GLOBAL TESTING AGAINST SPARSE ALTERNATIVES UNDER ISING MODELS

被引:19
作者
Mukherjee, Rajarshi [1 ]
Mukherjee, Sumit [2 ]
Yuan, Ming [2 ]
机构
[1] Univ Calif Berkeley, Div Biostat, Haviland Hall, Berkeley, CA 94720 USA
[2] Columbia Univ, Dept Stat, 1255 Amsterdam Ave, New York, NY 10027 USA
关键词
Detection boundary; Ising models; phase transitions; sparse signals; HIGHER CRITICISM; DETECTION BOUNDARY; STEINS METHOD; STATISTICS;
D O I
10.1214/17-AOS1612
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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.
引用
收藏
页码:2062 / 2093
页数:32
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