Abstract The Random Geometric Graph (RGG) is a random graph model for network data
with an underlying spatial representation. Geometry endows RGGs with a rich dependence …

We are interested in the problem of two-sample network hypothesis testing: given two
networks with the same set of nodes, we wish to test whether the underlying Bernoulli …

This paper provides a selective review of the statistical network analysis literature focused
on clustering and inference problems for stochastic blockmodels and their variants. We …

In this paper, we consider the problem of two-sample test of large networks with community
structures. A test statistic is proposed based on the maximum entry of the difference between …

We study the problem of estimating the left and right singular subspaces for a collection of
heterogeneous random graphs with a shared common structure. We analyze an algorithm …

Two-sample hypothesis testing for comparing two networks is an important yet difficult
problem. Major challenges include: potentially different sizes and sparsity levels; non …

It has become an increasingly common practice in modern science and engineering to
collect samples of multiple network data in which a network serves as a basic data object …

Hypothesis testing for equality of latent positions in random graphs Page 1 Bernoulli 29(4),
2023, 3221–3254 https://doi.org/10.3150/22-BEJ1581 Hypothesis testing for equality of latent …

We propose a nonparametric two-sample test statistic for low-rank, conditionally
independent edge random graphs whose edge probability matrices have negative …

How does neural connectivity in autistic children differ from neural connectivity in healthy
children or autistic youths? What patterns in global trade networks are shared across …