Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster Random Effects Models
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Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesian estimation method ... ...
