Minimax Euclidean separation rates for testing convex hypotheses in \(\mathbb{R}^{d}\)

DOI10.1214/18-EJS1472zbMath1402.60126arXiv1702.03760OpenAlexW2725018157MaRDI QIDQ1627564

Maurilio Gutzeit, Gilles Blanchard, Alexandra Carpentier

Publication date: 30 November 2018

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.03760

zbMATH Keywords

minimax hypothesis testingGaussian sequence modelnonasymptotic minimax separation rate

Mathematics Subject Classification ID

Interacting random processes; statistical mechanics type models; percolation theory (60K35)

Related Items (6)

Optimal rates of estimation for multi-reference alignment ⋮ Inference on the maximal rank of time-varying covariance matrices using high-frequency data ⋮ Nonasymptotic one- and two-sample tests in high dimension with unknown covariance structure ⋮ Dimension-agnostic inference using cross U-statistics ⋮ Optimal nonparametric testing of missing completely at random and its connections to compatibility ⋮ Optimal detection of the feature matching map in presence of noise and outliers

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