Detecting changes in the second moment structure of high-dimensional sensor-type data in a K-sample setting

DOI10.1080/07474946.2020.1823192zbMath1461.62158arXiv2001.05204OpenAlexW3121011312MaRDI QIDQ4965652

Ansgar Steland, Nils Mause

Publication date: 9 March 2021

Published in: Sequential Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2001.05204

zbMATH Keywords

time seriesBrownian motionlinear processchange pointsmultivariate analysisstrong approximationdata sciencesensor monitoring

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics in engineering and industry; control charts (62P30) Brownian motion (60J65) Sequential statistical analysis (62L10) Functional limit theorems; invariance principles (60F17) Statistical aspects of big data and data science (62R07)

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Testing and estimating change-points in the covariance matrix of a high-dimensional time series

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