Mathematics > Statistics Theory
[Submitted on 22 Apr 2025
]
Title: Detecting Correlation between Multiple Unlabeled Gaussian Networks
Title: 检测多个未标记高斯网络之间的相关性
Abstract: This paper studies the hypothesis testing problem to determine whether m > 2 unlabeled graphs with Gaussian edge weights are correlated under a latent permutation. Previously, a sharp detection threshold for the correlation parameter \rho was established by Wu, Xu and Yu for this problem when m = 2. Presently, their result is leveraged to derive necessary and sufficient conditions for general m. In doing so, an interval for \rho is uncovered for which detection is impossible using 2 graphs alone but becomes possible with m > 2 graphs.
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