R package ecp: Non-Parametric Multiple Change-Point Analysis of Multivariate Data. Implements various procedures for finding multiple change-points. Two methods make use of dynamic programming and probabilistic pruning, with no distributional assumptions other than the existence of certain absolute moments in one method. Hierarchical and exact search methods are included. All methods return the set of estimated change- points as well as other summary information.

References in zbMATH (referenced in 13 articles , 1 standard article )

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  1. Siddiqa, Hajra; Ali, Sajid; Shah, Ismail: Most recent changepoint detection in censored panel data (2021)
  2. Grundy, Thomas; Killick, Rebecca; Mihaylov, Gueorgui: High-dimensional changepoint detection via a geometrically inspired mapping (2020)
  3. Hlávka, Zdeněk; Hušková, Marie; Meintanis, Simos G.: Change-point methods for multivariate time-series: paired vectorial observations (2020)
  4. Arlot, Sylvain; Celisse, Alain; Harchaoui, Zaid: A kernel multiple change-point algorithm via model selection (2019)
  5. Baranowski, Rafal; Chen, Yining; Fryzlewicz, Piotr: Narrowest-over-threshold detection of multiple change points and change-point-like features (2019)
  6. Herlands, William; Neill, Daniel B.; Nickisch, Hannes; Wilson, Andrew Gordon: Change surfaces for expressive multidimensional changepoints and counterfactual prediction (2019)
  7. Plasse, Joshua; Adams, Niall M.: Multiple changepoint detection in categorical data streams (2019)
  8. Avanesov, Valeriy; Buzun, Nazar: Change-point detection in high-dimensional covariance structure (2018)
  9. Celisse, A.; Marot, G.; Pierre-Jean, M.; Rigaill, G. J.: New efficient algorithms for multiple change-point detection with reproducing kernels (2018)
  10. Charles Truong, Laurent Oudre, Nicolas Vayatis: ruptures: change point detection in Python (2018) arXiv
  11. Wang, Tengyao; Samworth, Richard J.: High dimensional change point estimation via sparse projection (2018)
  12. Nyamundanda, Gift; Hegarty, Avril; Hayes, Kevin: Product partition latent variable model for multiple change-point detection in multivariate data (2015)
  13. Nicholas A. James, David S. Matteson: ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data (2013) arXiv