changepoint

R package changepoint: Analysis of Changepoint Models. Implements various mainstream and specialised changepoint methods for finding single and multiple changepoints within data. Many popular non-parametric and frequentist methods are included. The cpt.mean, cpt.var, cpt.meanvar functions should be your first point of call.

Keywords for this software

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References in zbMATH (referenced in 18 articles , 1 standard article )

Showing results 1 to 18 of 18.
Sorted by year (citations)

  1. Aston, John A. D.; Kirch, Claudia: High dimensional efficiency with applications to change point tests (2018)
  2. Charles Truong, Laurent Oudre, Nicolas Vayatis: ruptures: change point detection in Python (2018) arXiv
  3. Fasola, Salvatore; Muggeo, Vito M. R.; Küchenhoff, Helmut: A heuristic, iterative algorithm for change-point detection in abrupt change models (2018)
  4. Felix Pretis; J. Reade; Genaro Sucarrat: Automated General-to-Specific (GETS) Regression Modeling and Indicator Saturation for Outliers and Structural Breaks (2018) not zbMATH
  5. Hernández, Belinda; Raftery, Adrian E.; Pennington, Stephen R.; Parnell, Andrew C.: Bayesian additive regression trees using Bayesian model averaging (2018)
  6. Hyun, Sangwon; G’sell, Max; Tibshirani, Ryan J.: Exact post-selection inference for the generalized lasso path (2018)
  7. Bodenham, Dean A.; Adams, Niall M.: Continuous monitoring for changepoints in data streams using adaptive estimation (2017)
  8. Chatterjee, Subhashis; Shukla, Ankur: An ideal software release policy for an improved software reliability growth model incorporating imperfect debugging with fault removal efficiency and change point (2017)
  9. Chatterjee, Subhashis; Shukla, Ankur: Modeling and analysis of software fault detection and correction process through Weibull-type fault reduction factor, change point and imperfect debugging (2016)
  10. Hirotsu, Chihiro; Yamamoto, Shoichi; Tsuruta, Harukazu: A unifying approach to the shape and change-point hypotheses in the discrete univariate exponential family (2016)
  11. Shi, Xiaoping; Wang, Xiang-Sheng; Wei, Dongwei; Wu, Yuehua: A sequential multiple change-point detection procedure via VIF regression (2016)
  12. Gordon Ross: Parametric and Nonparametric Sequential Change Detection in R: The cpm Package (2015) not zbMATH
  13. Cleynen, Alice; Dudoit, Sandrine; Robin, Stéphane: Comparing segmentation methods for genome annotation based on RNA-seq data (2014)
  14. Quentin Grimonprez, Alain Celisse, Meyling Cheok, Martin Figeac, Guillemette Marot: MPAgenomics : An R package for multi-patients analysis of genomic markers (2014) arXiv
  15. Rebecca Killick; Idris Eckley: changepoint: An R Package for Changepoint Analysis (2014) not zbMATH
  16. Killick, R.; Eckley, I. A.; Jonathan, P.: A wavelet-based approach for detecting changes in second order structure within nonstationary time series (2013)
  17. Nicholas A. James, David S. Matteson: ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data (2013) arXiv
  18. Killick, R.; Fearnhead, P.; Eckley, I. A.: Optimal detection of changepoints with a linear computational cost (2012)