197 citations · 334 across the 7 of their papers we have counts for
6 papers · 1 filter
Latent Space Models for Dynamic Networks
Daniel K. Sewell, Yuguo Chen
Dynamic networks are used in a variety of fields to represent the structure and evolution of the relationships between entities. We present a model which embeds longitudinal networ…
Simultaneous and Temporal Autoregressive Network Models
Daniel K. Sewell
While logistic regression models are easily accessible to researchers, when applied to network data there are unrealistic assumptions made about the dependence structure of the dat…
Network Autocorrelation Models with Egocentric Data
Daniel K. Sewell
Network autocorrelation models have been widely used for decades to model the joint distribution of the attributes of a network's actors. This class of models can estimate both the…
Latent Space Approaches to Community Detection in Dynamic Networks
Daniel K. Sewell, Yuguo Chen
Embedding dyadic data into a latent space has long been a popular approach to modeling networks of all kinds. While clustering has been done using this approach for static networks…
Model-Based Longitudinal Clustering with Varying Cluster Assignments
Daniel K. Sewell, Yuguo Chen, William Bernhard +1
It is often of interest to perform clustering on longitudinal data, yet it is difficult to formulate an intuitive model for which estimation is computationally feasible. We propose…
Latent Space Models for Dynamic Networks with Weighted Edges
Daniel K. Sewell, Yuguo Chen
Longitudinal binary relational data can be better understood by implementing a latent space model for dynamic networks. This approach can be broadly extended to many types of weigh…