Overview
- Provides a unified exposition of fundamental problems in high-dimensional statistics
- Tackles canonical problems of detection and support estimation for sparse signals observed with noise
- Gives an application to statistical genetics
Part of the book series: SpringerBriefs in Probability and Mathematical Statistics (SBPMS)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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.
Authors and Affiliations
About the authors
Stilian Stoev is a Full Professor of Statistics at the University of Michigan, Ann Arbor. His research involves topics in applied probability, statistics and their applications to insurance and computer networks. Most recently, he has been working on extreme value theory.
Bibliographic Information
Book Title: Concentration of Maxima and Fundamental Limits in High-Dimensional Testing and Inference
Authors: Zheng Gao, Stilian Stoev
Series Title: SpringerBriefs in Probability and Mathematical Statistics
DOI: https://doi.org/10.1007/978-3-030-80964-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-80963-8Published: 08 September 2021
eBook ISBN: 978-3-030-80964-5Published: 07 September 2021
Series ISSN: 2365-4333
Series E-ISSN: 2365-4341
Edition Number: 1
Number of Pages: XIII, 140
Number of Illustrations: 10 b/w illustrations, 2 illustrations in colour
Topics: Probability Theory and Stochastic Processes, Statistics, general