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Full Description
This book provides a unified exposition of some fundamental theoretical problems in high-dimensional statistics. It specifically considers the canonical problems of detection and support estimation for sparse signals observed with noise. Novel phase-transition results are obtained for the signal support estimation problem under a variety of statistical risks. Based on a surprising connection to a concentration of maxima probabilistic phenomenon, the authors obtain a complete characterization of the exact support recovery problem for thresholding estimators under dependent errors.
Contents
Chapter 1 Introduction and Guiding Examples.- Chapter 2 Risks, Procedures, and Error Models.- Chapter 3 A Panorama of Phase Transitions.- Chapter 4 Exact Support Recovery Under Dependence.- Chapter 5 Bayes and Minimax Optimality.- Chapter 6 Uniform Relative Stability for Gaussian Array.- Chapter 7 Fundamental Statistical Limits in Genome-wide Association Studies.- References.- Additional proofs.- Exact support recovery in non AGG models.