Normal approximation for generalized U-statistics and weighted random graphs
Probability
2020-07-28 v1
Abstract
We derive normal approximation bounds in the Wasserstein distance for sums of weighted U-statistics, based on a general distance bound for functionals of independent random variables of arbitrary distributions. Those bounds are applied to normal approximation for the combined weights of subgraphs in the Erd\H{o}s-R\'enyi random graph, extending the graph counting results of [1] to the setting of graph weighting. Our approach relies on a general stochastic analytic framework for functionals of independent random sequences.
Cite
@article{arxiv.2007.12811,
title = {Normal approximation for generalized U-statistics and weighted random graphs},
author = {Nicolas Privault and Grzegorz Serafin},
journal= {arXiv preprint arXiv:2007.12811},
year = {2020}
}