Approximating Distributions on Vertex Degrees in Random Hypergraphs via Stein's Method
Xianghe Zhu, Wenkai Xu, Gesine Reinert
Abstract
Complex data are increasingly represented as hypergraphs. We establish bounds for approximating joint vertex-degree distributions by independent multivariate Poisson and correlated normal distributions in hypergraph models with independent hyperedges. We discuss the approximation of the distribution under different density regimes which are further supported by simulation studies.
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