STLGMLDec 20, 2021

Quasi-uniform designs with optimal and near-optimal uniformity constant

arXiv:2112.10401v115 citations
Originality Incremental advance
AI Analysis

This work addresses a theoretical problem in design of experiments, likely incremental as it builds on existing greedy methods.

The paper tackles the problem of constructing nested designs with optimal uniformity constant by deriving a lower bound and showing that a simple greedy construction achieves it, then extends the scheme for more flexibility.

A design is a collection of distinct points in a given set $X$, which is assumed to be a compact subset of $R^d$, and the mesh-ratio of a design is the ratio of its fill distance to its separation radius. The uniformity constant of a sequence of nested designs is the smallest upper bound for the mesh-ratios of the designs. We derive a lower bound on this uniformity constant and show that a simple greedy construction achieves this lower bound. We then extend this scheme to allow more flexibility in the design construction.

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