Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
131 tokens/sec
GPT-4o
10 tokens/sec
Gemini 2.5 Pro Pro
47 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Learning cross-layer dependence structure in multilayer networks (2307.14982v2)

Published 27 Jul 2023 in math.ST, stat.ME, and stat.TH

Abstract: 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 layers may influence interactions in other layers. Our approach separates the network formation process from the layer formation process, and is able to extend existing single-layer network models to multilayer network models that accommodate cross-layer dependence. We establish non-asymptotic and minimax-optimal error bounds for maximum likelihood estimators and demonstrate the convergence rate in scenarios of increasing parameter dimension. Additionally, we establish non-asymptotic error bounds for multivariate normal approximations and propose a model selection method that controls the false discovery rate. Simulation studies and an application to the Lazega lawyers network show that our framework and method perform well in realistic settings.

Summary

We haven't generated a summary for this paper yet.