# Bayesian Inference in the Presence of Intractable Normalizing Functions

@inproceedings{Park2017BayesianII, title={Bayesian Inference in the Presence of Intractable Normalizing Functions}, author={Jaewoo Park and Murali Haran}, year={2017} }

ABSTRACTModels with intractable normalizing functions arise frequently in statistics. Common examples of such models include exponential random graph models for social networks and Markov point processes for ecology and disease modeling. Inference for these models is complicated because the normalizing functions of their probability distributions include the parameters of interest. In Bayesian analysis, they result in so-called doubly intractable posterior distributions which pose significant… CONTINUE READING

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