Modeling and Change Detection for Count-Weighted Multilayer Networks
- May 2020
- Volume 62 Issue 2
- pp. 184-195
- Dong, Hang, Chen, Nan, Wang, Kaibo
The copyright of this article is not held by ASQ.
In a typical network with a set of individuals, it is common to have multiple types of interactions between two individuals. In practice, these interactions are usually sparse and correlated, which is not sufficiently accounted for in the literature. This article proposes a multilayer weighted stochastic block model (MZIP-SBM) based on a multivariate zero-inflated Poisson (MZIP) distribution to characterize the sparse and correlated multilayer interactions of individuals. A variational-EM algorithm is developed to estimate the parameters in this model. We further propose a monitoring statistic based on the score test of MZIP-SBM model parameters for change detection in multilayer networks. The proposed model and monitoring scheme are validated using extensive simulation studies and the case study from Enron E-mail network.*Supplemental material accessed online through Taylor & Francis.