not: Narrowest-Over-Threshold Change-Point Detection

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. For details, see Baranowski, Chen and Fryzlewicz (2019) <doi:10.1111/rssb.12322>.

Version: 1.5
Depends: graphics, stats, splines
Published: 2023-02-01
DOI: 10.32614/CRAN.package.not
Author: Rafal Baranowski, Yining Chen, Piotr Fryzlewicz
Maintainer: Yining Chen <Y.Chen101 at>
License: GPL-2
NeedsCompilation: yes
CRAN checks: not results


Reference manual: not.pdf


Package source: not_1.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): not_1.5.tgz, r-oldrel (arm64): not_1.5.tgz, r-release (x86_64): not_1.5.tgz, r-oldrel (x86_64): not_1.5.tgz
Old sources: not archive

Reverse dependencies:

Reverse suggests: fastcpd


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