English

Strong Laws of Large Numbers for Generalizations of Fr\'echet Mean Sets

Probability 2025-08-04 v3 Statistics Theory Statistics Theory

Abstract

A Fr\'echet mean of a random variable YY with values in a metric space (Q,d)(\mathcal Q, d) is an element of the metric space that minimizes qE[d(Y,q)2]q \mapsto \mathbb E[d(Y,q)^2]. This minimizer may be non-unique. We study strong laws of large numbers for sets of generalized Fr\'echet means. Following generalizations are considered: the minimizers of E[d(Y,q)α]\mathbb E[d(Y, q)^\alpha] for α>0\alpha > 0, the minimizers of E[H(d(Y,q))]\mathbb E[H(d(Y, q))] for integrals HH of non-decreasing functions, and the minimizers of E[c(Y,q)]\mathbb E[\mathfrak c(Y, q)] for a quite unrestricted class of cost functions c\mathfrak c. We show convergence of empirical versions of these sets in outer limit and in one-sided Hausdorff distance. The derived results require only minimal assumptions.

Keywords

Cite

@article{arxiv.2012.12762,
  title  = {Strong Laws of Large Numbers for Generalizations of Fr\'echet Mean Sets},
  author = {Christof Schötz},
  journal= {arXiv preprint arXiv:2012.12762},
  year   = {2025}
}