Global testing against sparse alternatives under Ising models
Rajarshi Mukherjee, Sumit Mukherjee, Ming Yuan
The Annals of Statistics · 2018 · Volume 46 · Issue 5
Abstract
In this paper, we study the effect of dependence on detecting sparse signals. In particular, we focus on global testing against sparse alternatives for the means of binary outcomes following an Ising model, and establish how the interplay between the strength and sparsity of a signal determines its detectability under various notions of dependence. The profound impact of dependence is best illustrated under the Curie–Weiss model where we observe the effect of a “thermodynamic” phase transition. In particular, the critical state exhibits a subtle “blessing of dependence” phenomenon in that one can detect much weaker signals at criticality than otherwise. Furthermore, we develop a testing procedure that is broadly applicable to account for dependence and show that it is asymptotically minimax optimal under fairly general regularity conditions.
Keywords
62C20, 62G10, 62G20, Detection boundary, Ising models, Phase transitions, sparse signals
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