Bayesian Mixed-Membership Models of Complex and Evolving Networks

摘要

This thesis provides a methodological framework for the statistical analysis of complex graphs and dynamic networks. In it, I develop probabilistic algorithms that generate, evolve and integrate a heterogeneous collection of graphs, I study the statistical models these algorithms implicitly specify, and I develop strategies for estimating the set of quantities on which they depend in the context of applications to social and biological networks.