Sharp detection of smooth signals in a high-dimensional sparse matrix with indirect observations

DOI10.1214/15-AIHP689zbMath1353.62056arXiv1301.4660OpenAlexW1714071681MaRDI QIDQ503078

Cristina Butucea, Ghislaine Gayraud

Publication date: 11 January 2017

Published in: Annales de l'Institut Henri Poincaré. Probabilités et Statistiques (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1301.4660

zbMATH Keywords

inverse problemshigh-dimensional dataGaussian white noise modelsparsitydetection boundaryasymptotic minimax testheterogeneous observationsindirect observationssharp rates

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Gaussian processes (60G15) Asymptotic properties of nonparametric inference (62G20) Hypothesis testing in multivariate analysis (62H15) Minimax procedures in statistical decision theory (62C20)

Related Items (3)

Sharp minimax tests for large covariance matrices and adaptation ⋮ Connection between the selection problem for a sparse submatrix of a large-size matrix and the Bayesian problem of hypotheses testing ⋮ Sharp variable selection of a sparse submatrix in a high-dimensional noisy matrix

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