Work

Heterogeneous dense subhypergraph detection

Year: 2024

Type: article

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.

Source: Statistica Neerlandica

DOI: 10.1111/stan.12360

Authors: Mingao Yuan, Zuofeng Shang

Institutions: North Dakota State University, New Jersey Institute of Technology

Language: English

Topic: Limits and Structures in Graph Theory

Subfield: Discrete Mathematics and Combinatorics

Field: Mathematics

Domain: Physical Sciences

Open Access status: bronze

Funders: National Science Foundation, National Science Foundation of Sri Lanka

Awards: G11857770, Collaborative Research: Nonparametric Bayesian Aggregation for Massive Data, G5423101233, CDS&E: Collaborative Research: Scalable Nonparametric Learning for Massive Data with Statistical Guarantees