A perfect sampling method for exponential family random graph models |
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Authors: | Carter T Butts |
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Institution: | Departments of Sociology, Statistics, and EECS and Institute for Mathematical Behavioral Sciences, University of California, Irvine, CA, USA |
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Abstract: | Generation of deviates from random graph models with nontrivial edge dependence is an increasingly important problem. Here, we introduce a method which allows perfect sampling from random graph models in exponential family form (“exponential family random graph” models), using a variant of Coupling From The Past. We illustrate the use of the method via an application to the Markov graphs, a family that has been the subject of considerable research. We also show how the method can be applied to a variant of the biased net models, which are not exponentially parameterized. |
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Keywords: | Perfect sampling exponential random graphs discrete exponential families Markov chain Monte Carlo coupling from the past biased nets |
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