Incremental Space-Filling Design Based on Coverings and Spacings: Improving Upon Low Discrepancy Sequences

Gomez A.N. Pronzato L. Rendas M.-J.
Journal of Statistical Theory and Practice
Doi 10.1007/s42519-021-00210-2
Volumen 15
2021-12-01
Citas: 4
Abstract
© 2021, Grace Scientific Publishing.The paper addresses the problem of defining families of ordered sequences {xi}i?N of elements of a compact subset X of Rd whose prefixes Xn={xi}i=1n, for all orders n, have good space-filling properties as measured by the dispersion (covering radius) criterion. Our ultimate aim is the definition of incremental algorithms that generate sequences Xn with small optimality gap, i.e., with a small increase in the maximum distance between points of X and the elements of Xn with respect to the optimal solution Xn?. The paper is a first step in this direction, presenting incremental design algorithms with proven optimality bound for one-parameter families of criteria based on coverings and spacings that both converge to dispersion for large values of their parameter. The examples presented show that the covering-based method outperforms state-of-the-art competitors, including coffee-house, suggesting that it inherits from its guaranteed 50% optimality gap.
Computer experiments, Covering, Greedy algorithm, Space-filling design, Spacing, Submodularity
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