Preprint arXiv:2103.08705 [stat.ME]; last accessed March 29, 2021.
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: Thanks to the increasing availability in computing power, high-dimensional engineering problems seem to be at reach. But the curse of dimensionality will always prevent us to try out extensively all the hypotheses. There is a vast literature on efficient methods to construct a Design of Experiments (DoE) such as low discrepancy sequences and optimized designs. Classically, the performance of these methods is assessed using a discrepancy metric. Having a fast discrepancy measure is of prime importance if ones want to optimize a design. This work proposes a new methodology to assess the quality of a random sampling by using a flavor of Newcomb-Benford's law. The performance of the new metric is compared to classical discrepancy measures and showed to offer similar information at a fraction of the computational cost of traditional discrepancy measures.
Bibtex:
@misc{,
title={Newcomb-Benford's law as a fast ersatz of discrepancy measures},
author={Pamphile T. Roy},
year={2021},
eprint={2103.08705},
archivePrefix={arXiv},
primaryClass={stat.ME},
url = {https://arxiv.org/abs/2103.08705},
}
Reference Type: Preprint
Subject Area(s): Statistics