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Limit Theorems for Fr\'echet Mean Sets

Probability 2025-07-03 v2 Statistics Theory Statistics Theory

Abstract

For 1p1\le p \le \infty, the Fr\'echet pp-mean of a probability measure on a metric space is an important notion of central tendency that generalizes the usual notions in the real line of mean (p=2p=2) and median (p=1p=1). In this work we prove a collection of limit theorems for Fr\'echet means and related objects, which, in general, constitute a sequence of random closed sets. On the one hand, we show that many limit theorems (a strong law of large numbers, an ergodic theorem, and a large deviations principle) can be simply descended from analogous theorems on the space of probability measures via purely topological considerations. On the other hand, we provide the first sufficient conditions for the strong law of large numbers to hold in a T2T_2 topology (in particular, the Fell topology), and we show that this condition is necessary in some special cases. We also discuss statistical and computational implications of the results herein.

Keywords

Cite

@article{arxiv.2012.12859,
  title  = {Limit Theorems for Fr\'echet Mean Sets},
  author = {Steven N. Evans and Adam Q. Jaffe},
  journal= {arXiv preprint arXiv:2012.12859},
  year   = {2025}
}

Comments

33 pages, 1 figure

R2 v1 2026-06-23T21:19:02.992Z