High-dimensional changepoint detection via a geometrically inspired mapping

DOI10.1007/s11222-020-09940-yzbMath1448.62132arXiv2001.05241OpenAlexW3105047319MaRDI QIDQ139173

Thomas Grundy, Gueorgui Mihaylov, Rebecca Killick, Gueorgui Mihaylov, Thomas Grundy, Rebecca Killick

Publication date: 28 March 2020

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2001.05241

zbMATH Keywords

changepointtime serieshigh-dimensionalPruned Exact Linear Time (PELT) method

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (6)

Epidemic changepoint detection in the presence of nuisance changes ⋮ On the trend detection of time-ordered intensity images of point processes on linear networks ⋮ Doubly-online changepoint detection for monitoring health status during sports activities ⋮ BayesProject: fast computation of a projection direction for multivariate changepoint detection ⋮ Graphical Influence Diagnostics for Changepoint Models ⋮ changepoint.geo

Uses Software

• R
• CRAN
• changepoint
• wbs
• InspectChangepoint
• changepoint.np
• ecp
• SP500R

Cites Work

• Wild binary segmentation for multiple change-point detection
• Uniform change point tests in high dimension
• High-dimensional change-point detection under sparse alternatives
• A computationally efficient nonparametric approach for changepoint detection
• Nonparametric maximum likelihood approach to multiple change-point problems
• Detecting simultaneous changepoints in multiple sequences
• High Dimensional Change Point Estimation via Sparse Projection
• A Cluster Analysis Method for Grouping Means in the Analysis of Variance
• Optimal Detection of Changepoints With a Linear Computational Cost
• A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data
• Random change point models: investigating cognitive decline in the presence of missing data
• Detection of multiple change-points in multivariate data
• Greedy Kernel Change-Point Detection
• Change‐point detection in panel data
• A Modified Bayes Information Criterion with Applications to the Analysis of Comparative Genomic Hybridization Data
• CONTINUOUS INSPECTION SCHEMES
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