2 papers
math.ST2025
Pseudo-likelihood-based -estimation of random graphs with dependent edges and parameter vectors of increasing dimension
Jonathan R. Stewart, Michael Schweinberger
An important question in statistical network analysis is how to estimate models of discrete and dependent network data with intractable likelihood functions, without sacrificing co…
math.ST2025
Learning cross-layer dependence structure in multilayer networks
Jiaheng Li, Jonathan R. Stewart
We propose a novel class of separable multilayer network models to capture cross-layer dependencies in multilayer networks, enabling the analysis of how interactions in one or more…