Mixed-Effect Time-Varying Network Model and Application in Brain Connectivity Analysis
Methodology
2018-06-12 v1
Abstract
Time-varying networks are fast emerging in a wide range of scientific and business disciplines. Most existing dynamic network models are limited to a single-subject and discrete-time setting. In this article, we propose a mixed-effect multi-subject continuous-time stochastic blockmodel that characterizes the time-varying behavior of the network at the population level, meanwhile taking into account individual subject variability. We develop a multi-step optimization procedure for a constrained stochastic blockmodel estimation, and derive the asymptotic property of the estimator. We demonstrate the effectiveness of our method through both simulations and an application to a study of brain development in youth.
Cite
@article{arxiv.1806.03829,
title = {Mixed-Effect Time-Varying Network Model and Application in Brain Connectivity Analysis},
author = {Jingfei Zhang and Will Wei Sun and Lexin Li},
journal= {arXiv preprint arXiv:1806.03829},
year = {2018}
}