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Main Authors: Cao, Fei, Gong, Xiaoqian
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2404.04499
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author Cao, Fei
Gong, Xiaoqian
author_facet Cao, Fei
Gong, Xiaoqian
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2404_04499
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On the equivalence between Fourier-based and Wasserstein distances for probability measures on $\mathbb N$
Cao, Fei
Gong, Xiaoqian
Probability
91B70, 91B80
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.
title On the equivalence between Fourier-based and Wasserstein distances for probability measures on $\mathbb N$
topic Probability
91B70, 91B80
url https://arxiv.org/abs/2404.04499