On the Uniqueness of Fréchet Means for Polytope Norms

Fuente: arXiv
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Autori principali: Talbut, Roan, McCormack, Andrew, Monod, Anthea
Natura: Preprint
Pubblicazione: 2026
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author Talbut, Roan
McCormack, Andrew
Monod, Anthea
author_facet Talbut, Roan
McCormack, Andrew
Monod, Anthea
contents Fréchet means are a popular type of average for non-Euclidean datasets, defined as those points which minimise the average squared distance to a set of data points. We consider the behaviour of sample Fréchet means on normed spaces whose unit ball is a polytope; this setting is rarely covered by existing literature on Fréchet means, which focuses on smooth spaces or spaces with bounded curvature. We study the geometry of the set of Fréchet means over polytope normed spaces, with a focus on dimension and probabilistic conditions for uniqueness. In particular, we provide a geometric characterisation of the threshold sample size at which Fréchet means have a positive probability of being unique, and we prove that this threshold is at most one more than the dimension of our space. We are able to use this geometric characterisation to compute the unique Fréchet mean sample threshold in the case of the $\ell_\infty$ and $\ell_1$ norms.
format Preprint
id arxiv_https___arxiv_org_abs_2603_15785
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle On the Uniqueness of Fréchet Means for Polytope Norms
Talbut, Roan
McCormack, Andrew
Monod, Anthea
Probability
Metric Geometry
Statistics Theory
Fréchet means are a popular type of average for non-Euclidean datasets, defined as those points which minimise the average squared distance to a set of data points. We consider the behaviour of sample Fréchet means on normed spaces whose unit ball is a polytope; this setting is rarely covered by existing literature on Fréchet means, which focuses on smooth spaces or spaces with bounded curvature. We study the geometry of the set of Fréchet means over polytope normed spaces, with a focus on dimension and probabilistic conditions for uniqueness. In particular, we provide a geometric characterisation of the threshold sample size at which Fréchet means have a positive probability of being unique, and we prove that this threshold is at most one more than the dimension of our space. We are able to use this geometric characterisation to compute the unique Fréchet mean sample threshold in the case of the $\ell_\infty$ and $\ell_1$ norms.
title On the Uniqueness of Fréchet Means for Polytope Norms
topic Probability
Metric Geometry
Statistics Theory
url https://arxiv.org/abs/2603.15785