Relevant change points in high dimensional time series

DOI10.1214/18-EJS1464zbMath1403.62158arXiv1704.04614OpenAlexW2963353355MaRDI QIDQ1786570

Josua Gösmann, Dette, Holger

Publication date: 24 September 2018

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1704.04614

zbMATH Keywords

CUSUMchange point analysishigh-dimensional time seriesphysical dependence measureprecise hypothesesrelevant changes

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: hypothesis testing (62M07) Asymptotic properties of parametric tests (62F05)

Related Items (5)

Estimating a Change Point in a Sequence of Very High-Dimensional Covariance Matrices ⋮ Inference for change points in high-dimensional data via selfnormalization ⋮ Optimal multiple change-point detection for high-dimensional data ⋮ Sequential change point detection in high dimensional time series ⋮ Detecting Abrupt Changes in High-Dimensional Self-Exciting Poisson Processes

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