Exponential random graph models (ERGMs) are one of the most popular statistical methods for analysing relational network structures. ERGMs represent generative statistical network processes that allow researchers to specify sufficient statistics in the form of counts of network configurations associated to potential dependencies between and across particular sets of nodes. In this paper, we review some of the most interesting recent advances for the ERGM framework.
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Caimo et al. (2022) studied this question.
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