On the equivalence between Fourier-based and Wasserstein distances for probability measures on $\mathbb N$
Abstract
In this manuscript we investigate the equivalence of Fourier-based metrics on discrete state spaces with the well-known Wasserstein distances. While the use of Fourier-based metrics in continuous state spaces is ubiquitous since its introduction by Giuseppe Toscani and his colleagues [9, 14, 16] in the study of kinetic-type partial differential equations, the introduction of its discrete analog is recent [2] and seems to be far less studied. In this work, various relations between Fourier-based metrics and Wasserstein distances are shown to hold when the state space is the set of non-negative integers $\mathbb N$. Lastly, we also describe potential applications of such equivalence of metrics in models from econophysics which motivate the present work.
- Publication:
-
arXiv e-prints
- Pub Date:
- April 2024
- DOI:
- 10.48550/arXiv.2404.04499
- arXiv:
- arXiv:2404.04499
- Bibcode:
- 2024arXiv240404499C
- Keywords:
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- Mathematics - Probability;
- 91B70;
- 91B80
- E-Print:
- 14 pages, 0 figure