August 2024 Signal detection in degree corrected ERGMs
Yuanzhe Xu, Sumit Mukherjee
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Bernoulli 30(3): 1746-1773 (August 2024). DOI: 10.3150/23-BEJ1651

Abstract

In this paper, we study sparse signal detection problems in “degree corrected” Exponential Random Graph Models (ERGMs). We study the performance of two tests based on conditionally centered sum of degrees/maximum of degrees, for a wide class of such ERGMs. The performance of these tests match the performance of corresponding uncentered tests in the β model (Ann. Statist. 46 (2018) 1288–1317). Focusing on the degree corrected two star ERGM, we show that improved detection is possible at “criticality” using a test based on (unconditional) sum of degrees. In this setting we provide matching lower bounds in all parameter regimes, which is based on correlations estimates between degrees under the alternative, and is of possible independent interest.

Acknowledgements

The authors thank Rajarshi Mukherjee for helpful discussions throughout the project. The authors also thank the AE and an anonymous referee for helpful comments. SM gratefully thanks NSF (DMS 1712037) for support during this research.

Citation

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Yuanzhe Xu. Sumit Mukherjee. "Signal detection in degree corrected ERGMs." Bernoulli 30 (3) 1746 - 1773, August 2024. https://doi.org/10.3150/23-BEJ1651

Information

Received: 1 October 2022; Published: August 2024
First available in Project Euclid: 14 May 2024

Digital Object Identifier: 10.3150/23-BEJ1651

Keywords: Asymptotic efficiency , auxiliary variables , ERGM , phase transition , signal detection , two star

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Vol.30 • No. 3 • August 2024
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