three basic and popular space-filling criteria proposed from different perspectives, but their relationships have been rarely investigated. We show that the average squared correlation metric is a function of the pairwise L 2-distances between the rows only. We further explore the connection between uniform projection designs and maximin L 1-distance designs. Based on these connections, we develop new lower and upper bounds for column-orthogonality and projection uniformity from the perspective of distance between design points. These results not only provide new theoretical justifications for each criterion but also help in finding better space-filling designs under multiple criteria. Supplementary materials for this article are available online.
| Original language | English |
|---|---|
| Pages (from-to) | 375-385 |
| Number of pages | 11 |
| Journal | Journal of the American Statistical Association |
| Volume | 117 |
| Issue number | 537 |
| DOIs | |
| State | Published - 2022 |
Keywords
- Correlation
- L -distance
- Latin hypercube design
- Space-filling property
- Uniform projection designs