Supplemental Material: CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent Estimation

The spectral clustering algorithm for directed networks that we consider in this paper is shown in Algorithm A.1. This algorithm is used for the community detection step in our proposed CHIP estimation procedure. For undirected networks, which we use for the theoretical analysis in Section 4, spectral clustering is performed by running k-means clustering on the rows of the eigenvector matrix of N or A, not the rows of the concatenated singular vector matrix. The three parameters µ, α, β can be estimated by maximizing (A.1) using standard numerical methods for non-linear optimization (Nocedal & Wright, 2006). In our CHIP model, we have separate (µ, α, β) parameters for each block pair (a, b).