Minimax rates in sparse, high-dimensional change point detection

DOI10.1214/20-AOS1994zbMath1472.62013arXiv1907.10012OpenAlexW3140784025MaRDI QIDQ2039806

Haoyang Liu, Richard J. Samworth, Chao Gao

Publication date: 5 July 2021

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.10012

zbMATH Keywords

time seriesiterated logarithmminimax detection boundary

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Minimax procedures in statistical decision theory (62C20)

Related Items (11)

A robust bootstrap change point test for high-dimensional location parameter ⋮ Scalable change-point and anomaly detection in cross-correlated data with an application to condition monitoring ⋮ Adaptive Inference for Change Points in High-Dimensional Data ⋮ Inference of Breakpoints in High-dimensional Time Series ⋮ Detecting structured signals in Ising models ⋮ Optimal permutation estimation in crowdsourcing problems ⋮ Optimal change-point detection and localization ⋮ Minimax and adaptive tests for detecting abrupt and possibly transitory changes in a Poisson process ⋮ Estimation of high-dimensional change-points under a group sparsity structure ⋮ High dimensional change point inference: recent developments and extensions ⋮ Robust inference for change points in high dimension

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