Optimal covariance change point localization in high dimensions

DOI10.3150/20-bej1249zbMath1479.62077arXiv1712.09912OpenAlexW3110221193MaRDI QIDQ97725

Daren Wang, Yi Yu, Alessandro Rinaldo, Daren Wang, Yi Yu, Alessandro Rinaldo

Publication date: 1 February 2021

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1712.09912

zbMATH Keywords

binary segmentationchange point detectionminimax optimalwild binary segmentationhigh-dimensional covariance testingindependent projection

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Hypothesis testing in multivariate analysis (62H15)

Related Items (12)

Optimal multiple change-point detection for high-dimensional data ⋮ Change-Point Detection for Graphical Models in the Presence of Missing Values ⋮ Efficient multiple change point detection for high‐dimensional generalized linear models ⋮ Bayesian Change Point Detection with Spike-and-Slab Priors ⋮ A generalized knockoff procedure for FDR control in structural change detection ⋮ Detection of Multiple Structural Breaks in Large Covariance Matrices ⋮ Efficient change point detection and estimation in high-dimensional correlation matrices ⋮ Unnamed Item ⋮ Optimal nonparametric change point analysis ⋮ changepoints ⋮ High dimensional change point inference: recent developments and extensions ⋮ A computationally efficient and flexible algorithm for high dimensional mean and covariance matrix change point models

Uses Software

• wbs
• factorcpt

Cites Work

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