not-package: Narrowest-Over-Threshold Change-Point Detection
In not: Narrowest-Over-Threshold Change-Point Detection
not-package R Documentation
Narrowest-Over-Threshold Change-Point Detection
Description
Implements the Narrowest-Over-Threshold approach for general multiple change-point
detection in one-dimensional data following 'deterministic signal + noise' model. Scenarios that are currently implemented 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 standard deviation of the noise. The main routines of the package are not and features.
References
R. Baranowski, Y. Chen, and P. Fryzlewicz (2019). Narrowest-Over-Threshold Change-Point Detection. (http://stats.lse.ac.uk/fryzlewicz/not/not.pdf)
not documentation built on Feb. 16, 2023, 9:55 p.m.
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| not-package | R Documentation |
Narrowest-Over-Threshold Change-Point Detection
Description
Implements the Narrowest-Over-Threshold approach for general multiple change-point
detection in one-dimensional data following 'deterministic signal + noise' model. Scenarios that are currently implemented 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 standard deviation of the noise. The main routines of the package are not and features.
References
R. Baranowski, Y. Chen, and P. Fryzlewicz (2019). Narrowest-Over-Threshold Change-Point Detection. (http://stats.lse.ac.uk/fryzlewicz/not/not.pdf)
R Package Documentation
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