R package not. Provides efficient implementation of the Narrowest-Over-Threshold methodology for detecting an unknown number of change-points occurring at unknown locations in one-dimensional data following ’deterministic signal + noise’ model. Currently implemented scenarios are: piecewise-constant signal, piecewise-constant signal with a heavy-tailed noise, piecewise-linear signal, piecewise-quadratic signal, piecewise-constant signal and with piecewise-constant variance of the noise.
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References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Alexander Meier, Claudia Kirch, Haeran Cho: mosum: A Package for Moving Sums in Change-Point Analysis (2021) not zbMATH
- Baranowski, Rafal; Chen, Yining; Fryzlewicz, Piotr: Ranking-based variable selection for high-dimensional data (2020)
- Andreas Anastasiou, Piotr Fryzlewicz: Detecting multiple generalized change-points by isolating single ones (2019) arXiv
- Baranowski, Rafal; Chen, Yining; Fryzlewicz, Piotr: Narrowest-over-threshold detection of multiple change points and change-point-like features (2019)
- Fryzlewicz, Piotr: Wild binary segmentation for multiple change-point detection (2014)