A Stein goodness-of-test for exponential random graph models
We propose and analyse a novel nonparametric goodness-of-fit testing procedure for exchangeable exponential random graph model (ERGM) when a single network realisation is observed. The test determines how likely it is that the observation is generated from a target unnormalised ERGM density. Our tes...
| Main Authors: | , |
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| 格式: | Journal article |
| 语言: | English |
| 出版: |
Journal of Machine Learning Research
2021
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