Power enhancement and phase transitions for global testing of the mixed membership stochastic block model

Author:

Cammarata Louis V.1,Ke Zheng Tracy1

Affiliation:

1. Statistics Department, Harvard University, Cambridge, MA 02138, USA

Publisher

Bernoulli Society for Mathematical Statistics and Probability

Subject

Statistics and Probability

Reference24 articles.

1. Arias-Castro, E. and Verzelen, N. (2014). Community detection in dense random networks. Ann. Statist. 42 940–969. 10.1214/14-AOS1208

2. Banerjee, D. (2018). Contiguity and non-reconstruction results for planted partition models: The dense case. Electron. J. Probab. 23 Paper No. 18. 10.1214/17-EJP128

3. Banerjee, D. and Ma, Z. (2017). Optimal hypothesis testing for stochastic block models with growing degrees. Available at arXiv:1705.05305.

4. Banerjee, D. and Ma, Z. (2022). Asymptotic normality and analysis of variance of log-likelihood ratios in spiked random matrix models. Ann. Statist. To appear.

5. Banks, J., Moore, C., Neeman, J. and Netrapalli, P. (2016). Information-theoretic thresholds for community detection in sparse networks. In Conference on Learning Theory 383–416. PMLR.

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