Preprint arXiv:2502.16314 [cs.IT]; last accessed April 18, 2025.
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: Benford's Law is an important instance of experimental mathematics that appears to constrain the information-theoretic behavior of numbers. Elias' encoding for integers is a remarkable approach to universality and optimality of codes. In the present analysis we seek to deduce a general law and its particular implications for these two cases from optimality and renormalization as applied to information-theoretical functionals. Both theoretical and experimental results corroborate our conclusions.
Bibtex:
@misc{,
title={Optimality and Renormalization imply Statistical Laws},
author={Alexander Kolpakov and Aidan Rocke},
year={2025},
eprint={2502.16314},
archivePrefix={arXiv},
primaryClass={cs.IT},
url={https://arxiv.org/abs/2502.16314},
}
Reference Type: Preprint
Subject Area(s): Computer Science, Number Theory, Statistics