Inference in curved exponential family models for networks

@inproceedings{Hunter2004InferenceIC,
  title={Inference in curved exponential family models for networks},
  author={D. R. Hunter},
  year={2004}
}
Network data arise in a wide variety of applications. Although descriptive statistics for networks abound in the literature, the science of fitting statistical models to complex network data is still in its infancy. The models considered in this article are based on exponential families; therefore, we refer to them as exponential random graph models (ERGMs). Although ERGMs are easy to postulate, maximum likelihood estimation of parameters in these models is very difficult. In this article, we… CONTINUE READING
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