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.

Version: 1.0
Depends: graphics, stats, splines
Published: 2016-08-23
Author: Rafal Baranowski, Yining Chen, Piotr Fryzlewicz
Maintainer: Rafal Baranowski <r.baranowski at lse.ac.uk>
License: GPL-2
NeedsCompilation: yes
CRAN checks: not results

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Reference manual: not.pdf
Package source: not_1.0.tar.gz
Windows binaries: r-devel: not_1.0.zip, r-release: not_1.0.zip, r-oldrel: not_1.0.zip
OS X El Capitan binaries: r-release: not_1.0.tgz
OS X Mavericks binaries: r-oldrel: not_1.0.tgz

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