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 with values in a metric space is an element of the metric space that minimizes . 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 for , the minimizers of for integrals of non-decreasing functions, and the minimizers of for a quite unrestricted class of cost functions . 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}
}