# Model Selection for Degree-corrected Block Models

@article{Yan2014ModelSF, title={Model Selection for Degree-corrected Block Models}, author={Xiaoran Yan and Jacob E. Jensen and F. Krzakala and C. Moore and C. Shalizi and L. Zdeborov{\'a} and P. Zhang and Yaojia Zhu}, journal={Journal of statistical mechanics}, year={2014}, volume={2014 5} }

The proliferation of models for networks raises challenging problems of model selection: the data are sparse and globally dependent, and models are typically high-dimensional and have large numbers of latent variables. Together, these issues mean that the usual model-selection criteria do not work properly for networks. We illustrate these challenges, and show one way to resolve them, by considering the key network-analysis problem of dividing a graph into communities or blocks of nodes with… CONTINUE READING

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