Multiple change-point detection via a screening and ranking algorithm

DOI10.5705/ss.2012.018szbMath1417.62236OpenAlexW2102133987WikidataQ37518512 ScholiaQ37518512MaRDI QIDQ2864543

Heping Zhang, Ning Hao, Yue Selena Niu

Publication date: 25 November 2013

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3902887

zbMATH Keywords

false discovery ratehigh dimensional datachange-point detectionscreening and ranking algorithmcopy number variation

Mathematics Subject Classification ID

Bayesian inference (62F15) Statistical ranking and selection procedures (62F07) Non-Markovian processes: hypothesis testing (62M07)

Related Items (17)

Rank-based multiple change-point detection ⋮ Detecting Multiple Change Points: The PULSE Criterion ⋮ Data-driven selection of the number of change-points via error rate control ⋮ Multiple change-points detection in high dimension ⋮ Change-detection-assisted multiple testing for spatiotemporal data ⋮ Covariate-assisted matrix completion with multiple structural breaks ⋮ Segmentation and estimation of change-point models: false positive control and confidence regions ⋮ Multiple change point detection and validation in autoregressive time series data ⋮ False discovery rates for large-scale model checking under certain dependence ⋮ Asymptotic properties of \(M\)-estimators based on estimating equations and censored data in semi-parametric models with multiple change points ⋮ Consistent selection of the number of change-points via sample-splitting ⋮ FDR-control in multiscale change-point segmentation ⋮ Bayesian multiple change-points detection in a normal model with heterogeneous variances ⋮ Multiple change-point detection: a selective overview ⋮ Nonparametric maximum likelihood approach to multiple change-point problems ⋮ A shape-based cutting and clustering algorithm for multiple change-point detection ⋮ Asymptotic properties of semiparametric \(M\)-estimators with multiple change points

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