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Title: Network dependence testing via diffusion maps and distance-based correlations
Summary Deciphering the associations between network connectivity and nodal attributes is one of the core problems in network science. The dependency structure and high dimensionality of networks pose unique challenges to traditional dependency tests in terms of theoretical guarantees and empirical performance. We propose an approach to test network dependence via diffusion maps and distance-based correlations. We prove that the new method yields a consistent test statistic under mild distributional assumptions on the graph structure, and demonstrate that it is able to efficiently identify the most informative graph embedding with respect to the diffusion time. The methodology is illustrated on both simulated and real data.  more » « less
Award ID(s):
1921310
PAR ID:
10166928
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Biometrika
Volume:
106
Issue:
4
ISSN:
0006-3444
Page Range / eLocation ID:
857 to 873
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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