Heterogeneous dense subhypergraph detection

Abstract We study the problem of testing the existence of a heterogeneous dense subhypergraph. The null hypothesis corresponds to a heterogeneous Erdös–Rényi uniform random hypergraph and the alternative hypothesis corresponds to a heterogeneous uniform random hypergraph that contains a dense subhypergraph. We establish detection boundaries when the edge probabilities are known and construct an asymptotically powerful test for distinguishing the hypotheses. We also construct an adaptive test which does not involve edge probabilities, and hence, is more practically useful.

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Publication Details

Journal
Statistica Neerlandica
Published
2024-09-03
DOI
https://doi.org/10.1111/stan.12360
Citations
1
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.25

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article

Heterogeneous dense subhypergraph detection

Mingao Yuan, Zuofeng Shang
1 citations
Statistica Neerlandica
Data Visualization and Analytics
0.25
article

Heterogeneous dense subhypergraph detection

Mingao Yuan, Zuofeng Shang
article en
1 citations

Abstract

Abstract We study the problem of testing the existence of a heterogeneous dense subhypergraph. The null hypothesis corresponds to a heterogeneous Erdös–Rényi uniform random hypergraph and the alternative hypothesis corresponds to a heterogeneous uniform random hypergraph that contains a dense subhypergraph. We establish detection boundaries when the edge probabilities are known and construct an asymptotically powerful test for distinguishing the hypotheses. We also construct an adaptive test which does not involve edge probabilities, and hence, is more practically useful.

Statistica NeerlandicaVol. 78(4)
New Jersey Institute of Technology (US), North Dakota State University (US)
National Science Foundation, National Science Foundation of Sri Lanka
Reduced inequalities
Openalex Percentile: Top 48%
Data Visualization and Analytics
0.25
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